diff --git a/eng/dependency_tools.txt b/eng/dependency_tools.txt index 3ccc2ab48ce5..39dcb2d56626 100644 --- a/eng/dependency_tools.txt +++ b/eng/dependency_tools.txt @@ -1 +1,2 @@ -../../../tools/azure-sdk-tools \ No newline at end of file +../../../tools/azure-sdk-tools +aiohttp>=3.0; python_version >= '3.5' diff --git a/eng/pipelines/templates/steps/build-test.yml b/eng/pipelines/templates/steps/build-test.yml index e4c41d912486..b72d43e655e3 100644 --- a/eng/pipelines/templates/steps/build-test.yml +++ b/eng/pipelines/templates/steps/build-test.yml @@ -61,12 +61,12 @@ steps: Get-Content $_ } displayName: 'Show .coverage files' - condition: and(succeededOrFailed(), ${{ parameters.RunCoverage }}) + condition: and(succeeded(), ${{ parameters.RunCoverage }}) - task: PublishPipelineArtifact@1 displayName: 'Publish .coverage files' continueOnError: true - condition: and(succeededOrFailed(), ${{ parameters.RunCoverage }}) + condition: and(succeeded(), ${{ parameters.RunCoverage }}) inputs: targetPath: '$(Build.SourcesDirectory)/_coverage' artifactType: 'pipeline' diff --git a/eng/tox/install_depend_packages.py b/eng/tox/install_depend_packages.py index 7138482cf0e3..9692fd54846d 100644 --- a/eng/tox/install_depend_packages.py +++ b/eng/tox/install_depend_packages.py @@ -84,7 +84,7 @@ def process_requirement(req, dependency_type): # get available versions on PyPI client = PyPIClient() - versions = [str(v) for v in client.get_ordered_versions(pkg_name)] + versions = [str(v) for v in client.get_ordered_versions(pkg_name, True)] logging.info("Versions available on PyPI for %s: %s", pkg_name, versions) if pkg_name in MINIMUM_VERSION_SUPPORTED_OVERRIDE: diff --git a/scripts/devops_tasks/common_tasks.py b/scripts/devops_tasks/common_tasks.py index af96f0550d61..317ae2026230 100644 --- a/scripts/devops_tasks/common_tasks.py +++ b/scripts/devops_tasks/common_tasks.py @@ -43,6 +43,7 @@ "azure", "azure-mgmt", "azure-storage", + "azure-mgmt-regionmove" ] MANAGEMENT_PACKAGE_IDENTIFIERS = [ "mgmt", diff --git a/sdk/core/azure-core/CHANGELOG.md b/sdk/core/azure-core/CHANGELOG.md index 441fc3877c1b..4ef32399e2d5 100644 --- a/sdk/core/azure-core/CHANGELOG.md +++ b/sdk/core/azure-core/CHANGELOG.md @@ -4,6 +4,7 @@ ### Features +- Added `CaseInsensitiveEnumMeta` class for case-insensitive enums. #16316 - Add `raise_for_status` method onto `HttpResponse`. Calling `response.raise_for_status()` on a response with an error code will raise an `HttpResponseError`. Calling it on a good response will do nothing #16399 diff --git a/sdk/core/azure-core/README.md b/sdk/core/azure-core/README.md index 5d506d660ea5..2e5391ae84ea 100644 --- a/sdk/core/azure-core/README.md +++ b/sdk/core/azure-core/README.md @@ -148,6 +148,20 @@ class MatchConditions(Enum): IfMissing = 5 ``` +#### CaseInsensitiveEnumMeta + +A metaclass to support case-insensitive enums. +```python +from enum import Enum +from six import with_metaclass + +from azure.core import CaseInsensitiveEnumMeta + +class MyCustomEnum(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)): + FOO = 'foo' + BAR = 'bar' +``` + ## Contributing This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have diff --git a/sdk/core/azure-core/azure/core/__init__.py b/sdk/core/azure-core/azure/core/__init__.py index 40ed75d540a6..ddd1d8da4b69 100644 --- a/sdk/core/azure-core/azure/core/__init__.py +++ b/sdk/core/azure-core/azure/core/__init__.py @@ -29,11 +29,13 @@ from ._pipeline_client import PipelineClient from ._match_conditions import MatchConditions +from ._enum_meta import CaseInsensitiveEnumMeta __all__ = [ "PipelineClient", - "MatchConditions" + "MatchConditions", + "CaseInsensitiveEnumMeta" ] try: diff --git a/sdk/core/azure-core/azure/core/_enum_meta.py b/sdk/core/azure-core/azure/core/_enum_meta.py new file mode 100644 index 000000000000..8c225f88cc74 --- /dev/null +++ b/sdk/core/azure-core/azure/core/_enum_meta.py @@ -0,0 +1,61 @@ +# -------------------------------------------------------------------------- +# +# Copyright (c) Microsoft Corporation. All rights reserved. +# +# The MIT License (MIT) +# +# Permission is hereby granted, free of charge, to any person obtaining a copy +# of this software and associated documentation files (the ""Software""), to +# deal in the Software without restriction, including without limitation the +# rights to use, copy, modify, merge, publish, distribute, sublicense, and/or +# sell copies of the Software, and to permit persons to whom the Software is +# furnished to do so, subject to the following conditions: +# +# The above copyright notice and this permission notice shall be included in +# all copies or substantial portions of the Software. +# +# THE SOFTWARE IS PROVIDED *AS IS*, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING +# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS +# IN THE SOFTWARE. +# +# -------------------------------------------------------------------------- + +from enum import EnumMeta + + +class CaseInsensitiveEnumMeta(EnumMeta): + """Enum metaclass to allow for interoperability with case-insensitive strings. + + Consuming this metaclass in an SDK should be done in the following manner: + + .. code-block:: python + + from enum import Enum + from six import with_metaclass + from azure.core import CaseInsensitiveEnumMeta + + class MyCustomEnum(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)): + FOO = 'foo' + BAR = 'bar' + + """ + + def __getitem__(cls, name): + # disabling pylint bc of pylint bug https://github.com/PyCQA/astroid/issues/713 + return super(CaseInsensitiveEnumMeta, cls).__getitem__(name.upper()) # pylint: disable=no-value-for-parameter + + def __getattr__(cls, name): + """Return the enum member matching `name` + We use __getattr__ instead of descriptors or inserting into the enum + class' __dict__ in order to support `name` and `value` being both + properties for enum members (which live in the class' __dict__) and + enum members themselves. + """ + try: + return cls._member_map_[name.upper()] + except KeyError: + raise AttributeError(name) diff --git a/sdk/core/azure-core/tests/test_enums.py b/sdk/core/azure-core/tests/test_enums.py new file mode 100644 index 000000000000..d164568ecdce --- /dev/null +++ b/sdk/core/azure-core/tests/test_enums.py @@ -0,0 +1,44 @@ +# -------------------------------------------------------------------------- +# +# Copyright (c) Microsoft Corporation. All rights reserved. +# +# The MIT License (MIT) +# +# Permission is hereby granted, free of charge, to any person obtaining a copy +# of this software and associated documentation files (the ""Software""), to deal +# in the Software without restriction, including without limitation the rights +# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +# copies of the Software, and to permit persons to whom the Software is +# furnished to do so, subject to the following conditions: +# +# The above copyright notice and this permission notice shall be included in +# all copies or substantial portions of the Software. +# +# THE SOFTWARE IS PROVIDED *AS IS*, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN +# THE SOFTWARE. +# +# -------------------------------------------------------------------------- +from enum import Enum +from six import with_metaclass + +from azure.core import CaseInsensitiveEnumMeta + +class MyCustomEnum(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)): + FOO = 'foo' + BAR = 'bar' + + +def test_case_insensitive_enums(): + assert MyCustomEnum.foo.value == 'foo' + assert MyCustomEnum.FOO.value == 'foo' + assert MyCustomEnum('bar').value == 'bar' + assert 'bar' == MyCustomEnum.BAR + assert 'bar' == MyCustomEnum.bar + assert MyCustomEnum['foo'] == 'foo' + assert MyCustomEnum['FOO'] == 'foo' + assert isinstance(MyCustomEnum.BAR, str) diff --git a/sdk/eventhub/azure-eventhub/README.md b/sdk/eventhub/azure-eventhub/README.md index 36caca519e46..bfb02bd77b86 100644 --- a/sdk/eventhub/azure-eventhub/README.md +++ b/sdk/eventhub/azure-eventhub/README.md @@ -423,6 +423,14 @@ Reference documentation is available [here](https://azuresdkdocs.blob.core.windo The EventHubs SDK integrates nicely with the [Schema Registry][schemaregistry_service] service and [Avro][avro]. For more information, please refer to [Schema Registry SDK][schemaregistry_repo] and [Schema Registry Avro Serializer SDK][schemaregistry_avroserializer_repo]. +### Building uAMQP wheel from source + +`azure-eventhub` depends on the [uAMQP](https://pypi.org/project/uamqp/) for the AMQP protocol implementation. +uAMQP wheels are provided for most major operating systems and will be installed automatically when installing `azure-eventhub`. + +If you're running on a platform for which uAMQP wheels are not provided, please follow + the [uAMQP Installation](https://github.com/Azure/azure-uamqp-python#installation) guidance to install from source. + ### Provide Feedback If you encounter any bugs or have suggestions, please file an issue in the [Issues](https://github.com/Azure/azure-sdk-for-python/issues) section of the project. diff --git a/sdk/eventhub/ci.yml b/sdk/eventhub/ci.yml index e4605fc4101b..16d7ba56991d 100644 --- a/sdk/eventhub/ci.yml +++ b/sdk/eventhub/ci.yml @@ -42,3 +42,4 @@ extends: safeName: azureeventhubcheckpointstoreblob - name: azure_mgmt_eventhub safeName: azuremgmteventhub + SkipPythonVersion: 'pypy3' diff --git a/sdk/formrecognizer/azure-ai-formrecognizer/samples/async_samples/sample_recognize_invoices_async.py b/sdk/formrecognizer/azure-ai-formrecognizer/samples/async_samples/sample_recognize_invoices_async.py index 3f5c53f756b1..bdd8aca10925 100644 --- a/sdk/formrecognizer/azure-ai-formrecognizer/samples/async_samples/sample_recognize_invoices_async.py +++ b/sdk/formrecognizer/azure-ai-formrecognizer/samples/async_samples/sample_recognize_invoices_async.py @@ -31,7 +31,7 @@ class RecognizeInvoiceSampleAsync(object): async def recognize_invoice(self): path_to_sample_forms = os.path.abspath(os.path.join(os.path.abspath(__file__), - "..", "..", "./sample_forms/forms/Invoice_1.pdf")) + "..", "..", "./sample_forms/forms/sample_invoice.jpg")) # [START recognize_invoices_async] from azure.core.credentials import AzureKeyCredential @@ -55,9 +55,15 @@ async def recognize_invoice(self): vendor_address = invoice.fields.get("VendorAddress") if vendor_address: print("Vendor Address: {} has confidence: {}".format(vendor_address.value, vendor_address.confidence)) + vendor_address_recipient = invoice.fields.get("VendorAddressRecipient") + if vendor_address_recipient: + print("Vendor Address Recipient: {} has confidence: {}".format(vendor_address_recipient.value, vendor_address_recipient.confidence)) customer_name = invoice.fields.get("CustomerName") if customer_name: print("Customer Name: {} has confidence: {}".format(customer_name.value, customer_name.confidence)) + customer_id = invoice.fields.get("CustomerId") + if customer_id: + print("Customer Id: {} has confidence: {}".format(customer_id.value, customer_id.confidence)) customer_address = invoice.fields.get("CustomerAddress") if customer_address: print("Customer Address: {} has confidence: {}".format(customer_address.value, customer_address.confidence)) @@ -76,6 +82,51 @@ async def recognize_invoice(self): due_date = invoice.fields.get("DueDate") if due_date: print("Due Date: {} has confidence: {}".format(due_date.value, due_date.confidence)) + purchase_order = invoice.fields.get("PurchaseOrder") + if purchase_order: + print("Purchase Order: {} has confidence: {}".format(purchase_order.value, purchase_order.confidence)) + billing_address = invoice.fields.get("BillingAddress") + if billing_address: + print("Billing Address: {} has confidence: {}".format(billing_address.value, billing_address.confidence)) + billing_address_recipient = invoice.fields.get("BillingAddressRecipient") + if billing_address_recipient: + print("Billing Address Recipient: {} has confidence: {}".format(billing_address_recipient.value, billing_address_recipient.confidence)) + shipping_address = invoice.fields.get("ShippingAddress") + if shipping_address: + print("Shipping Address: {} has confidence: {}".format(shipping_address.value, shipping_address.confidence)) + shipping_address_recipient = invoice.fields.get("ShippingAddressRecipient") + if shipping_address_recipient: + print("Shipping Address Recipient: {} has confidence: {}".format(shipping_address_recipient.value, shipping_address_recipient.confidence)) + subtotal = invoice.fields.get("SubTotal") + if subtotal: + print("Subtotal: {} has confidence: {}".format(subtotal.value, subtotal.confidence)) + total_tax = invoice.fields.get("TotalTax") + if total_tax: + print("Total Tax: {} has confidence: {}".format(total_tax.value, total_tax.confidence)) + previous_unpaid_balance = invoice.fields.get("PreviousUnpaidBalance") + if previous_unpaid_balance: + print("Previous Unpaid Balance: {} has confidence: {}".format(previous_unpaid_balance.value, previous_unpaid_balance.confidence)) + amount_due = invoice.fields.get("AmountDue") + if amount_due: + print("Amount Due: {} has confidence: {}".format(amount_due.value, amount_due.confidence)) + service_start_date = invoice.fields.get("ServiceStartDate") + if service_start_date: + print("Service Start Date: {} has confidence: {}".format(service_start_date.value, service_start_date.confidence)) + service_end_date = invoice.fields.get("ServiceEndDate") + if service_end_date: + print("Service End Date: {} has confidence: {}".format(service_end_date.value, service_end_date.confidence)) + service_address = invoice.fields.get("ServiceAddress") + if service_address: + print("Service Address: {} has confidence: {}".format(service_address.value, service_address.confidence)) + service_address_recipient = invoice.fields.get("ServiceAddressRecipient") + if service_address_recipient: + print("Service Address Recipient: {} has confidence: {}".format(service_address_recipient.value, service_address_recipient.confidence)) + remittance_address = invoice.fields.get("RemittanceAddress") + if remittance_address: + print("Remittance Address: {} has confidence: {}".format(remittance_address.value, remittance_address.confidence)) + remittance_address_recipient = invoice.fields.get("RemittanceAddressRecipient") + if remittance_address_recipient: + print("Remittance Address Recipient: {} has confidence: {}".format(remittance_address_recipient.value, remittance_address_recipient.confidence)) # [END recognize_invoices_async] async def main(): diff --git a/sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_forms/forms/sample_invoice.jpg b/sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_forms/forms/sample_invoice.jpg new file mode 100644 index 000000000000..6f8796469d78 Binary files /dev/null and b/sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_forms/forms/sample_invoice.jpg differ diff --git a/sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_recognize_invoices.py b/sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_recognize_invoices.py index df81ada09fef..72cf0709a2a8 100644 --- a/sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_recognize_invoices.py +++ b/sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_recognize_invoices.py @@ -30,7 +30,7 @@ class RecognizeInvoiceSample(object): def recognize_invoice(self): path_to_sample_forms = os.path.abspath(os.path.join(os.path.abspath(__file__), - "..", "./sample_forms/forms/Invoice_1.pdf")) + "..", "./sample_forms/forms/sample_invoice.jpg")) # [START recognize_invoices] from azure.core.credentials import AzureKeyCredential @@ -54,9 +54,15 @@ def recognize_invoice(self): vendor_address = invoice.fields.get("VendorAddress") if vendor_address: print("Vendor Address: {} has confidence: {}".format(vendor_address.value, vendor_address.confidence)) + vendor_address_recipient = invoice.fields.get("VendorAddressRecipient") + if vendor_address_recipient: + print("Vendor Address Recipient: {} has confidence: {}".format(vendor_address_recipient.value, vendor_address_recipient.confidence)) customer_name = invoice.fields.get("CustomerName") if customer_name: print("Customer Name: {} has confidence: {}".format(customer_name.value, customer_name.confidence)) + customer_id = invoice.fields.get("CustomerId") + if customer_id: + print("Customer Id: {} has confidence: {}".format(customer_id.value, customer_id.confidence)) customer_address = invoice.fields.get("CustomerAddress") if customer_address: print("Customer Address: {} has confidence: {}".format(customer_address.value, customer_address.confidence)) @@ -75,6 +81,51 @@ def recognize_invoice(self): due_date = invoice.fields.get("DueDate") if due_date: print("Due Date: {} has confidence: {}".format(due_date.value, due_date.confidence)) + purchase_order = invoice.fields.get("PurchaseOrder") + if purchase_order: + print("Purchase Order: {} has confidence: {}".format(purchase_order.value, purchase_order.confidence)) + billing_address = invoice.fields.get("BillingAddress") + if billing_address: + print("Billing Address: {} has confidence: {}".format(billing_address.value, billing_address.confidence)) + billing_address_recipient = invoice.fields.get("BillingAddressRecipient") + if billing_address_recipient: + print("Billing Address Recipient: {} has confidence: {}".format(billing_address_recipient.value, billing_address_recipient.confidence)) + shipping_address = invoice.fields.get("ShippingAddress") + if shipping_address: + print("Shipping Address: {} has confidence: {}".format(shipping_address.value, shipping_address.confidence)) + shipping_address_recipient = invoice.fields.get("ShippingAddressRecipient") + if shipping_address_recipient: + print("Shipping Address Recipient: {} has confidence: {}".format(shipping_address_recipient.value, shipping_address_recipient.confidence)) + subtotal = invoice.fields.get("SubTotal") + if subtotal: + print("Subtotal: {} has confidence: {}".format(subtotal.value, subtotal.confidence)) + total_tax = invoice.fields.get("TotalTax") + if total_tax: + print("Total Tax: {} has confidence: {}".format(total_tax.value, total_tax.confidence)) + previous_unpaid_balance = invoice.fields.get("PreviousUnpaidBalance") + if previous_unpaid_balance: + print("Previous Unpaid Balance: {} has confidence: {}".format(previous_unpaid_balance.value, previous_unpaid_balance.confidence)) + amount_due = invoice.fields.get("AmountDue") + if amount_due: + print("Amount Due: {} has confidence: {}".format(amount_due.value, amount_due.confidence)) + service_start_date = invoice.fields.get("ServiceStartDate") + if service_start_date: + print("Service Start Date: {} has confidence: {}".format(service_start_date.value, service_start_date.confidence)) + service_end_date = invoice.fields.get("ServiceEndDate") + if service_end_date: + print("Service End Date: {} has confidence: {}".format(service_end_date.value, service_end_date.confidence)) + service_address = invoice.fields.get("ServiceAddress") + if service_address: + print("Service Address: {} has confidence: {}".format(service_address.value, service_address.confidence)) + service_address_recipient = invoice.fields.get("ServiceAddressRecipient") + if service_address_recipient: + print("Service Address Recipient: {} has confidence: {}".format(service_address_recipient.value, service_address_recipient.confidence)) + remittance_address = invoice.fields.get("RemittanceAddress") + if remittance_address: + print("Remittance Address: {} has confidence: {}".format(remittance_address.value, remittance_address.confidence)) + remittance_address_recipient = invoice.fields.get("RemittanceAddressRecipient") + if remittance_address_recipient: + print("Remittance Address Recipient: {} has confidence: {}".format(remittance_address_recipient.value, remittance_address_recipient.confidence)) # [END recognize_invoices] if __name__ == '__main__': diff --git a/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_business_card_from_url.py b/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_business_card_from_url.py index a69af7f44b1a..02c5de22b888 100644 --- a/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_business_card_from_url.py +++ b/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_business_card_from_url.py @@ -20,7 +20,7 @@ GlobalClientPreparer = functools.partial(_GlobalClientPreparer, FormRecognizerClient) - +@pytest.mark.skip class TestBusinessCardFromUrl(FormRecognizerTest): @FormRecognizerPreparer() diff --git a/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_business_card_from_url_async.py b/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_business_card_from_url_async.py index 962095ed26f9..1be2acce25dc 100644 --- a/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_business_card_from_url_async.py +++ b/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_business_card_from_url_async.py @@ -20,7 +20,7 @@ GlobalClientPreparer = functools.partial(_GlobalClientPreparer, FormRecognizerClient) - +@pytest.mark.skip class TestBusinessCardFromUrlAsync(AsyncFormRecognizerTest): @FormRecognizerPreparer() diff --git a/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_invoice_from_url.py b/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_invoice_from_url.py index dc86f3ffdc75..0b078d864fc0 100644 --- a/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_invoice_from_url.py +++ b/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_invoice_from_url.py @@ -19,7 +19,7 @@ GlobalClientPreparer = functools.partial(_GlobalClientPreparer, FormRecognizerClient) - +@pytest.mark.skip class TestInvoiceFromUrl(FormRecognizerTest): @FormRecognizerPreparer() diff --git a/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_invoice_from_url_async.py b/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_invoice_from_url_async.py index c44784bc4bf0..03ddac308b56 100644 --- a/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_invoice_from_url_async.py +++ b/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_invoice_from_url_async.py @@ -21,7 +21,7 @@ GlobalClientPreparer = functools.partial(_GlobalClientPreparer, FormRecognizerClient) - +@pytest.mark.skip class TestInvoiceFromUrlAsync(AsyncFormRecognizerTest): @FormRecognizerPreparer() diff --git a/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_receipt_from_url.py b/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_receipt_from_url.py index 558f18d34542..47052c921050 100644 --- a/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_receipt_from_url.py +++ b/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_receipt_from_url.py @@ -18,7 +18,7 @@ GlobalClientPreparer = functools.partial(_GlobalClientPreparer, FormRecognizerClient) - +@pytest.mark.skip class TestReceiptFromUrl(FormRecognizerTest): @FormRecognizerPreparer() diff --git a/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_receipt_from_url_async.py b/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_receipt_from_url_async.py index aea49d21b039..cdfa91cdebed 100644 --- a/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_receipt_from_url_async.py +++ b/sdk/formrecognizer/azure-ai-formrecognizer/tests/test_receipt_from_url_async.py @@ -20,7 +20,7 @@ GlobalClientPreparer = functools.partial(_GlobalClientPreparer, FormRecognizerClient) - +@pytest.mark.skip class TestReceiptFromUrlAsync(AsyncFormRecognizerTest): @FormRecognizerPreparer() diff --git a/sdk/identity/azure-identity/CHANGELOG.md b/sdk/identity/azure-identity/CHANGELOG.md index 19b35d6ba023..7b83f97da478 100644 --- a/sdk/identity/azure-identity/CHANGELOG.md +++ b/sdk/identity/azure-identity/CHANGELOG.md @@ -8,6 +8,11 @@ ### Added - `InteractiveBrowserCredential` uses PKCE internally to protect authorization codes +- `CertificateCredential` can load a certificate from bytes instead of a file + path. To provide a certificate as bytes, use the keyword argument + `certificate_bytes` instead of `certificate_path`, for example: + `CertificateCredential(tenant_id, client_id, certificate_bytes=cert_bytes)` + ([#14055](https://github.com/Azure/azure-sdk-for-python/issues/14055)) ## 1.5.0 (2020-11-11) ### Breaking Changes diff --git a/sdk/identity/azure-identity/azure/identity/_credentials/certificate.py b/sdk/identity/azure-identity/azure/identity/_credentials/certificate.py index 49fc06ee0f67..bec722cf8e19 100644 --- a/sdk/identity/azure-identity/azure/identity/_credentials/certificate.py +++ b/sdk/identity/azure-identity/azure/identity/_credentials/certificate.py @@ -14,7 +14,7 @@ from .._internal.client_credential_base import ClientCredentialBase if TYPE_CHECKING: - from typing import Any + from typing import Any, Optional, Union class CertificateCredential(ClientCredentialBase): @@ -22,11 +22,13 @@ class CertificateCredential(ClientCredentialBase): :param str tenant_id: ID of the service principal's tenant. Also called its 'directory' ID. :param str client_id: the service principal's client ID - :param str certificate_path: path to a PEM-encoded certificate file including the private key. + :param str certificate_path: path to a PEM-encoded certificate file including the private key. If not provided, + `certificate_bytes` is required. :keyword str authority: Authority of an Azure Active Directory endpoint, for example 'login.microsoftonline.com', the authority for Azure Public Cloud (which is the default). :class:`~azure.identity.AzureAuthorityHosts` defines authorities for other clouds. + :keyword bytes certificate_bytes: the bytes of a certificate in PEM format, including the private key :keyword password: The certificate's password. If a unicode string, it will be encoded as UTF-8. If the certificate requires a different encoding, pass appropriately encoded bytes instead. :paramtype password: str or bytes @@ -39,37 +41,11 @@ class CertificateCredential(ClientCredentialBase): is unavailable. Default to False. Has no effect when `enable_persistent_cache` is False. """ - def __init__(self, tenant_id, client_id, certificate_path, **kwargs): - # type: (str, str, str, **Any) -> None + def __init__(self, tenant_id, client_id, certificate_path=None, **kwargs): + # type: (str, str, Optional[str], **Any) -> None validate_tenant_id(tenant_id) - if not certificate_path: - raise ValueError( - "'certificate_path' must be the path to a PEM file containing an x509 certificate and its private key" - ) - password = kwargs.pop("password", None) - if isinstance(password, six.text_type): - password = password.encode(encoding="utf-8") - - with open(certificate_path, "rb") as f: - pem_bytes = f.read() - - cert = x509.load_pem_x509_certificate(pem_bytes, default_backend()) - fingerprint = cert.fingerprint(hashes.SHA1()) # nosec - - client_credential = {"private_key": pem_bytes, "thumbprint": hexlify(fingerprint).decode("utf-8")} - if password: - client_credential["passphrase"] = password - - if kwargs.pop("send_certificate_chain", False): - try: - # the JWT needs the whole chain but load_pem_x509_certificate deserializes only the signing cert - chain = extract_cert_chain(pem_bytes) - client_credential["public_certificate"] = six.ensure_str(chain) - except ValueError as ex: - # we shouldn't land here, because load_pem_private_key should have raised when given a malformed file - message = 'Found no PEM encoded certificate in "{}"'.format(certificate_path) - six.raise_from(ValueError(message), ex) + client_credential = get_client_credential(certificate_path, **kwargs) super(CertificateCredential, self).__init__( client_id=client_id, client_credential=client_credential, tenant_id=tenant_id, **kwargs @@ -84,6 +60,38 @@ def extract_cert_chain(pem_bytes): start = pem_bytes.index(b"-----BEGIN CERTIFICATE-----") footer = b"-----END CERTIFICATE-----" end = pem_bytes.rindex(footer) - chain = pem_bytes[start:end + len(footer) + 1] + chain = pem_bytes[start : end + len(footer) + 1] return b"".join(chain.splitlines()) + + +def get_client_credential(certificate_path, password=None, certificate_bytes=None, send_certificate_chain=False, **_): + # type: (Optional[str], Optional[Union[bytes, str]], Optional[bytes], bool, **Any) -> dict + """Load a certificate from a filesystem path or bytes, return it as a dict suitable for msal.ClientApplication""" + + if certificate_path: + with open(certificate_path, "rb") as f: + certificate_bytes = f.read() + elif not certificate_bytes: + raise ValueError('This credential requires a value for "certificate_path" or "certificate_bytes"') + + if isinstance(password, six.text_type): + password = password.encode(encoding="utf-8") + + cert = x509.load_pem_x509_certificate(certificate_bytes, default_backend()) + fingerprint = cert.fingerprint(hashes.SHA1()) # nosec + + client_credential = {"private_key": certificate_bytes, "thumbprint": hexlify(fingerprint).decode("utf-8")} + if password: + client_credential["passphrase"] = password + + if send_certificate_chain: + try: + # the JWT needs the whole chain but load_pem_x509_certificate deserializes only the signing cert + chain = extract_cert_chain(certificate_bytes) + client_credential["public_certificate"] = six.ensure_str(chain) + except ValueError as ex: + # we shouldn't land here--cryptography already loaded the cert and would have raised if it were malformed + six.raise_from(ValueError("Malformed certificate"), ex) + + return client_credential diff --git a/sdk/identity/azure-identity/azure/identity/_internal/__init__.py b/sdk/identity/azure-identity/azure/identity/_internal/__init__.py index 46b420b5b1a7..da0c1ff1e20a 100644 --- a/sdk/identity/azure-identity/azure/identity/_internal/__init__.py +++ b/sdk/identity/azure-identity/azure/identity/_internal/__init__.py @@ -47,7 +47,6 @@ def validate_tenant_id(tenant_id): from .aad_client_base import AadClientBase from .auth_code_redirect_handler import AuthCodeRedirectServer from .aadclient_certificate import AadClientCertificate -from .certificate_credential_base import CertificateCredentialBase from .client_secret_credential_base import ClientSecretCredentialBase from .decorators import wrap_exceptions from .interactive import InteractiveCredential @@ -72,7 +71,6 @@ def _scopes_to_resource(*scopes): "AadClientBase", "AuthCodeRedirectServer", "AadClientCertificate", - "CertificateCredentialBase", "ClientSecretCredentialBase", "get_default_authority", "InteractiveCredential", diff --git a/sdk/identity/azure-identity/azure/identity/_internal/certificate_credential_base.py b/sdk/identity/azure-identity/azure/identity/_internal/certificate_credential_base.py deleted file mode 100644 index 32524d3d5682..000000000000 --- a/sdk/identity/azure-identity/azure/identity/_internal/certificate_credential_base.py +++ /dev/null @@ -1,61 +0,0 @@ -# ------------------------------------ -# Copyright (c) Microsoft Corporation. -# Licensed under the MIT License. -# ------------------------------------ -import abc - -from msal import TokenCache -import six - -from . import AadClientCertificate -from .persistent_cache import load_service_principal_cache -from .._internal import validate_tenant_id - -try: - ABC = abc.ABC -except AttributeError: # Python 2.7, abc exists, but not ABC - ABC = abc.ABCMeta("ABC", (object,), {"__slots__": ()}) # type: ignore - -try: - from typing import TYPE_CHECKING -except ImportError: - TYPE_CHECKING = False - -if TYPE_CHECKING: - # pylint:disable=unused-import - from typing import Any - - -class CertificateCredentialBase(ABC): - def __init__(self, tenant_id, client_id, certificate_path, **kwargs): - # type: (str, str, str, **Any) -> None - validate_tenant_id(tenant_id) - if not certificate_path: - raise ValueError( - "'certificate_path' must be the path to a PEM file containing an x509 certificate and its private key" - ) - - super(CertificateCredentialBase, self).__init__() - - password = kwargs.pop("password", None) - if isinstance(password, six.text_type): - password = password.encode(encoding="utf-8") - - with open(certificate_path, "rb") as f: - pem_bytes = f.read() - - self._certificate = AadClientCertificate(pem_bytes, password=password) - - enable_persistent_cache = kwargs.pop("enable_persistent_cache", False) - if enable_persistent_cache: - allow_unencrypted = kwargs.pop("allow_unencrypted_cache", False) - cache = load_service_principal_cache(allow_unencrypted) - else: - cache = TokenCache() - - self._client = self._get_auth_client(tenant_id, client_id, cache=cache, **kwargs) - self._client_id = client_id - - @abc.abstractmethod - def _get_auth_client(self, tenant_id, client_id, **kwargs): - pass diff --git a/sdk/identity/azure-identity/azure/identity/aio/_credentials/certificate.py b/sdk/identity/azure-identity/azure/identity/aio/_credentials/certificate.py index 68ac0b8a0539..ef56142a76b5 100644 --- a/sdk/identity/azure-identity/azure/identity/aio/_credentials/certificate.py +++ b/sdk/identity/azure-identity/azure/identity/aio/_credentials/certificate.py @@ -4,30 +4,56 @@ # ------------------------------------ from typing import TYPE_CHECKING +from msal import TokenCache + from .._internal import AadClient, AsyncContextManager from .._internal.decorators import log_get_token_async -from ..._internal import CertificateCredentialBase +from ..._credentials.certificate import get_client_credential +from ..._internal import AadClientCertificate, validate_tenant_id +from ..._internal.persistent_cache import load_service_principal_cache if TYPE_CHECKING: - from typing import Any + from typing import Any, Optional from azure.core.credentials import AccessToken -class CertificateCredential(CertificateCredentialBase, AsyncContextManager): +class CertificateCredential(AsyncContextManager): """Authenticates as a service principal using a certificate. :param str tenant_id: ID of the service principal's tenant. Also called its 'directory' ID. :param str client_id: the service principal's client ID - :param str certificate_path: path to a PEM-encoded certificate file including the private key + :param str certificate_path: path to a PEM-encoded certificate file including the private key. If not provided, + `certificate_bytes` is required. :keyword str authority: Authority of an Azure Active Directory endpoint, for example 'login.microsoftonline.com', the authority for Azure Public Cloud (which is the default). :class:`~azure.identity.AzureAuthorityHosts` defines authorities for other clouds. + :keyword bytes certificate_bytes: the bytes of a certificate in PEM format, including the private key :keyword password: The certificate's password. If a unicode string, it will be encoded as UTF-8. If the certificate requires a different encoding, pass appropriately encoded bytes instead. :paramtype password: str or bytes """ + def __init__(self, tenant_id, client_id, certificate_path=None, **kwargs): + # type: (str, str, Optional[str], **Any) -> None + validate_tenant_id(tenant_id) + + client_credential = get_client_credential(certificate_path, **kwargs) + + self._certificate = AadClientCertificate( + client_credential["private_key"], password=client_credential.get("passphrase") + ) + + enable_persistent_cache = kwargs.pop("enable_persistent_cache", False) + if enable_persistent_cache: + allow_unencrypted = kwargs.pop("allow_unencrypted_cache", False) + cache = load_service_principal_cache(allow_unencrypted) + else: + cache = TokenCache() + + self._client = AadClient(tenant_id, client_id, cache=cache, **kwargs) + self._client_id = client_id + async def __aenter__(self): await self._client.__aenter__() return self @@ -61,6 +87,3 @@ async def get_token(self, *scopes: str, **kwargs: "Any") -> "AccessToken": # py except Exception: # pylint: disable=broad-except pass return token - - def _get_auth_client(self, tenant_id, client_id, **kwargs): - return AadClient(tenant_id, client_id, **kwargs) diff --git a/sdk/identity/azure-identity/conftest.py b/sdk/identity/azure-identity/conftest.py index c176fc659d34..fbca098472cd 100644 --- a/sdk/identity/azure-identity/conftest.py +++ b/sdk/identity/azure-identity/conftest.py @@ -6,6 +6,7 @@ import sys import pytest +import six from azure.identity._constants import DEVELOPER_SIGN_ON_CLIENT_ID, EnvironmentVariables @@ -62,43 +63,32 @@ def live_service_principal(): # pylint:disable=inconsistent-return-statements @pytest.fixture() -def live_certificate(live_service_principal): # pylint:disable=inconsistent-return-statements,redefined-outer-name - """Provides a path to a PEM-encoded certificate with no password""" - - pem_content = os.environ.get("PEM_CONTENT") - if not pem_content: - pytest.skip("Expected PEM content in environment variable 'PEM_CONTENT'") - return - - pem_path = os.path.join(os.path.dirname(__file__), "certificate.pem") - try: - with open(pem_path, "w") as pem_file: - pem_file.write(pem_content) - return dict(live_service_principal, cert_path=pem_path) - except IOError as ex: - pytest.skip("Failed to write file '{}': {}".format(pem_path, ex)) +def live_certificate(live_service_principal): + content = os.environ.get("PEM_CONTENT") + password_protected_content = os.environ.get("PEM_CONTENT_PASSWORD_PROTECTED") + password = os.environ.get("CERTIFICATE_PASSWORD") + if content and password_protected_content and password: + current_directory = os.path.dirname(__file__) + parameters = { + "cert_bytes": six.ensure_binary(content), + "cert_path": os.path.join(current_directory, "certificate.pem"), + "cert_with_password_bytes": six.ensure_binary(password_protected_content), + "cert_with_password_path": os.path.join(current_directory, "certificate-with-password.pem"), + "password": password, + } -@pytest.fixture() -def live_certificate_with_password(live_service_principal): - """Provides a path to a PEM-encoded, password-protected certificate, and its password""" + try: + with open(parameters["cert_path"], "wb") as f: + f.write(parameters["cert_bytes"]) + with open(parameters["cert_with_password_path"], "wb") as f: + f.write(parameters["cert_with_password_bytes"]) + except IOError as ex: + pytest.skip("Failed to write a file: {}".format(ex)) - pem_content = os.environ.get("PEM_CONTENT_PASSWORD_PROTECTED") - password = os.environ.get("CERTIFICATE_PASSWORD") - if not (pem_content and password): - pytest.skip( - "Expected password-protected PEM content in environment variable 'PEM_CONTENT_PASSWORD_PROTECTED'" - + " and the password in 'CERTIFICATE_PASSWORD'" - ) - return + return dict(live_service_principal, **parameters) - pem_path = os.path.join(os.path.dirname(__file__), "certificate-with-password.pem") - try: - with open(pem_path, "w") as pem_file: - pem_file.write(pem_content) - return dict(live_service_principal, cert_path=pem_path, password=password) - except IOError as ex: - pytest.skip("Failed to write file '{}': {}".format(pem_path, ex)) + pytest.skip("Missing PEM certificate configuration") @pytest.fixture() @@ -114,6 +104,7 @@ def live_user_details(): else: return user_details + @pytest.fixture() def event_loop(): """Ensure the event loop used by pytest-asyncio on Windows is ProactorEventLoop, which supports subprocesses. diff --git a/sdk/identity/azure-identity/tests/test_certificate_credential.py b/sdk/identity/azure-identity/tests/test_certificate_credential.py index d8562fd36094..f2f756faf24d 100644 --- a/sdk/identity/azure-identity/tests/test_certificate_credential.py +++ b/sdk/identity/azure-identity/tests/test_certificate_credential.py @@ -125,6 +125,21 @@ def test_authority(authority): assert kwargs["authority"] == expected_authority +def test_requires_certificate(): + """the credential should raise ValueError when not given a certificate""" + + with pytest.raises(ValueError): + CertificateCredential("tenant", "client-id") + with pytest.raises(ValueError): + CertificateCredential("tenant", "client-id", certificate_path=None) + with pytest.raises(ValueError): + CertificateCredential("tenant", "client-id", certificate_path="") + with pytest.raises(ValueError): + CertificateCredential("tenant", "client-id", certificate_bytes=None) + with pytest.raises(ValueError): + CertificateCredential("tenant", "client-id", certificate_path="", certificate_bytes=None) + + @pytest.mark.parametrize("cert_path,cert_password", BOTH_CERTS) @pytest.mark.parametrize("send_certificate_chain", (True, False)) def test_request_body(cert_path, cert_password, send_certificate_chain): @@ -158,6 +173,22 @@ def mock_send(request, **kwargs): token = cred.get_token(expected_scope) assert token.token == access_token + # credential should also accept the certificate as bytes + with open(cert_path, "rb") as f: + cert_bytes = f.read() + + cred = CertificateCredential( + tenant_id, + client_id, + certificate_bytes=cert_bytes, + password=cert_password, + transport=Mock(send=mock_send), + authority=authority, + send_certificate_chain=send_certificate_chain, + ) + token = cred.get_token(expected_scope) + assert token.token == access_token + def validate_jwt(request, client_id, pem_bytes, expect_x5c=False): """Validate the request meets AAD's expectations for a client credential grant using a certificate, as documented diff --git a/sdk/identity/azure-identity/tests/test_certificate_credential_async.py b/sdk/identity/azure-identity/tests/test_certificate_credential_async.py index 973994be2b9c..61d0ca14ce3c 100644 --- a/sdk/identity/azure-identity/tests/test_certificate_credential_async.py +++ b/sdk/identity/azure-identity/tests/test_certificate_credential_async.py @@ -123,6 +123,21 @@ async def mock_send(request, **kwargs): assert token.token == access_token +def test_requires_certificate(): + """the credential should raise ValueError when not given a certificate""" + + with pytest.raises(ValueError): + CertificateCredential("tenant", "client-id") + with pytest.raises(ValueError): + CertificateCredential("tenant", "client-id", certificate_path=None) + with pytest.raises(ValueError): + CertificateCredential("tenant", "client-id", certificate_path="") + with pytest.raises(ValueError): + CertificateCredential("tenant", "client-id", certificate_bytes=None) + with pytest.raises(ValueError): + CertificateCredential("tenant", "client-id", certificate_path="", certificate_bytes=None) + + @pytest.mark.asyncio @pytest.mark.parametrize("cert_path,cert_password", BOTH_CERTS) async def test_request_body(cert_path, cert_password): @@ -144,8 +159,22 @@ async def mock_send(request, **kwargs): cred = CertificateCredential( tenant_id, client_id, cert_path, password=cert_password, transport=Mock(send=mock_send), authority=authority ) - token = await cred.get_token("scope") + token = await cred.get_token(expected_scope) + assert token.token == access_token + # credential should also accept the certificate as bytes + with open(cert_path, "rb") as f: + cert_bytes = f.read() + + cred = CertificateCredential( + tenant_id, + client_id, + certificate_bytes=cert_bytes, + password=cert_password, + transport=Mock(send=mock_send), + authority=authority, + ) + token = await cred.get_token(expected_scope) assert token.token == access_token diff --git a/sdk/identity/azure-identity/tests/test_live.py b/sdk/identity/azure-identity/tests/test_live.py index 0d0ce074e8f9..9ffe032b58bf 100644 --- a/sdk/identity/azure-identity/tests/test_live.py +++ b/sdk/identity/azure-identity/tests/test_live.py @@ -25,18 +25,25 @@ def get_token(credential): def test_certificate_credential(live_certificate): + tenant_id = live_certificate["tenant_id"] + client_id = live_certificate["client_id"] + + credential = CertificateCredential(tenant_id, client_id, live_certificate["cert_path"]) + get_token(credential) + credential = CertificateCredential( - live_certificate["tenant_id"], live_certificate["client_id"], live_certificate["cert_path"] + tenant_id, client_id, live_certificate["cert_with_password_path"], password=live_certificate["password"] ) get_token(credential) + credential = CertificateCredential(tenant_id, client_id, certificate_bytes=live_certificate["cert_bytes"]) + get_token(credential) -def test_certificate_credential_with_password(live_certificate_with_password): credential = CertificateCredential( - live_certificate_with_password["tenant_id"], - live_certificate_with_password["client_id"], - live_certificate_with_password["cert_path"], - password=live_certificate_with_password["password"], + tenant_id, + client_id, + certificate_bytes=live_certificate["cert_with_password_bytes"], + password=live_certificate["password"], ) get_token(credential) diff --git a/sdk/identity/azure-identity/tests/test_live_async.py b/sdk/identity/azure-identity/tests/test_live_async.py index c85f66020b9a..c125a6da6336 100644 --- a/sdk/identity/azure-identity/tests/test_live_async.py +++ b/sdk/identity/azure-identity/tests/test_live_async.py @@ -18,19 +18,25 @@ async def get_token(credential): @pytest.mark.asyncio async def test_certificate_credential(live_certificate): + tenant_id = live_certificate["tenant_id"] + client_id = live_certificate["client_id"] + + credential = CertificateCredential(tenant_id, client_id, live_certificate["cert_path"]) + await get_token(credential) + credential = CertificateCredential( - live_certificate["tenant_id"], live_certificate["client_id"], live_certificate["cert_path"] + tenant_id, client_id, live_certificate["cert_with_password_path"], password=live_certificate["password"] ) await get_token(credential) + credential = CertificateCredential(tenant_id, client_id, certificate_bytes=live_certificate["cert_bytes"]) + await get_token(credential) -@pytest.mark.asyncio -async def test_certificate_credential_with_password(live_certificate_with_password): credential = CertificateCredential( - live_certificate_with_password["tenant_id"], - live_certificate_with_password["client_id"], - live_certificate_with_password["cert_path"], - password=live_certificate_with_password["password"], + tenant_id, + client_id, + certificate_bytes=live_certificate["cert_with_password_bytes"], + password=live_certificate["password"], ) await get_token(credential) diff --git a/sdk/servicebus/azure-servicebus/README.md b/sdk/servicebus/azure-servicebus/README.md index ea1df6a79816..a520a8d76dcc 100644 --- a/sdk/servicebus/azure-servicebus/README.md +++ b/sdk/servicebus/azure-servicebus/README.md @@ -458,6 +458,14 @@ For users seeking to perform management operations against ServiceBus (Creating please see the [azure-mgmt-servicebus documentation][service_bus_mgmt_docs] for API documentation. Terse usage examples can be found [here](https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/servicebus/azure-mgmt-servicebus/tests) as well. +### Building uAMQP wheel from source + +`azure-servicebus` depends on the [uAMQP](https://pypi.org/project/uamqp/) for the AMQP protocol implementation. +uAMQP wheels are provided for most major operating systems and will be installed automatically when installing `azure-servicebus`. + +If you're running on a platform for which uAMQP wheels are not provided, please follow + the [uAMQP Installation](https://github.com/Azure/azure-uamqp-python#installation) guidance to install from source. + ## Contributing This project welcomes contributions and suggestions. Most contributions require you to agree to a diff --git a/sdk/servicebus/azure-servicebus/azure/servicebus/_base_handler.py b/sdk/servicebus/azure-servicebus/azure/servicebus/_base_handler.py index 36e7e5a877fc..560bb289d4c7 100644 --- a/sdk/servicebus/azure-servicebus/azure/servicebus/_base_handler.py +++ b/sdk/servicebus/azure-servicebus/azure/servicebus/_base_handler.py @@ -10,9 +10,10 @@ from typing import cast, Optional, Tuple, TYPE_CHECKING, Dict, Any, Callable try: - from urllib import quote_plus # type: ignore + from urllib.parse import quote_plus, urlparse except ImportError: - from urllib.parse import quote_plus + from urllib import quote_plus # type: ignore + from urlparse import urlparse # type: ignore import uamqp from uamqp import utils, compat @@ -48,33 +49,37 @@ _LOGGER = logging.getLogger(__name__) -def _parse_conn_str(conn_str): - # type: (str) -> Tuple[str, Optional[str], Optional[str], str, Optional[str], Optional[int]] +def _parse_conn_str(conn_str, check_case=False): + # type: (str, Optional[bool]) -> Tuple[str, Optional[str], Optional[str], str, Optional[str], Optional[int]] endpoint = None shared_access_key_name = None shared_access_key = None entity_path = None # type: Optional[str] shared_access_signature = None # type: Optional[str] shared_access_signature_expiry = None # type: Optional[int] - for element in conn_str.strip().split(";"): - key, _, value = element.partition("=") - if key.lower() == "endpoint": - endpoint = value.rstrip("/") - elif key.lower() == "hostname": - endpoint = value.rstrip("/") - elif key.lower() == "sharedaccesskeyname": - shared_access_key_name = value - elif key.lower() == "sharedaccesskey": - shared_access_key = value - elif key.lower() == "entitypath": - entity_path = value - elif key.lower() == "sharedaccesssignature": + + # split connection string into properties + conn_properties = [s.split("=", 1) for s in conn_str.strip().rstrip(";").split(";")] + if any(len(tup) != 2 for tup in conn_properties): + raise ValueError("Connection string is either blank or malformed.") + conn_settings = dict(conn_properties) # type: ignore + + # case sensitive check when parsing for connection string properties + if check_case: + shared_access_key = conn_settings.get("SharedAccessKey") + shared_access_key_name = conn_settings.get("SharedAccessKeyName") + endpoint = conn_settings.get("Endpoint") + entity_path = conn_settings.get("EntityPath") + + # non case sensitive check when parsing connection string for internal use + for key, value in conn_settings.items(): + # only sas check is non case sensitive for both conn str properties and internal use + if key.lower() == "sharedaccesssignature": shared_access_signature = value try: # Expiry can be stored in the "se=" clause of the token. ('&'-separated key-value pairs) - # type: ignore shared_access_signature_expiry = int( - shared_access_signature.split("se=")[1].split("&")[0] + shared_access_signature.split("se=")[1].split("&")[0] # type: ignore ) except ( IndexError, @@ -83,19 +88,42 @@ def _parse_conn_str(conn_str): ): # Fallback since technically expiry is optional. # An arbitrary, absurdly large number, since you can't renew. shared_access_signature_expiry = int(time.time() * 2) - if not ( - all((endpoint, shared_access_key_name, shared_access_key)) - or all((endpoint, shared_access_signature)) - ) or all( - (shared_access_key_name, shared_access_signature) - ): # this latter clause since we don't accept both + if not check_case: + if key.lower() == "endpoint": + endpoint = value.rstrip("/") + elif key.lower() == "hostname": + endpoint = value.rstrip("/") + elif key.lower() == "sharedaccesskeyname": + shared_access_key_name = value + elif key.lower() == "sharedaccesskey": + shared_access_key = value + elif key.lower() == "entitypath": + entity_path = value + + entity = cast(str, entity_path) + + # check that endpoint is valid + if not endpoint: + raise ValueError("Connection string is either blank or malformed.") + parsed = urlparse(endpoint) + if not parsed.netloc: + raise ValueError("Invalid Endpoint on the Connection String.") + host = cast(str, parsed.netloc.strip()) + + if any([shared_access_key, shared_access_key_name]) and not all( + [shared_access_key, shared_access_key_name] + ): raise ValueError( - "Invalid connection string. Should be in the format: " - "Endpoint=sb:///;SharedAccessKeyName=;SharedAccessKey=" - "\nWith alternate option of providing SharedAccessSignature instead of SharedAccessKeyName and Key" + "Connection string must have both SharedAccessKeyName and SharedAccessKey." + ) + if shared_access_signature and shared_access_key: + raise ValueError( + "Only one of the SharedAccessKey or SharedAccessSignature must be present." + ) + if not shared_access_signature and not shared_access_key: + raise ValueError( + "At least one of the SharedAccessKey or SharedAccessSignature must be present." ) - entity = cast(str, entity_path) - host = cast(str, strip_protocol_from_uri(cast(str, endpoint))) return ( host, diff --git a/sdk/servicebus/azure-servicebus/azure/servicebus/_common/_connection_string_parser.py b/sdk/servicebus/azure-servicebus/azure/servicebus/_common/_connection_string_parser.py index a67f3816015c..466deaef0a62 100644 --- a/sdk/servicebus/azure-servicebus/azure/servicebus/_common/_connection_string_parser.py +++ b/sdk/servicebus/azure-servicebus/azure/servicebus/_common/_connection_string_parser.py @@ -2,13 +2,9 @@ # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------------------------------- -try: - from urllib.parse import urlparse -except ImportError: - from urlparse import urlparse # type: ignore - from ..management._models import DictMixin +from .._base_handler import _parse_conn_str class ServiceBusConnectionStringProperties(DictMixin): @@ -71,39 +67,14 @@ def parse_connection_string(conn_str): :type conn_str: str :rtype: ~azure.servicebus.ServiceBusConnectionStringProperties """ - conn_settings = [s.split("=", 1) for s in conn_str.split(";")] - if any(len(tup) != 2 for tup in conn_settings): - raise ValueError("Connection string is either blank or malformed.") - conn_settings = dict(conn_settings) - shared_access_signature = None - for key, value in conn_settings.items(): - if key.lower() == "sharedaccesssignature": - shared_access_signature = value - shared_access_key = conn_settings.get("SharedAccessKey") - shared_access_key_name = conn_settings.get("SharedAccessKeyName") - if any([shared_access_key, shared_access_key_name]) and not all( - [shared_access_key, shared_access_key_name] - ): - raise ValueError( - "Connection string must have both SharedAccessKeyName and SharedAccessKey." - ) - if shared_access_signature is not None and shared_access_key is not None: - raise ValueError( - "Only one of the SharedAccessKey or SharedAccessSignature must be present." - ) - endpoint = conn_settings.get("Endpoint") - if not endpoint: - raise ValueError("Connection string is either blank or malformed.") - parsed = urlparse(endpoint.rstrip("/")) - if not parsed.netloc: - raise ValueError("Invalid Endpoint on the Connection String.") - namespace = parsed.netloc.strip() + fully_qualified_namespace, policy, key, entity, signature = _parse_conn_str(conn_str, True)[:-1] + endpoint = "sb://" + fully_qualified_namespace + "/" props = { - "fully_qualified_namespace": namespace, + "fully_qualified_namespace": fully_qualified_namespace, "endpoint": endpoint, - "entity_path": conn_settings.get("EntityPath"), - "shared_access_signature": shared_access_signature, - "shared_access_key_name": shared_access_key_name, - "shared_access_key": shared_access_key, + "entity_path": entity, + "shared_access_signature": signature, + "shared_access_key_name": policy, + "shared_access_key": key, } return ServiceBusConnectionStringProperties(**props) diff --git a/sdk/servicebus/azure-servicebus/tests/test_connection_string_parser.py b/sdk/servicebus/azure-servicebus/tests/test_connection_string_parser.py index fd0657006f54..6877c1171ce4 100644 --- a/sdk/servicebus/azure-servicebus/tests/test_connection_string_parser.py +++ b/sdk/servicebus/azure-servicebus/tests/test_connection_string_parser.py @@ -34,6 +34,12 @@ def test_sb_parse_malformed_conn_str_no_endpoint(self, **kwargs): parse_result = parse_connection_string(conn_str) assert str(e.value) == 'Connection string is either blank or malformed.' + def test_sb_parse_malformed_conn_str_no_endpoint_value(self, **kwargs): + conn_str = 'Endpoint=;SharedAccessKeyName=test;SharedAccessKey=THISISATESTKEYXXXXXXXXXXXXXXXXXXXXXXXXXXXX=' + with pytest.raises(ValueError) as e: + parse_result = parse_connection_string(conn_str) + assert str(e.value) == 'Connection string is either blank or malformed.' + def test_sb_parse_malformed_conn_str_no_netloc(self, **kwargs): conn_str = 'Endpoint=MALFORMED;SharedAccessKeyName=test;SharedAccessKey=THISISATESTKEYXXXXXXXXXXXXXXXXXXXXXXXXXXXX=' with pytest.raises(ValueError) as e: @@ -48,6 +54,22 @@ def test_sb_parse_conn_str_sas(self, **kwargs): assert parse_result.shared_access_signature == 'THISISATESTKEYXXXXXXXXXXXXXXXXXXXXXXXXXXXX=' assert parse_result.shared_access_key_name == None + def test_sb_parse_conn_str_whitespace_trailing_semicolon(self, **kwargs): + conn_str = ' Endpoint=sb://resourcename.servicebus.windows.net/;SharedAccessSignature=THISISATESTKEYXXXXXXXXXXXXXXXXXXXXXXXXXXXX=; ' + parse_result = parse_connection_string(conn_str) + assert parse_result.endpoint == 'sb://resourcename.servicebus.windows.net/' + assert parse_result.fully_qualified_namespace == 'resourcename.servicebus.windows.net' + assert parse_result.shared_access_signature == 'THISISATESTKEYXXXXXXXXXXXXXXXXXXXXXXXXXXXX=' + assert parse_result.shared_access_key_name == None + + def test_sb_parse_conn_str_sas_trailing_semicolon(self, **kwargs): + conn_str = 'Endpoint=sb://resourcename.servicebus.windows.net/;SharedAccessSignature=THISISATESTKEYXXXXXXXXXXXXXXXXXXXXXXXXXXXX=;' + parse_result = parse_connection_string(conn_str) + assert parse_result.endpoint == 'sb://resourcename.servicebus.windows.net/' + assert parse_result.fully_qualified_namespace == 'resourcename.servicebus.windows.net' + assert parse_result.shared_access_signature == 'THISISATESTKEYXXXXXXXXXXXXXXXXXXXXXXXXXXXX=' + assert parse_result.shared_access_key_name == None + def test_sb_parse_conn_str_no_keyname(self, **kwargs): conn_str = 'Endpoint=sb://resourcename.servicebus.windows.net/;SharedAccessKey=THISISATESTKEYXXXXXXXXXXXXXXXXXXXXXXXXXXXX=' with pytest.raises(ValueError) as e: @@ -59,3 +81,27 @@ def test_sb_parse_conn_str_no_key(self, **kwargs): with pytest.raises(ValueError) as e: parse_result = parse_connection_string(conn_str) assert str(e.value) == 'Connection string must have both SharedAccessKeyName and SharedAccessKey.' + + def test_sb_parse_conn_str_no_key_or_sas(self, **kwargs): + conn_str = 'Endpoint=sb://resourcename.servicebus.windows.net/' + with pytest.raises(ValueError) as e: + parse_result = parse_connection_string(conn_str) + assert str(e.value) == 'At least one of the SharedAccessKey or SharedAccessSignature must be present.' + + def test_sb_parse_malformed_conn_str_lowercase_endpoint(self, **kwargs): + conn_str = 'endpoint=sb://resourcename.servicebus.windows.net/;SharedAccessKeyName=test;SharedAccessKey=THISISATESTKEYXXXXXXXXXXXXXXXXXXXXXXXXXXXX=' + with pytest.raises(ValueError) as e: + parse_result = parse_connection_string(conn_str) + assert str(e.value) == 'Connection string is either blank or malformed.' + + def test_sb_parse_malformed_conn_str_lowercase_sa_key_name(self, **kwargs): + conn_str = 'Endpoint=sb://resourcename.servicebus.windows.net/;sharedaccesskeyname=test;SharedAccessKey=THISISATESTKEYXXXXXXXXXXXXXXXXXXXXXXXXXXXX=' + with pytest.raises(ValueError) as e: + parse_result = parse_connection_string(conn_str) + assert str(e.value) == 'Connection string must have both SharedAccessKeyName and SharedAccessKey.' + + def test_sb_parse_malformed_conn_str_lowercase_sa_key_name(self, **kwargs): + conn_str = 'Endpoint=sb://resourcename.servicebus.windows.net/;SharedAccessKeyName=test;sharedaccesskey=THISISATESTKEYXXXXXXXXXXXXXXXXXXXXXXXXXXXX=' + with pytest.raises(ValueError) as e: + parse_result = parse_connection_string(conn_str) + assert str(e.value) == 'Connection string must have both SharedAccessKeyName and SharedAccessKey.' \ No newline at end of file diff --git a/sdk/tables/azure-data-tables/dev_requirements.txt b/sdk/tables/azure-data-tables/dev_requirements.txt index 09879429984a..164bdcbd37da 100644 --- a/sdk/tables/azure-data-tables/dev_requirements.txt +++ b/sdk/tables/azure-data-tables/dev_requirements.txt @@ -1,8 +1,8 @@ -e ../../../tools/azure-devtools -e ../../../tools/azure-sdk-tools +-e ../../cosmos/azure-mgmt-cosmosdb ../../core/azure-core +../azure-data-nspkg cryptography>=2.1.4 aiohttp>=3.0; python_version >= '3.5' --e ../../cosmos/azure-mgmt-cosmosdb azure-identity -../azure-data-nspkg diff --git a/sdk/textanalytics/azure-ai-textanalytics/CHANGELOG.md b/sdk/textanalytics/azure-ai-textanalytics/CHANGELOG.md index ec47b71e09db..65ff940755b6 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/CHANGELOG.md +++ b/sdk/textanalytics/azure-ai-textanalytics/CHANGELOG.md @@ -2,6 +2,15 @@ ## 5.1.0b5 (Unreleased) +**Breaking Changes** + +- Rename `begin_analyze` to `begin_analyze_batch_actions`. +- Now instead of separate parameters for all of the different types of actions you can pass to `begin_analyze_batch_actions`, we accept one parameter `actions`, +which is a list of actions you would like performed. The results of the actions are returned in the same order as when inputted. +- The response object from `begin_analyze_batch_actions` has also changed. Now, after the completion of your long running operation, we return a paged iterable +of action results, in the same order they've been inputted. The actual document results for each action are included under property `document_results` of +each action result. + **New Features** - No longer need to specify `api_version=TextAnalyticsApiVersion.V3_1_PREVIEW_3` when calling `begin_analyze` and `begin_analyze_healthcare`. `begin_analyze_healthcare` is still in gated preview though. - Added a new parameter `string_index_type` to the service client methods `begin_analyze_healthcare`, `analyze_sentiment`, `recognize_entities`, `recognize_pii_entities`, and `recognize_linked_entities`. diff --git a/sdk/textanalytics/azure-ai-textanalytics/README.md b/sdk/textanalytics/azure-ai-textanalytics/README.md index eab6ce91a4ee..01352ec67c45 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/README.md +++ b/sdk/textanalytics/azure-ai-textanalytics/README.md @@ -1,32 +1,36 @@ # Azure Text Analytics client library for Python -Text Analytics is a cloud-based service that provides advanced natural language processing over raw text, and includes six main functions: -* Sentiment Analysis -* Named Entity Recognition -* Linked Entity Recognition -* Personally Identifiable Information (PII) Entity Recognition -* Language Detection -* Key Phrase Extraction -* Healthcare Analysis (Gated Preview) +Text Analytics is a cloud-based service that provides advanced natural language processing over raw text, and includes the following main functions: -[Source code][source_code] | [Package (PyPI)][TA_pypi] | [API reference documentation][TA_ref_docs]| [Product documentation][TA_product_documentation] | [Samples][TA_samples] +- Sentiment Analysis +- Named Entity Recognition +- Linked Entity Recognition +- Personally Identifiable Information (PII) Entity Recognition +- Language Detection +- Key Phrase Extraction +- Batch Analysis +- Healthcare Analysis (Gated Preview) + +[Source code][source_code] | [Package (PyPI)][ta_pypi] | [API reference documentation][ta_ref_docs]| [Product documentation][ta_product_documentation] | [Samples][ta_samples] ## Getting started ### Prerequisites -* Python 2.7, or 3.5 or later is required to use this package. -* You must have an [Azure subscription][azure_subscription] and a -[Cognitive Services or Text Analytics resource][TA_or_CS_resource] to use this package. + +- Python 2.7, or 3.5 or later is required to use this package. +- You must have an [Azure subscription][azure_subscription] and a + [Cognitive Services or Text Analytics resource][ta_or_cs_resource] to use this package. #### Create a Cognitive Services or Text Analytics resource + Text Analytics supports both [multi-service and single-service access][multi_and_single_service]. Create a Cognitive Services resource if you plan to access multiple cognitive services under a single endpoint/key. For Text Analytics access only, create a Text Analytics resource. You can create the resource using -**Option 1:** [Azure Portal][azure_portal_create_TA_resource] +**Option 1:** [Azure Portal][azure_portal_create_ta_resource] -**Option 2:** [Azure CLI][azure_cli_create_TA_resource]. +**Option 2:** [Azure CLI][azure_cli_create_ta_resource]. Below is an example of how you can create a Text Analytics resource using the CLI: ```bash @@ -63,6 +67,7 @@ name for your resource the endpoint may look different than in the above code sn For example, `https://.cognitiveservices.azure.com/`. ### Install the package + Install the Azure Text Analytics client library for Python with [pip][pip]: ```bash @@ -73,14 +78,15 @@ pip install azure-ai-textanalytics --pre This table shows the relationship between SDK versions and supported API versions of the service -|SDK version|Supported API version of service -|-|- -|5.0.0 - Latest GA release (can be installed by removing the `--pre` flag)| 3.0 -|5.1.0b4 - Latest release (beta)| 3.0, 3.1-preview.2, 3.1-preview.3 - +| SDK version | Supported API version of service | +| ------------------------------------------------------------------------- | --------------------------------- | +| 5.0.0 - Latest GA release (can be installed by removing the `--pre` flag) | 3.0 | +| 5.1.0b4 - Latest release (beta) | 3.0, 3.1-preview.2, 3.1-preview.3 | ### Authenticate the client + #### Get the endpoint + You can find the endpoint for your text analytics resource using the [Azure Portal][azure_portal_get_endpoint] or [Azure CLI][azure_cli_endpoint_lookup]: @@ -91,12 +97,14 @@ az cognitiveservices account show --name "resource-name" --resource-group "resou ``` #### Get the API Key + You can get the [API key][cognitive_authentication_api_key] from the Cognitive Services or Text Analytics resource in the [Azure Portal][azure_portal_get_endpoint]. Alternatively, you can use [Azure CLI][azure_cli_endpoint_lookup] snippet below to get the API key of your resource. -```az cognitiveservices account keys list --name "resource-name" --resource-group "resource-group-name"``` +`az cognitiveservices account keys list --name "resource-name" --resource-group "resource-group-name"` #### Create a TextAnalyticsClient with an API Key Credential + Once you have the value for the API key, you can pass it as a string into an instance of [AzureKeyCredential][azure-key-credential]. Use the key as the credential parameter to authenticate the client: @@ -109,6 +117,7 @@ text_analytics_client = TextAnalyticsClient(endpoint="https://.api.cogni ``` #### Create a TextAnalyticsClient with an Azure Active Directory Credential + To use an [Azure Active Directory (AAD) token credential][cognitive_authentication_aad], provide an instance of the desired credential type obtained from the [azure-identity][azure_identity_credentials] library. @@ -116,9 +125,10 @@ Note that regional endpoints do not support AAD authentication. Create a [custom name for your resource in order to use this type of authentication. Authentication with AAD requires some initial setup: -* [Install azure-identity][install_azure_identity] -* [Register a new AAD application][register_aad_app] -* [Grant access][grant_role_access] to Text Analytics by assigning the `"Cognitive Services User"` role to your service principal. + +- [Install azure-identity][install_azure_identity] +- [Register a new AAD application][register_aad_app] +- [Grant access][grant_role_access] to Text Analytics by assigning the `"Cognitive Services User"` role to your service principal. After setup, you can choose which type of [credential][azure_identity_credentials] from azure.identity to use. As an example, [DefaultAzureCredential][default_azure_credential] @@ -128,6 +138,7 @@ Set the values of the client ID, tenant ID, and client secret of the AAD applica AZURE_CLIENT_ID, AZURE_TENANT_ID, AZURE_CLIENT_SECRET Use the returned token credential to authenticate the client: + ```python from azure.ai.textanalytics import TextAnalyticsClient from azure.identity import DefaultAzureCredential @@ -139,14 +150,17 @@ text_analytics_client = TextAnalyticsClient(endpoint="https://") @@ -482,50 +510,52 @@ text_analytics_client = TextAnalyticsClient(endpoint, credential) documents = ["Microsoft was founded by Bill Gates and Paul Allen."] -poller = text_analytics_client.begin_analyze( +poller = text_analytics_client.begin_analyze_batch_actions( documents, display_name="Sample Text Analysis", - entities_recognition_tasks=[EntitiesRecognitionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()] + actions=[ + RecognizeEntitiesAction(), + RecognizePiiEntitiesAction(), + ExtractKeyPhrasesAction(), + ] ) +# returns batch actions results in the same order as the inputted actions result = poller.result() -for page in result: - for task in page.entities_recognition_results: - print("Results of Entities Recognition task:") - - docs = [doc for doc in task.results if not doc.is_error] - for idx, doc in enumerate(docs): - print("\nDocument text: {}".format(documents[idx])) - for entity in doc.entities: - print("Entity: {}".format(entity.text)) - print("...Category: {}".format(entity.category)) - print("...Confidence Score: {}".format(entity.confidence_score)) - print("...Offset: {}".format(entity.offset)) - print("------------------------------------------") - - for task in page.pii_entities_recognition_results: - print("Results of PII Entities Recognition task:") - - docs = [doc for doc in task.results if not doc.is_error] - for idx, doc in enumerate(docs): - print("Document text: {}".format(documents[idx])) - for entity in doc.entities: - print("Entity: {}".format(entity.text)) - print("Category: {}".format(entity.category)) - print("Confidence Score: {}\n".format(entity.confidence_score)) - print("------------------------------------------") - - for task in page.key_phrase_extraction_results: - print("Results of Key Phrase Extraction task:") - - docs = [doc for doc in task.results if not doc.is_error] - for idx, doc in enumerate(docs): - print("Document text: {}\n".format(documents[idx])) - print("Key Phrases: {}\n".format(doc.key_phrases)) - print("------------------------------------------") +first_action_result = next(result) +print("Results of Entities Recognition action:") +docs = [doc for doc in first_action_result.document_results if not doc.is_error] + +for idx, doc in enumerate(docs): + print("\nDocument text: {}".format(documents[idx])) + for entity in doc.entities: + print("Entity: {}".format(entity.text)) + print("...Category: {}".format(entity.category)) + print("...Confidence Score: {}".format(entity.confidence_score)) + print("...Offset: {}".format(entity.offset)) + print("------------------------------------------") + +second_action_result = next(result) +print("Results of PII Entities Recognition action:") +docs = [doc for doc in second_action_result.document_results if not doc.is_error] + +for idx, doc in enumerate(docs): + print("Document text: {}".format(documents[idx])) + for entity in doc.entities: + print("Entity: {}".format(entity.text)) + print("Category: {}".format(entity.category)) + print("Confidence Score: {}\n".format(entity.confidence_score)) + print("------------------------------------------") + +third_action_result = next(result) +print("Results of Key Phrase Extraction action:") +docs = [doc for doc in third_action_result.document_results if not doc.is_error] + +for idx, doc in enumerate(docs): + print("Document text: {}\n".format(documents[idx])) + print("Key Phrases: {}\n".format(doc.key_phrases)) + print("------------------------------------------") ``` The returned response is an object encapsulating multiple iterables, each representing results of individual analyses. @@ -541,9 +571,11 @@ describes available configurations for retries, logging, transport protocols, an ## Troubleshooting ### General + The Text Analytics client will raise exceptions defined in [Azure Core][azure_core]. ### Logging + This library uses the standard [logging][python_logging] library for logging. Basic information about HTTP sessions (URLs, headers, etc.) is logged at INFO @@ -551,6 +583,7 @@ level. Detailed DEBUG level logging, including request/response bodies and unredacted headers, can be enabled on a client with the `logging_enable` keyword argument: + ```python import sys import logging @@ -575,6 +608,7 @@ result = text_analytics_client.analyze_sentiment(["I did not like the restaurant Similarly, `logging_enable` can enable detailed logging for a single operation, even when it isn't enabled for the client: + ```python result = text_analytics_client.analyze_sentiment(documents, logging_enable=True) ``` @@ -588,26 +622,31 @@ The async versions of the samples (the python sample files appended with `_async with Text Analytics and require Python 3.5 or later. Authenticate the client with a Cognitive Services/Text Analytics API key or a token credential from [azure-identity][azure_identity]: -* [sample_authentication.py][sample_authentication] ([async version][sample_authentication_async]) + +- [sample_authentication.py][sample_authentication] ([async version][sample_authentication_async]) Common scenarios -* Analyze sentiment: [sample_analyze_sentiment.py][analyze_sentiment_sample] ([async version][analyze_sentiment_sample_async]) -* Recognize entities: [sample_recognize_entities.py][recognize_entities_sample] ([async version][recognize_entities_sample_async]) -* Recognize personally identifiable information: [sample_recognize_pii_entities.py][recognize_pii_entities_sample]([async version][recognize_pii_entities_sample_async]) -* Recognize linked entities: [sample_recognize_linked_entities.py][recognize_linked_entities_sample] ([async version][recognize_linked_entities_sample_async]) -* Extract key phrases: [sample_extract_key_phrases.py][extract_key_phrases_sample] ([async version][extract_key_phrases_sample_async]) -* Detect language: [sample_detect_language.py][detect_language_sample] ([async version][detect_language_sample_async]) -* Healthcare Analysis: [sample_analyze_healthcare.py][analyze_healthcare_sample] ([async version][analyze_healthcare_sample_async]) -* Batch Analysis: [sample_anayze.py][analyze_sample] ([async version][analyze_sample_async]) + +- Analyze sentiment: [sample_analyze_sentiment.py][analyze_sentiment_sample] ([async version][analyze_sentiment_sample_async]) +- Recognize entities: [sample_recognize_entities.py][recognize_entities_sample] ([async version][recognize_entities_sample_async]) +- Recognize personally identifiable information: [sample_recognize_pii_entities.py][recognize_pii_entities_sample]([async version][recognize_pii_entities_sample_async]) +- Recognize linked entities: [sample_recognize_linked_entities.py][recognize_linked_entities_sample] ([async version][recognize_linked_entities_sample_async]) +- Extract key phrases: [sample_extract_key_phrases.py][extract_key_phrases_sample] ([async version][extract_key_phrases_sample_async]) +- Detect language: [sample_detect_language.py][detect_language_sample] ([async version][detect_language_sample_async]) +- Healthcare Analysis: [sample_analyze_healthcare.py][analyze_healthcare_sample] ([async version][analyze_healthcare_sample_async]) +- Batch Analysis: [sample_analyze_batch_actions.py][analyze_sample] ([async version][analyze_sample_async]) Advanced scenarios -* Opinion Mining: [sample_analyze_sentiment_with_opinion_mining.py][opinion_mining_sample] ([async_version][opinion_mining_sample_async]) + +- Opinion Mining: [sample_analyze_sentiment_with_opinion_mining.py][opinion_mining_sample] ([async_version][opinion_mining_sample_async]) ### Additional documentation -For more extensive documentation on Azure Cognitive Services Text Analytics, see the [Text Analytics documentation][TA_product_documentation] on docs.microsoft.com. + +For more extensive documentation on Azure Cognitive Services Text Analytics, see the [Text Analytics documentation][ta_product_documentation] on docs.microsoft.com. ## Contributing -This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit [cla.microsoft.com][cla]. + +This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit [cla.microsoft.com][cla]. When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA. @@ -616,16 +655,15 @@ This project has adopted the [Microsoft Open Source Code of Conduct][code_of_con [source_code]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics -[TA_pypi]: https://pypi.org/project/azure-ai-textanalytics/ -[TA_ref_docs]: https://aka.ms/azsdk-python-textanalytics-ref-docs -[TA_samples]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples -[TA_product_documentation]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/overview +[ta_pypi]: https://pypi.org/project/azure-ai-textanalytics/ +[ta_ref_docs]: https://aka.ms/azsdk-python-textanalytics-ref-docs +[ta_samples]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples +[ta_product_documentation]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/overview [azure_subscription]: https://azure.microsoft.com/free/ -[TA_or_CS_resource]: https://docs.microsoft.com/azure/cognitive-services/cognitive-services-apis-create-account?tabs=multiservice%2Cwindows +[ta_or_cs_resource]: https://docs.microsoft.com/azure/cognitive-services/cognitive-services-apis-create-account?tabs=multiservice%2Cwindows [pip]: https://pypi.org/project/pip/ - -[azure_portal_create_TA_resource]: https://ms.portal.azure.com/#create/Microsoft.CognitiveServicesTextAnalytics -[azure_cli_create_TA_resource]: https://docs.microsoft.com/azure/cognitive-services/cognitive-services-apis-create-account-cli?tabs=windows +[azure_portal_create_ta_resource]: https://ms.portal.azure.com/#create/Microsoft.CognitiveServicesTextAnalytics +[azure_cli_create_ta_resource]: https://docs.microsoft.com/azure/cognitive-services/cognitive-services-apis-create-account-cli?tabs=windows [multi_and_single_service]: https://docs.microsoft.com/azure/cognitive-services/cognitive-services-apis-create-account?tabs=multiservice%2Cwindows [azure_cli_endpoint_lookup]: https://docs.microsoft.com/cli/azure/cognitiveservices/account?view=azure-cli-latest#az-cognitiveservices-account-show [azure_portal_get_endpoint]: https://docs.microsoft.com/azure/cognitive-services/cognitive-services-apis-create-account?tabs=multiservice%2Cwindows#get-the-keys-for-your-resource @@ -641,7 +679,6 @@ This project has adopted the [Microsoft Open Source Code of Conduct][code_of_con [default_azure_credential]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/identity/azure-identity#defaultazurecredential [service_limits]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/overview#data-limits [azure-key-credential]: https://aka.ms/azsdk-python-core-azurekeycredential - [document_error]: https://aka.ms/azsdk-python-textanalytics-documenterror [detect_language_result]: https://aka.ms/azsdk-python-textanalytics-detectlanguageresult [recognize_entities_result]: https://aka.ms/azsdk-python-textanalytics-recognizeentitiesresult @@ -652,14 +689,12 @@ This project has adopted the [Microsoft Open Source Code of Conduct][code_of_con [text_document_input]: https://aka.ms/azsdk-python-textanalytics-textdocumentinput [detect_language_input]: https://aka.ms/azsdk-python-textanalytics-detectlanguageinput [text_analytics_client]: https://aka.ms/azsdk-python-textanalytics-textanalyticsclient - [analyze_sentiment]: https://aka.ms/azsdk-python-textanalytics-analyzesentiment [recognize_entities]: https://aka.ms/azsdk-python-textanalytics-recognizeentities [recognize_pii_entities]: https://aka.ms/azsdk-python-textanalytics-recognizepiientities [recognize_linked_entities]: https://aka.ms/azsdk-python-textanalytics-recognizelinkedentities [extract_key_phrases]: https://aka.ms/azsdk-python-textanalytics-extractkeyphrases [detect_language]: https://aka.ms/azsdk-python-textanalytics-detectlanguage - [language_detection]: https://docs.microsoft.com/azure/cognitive-services/Text-Analytics/how-tos/text-analytics-how-to-language-detection [language_and_regional_support]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/language-support [sentiment_analysis]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-sentiment-analysis @@ -669,7 +704,6 @@ This project has adopted the [Microsoft Open Source Code of Conduct][code_of_con [pii_entity_categories]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/named-entity-types?tabs=personal [named_entity_recognition]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-entity-linking [named_entity_categories]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/named-entity-types?tabs=general - [azure_core_ref_docs]: https://aka.ms/azsdk-python-core-policies [azure_core]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/core/azure-core/README.md [azure_identity]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/identity/azure-identity @@ -690,12 +724,10 @@ This project has adopted the [Microsoft Open Source Code of Conduct][code_of_con [recognize_pii_entities_sample_async]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_recognize_pii_entities_async.py [analyze_healthcare_sample]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples/sample_analyze_healthcare.py [analyze_healthcare_sample_async]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_analyze_healthcare_async.py -[analyze_sample]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples/sample_analyze.py -[analyze_sample_async]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_analyze_async.py - +[analyze_sample]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples/sample_analyze_batch_actions.py +[analyze_sample_async]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_analyze_batch_actions_async.py [opinion_mining_sample]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples/sample_analyze_sentiment_with_opinion_mining.py [opinion_mining_sample_async]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_analyze_sentiment_with_opinion_mining_async.py - [cla]: https://cla.microsoft.com [code_of_conduct]: https://opensource.microsoft.com/codeofconduct/ [coc_faq]: https://opensource.microsoft.com/codeofconduct/faq/ diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/__init__.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/__init__.py index 5395ff76bc8c..9b0d0bc5ddfb 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/__init__.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/__init__.py @@ -36,11 +36,13 @@ HealthcareEntity, HealthcareRelation, HealthcareEntityLink, - EntitiesRecognitionTask, - PiiEntitiesRecognitionTask, - KeyPhraseExtractionTask, - TextAnalysisResult, - RequestStatistics + RecognizeEntitiesAction, + RecognizePiiEntitiesAction, + ExtractKeyPhrasesAction, + AnalyzeBatchActionsResult, + RequestStatistics, + AnalyzeBatchActionsType, + AnalyzeBatchActionsError, ) from._paging import AnalyzeHealthcareResult @@ -76,11 +78,13 @@ 'HealthcareEntity', 'HealthcareRelation', 'HealthcareEntityLink', - 'EntitiesRecognitionTask', - 'PiiEntitiesRecognitionTask', - 'KeyPhraseExtractionTask', - 'TextAnalysisResult', - 'RequestStatistics' + 'RecognizeEntitiesAction', + 'RecognizePiiEntitiesAction', + 'ExtractKeyPhrasesAction', + 'AnalyzeBatchActionsResult', + 'RequestStatistics', + 'AnalyzeBatchActionsType', + "AnalyzeBatchActionsError", ] __version__ = VERSION diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_async_lro.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_async_lro.py index 8d075c7a97c1..2f6fd71f93f8 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_async_lro.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_async_lro.py @@ -6,6 +6,8 @@ from azure.core.polling.base_polling import OperationFailed, BadStatus from azure.core.polling.async_base_polling import AsyncLROBasePolling +from azure.core.polling import AsyncLROPoller +from azure.core.polling._async_poller import PollingReturnType _FINISHED = frozenset(["succeeded", "cancelled", "failed", "partiallysucceeded"]) @@ -73,3 +75,101 @@ async def _poll(self): # pylint:disable=invalid-overridden-method TextAnalyticsAsyncLROPollingMethod._raise_if_bad_http_status_and_method( self._pipeline_response.http_response ) + +class AsyncAnalyzeBatchActionsLROPollingMethod(TextAnalyticsAsyncLROPollingMethod): + + @property + def _current_body(self): + from ._generated.v3_1_preview_3.models import JobMetadata + return JobMetadata.deserialize(self._pipeline_response) + + @property + def created_on(self): + if not self._current_body: + return None + return self._current_body.created_date_time + + @property + def display_name(self): + if not self._current_body: + return None + return self._current_body.display_name + + @property + def expires_on(self): + if not self._current_body: + return None + return self._current_body.expiration_date_time + + @property + def actions_failed_count(self): + if not self._current_body: + return None + return self._current_body.additional_properties['tasks']['failed'] + + @property + def actions_in_progress_count(self): + if not self._current_body: + return None + return self._current_body.additional_properties['tasks']['inProgress'] + + @property + def actions_succeeded_count(self): + if not self._current_body: + return None + return self._current_body.additional_properties['tasks']["completed"] + + @property + def last_modified_on(self): + if not self._current_body: + return None + return self._current_body.last_update_date_time + + @property + def total_actions_count(self): + if not self._current_body: + return None + return self._current_body.additional_properties['tasks']["total"] + + @property + def id(self): + if not self._current_body: + return None + return self._current_body.job_id + +class AsyncAnalyzeBatchActionsLROPoller(AsyncLROPoller[PollingReturnType]): + + @property + def created_on(self): + return self._polling_method.created_on + + @property + def display_name(self): + return self._polling_method.display_name + + @property + def expires_on(self): + return self._polling_method.expires_on + + @property + def actions_failed_count(self): + return self._polling_method.actions_failed_count + + @property + def actions_in_progress_count(self): + return self._polling_method.actions_in_progress_count + + @property + def actions_succeeded_count(self): + return self._polling_method.actions_succeeded_count + + @property + def last_modified_on(self): + return self._polling_method.last_modified_on + @property + def total_actions_count(self): + return self._polling_method.total_actions_count + + @property + def id(self): + return self._polling_method.id diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/_operations_mixin.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/_operations_mixin.py index 0b6c482fa211..dd1be3b9a11e 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/_operations_mixin.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/_operations_mixin.py @@ -12,6 +12,8 @@ from typing import TYPE_CHECKING import warnings +# FIXME: have to manually reconfigure import path for multiapi operation mixin +from .._lro import AnalyzeBatchActionsLROPoller, AnalyzeBatchActionsLROPollingMethod from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error from azure.core.pipeline import PipelineResponse from azure.core.pipeline.transport import HttpRequest, HttpResponse @@ -82,12 +84,12 @@ def begin_analyze( :type body: ~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeBatchInput :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. - :keyword polling: Pass in True if you'd like the LROBasePolling polling method, + :keyword polling: Pass in True if you'd like the AnalyzeBatchActionsLROPollingMethod polling method, False for no polling, or your own initialized polling object for a personal polling strategy. :paramtype polling: bool or ~azure.core.polling.PollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. - :return: An instance of LROPoller that returns either None or the result of cls(response) - :rtype: ~azure.core.polling.LROPoller[None] + :return: An instance of AnalyzeBatchActionsLROPoller that returns either AnalyzeJobState or the result of cls(response) + :rtype: ~...._lro.AnalyzeBatchActionsLROPoller[~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeJobState] :raises ~azure.core.exceptions.HttpResponseError: """ api_version = self._get_api_version('begin_analyze') @@ -160,12 +162,12 @@ def begin_health( :type string_index_type: str or ~azure.ai.textanalytics.v3_1_preview_3.models.StringIndexType :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. - :keyword polling: Pass in True if you'd like the LROBasePolling polling method, + :keyword polling: Pass in True if you'd like the AnalyzeBatchActionsLROPollingMethod polling method, False for no polling, or your own initialized polling object for a personal polling strategy. :paramtype polling: bool or ~azure.core.polling.PollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. - :return: An instance of LROPoller that returns either None or the result of cls(response) - :rtype: ~azure.core.polling.LROPoller[None] + :return: An instance of AnalyzeBatchActionsLROPoller that returns either HealthcareJobState or the result of cls(response) + :rtype: ~...._lro.AnalyzeBatchActionsLROPoller[~azure.ai.textanalytics.v3_1_preview_3.models.HealthcareJobState] :raises ~azure.core.exceptions.HttpResponseError: """ api_version = self._get_api_version('begin_health') diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/aio/_operations_mixin.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/aio/_operations_mixin.py index f6c7cd262866..101c1b1cf923 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/aio/_operations_mixin.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/aio/_operations_mixin.py @@ -12,6 +12,8 @@ from typing import Any, Callable, Dict, Generic, List, Optional, TypeVar, Union import warnings +# FIXME: have to manually reconfigure import path for multiapi operation mixin +from ..._async_lro import AsyncAnalyzeBatchActionsLROPoller, AsyncAnalyzeBatchActionsLROPollingMethod from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error from azure.core.pipeline import PipelineResponse from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest @@ -68,7 +70,7 @@ async def begin_analyze( self, body: Optional["_models.AnalyzeBatchInput"] = None, **kwargs - ) -> AsyncLROPoller[None]: + ) -> AsyncAnalyzeBatchActionsLROPoller["_models.AnalyzeJobState"]: """Submit analysis job. Submit a collection of text documents for analysis. Specify one or more unique tasks to be @@ -78,12 +80,12 @@ async def begin_analyze( :type body: ~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeBatchInput :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. - :keyword polling: Pass in True if you'd like the AsyncLROBasePolling polling method, + :keyword polling: Pass in True if you'd like the AsyncAnalyzeBatchActionsLROPollingMethod polling method, False for no polling, or your own initialized polling object for a personal polling strategy. :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. - :return: An instance of AsyncLROPoller that returns either None or the result of cls(response) - :rtype: ~azure.core.polling.AsyncLROPoller[None] + :return: An instance of AsyncAnalyzeBatchActionsLROPoller that returns either AnalyzeJobState or the result of cls(response) + :rtype: ~...._async_lro.AsyncAnalyzeBatchActionsLROPoller[~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeJobState] :raises ~azure.core.exceptions.HttpResponseError: """ api_version = self._get_api_version('begin_analyze') @@ -139,7 +141,7 @@ async def begin_health( model_version: Optional[str] = None, string_index_type: Optional[Union[str, "_models.StringIndexType"]] = "TextElements_v8", **kwargs - ) -> AsyncLROPoller[None]: + ) -> AsyncAnalyzeBatchActionsLROPoller["_models.HealthcareJobState"]: """Submit healthcare analysis job. Start a healthcare analysis job to recognize healthcare related entities (drugs, conditions, @@ -156,12 +158,12 @@ async def begin_health( :type string_index_type: str or ~azure.ai.textanalytics.v3_1_preview_3.models.StringIndexType :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. - :keyword polling: Pass in True if you'd like the AsyncLROBasePolling polling method, + :keyword polling: Pass in True if you'd like the AsyncAnalyzeBatchActionsLROPollingMethod polling method, False for no polling, or your own initialized polling object for a personal polling strategy. :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. - :return: An instance of AsyncLROPoller that returns either None or the result of cls(response) - :rtype: ~azure.core.polling.AsyncLROPoller[None] + :return: An instance of AsyncAnalyzeBatchActionsLROPoller that returns either HealthcareJobState or the result of cls(response) + :rtype: ~...._async_lro.AsyncAnalyzeBatchActionsLROPoller[~azure.ai.textanalytics.v3_1_preview_3.models.HealthcareJobState] :raises ~azure.core.exceptions.HttpResponseError: """ api_version = self._get_api_version('begin_health') diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_0/_metadata.json b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_0/_metadata.json index a0eee3f2e0f2..c4af58b22177 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_0/_metadata.json +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_0/_metadata.json @@ -44,7 +44,37 @@ }, "constant": { }, - "call": "credential, endpoint" + "call": "credential, endpoint", + "service_client_specific": { + "sync": { + "api_version": { + "signature": "api_version=None, # type: Optional[str]", + "description": "API version to use if no profile is provided, or if missing in profile.", + "docstring_type": "str", + "required": false + }, + "profile": { + "signature": "profile=KnownProfiles.default, # type: KnownProfiles", + "description": "A profile definition, from KnownProfiles to dict.", + "docstring_type": "azure.profiles.KnownProfiles", + "required": false + } + }, + "async": { + "api_version": { + "signature": "api_version: Optional[str] = None,", + "description": "API version to use if no profile is provided, or if missing in profile.", + "docstring_type": "str", + "required": false + }, + "profile": { + "signature": "profile: KnownProfiles = KnownProfiles.default,", + "description": "A profile definition, from KnownProfiles to dict.", + "docstring_type": "azure.profiles.KnownProfiles", + "required": false + } + } + } }, "config": { "credential": true, diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_0/aio/operations/_text_analytics_client_operations.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_0/aio/operations/_text_analytics_client_operations.py index 76a7d9ebb856..3d0f1594a98f 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_0/aio/operations/_text_analytics_client_operations.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_0/aio/operations/_text_analytics_client_operations.py @@ -84,7 +84,7 @@ async def entities_recognition_general( if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) - error = self._deserialize(_models.ErrorResponse, response) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, response) raise HttpResponseError(response=response, model=error) deserialized = self._deserialize('EntitiesResult', pipeline_response) @@ -159,7 +159,7 @@ async def entities_linking( if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) - error = self._deserialize(_models.ErrorResponse, response) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, response) raise HttpResponseError(response=response, model=error) deserialized = self._deserialize('EntityLinkingResult', pipeline_response) @@ -234,7 +234,7 @@ async def key_phrases( if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) - error = self._deserialize(_models.ErrorResponse, response) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, response) raise HttpResponseError(response=response, model=error) deserialized = self._deserialize('KeyPhraseResult', pipeline_response) @@ -310,7 +310,7 @@ async def languages( if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) - error = self._deserialize(_models.ErrorResponse, response) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, response) raise HttpResponseError(response=response, model=error) deserialized = self._deserialize('LanguageResult', pipeline_response) @@ -386,7 +386,7 @@ async def sentiment( if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) - error = self._deserialize(_models.ErrorResponse, response) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, response) raise HttpResponseError(response=response, model=error) deserialized = self._deserialize('SentimentResponse', pipeline_response) diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_0/operations/_text_analytics_client_operations.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_0/operations/_text_analytics_client_operations.py index 1ba616f6370c..913f3155c4c1 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_0/operations/_text_analytics_client_operations.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_0/operations/_text_analytics_client_operations.py @@ -89,7 +89,7 @@ def entities_recognition_general( if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) - error = self._deserialize(_models.ErrorResponse, response) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, response) raise HttpResponseError(response=response, model=error) deserialized = self._deserialize('EntitiesResult', pipeline_response) @@ -165,7 +165,7 @@ def entities_linking( if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) - error = self._deserialize(_models.ErrorResponse, response) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, response) raise HttpResponseError(response=response, model=error) deserialized = self._deserialize('EntityLinkingResult', pipeline_response) @@ -241,7 +241,7 @@ def key_phrases( if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) - error = self._deserialize(_models.ErrorResponse, response) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, response) raise HttpResponseError(response=response, model=error) deserialized = self._deserialize('KeyPhraseResult', pipeline_response) @@ -318,7 +318,7 @@ def languages( if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) - error = self._deserialize(_models.ErrorResponse, response) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, response) raise HttpResponseError(response=response, model=error) deserialized = self._deserialize('LanguageResult', pipeline_response) @@ -395,7 +395,7 @@ def sentiment( if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) - error = self._deserialize(_models.ErrorResponse, response) + error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, response) raise HttpResponseError(response=response, model=error) deserialized = self._deserialize('SentimentResponse', pipeline_response) diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/_metadata.json b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/_metadata.json index 6d9669151afb..1758cf5ae7e5 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/_metadata.json +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/_metadata.json @@ -44,7 +44,37 @@ }, "constant": { }, - "call": "credential, endpoint" + "call": "credential, endpoint", + "service_client_specific": { + "sync": { + "api_version": { + "signature": "api_version=None, # type: Optional[str]", + "description": "API version to use if no profile is provided, or if missing in profile.", + "docstring_type": "str", + "required": false + }, + "profile": { + "signature": "profile=KnownProfiles.default, # type: KnownProfiles", + "description": "A profile definition, from KnownProfiles to dict.", + "docstring_type": "azure.profiles.KnownProfiles", + "required": false + } + }, + "async": { + "api_version": { + "signature": "api_version: Optional[str] = None,", + "description": "API version to use if no profile is provided, or if missing in profile.", + "docstring_type": "str", + "required": false + }, + "profile": { + "signature": "profile: KnownProfiles = KnownProfiles.default,", + "description": "A profile definition, from KnownProfiles to dict.", + "docstring_type": "azure.profiles.KnownProfiles", + "required": false + } + } + } }, "config": { "credential": true, @@ -58,30 +88,30 @@ "operation_groups": { }, "operation_mixins": { - "sync_imports": "{\"regular\": {\"azurecore\": {\"azure.core.exceptions\": [\"ClientAuthenticationError\", \"HttpResponseError\", \"ResourceExistsError\", \"ResourceNotFoundError\", \"map_error\"], \"azure.core.pipeline\": [\"PipelineResponse\"], \"azure.core.pipeline.transport\": [\"HttpRequest\", \"HttpResponse\"], \"azure.core.polling\": [\"LROPoller\", \"NoPolling\", \"PollingMethod\"], \"azure.core.polling.base_polling\": [\"LROBasePolling\"]}, \"stdlib\": {\"warnings\": [null]}}, \"conditional\": {\"stdlib\": {\"typing\": [\"Any\", \"Callable\", \"Dict\", \"Generic\", \"List\", \"Optional\", \"TypeVar\", \"Union\"]}}}", - "async_imports": "{\"regular\": {\"azurecore\": {\"azure.core.exceptions\": [\"ClientAuthenticationError\", \"HttpResponseError\", \"ResourceExistsError\", \"ResourceNotFoundError\", \"map_error\"], \"azure.core.pipeline\": [\"PipelineResponse\"], \"azure.core.pipeline.transport\": [\"AsyncHttpResponse\", \"HttpRequest\"], \"azure.core.polling\": [\"AsyncLROPoller\", \"AsyncNoPolling\", \"AsyncPollingMethod\"], \"azure.core.polling.async_base_polling\": [\"AsyncLROBasePolling\"]}, \"stdlib\": {\"warnings\": [null]}}, \"conditional\": {\"stdlib\": {\"typing\": [\"Any\", \"Callable\", \"Dict\", \"Generic\", \"List\", \"Optional\", \"TypeVar\", \"Union\"]}}}", + "sync_imports": "{\"regular\": {\"azurecore\": {\"azure.core.exceptions\": [\"ClientAuthenticationError\", \"HttpResponseError\", \"ResourceExistsError\", \"ResourceNotFoundError\", \"map_error\"], \"azure.core.pipeline\": [\"PipelineResponse\"], \"azure.core.pipeline.transport\": [\"HttpRequest\", \"HttpResponse\"], \"...._lro\": [\"AnalyzeBatchActionsLROPoller\", \"AnalyzeBatchActionsLROPollingMethod\"], \"azure.core.polling\": [\"LROPoller\", \"NoPolling\", \"PollingMethod\"], \"azure.core.polling.base_polling\": [\"LROBasePolling\"]}, \"stdlib\": {\"warnings\": [null]}}, \"conditional\": {\"stdlib\": {\"typing\": [\"Any\", \"Callable\", \"Dict\", \"Generic\", \"List\", \"Optional\", \"TypeVar\", \"Union\"]}}}", + "async_imports": "{\"regular\": {\"azurecore\": {\"azure.core.exceptions\": [\"ClientAuthenticationError\", \"HttpResponseError\", \"ResourceExistsError\", \"ResourceNotFoundError\", \"map_error\"], \"azure.core.pipeline\": [\"PipelineResponse\"], \"azure.core.pipeline.transport\": [\"AsyncHttpResponse\", \"HttpRequest\"], \"...._async_lro\": [\"AsyncAnalyzeBatchActionsLROPoller\", \"AsyncAnalyzeBatchActionsLROPollingMethod\"], \"azure.core.polling\": [\"AsyncLROPoller\", \"AsyncNoPolling\", \"AsyncPollingMethod\"], \"azure.core.polling.async_base_polling\": [\"AsyncLROBasePolling\"]}, \"stdlib\": {\"warnings\": [null]}}, \"conditional\": {\"stdlib\": {\"typing\": [\"Any\", \"Callable\", \"Dict\", \"Generic\", \"List\", \"Optional\", \"TypeVar\", \"Union\"]}}}", "operations": { "_analyze_initial" : { "sync": { "signature": "def _analyze_initial(\n self,\n body=None, # type: Optional[\"_models.AnalyzeBatchInput\"]\n **kwargs # type: Any\n):\n", - "doc": "\"\"\"\n\n:param body: Collection of documents to analyze and tasks to execute.\n:type body: ~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeBatchInput\n:keyword callable cls: A custom type or function that will be passed the direct response\n:return: None, or the result of cls(response)\n:rtype: None\n:raises: ~azure.core.exceptions.HttpResponseError\n\"\"\"" + "doc": "\"\"\"\n\n:param body: Collection of documents to analyze and tasks to execute.\n:type body: ~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeBatchInput\n:keyword callable cls: A custom type or function that will be passed the direct response\n:return: AnalyzeJobState, or the result of cls(response)\n:rtype: ~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeJobState or None\n:raises: ~azure.core.exceptions.HttpResponseError\n\"\"\"" }, "async": { "coroutine": true, - "signature": "async def _analyze_initial(\n self,\n body: Optional[\"_models.AnalyzeBatchInput\"] = None,\n **kwargs\n) -\u003e None:\n", - "doc": "\"\"\"\n\n:param body: Collection of documents to analyze and tasks to execute.\n:type body: ~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeBatchInput\n:keyword callable cls: A custom type or function that will be passed the direct response\n:return: None, or the result of cls(response)\n:rtype: None\n:raises: ~azure.core.exceptions.HttpResponseError\n\"\"\"" + "signature": "async def _analyze_initial(\n self,\n body: Optional[\"_models.AnalyzeBatchInput\"] = None,\n **kwargs\n) -\u003e Optional[\"_models.AnalyzeJobState\"]:\n", + "doc": "\"\"\"\n\n:param body: Collection of documents to analyze and tasks to execute.\n:type body: ~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeBatchInput\n:keyword callable cls: A custom type or function that will be passed the direct response\n:return: AnalyzeJobState, or the result of cls(response)\n:rtype: ~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeJobState or None\n:raises: ~azure.core.exceptions.HttpResponseError\n\"\"\"" }, "call": "body" }, "begin_analyze" : { "sync": { "signature": "def begin_analyze(\n self,\n body=None, # type: Optional[\"_models.AnalyzeBatchInput\"]\n **kwargs # type: Any\n):\n", - "doc": "\"\"\"Submit analysis job.\n\nSubmit a collection of text documents for analysis. Specify one or more unique tasks to be\nexecuted.\n\n:param body: Collection of documents to analyze and tasks to execute.\n:type body: ~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeBatchInput\n:keyword callable cls: A custom type or function that will be passed the direct response\n:keyword str continuation_token: A continuation token to restart a poller from a saved state.\n:keyword polling: Pass in True if you\u0027d like the LROBasePolling polling method,\n False for no polling, or your own initialized polling object for a personal polling strategy.\n:paramtype polling: bool or ~azure.core.polling.PollingMethod\n:keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present.\n:return: An instance of LROPoller that returns either None or the result of cls(response)\n:rtype: ~azure.core.polling.LROPoller[None]\n:raises ~azure.core.exceptions.HttpResponseError:\n\"\"\"" + "doc": "\"\"\"Submit analysis job.\n\nSubmit a collection of text documents for analysis. Specify one or more unique tasks to be\nexecuted.\n\n:param body: Collection of documents to analyze and tasks to execute.\n:type body: ~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeBatchInput\n:keyword callable cls: A custom type or function that will be passed the direct response\n:keyword str continuation_token: A continuation token to restart a poller from a saved state.\n:keyword polling: Pass in True if you\u0027d like the AnalyzeBatchActionsLROPollingMethod polling method,\n False for no polling, or your own initialized polling object for a personal polling strategy.\n:paramtype polling: bool or ~azure.core.polling.PollingMethod\n:keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present.\n:return: An instance of AnalyzeBatchActionsLROPoller that returns either AnalyzeJobState or the result of cls(response)\n:rtype: ~...._lro.AnalyzeBatchActionsLROPoller[~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeJobState]\n:raises ~azure.core.exceptions.HttpResponseError:\n\"\"\"" }, "async": { "coroutine": true, - "signature": "async def begin_analyze(\n self,\n body: Optional[\"_models.AnalyzeBatchInput\"] = None,\n **kwargs\n) -\u003e AsyncLROPoller[None]:\n", - "doc": "\"\"\"Submit analysis job.\n\nSubmit a collection of text documents for analysis. Specify one or more unique tasks to be\nexecuted.\n\n:param body: Collection of documents to analyze and tasks to execute.\n:type body: ~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeBatchInput\n:keyword callable cls: A custom type or function that will be passed the direct response\n:keyword str continuation_token: A continuation token to restart a poller from a saved state.\n:keyword polling: Pass in True if you\u0027d like the AsyncLROBasePolling polling method,\n False for no polling, or your own initialized polling object for a personal polling strategy.\n:paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod\n:keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present.\n:return: An instance of AsyncLROPoller that returns either None or the result of cls(response)\n:rtype: ~azure.core.polling.AsyncLROPoller[None]\n:raises ~azure.core.exceptions.HttpResponseError:\n\"\"\"" + "signature": "async def begin_analyze(\n self,\n body: Optional[\"_models.AnalyzeBatchInput\"] = None,\n **kwargs\n) -\u003e AsyncAnalyzeBatchActionsLROPoller[\"_models.AnalyzeJobState\"]:\n", + "doc": "\"\"\"Submit analysis job.\n\nSubmit a collection of text documents for analysis. Specify one or more unique tasks to be\nexecuted.\n\n:param body: Collection of documents to analyze and tasks to execute.\n:type body: ~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeBatchInput\n:keyword callable cls: A custom type or function that will be passed the direct response\n:keyword str continuation_token: A continuation token to restart a poller from a saved state.\n:keyword polling: Pass in True if you\u0027d like the AsyncAnalyzeBatchActionsLROPollingMethod polling method,\n False for no polling, or your own initialized polling object for a personal polling strategy.\n:paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod\n:keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present.\n:return: An instance of AsyncAnalyzeBatchActionsLROPoller that returns either AnalyzeJobState or the result of cls(response)\n:rtype: ~...._async_lro.AsyncAnalyzeBatchActionsLROPoller[~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeJobState]\n:raises ~azure.core.exceptions.HttpResponseError:\n\"\"\"" }, "call": "body" }, @@ -136,24 +166,24 @@ "_health_initial" : { "sync": { "signature": "def _health_initial(\n self,\n documents, # type: List[\"_models.MultiLanguageInput\"]\n model_version=None, # type: Optional[str]\n string_index_type=\"TextElements_v8\", # type: Optional[Union[str, \"_models.StringIndexType\"]]\n **kwargs # type: Any\n):\n", - "doc": "\"\"\"\n\n:param documents: The set of documents to process as part of this batch.\n:type documents: list[~azure.ai.textanalytics.v3_1_preview_3.models.MultiLanguageInput]\n:param model_version: (Optional) This value indicates which model will be used for scoring. If\n a model-version is not specified, the API should default to the latest, non-preview version.\n:type model_version: str\n:param string_index_type: (Optional) Specifies the method used to interpret string offsets.\n Defaults to Text Elements (Graphemes) according to Unicode v8.0.0. For additional information\n see https://aka.ms/text-analytics-offsets.\n:type string_index_type: str or ~azure.ai.textanalytics.v3_1_preview_3.models.StringIndexType\n:keyword callable cls: A custom type or function that will be passed the direct response\n:return: None, or the result of cls(response)\n:rtype: None\n:raises: ~azure.core.exceptions.HttpResponseError\n\"\"\"" + "doc": "\"\"\"\n\n:param documents: The set of documents to process as part of this batch.\n:type documents: list[~azure.ai.textanalytics.v3_1_preview_3.models.MultiLanguageInput]\n:param model_version: (Optional) This value indicates which model will be used for scoring. If\n a model-version is not specified, the API should default to the latest, non-preview version.\n:type model_version: str\n:param string_index_type: (Optional) Specifies the method used to interpret string offsets.\n Defaults to Text Elements (Graphemes) according to Unicode v8.0.0. For additional information\n see https://aka.ms/text-analytics-offsets.\n:type string_index_type: str or ~azure.ai.textanalytics.v3_1_preview_3.models.StringIndexType\n:keyword callable cls: A custom type or function that will be passed the direct response\n:return: HealthcareJobState, or the result of cls(response)\n:rtype: ~azure.ai.textanalytics.v3_1_preview_3.models.HealthcareJobState or None\n:raises: ~azure.core.exceptions.HttpResponseError\n\"\"\"" }, "async": { "coroutine": true, - "signature": "async def _health_initial(\n self,\n documents: List[\"_models.MultiLanguageInput\"],\n model_version: Optional[str] = None,\n string_index_type: Optional[Union[str, \"_models.StringIndexType\"]] = \"TextElements_v8\",\n **kwargs\n) -\u003e None:\n", - "doc": "\"\"\"\n\n:param documents: The set of documents to process as part of this batch.\n:type documents: list[~azure.ai.textanalytics.v3_1_preview_3.models.MultiLanguageInput]\n:param model_version: (Optional) This value indicates which model will be used for scoring. If\n a model-version is not specified, the API should default to the latest, non-preview version.\n:type model_version: str\n:param string_index_type: (Optional) Specifies the method used to interpret string offsets.\n Defaults to Text Elements (Graphemes) according to Unicode v8.0.0. For additional information\n see https://aka.ms/text-analytics-offsets.\n:type string_index_type: str or ~azure.ai.textanalytics.v3_1_preview_3.models.StringIndexType\n:keyword callable cls: A custom type or function that will be passed the direct response\n:return: None, or the result of cls(response)\n:rtype: None\n:raises: ~azure.core.exceptions.HttpResponseError\n\"\"\"" + "signature": "async def _health_initial(\n self,\n documents: List[\"_models.MultiLanguageInput\"],\n model_version: Optional[str] = None,\n string_index_type: Optional[Union[str, \"_models.StringIndexType\"]] = \"TextElements_v8\",\n **kwargs\n) -\u003e Optional[\"_models.HealthcareJobState\"]:\n", + "doc": "\"\"\"\n\n:param documents: The set of documents to process as part of this batch.\n:type documents: list[~azure.ai.textanalytics.v3_1_preview_3.models.MultiLanguageInput]\n:param model_version: (Optional) This value indicates which model will be used for scoring. If\n a model-version is not specified, the API should default to the latest, non-preview version.\n:type model_version: str\n:param string_index_type: (Optional) Specifies the method used to interpret string offsets.\n Defaults to Text Elements (Graphemes) according to Unicode v8.0.0. For additional information\n see https://aka.ms/text-analytics-offsets.\n:type string_index_type: str or ~azure.ai.textanalytics.v3_1_preview_3.models.StringIndexType\n:keyword callable cls: A custom type or function that will be passed the direct response\n:return: HealthcareJobState, or the result of cls(response)\n:rtype: ~azure.ai.textanalytics.v3_1_preview_3.models.HealthcareJobState or None\n:raises: ~azure.core.exceptions.HttpResponseError\n\"\"\"" }, "call": "documents, model_version, string_index_type" }, "begin_health" : { "sync": { "signature": "def begin_health(\n self,\n documents, # type: List[\"_models.MultiLanguageInput\"]\n model_version=None, # type: Optional[str]\n string_index_type=\"TextElements_v8\", # type: Optional[Union[str, \"_models.StringIndexType\"]]\n **kwargs # type: Any\n):\n", - "doc": "\"\"\"Submit healthcare analysis job.\n\nStart a healthcare analysis job to recognize healthcare related entities (drugs, conditions,\nsymptoms, etc) and their relations.\n\n:param documents: The set of documents to process as part of this batch.\n:type documents: list[~azure.ai.textanalytics.v3_1_preview_3.models.MultiLanguageInput]\n:param model_version: (Optional) This value indicates which model will be used for scoring. If\n a model-version is not specified, the API should default to the latest, non-preview version.\n:type model_version: str\n:param string_index_type: (Optional) Specifies the method used to interpret string offsets.\n Defaults to Text Elements (Graphemes) according to Unicode v8.0.0. For additional information\n see https://aka.ms/text-analytics-offsets.\n:type string_index_type: str or ~azure.ai.textanalytics.v3_1_preview_3.models.StringIndexType\n:keyword callable cls: A custom type or function that will be passed the direct response\n:keyword str continuation_token: A continuation token to restart a poller from a saved state.\n:keyword polling: Pass in True if you\u0027d like the LROBasePolling polling method,\n False for no polling, or your own initialized polling object for a personal polling strategy.\n:paramtype polling: bool or ~azure.core.polling.PollingMethod\n:keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present.\n:return: An instance of LROPoller that returns either None or the result of cls(response)\n:rtype: ~azure.core.polling.LROPoller[None]\n:raises ~azure.core.exceptions.HttpResponseError:\n\"\"\"" + "doc": "\"\"\"Submit healthcare analysis job.\n\nStart a healthcare analysis job to recognize healthcare related entities (drugs, conditions,\nsymptoms, etc) and their relations.\n\n:param documents: The set of documents to process as part of this batch.\n:type documents: list[~azure.ai.textanalytics.v3_1_preview_3.models.MultiLanguageInput]\n:param model_version: (Optional) This value indicates which model will be used for scoring. If\n a model-version is not specified, the API should default to the latest, non-preview version.\n:type model_version: str\n:param string_index_type: (Optional) Specifies the method used to interpret string offsets.\n Defaults to Text Elements (Graphemes) according to Unicode v8.0.0. For additional information\n see https://aka.ms/text-analytics-offsets.\n:type string_index_type: str or ~azure.ai.textanalytics.v3_1_preview_3.models.StringIndexType\n:keyword callable cls: A custom type or function that will be passed the direct response\n:keyword str continuation_token: A continuation token to restart a poller from a saved state.\n:keyword polling: Pass in True if you\u0027d like the AnalyzeBatchActionsLROPollingMethod polling method,\n False for no polling, or your own initialized polling object for a personal polling strategy.\n:paramtype polling: bool or ~azure.core.polling.PollingMethod\n:keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present.\n:return: An instance of AnalyzeBatchActionsLROPoller that returns either HealthcareJobState or the result of cls(response)\n:rtype: ~...._lro.AnalyzeBatchActionsLROPoller[~azure.ai.textanalytics.v3_1_preview_3.models.HealthcareJobState]\n:raises ~azure.core.exceptions.HttpResponseError:\n\"\"\"" }, "async": { "coroutine": true, - "signature": "async def begin_health(\n self,\n documents: List[\"_models.MultiLanguageInput\"],\n model_version: Optional[str] = None,\n string_index_type: Optional[Union[str, \"_models.StringIndexType\"]] = \"TextElements_v8\",\n **kwargs\n) -\u003e AsyncLROPoller[None]:\n", - "doc": "\"\"\"Submit healthcare analysis job.\n\nStart a healthcare analysis job to recognize healthcare related entities (drugs, conditions,\nsymptoms, etc) and their relations.\n\n:param documents: The set of documents to process as part of this batch.\n:type documents: list[~azure.ai.textanalytics.v3_1_preview_3.models.MultiLanguageInput]\n:param model_version: (Optional) This value indicates which model will be used for scoring. If\n a model-version is not specified, the API should default to the latest, non-preview version.\n:type model_version: str\n:param string_index_type: (Optional) Specifies the method used to interpret string offsets.\n Defaults to Text Elements (Graphemes) according to Unicode v8.0.0. For additional information\n see https://aka.ms/text-analytics-offsets.\n:type string_index_type: str or ~azure.ai.textanalytics.v3_1_preview_3.models.StringIndexType\n:keyword callable cls: A custom type or function that will be passed the direct response\n:keyword str continuation_token: A continuation token to restart a poller from a saved state.\n:keyword polling: Pass in True if you\u0027d like the AsyncLROBasePolling polling method,\n False for no polling, or your own initialized polling object for a personal polling strategy.\n:paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod\n:keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present.\n:return: An instance of AsyncLROPoller that returns either None or the result of cls(response)\n:rtype: ~azure.core.polling.AsyncLROPoller[None]\n:raises ~azure.core.exceptions.HttpResponseError:\n\"\"\"" + "signature": "async def begin_health(\n self,\n documents: List[\"_models.MultiLanguageInput\"],\n model_version: Optional[str] = None,\n string_index_type: Optional[Union[str, \"_models.StringIndexType\"]] = \"TextElements_v8\",\n **kwargs\n) -\u003e AsyncAnalyzeBatchActionsLROPoller[\"_models.HealthcareJobState\"]:\n", + "doc": "\"\"\"Submit healthcare analysis job.\n\nStart a healthcare analysis job to recognize healthcare related entities (drugs, conditions,\nsymptoms, etc) and their relations.\n\n:param documents: The set of documents to process as part of this batch.\n:type documents: list[~azure.ai.textanalytics.v3_1_preview_3.models.MultiLanguageInput]\n:param model_version: (Optional) This value indicates which model will be used for scoring. If\n a model-version is not specified, the API should default to the latest, non-preview version.\n:type model_version: str\n:param string_index_type: (Optional) Specifies the method used to interpret string offsets.\n Defaults to Text Elements (Graphemes) according to Unicode v8.0.0. For additional information\n see https://aka.ms/text-analytics-offsets.\n:type string_index_type: str or ~azure.ai.textanalytics.v3_1_preview_3.models.StringIndexType\n:keyword callable cls: A custom type or function that will be passed the direct response\n:keyword str continuation_token: A continuation token to restart a poller from a saved state.\n:keyword polling: Pass in True if you\u0027d like the AsyncAnalyzeBatchActionsLROPollingMethod polling method,\n False for no polling, or your own initialized polling object for a personal polling strategy.\n:paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod\n:keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present.\n:return: An instance of AsyncAnalyzeBatchActionsLROPoller that returns either HealthcareJobState or the result of cls(response)\n:rtype: ~...._async_lro.AsyncAnalyzeBatchActionsLROPoller[~azure.ai.textanalytics.v3_1_preview_3.models.HealthcareJobState]\n:raises ~azure.core.exceptions.HttpResponseError:\n\"\"\"" }, "call": "documents, model_version, string_index_type" }, diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/aio/operations/_text_analytics_client_operations.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/aio/operations/_text_analytics_client_operations.py index b2ce981f0eeb..ed3357ce8ad7 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/aio/operations/_text_analytics_client_operations.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/aio/operations/_text_analytics_client_operations.py @@ -8,6 +8,7 @@ from typing import Any, Callable, Dict, Generic, List, Optional, TypeVar, Union import warnings +from ....._async_lro import AsyncAnalyzeBatchActionsLROPoller, AsyncAnalyzeBatchActionsLROPollingMethod from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error from azure.core.pipeline import PipelineResponse from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest @@ -25,8 +26,8 @@ async def _analyze_initial( self, body: Optional["_models.AnalyzeBatchInput"] = None, **kwargs - ) -> None: - cls = kwargs.pop('cls', None) # type: ClsType[None] + ) -> Optional["_models.AnalyzeJobState"]: + cls = kwargs.pop('cls', None) # type: ClsType[Optional["_models.AnalyzeJobState"]] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, @@ -63,23 +64,29 @@ async def _analyze_initial( pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response - if response.status_code not in [202]: + if response.status_code not in [200, 202]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response) response_headers = {} - response_headers['Operation-Location']=self._deserialize('str', response.headers.get('Operation-Location')) + deserialized = None + if response.status_code == 200: + deserialized = self._deserialize('AnalyzeJobState', pipeline_response) + + if response.status_code == 202: + response_headers['Operation-Location']=self._deserialize('str', response.headers.get('Operation-Location')) if cls: - return cls(pipeline_response, None, response_headers) + return cls(pipeline_response, deserialized, response_headers) + return deserialized _analyze_initial.metadata = {'url': '/analyze'} # type: ignore async def begin_analyze( self, body: Optional["_models.AnalyzeBatchInput"] = None, **kwargs - ) -> AsyncLROPoller[None]: + ) -> AsyncAnalyzeBatchActionsLROPoller["_models.AnalyzeJobState"]: """Submit analysis job. Submit a collection of text documents for analysis. Specify one or more unique tasks to be @@ -89,16 +96,16 @@ async def begin_analyze( :type body: ~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeBatchInput :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. - :keyword polling: Pass in True if you'd like the AsyncLROBasePolling polling method, + :keyword polling: Pass in True if you'd like the AsyncAnalyzeBatchActionsLROPollingMethod polling method, False for no polling, or your own initialized polling object for a personal polling strategy. :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. - :return: An instance of AsyncLROPoller that returns either None or the result of cls(response) - :rtype: ~azure.core.polling.AsyncLROPoller[None] + :return: An instance of AsyncAnalyzeBatchActionsLROPoller that returns either AnalyzeJobState or the result of cls(response) + :rtype: ~...._async_lro.AsyncAnalyzeBatchActionsLROPoller[~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeJobState] :raises ~azure.core.exceptions.HttpResponseError: """ polling = kwargs.pop('polling', False) # type: Union[bool, AsyncPollingMethod] - cls = kwargs.pop('cls', None) # type: ClsType[None] + cls = kwargs.pop('cls', None) # type: ClsType["_models.AnalyzeJobState"] lro_delay = kwargs.pop( 'polling_interval', self._config.polling_interval @@ -115,25 +122,28 @@ async def begin_analyze( kwargs.pop('content_type', None) def get_long_running_output(pipeline_response): + deserialized = self._deserialize('AnalyzeJobState', pipeline_response) + if cls: - return cls(pipeline_response, None, {}) + return cls(pipeline_response, deserialized, {}) + return deserialized path_format_arguments = { 'Endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True), } - if polling is True: polling_method = AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + if polling is True: polling_method = AsyncAnalyzeBatchActionsLROPollingMethod(lro_delay, path_format_arguments=path_format_arguments, **kwargs) elif polling is False: polling_method = AsyncNoPolling() else: polling_method = polling if cont_token: - return AsyncLROPoller.from_continuation_token( + return AsyncAnalyzeBatchActionsLROPoller.from_continuation_token( polling_method=polling_method, continuation_token=cont_token, client=self._client, deserialization_callback=get_long_running_output ) else: - return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) + return AsyncAnalyzeBatchActionsLROPoller(self._client, raw_result, get_long_running_output, polling_method) begin_analyze.metadata = {'url': '/analyze'} # type: ignore async def analyze_status( @@ -401,8 +411,8 @@ async def _health_initial( model_version: Optional[str] = None, string_index_type: Optional[Union[str, "_models.StringIndexType"]] = "TextElements_v8", **kwargs - ) -> None: - cls = kwargs.pop('cls', None) # type: ClsType[None] + ) -> Optional["_models.HealthcareJobState"]: + cls = kwargs.pop('cls', None) # type: ClsType[Optional["_models.HealthcareJobState"]] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, @@ -442,16 +452,22 @@ async def _health_initial( pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response - if response.status_code not in [202]: + if response.status_code not in [200, 202]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response) response_headers = {} - response_headers['Operation-Location']=self._deserialize('str', response.headers.get('Operation-Location')) + deserialized = None + if response.status_code == 200: + deserialized = self._deserialize('HealthcareJobState', pipeline_response) + + if response.status_code == 202: + response_headers['Operation-Location']=self._deserialize('str', response.headers.get('Operation-Location')) if cls: - return cls(pipeline_response, None, response_headers) + return cls(pipeline_response, deserialized, response_headers) + return deserialized _health_initial.metadata = {'url': '/entities/health/jobs'} # type: ignore async def begin_health( @@ -460,7 +476,7 @@ async def begin_health( model_version: Optional[str] = None, string_index_type: Optional[Union[str, "_models.StringIndexType"]] = "TextElements_v8", **kwargs - ) -> AsyncLROPoller[None]: + ) -> AsyncAnalyzeBatchActionsLROPoller["_models.HealthcareJobState"]: """Submit healthcare analysis job. Start a healthcare analysis job to recognize healthcare related entities (drugs, conditions, @@ -477,16 +493,16 @@ async def begin_health( :type string_index_type: str or ~azure.ai.textanalytics.v3_1_preview_3.models.StringIndexType :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. - :keyword polling: Pass in True if you'd like the AsyncLROBasePolling polling method, + :keyword polling: Pass in True if you'd like the AsyncAnalyzeBatchActionsLROPollingMethod polling method, False for no polling, or your own initialized polling object for a personal polling strategy. :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. - :return: An instance of AsyncLROPoller that returns either None or the result of cls(response) - :rtype: ~azure.core.polling.AsyncLROPoller[None] + :return: An instance of AsyncAnalyzeBatchActionsLROPoller that returns either HealthcareJobState or the result of cls(response) + :rtype: ~...._async_lro.AsyncAnalyzeBatchActionsLROPoller[~azure.ai.textanalytics.v3_1_preview_3.models.HealthcareJobState] :raises ~azure.core.exceptions.HttpResponseError: """ polling = kwargs.pop('polling', False) # type: Union[bool, AsyncPollingMethod] - cls = kwargs.pop('cls', None) # type: ClsType[None] + cls = kwargs.pop('cls', None) # type: ClsType["_models.HealthcareJobState"] lro_delay = kwargs.pop( 'polling_interval', self._config.polling_interval @@ -505,25 +521,28 @@ async def begin_health( kwargs.pop('content_type', None) def get_long_running_output(pipeline_response): + deserialized = self._deserialize('HealthcareJobState', pipeline_response) + if cls: - return cls(pipeline_response, None, {}) + return cls(pipeline_response, deserialized, {}) + return deserialized path_format_arguments = { 'Endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True), } - if polling is True: polling_method = AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + if polling is True: polling_method = AsyncAnalyzeBatchActionsLROPollingMethod(lro_delay, path_format_arguments=path_format_arguments, **kwargs) elif polling is False: polling_method = AsyncNoPolling() else: polling_method = polling if cont_token: - return AsyncLROPoller.from_continuation_token( + return AsyncAnalyzeBatchActionsLROPoller.from_continuation_token( polling_method=polling_method, continuation_token=cont_token, client=self._client, deserialization_callback=get_long_running_output ) else: - return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) + return AsyncAnalyzeBatchActionsLROPoller(self._client, raw_result, get_long_running_output, polling_method) begin_health.metadata = {'url': '/entities/health/jobs'} # type: ignore async def entities_recognition_general( diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/models/_models.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/models/_models.py index 2a8d8564a397..ebfc34f1abc8 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/models/_models.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/models/_models.py @@ -2011,7 +2011,7 @@ class TasksStateTasks(msrest.serialization.Model): All required parameters must be populated in order to send to Azure. :param details: - :type details: ~azure.ai.textanalytics.v3_1_preview_3.models.TaskState + :type details: ~azure.ai.textanalytics.v3_1_preview_3.models.TasksStateTasksDetails :param completed: Required. :type completed: int :param failed: Required. @@ -2039,7 +2039,7 @@ class TasksStateTasks(msrest.serialization.Model): } _attribute_map = { - 'details': {'key': 'details', 'type': 'TaskState'}, + 'details': {'key': 'details', 'type': 'TasksStateTasksDetails'}, 'completed': {'key': 'completed', 'type': 'int'}, 'failed': {'key': 'failed', 'type': 'int'}, 'in_progress': {'key': 'inProgress', 'type': 'int'}, diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/models/_models_py3.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/models/_models_py3.py index 2f18fb57dde7..46cfa90ec725 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/models/_models_py3.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/models/_models_py3.py @@ -2259,7 +2259,7 @@ class TasksStateTasks(msrest.serialization.Model): All required parameters must be populated in order to send to Azure. :param details: - :type details: ~azure.ai.textanalytics.v3_1_preview_3.models.TaskState + :type details: ~azure.ai.textanalytics.v3_1_preview_3.models.TasksStateTasksDetails :param completed: Required. :type completed: int :param failed: Required. @@ -2287,7 +2287,7 @@ class TasksStateTasks(msrest.serialization.Model): } _attribute_map = { - 'details': {'key': 'details', 'type': 'TaskState'}, + 'details': {'key': 'details', 'type': 'TasksStateTasksDetails'}, 'completed': {'key': 'completed', 'type': 'int'}, 'failed': {'key': 'failed', 'type': 'int'}, 'in_progress': {'key': 'inProgress', 'type': 'int'}, @@ -2304,7 +2304,7 @@ def __init__( failed: int, in_progress: int, total: int, - details: Optional["TaskState"] = None, + details: Optional["TasksStateTasksDetails"] = None, entity_recognition_tasks: Optional[List["TasksStateTasksEntityRecognitionTasksItem"]] = None, entity_recognition_pii_tasks: Optional[List["TasksStateTasksEntityRecognitionPiiTasksItem"]] = None, key_phrase_extraction_tasks: Optional[List["TasksStateTasksKeyPhraseExtractionTasksItem"]] = None, diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/operations/_text_analytics_client_operations.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/operations/_text_analytics_client_operations.py index c060a4f23d3f..1f8461df94fb 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/operations/_text_analytics_client_operations.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_generated/v3_1_preview_3/operations/_text_analytics_client_operations.py @@ -8,6 +8,7 @@ from typing import TYPE_CHECKING import warnings +from ...._lro import AnalyzeBatchActionsLROPoller, AnalyzeBatchActionsLROPollingMethod from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error from azure.core.pipeline import PipelineResponse from azure.core.pipeline.transport import HttpRequest, HttpResponse @@ -30,8 +31,8 @@ def _analyze_initial( body=None, # type: Optional["_models.AnalyzeBatchInput"] **kwargs # type: Any ): - # type: (...) -> None - cls = kwargs.pop('cls', None) # type: ClsType[None] + # type: (...) -> Optional["_models.AnalyzeJobState"] + cls = kwargs.pop('cls', None) # type: ClsType[Optional["_models.AnalyzeJobState"]] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, @@ -68,16 +69,22 @@ def _analyze_initial( pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response - if response.status_code not in [202]: + if response.status_code not in [200, 202]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response) response_headers = {} - response_headers['Operation-Location']=self._deserialize('str', response.headers.get('Operation-Location')) + deserialized = None + if response.status_code == 200: + deserialized = self._deserialize('AnalyzeJobState', pipeline_response) + + if response.status_code == 202: + response_headers['Operation-Location']=self._deserialize('str', response.headers.get('Operation-Location')) if cls: - return cls(pipeline_response, None, response_headers) + return cls(pipeline_response, deserialized, response_headers) + return deserialized _analyze_initial.metadata = {'url': '/analyze'} # type: ignore def begin_analyze( @@ -85,7 +92,7 @@ def begin_analyze( body=None, # type: Optional["_models.AnalyzeBatchInput"] **kwargs # type: Any ): - # type: (...) -> LROPoller[None] + # type: (...) -> AnalyzeBatchActionsLROPoller["_models.AnalyzeJobState"] """Submit analysis job. Submit a collection of text documents for analysis. Specify one or more unique tasks to be @@ -95,16 +102,16 @@ def begin_analyze( :type body: ~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeBatchInput :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. - :keyword polling: Pass in True if you'd like the LROBasePolling polling method, + :keyword polling: Pass in True if you'd like the AnalyzeBatchActionsLROPollingMethod polling method, False for no polling, or your own initialized polling object for a personal polling strategy. :paramtype polling: bool or ~azure.core.polling.PollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. - :return: An instance of LROPoller that returns either None or the result of cls(response) - :rtype: ~azure.core.polling.LROPoller[None] + :return: An instance of AnalyzeBatchActionsLROPoller that returns either AnalyzeJobState or the result of cls(response) + :rtype: ~...._lro.AnalyzeBatchActionsLROPoller[~azure.ai.textanalytics.v3_1_preview_3.models.AnalyzeJobState] :raises ~azure.core.exceptions.HttpResponseError: """ polling = kwargs.pop('polling', False) # type: Union[bool, PollingMethod] - cls = kwargs.pop('cls', None) # type: ClsType[None] + cls = kwargs.pop('cls', None) # type: ClsType["_models.AnalyzeJobState"] lro_delay = kwargs.pop( 'polling_interval', self._config.polling_interval @@ -121,25 +128,28 @@ def begin_analyze( kwargs.pop('content_type', None) def get_long_running_output(pipeline_response): + deserialized = self._deserialize('AnalyzeJobState', pipeline_response) + if cls: - return cls(pipeline_response, None, {}) + return cls(pipeline_response, deserialized, {}) + return deserialized path_format_arguments = { 'Endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True), } - if polling is True: polling_method = LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + if polling is True: polling_method = AnalyzeBatchActionsLROPollingMethod(lro_delay, path_format_arguments=path_format_arguments, **kwargs) elif polling is False: polling_method = NoPolling() else: polling_method = polling if cont_token: - return LROPoller.from_continuation_token( + return AnalyzeBatchActionsLROPoller.from_continuation_token( polling_method=polling_method, continuation_token=cont_token, client=self._client, deserialization_callback=get_long_running_output ) else: - return LROPoller(self._client, raw_result, get_long_running_output, polling_method) + return AnalyzeBatchActionsLROPoller(self._client, raw_result, get_long_running_output, polling_method) begin_analyze.metadata = {'url': '/analyze'} # type: ignore def analyze_status( @@ -412,8 +422,8 @@ def _health_initial( string_index_type="TextElements_v8", # type: Optional[Union[str, "_models.StringIndexType"]] **kwargs # type: Any ): - # type: (...) -> None - cls = kwargs.pop('cls', None) # type: ClsType[None] + # type: (...) -> Optional["_models.HealthcareJobState"] + cls = kwargs.pop('cls', None) # type: ClsType[Optional["_models.HealthcareJobState"]] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, @@ -453,16 +463,22 @@ def _health_initial( pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response - if response.status_code not in [202]: + if response.status_code not in [200, 202]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response) response_headers = {} - response_headers['Operation-Location']=self._deserialize('str', response.headers.get('Operation-Location')) + deserialized = None + if response.status_code == 200: + deserialized = self._deserialize('HealthcareJobState', pipeline_response) + + if response.status_code == 202: + response_headers['Operation-Location']=self._deserialize('str', response.headers.get('Operation-Location')) if cls: - return cls(pipeline_response, None, response_headers) + return cls(pipeline_response, deserialized, response_headers) + return deserialized _health_initial.metadata = {'url': '/entities/health/jobs'} # type: ignore def begin_health( @@ -472,7 +488,7 @@ def begin_health( string_index_type="TextElements_v8", # type: Optional[Union[str, "_models.StringIndexType"]] **kwargs # type: Any ): - # type: (...) -> LROPoller[None] + # type: (...) -> AnalyzeBatchActionsLROPoller["_models.HealthcareJobState"] """Submit healthcare analysis job. Start a healthcare analysis job to recognize healthcare related entities (drugs, conditions, @@ -489,16 +505,16 @@ def begin_health( :type string_index_type: str or ~azure.ai.textanalytics.v3_1_preview_3.models.StringIndexType :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. - :keyword polling: Pass in True if you'd like the LROBasePolling polling method, + :keyword polling: Pass in True if you'd like the AnalyzeBatchActionsLROPollingMethod polling method, False for no polling, or your own initialized polling object for a personal polling strategy. :paramtype polling: bool or ~azure.core.polling.PollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. - :return: An instance of LROPoller that returns either None or the result of cls(response) - :rtype: ~azure.core.polling.LROPoller[None] + :return: An instance of AnalyzeBatchActionsLROPoller that returns either HealthcareJobState or the result of cls(response) + :rtype: ~...._lro.AnalyzeBatchActionsLROPoller[~azure.ai.textanalytics.v3_1_preview_3.models.HealthcareJobState] :raises ~azure.core.exceptions.HttpResponseError: """ polling = kwargs.pop('polling', False) # type: Union[bool, PollingMethod] - cls = kwargs.pop('cls', None) # type: ClsType[None] + cls = kwargs.pop('cls', None) # type: ClsType["_models.HealthcareJobState"] lro_delay = kwargs.pop( 'polling_interval', self._config.polling_interval @@ -517,25 +533,28 @@ def begin_health( kwargs.pop('content_type', None) def get_long_running_output(pipeline_response): + deserialized = self._deserialize('HealthcareJobState', pipeline_response) + if cls: - return cls(pipeline_response, None, {}) + return cls(pipeline_response, deserialized, {}) + return deserialized path_format_arguments = { 'Endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True), } - if polling is True: polling_method = LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + if polling is True: polling_method = AnalyzeBatchActionsLROPollingMethod(lro_delay, path_format_arguments=path_format_arguments, **kwargs) elif polling is False: polling_method = NoPolling() else: polling_method = polling if cont_token: - return LROPoller.from_continuation_token( + return AnalyzeBatchActionsLROPoller.from_continuation_token( polling_method=polling_method, continuation_token=cont_token, client=self._client, deserialization_callback=get_long_running_output ) else: - return LROPoller(self._client, raw_result, get_long_running_output, polling_method) + return AnalyzeBatchActionsLROPoller(self._client, raw_result, get_long_running_output, polling_method) begin_health.metadata = {'url': '/entities/health/jobs'} # type: ignore def entities_recognition_general( diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_lro.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_lro.py index 0c7919ecd208..6c1da1bae8f1 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_lro.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_lro.py @@ -3,8 +3,8 @@ # Copyright (c) Microsoft Corporation. # Licensed under the MIT License. # ------------------------------------ - from six.moves.urllib.parse import urlencode +from azure.core.polling import LROPoller from azure.core.polling.base_polling import LROBasePolling, OperationResourcePolling, OperationFailed, BadStatus @@ -88,3 +88,101 @@ def _poll(self): if final_get_url: self._pipeline_response = self.request_status(final_get_url) TextAnalyticsLROPollingMethod._raise_if_bad_http_status_and_method(self._pipeline_response.http_response) + +class AnalyzeBatchActionsLROPollingMethod(TextAnalyticsLROPollingMethod): + + @property + def _current_body(self): + from ._generated.v3_1_preview_3.models import JobMetadata + return JobMetadata.deserialize(self._pipeline_response) + + @property + def created_on(self): + if not self._current_body: + return None + return self._current_body.created_date_time + + @property + def display_name(self): + if not self._current_body: + return None + return self._current_body.display_name + + @property + def expires_on(self): + if not self._current_body: + return None + return self._current_body.expiration_date_time + + @property + def actions_failed_count(self): + if not self._current_body: + return None + return self._current_body.additional_properties['tasks']['failed'] + + @property + def actions_in_progress_count(self): + if not self._current_body: + return None + return self._current_body.additional_properties['tasks']['inProgress'] + + @property + def actions_succeeded_count(self): + if not self._current_body: + return None + return self._current_body.additional_properties['tasks']["completed"] + + @property + def last_modified_on(self): + if not self._current_body: + return None + return self._current_body.last_update_date_time + + @property + def total_actions_count(self): + if not self._current_body: + return None + return self._current_body.additional_properties['tasks']["total"] + + @property + def id(self): + if not self._current_body: + return None + return self._current_body.job_id + +class AnalyzeBatchActionsLROPoller(LROPoller): + + @property + def created_on(self): + return self._polling_method.created_on + + @property + def display_name(self): + return self._polling_method.display_name + + @property + def expires_on(self): + return self._polling_method.expires_on + + @property + def actions_failed_count(self): + return self._polling_method.actions_failed_count + + @property + def actions_in_progress_count(self): + return self._polling_method.actions_in_progress_count + + @property + def actions_succeeded_count(self): + return self._polling_method.actions_succeeded_count + + @property + def last_modified_on(self): + return self._polling_method.last_modified_on + @property + def total_actions_count(self): + return self._polling_method.total_actions_count + + @property + def id(self): + return self._polling_method.id diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_models.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_models.py index 1cca6f5510c8..8a7bcb1ed5af 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_models.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_models.py @@ -68,7 +68,7 @@ def get(self, key, default=None): class PiiEntityDomainType(str, Enum): """The different domains of PII entities that users can filter by""" - PROTECTED_HEALTH_INFORMATION = "PHI" # See https://aka.ms/tanerpii for more information. + PROTECTED_HEALTH_INFORMATION = "phi" # See https://aka.ms/tanerpii for more information. class DetectedLanguage(DictMixin): @@ -765,6 +765,12 @@ def __repr__(self): class DetectLanguageInput(LanguageInput): """The input document to be analyzed for detecting language. + :keyword str id: Unique, non-empty document identifier. + :keyword str text: The input text to process. + :keyword str country_hint: A country hint to help better detect + the language of the text. Accepts two letter country codes + specified by ISO 3166-1 alpha-2. Defaults to "US". Pass + in the string "none" to not use a country_hint. :ivar id: Required. Unique, non-empty document identifier. :vartype id: str :ivar text: Required. The input text to process. @@ -903,7 +909,12 @@ def __repr__(self): class TextDocumentInput(DictMixin, MultiLanguageInput): """The input document to be analyzed by the service. - :ivar id: Required. A unique, non-empty document identifier. + :keyword str id: Unique, non-empty document identifier. + :keyword str text: The input text to process. + :keyword str language: This is the 2 letter ISO 639-1 representation + of a language. For example, use "en" for English; "es" for Spanish etc. If + not set, uses "en" for English as default. + :ivar id: Required. Unique, non-empty document identifier. :vartype id: str :ivar text: Required. The input text to process. :vartype text: str @@ -1224,13 +1235,81 @@ def __repr__(self): .format(self.positive, self.neutral, self.negative)[:1024] -class EntitiesRecognitionTask(DictMixin): - """EntitiesRecognitionTask encapsulates the parameters for starting a long-running Entities Recognition operation. +class AnalyzeBatchActionsType(str, Enum): + """The type of batch action that was applied to the documents + """ + RECOGNIZE_ENTITIES = "recognize_entities" #: Entities Recognition action. + RECOGNIZE_PII_ENTITIES = "recognize_pii_entities" #: PII Entities Recognition action. + EXTRACT_KEY_PHRASES = "extract_key_phrases" #: Key Phrase Extraction action. + + +class AnalyzeBatchActionsResult(DictMixin): + """AnalyzeBatchActionsResult contains the results of a recognize entities action + on a list of documents. Returned by `begin_analyze_batch_actions` + + :ivar document_results: A list of objects containing results for all Entity Recognition actions + included in the analysis. + :vartype document_results: list[~azure.ai.textanalytics.RecognizeEntitiesResult] + :ivar bool is_error: Boolean check for error item when iterating over list of + actions. Always False for an instance of a AnalyzeBatchActionsResult. + :ivar action_type: The type of batch action this class is a result of. + :vartype action_type: str or ~azure.ai.textanalytics.AnalyzeBatchActionsType + :ivar ~datetime.datetime completed_on: Date and time (UTC) when the result completed + on the service. + """ + def __init__(self, **kwargs): + self.document_results = kwargs.get("document_results") + self.is_error = False + self.action_type = kwargs.get("action_type") + self.completed_on = kwargs.get("completed_on") + + def __repr__(self): + return "AnalyzeBatchActionsResult(document_results={}, is_error={}, action_type={}, completed_on={})" \ + .format( + repr(self.document_results), + self.is_error, + self.action_type, + self.completed_on + )[:1024] + +class AnalyzeBatchActionsError(DictMixin): + """AnalyzeBatchActionsError is an error object which represents an an + error response for an action. + + :ivar error: The action result error. + :vartype error: ~azure.ai.textanalytics.TextAnalyticsError + :ivar bool is_error: Boolean check for error item when iterating over list of + results. Always True for an instance of a DocumentError. + """ + + def __init__(self, **kwargs): + self.error = kwargs.get("error") + self.is_error = True + + def __repr__(self): + return "AnalyzeBatchActionsError(error={}, is_error={}".format( + repr(self.error), self.is_error + ) + + @classmethod + def _from_generated(cls, error): + return cls( + error=TextAnalyticsError(code=error.code, message=error.message, target=error.target) + ) + + +class RecognizeEntitiesAction(DictMixin): + """RecognizeEntitiesAction encapsulates the parameters for starting a long-running Entities Recognition operation. + + If you just want to recognize entities in a list of documents, and not perform a batch + of long running actions on the input of documents, call method `recognize_entities` instead + of interfacing with this model. - :ivar str model_version: The model version to use for the analysis. - :ivar str string_index_type: Specifies the method used to interpret string offsets. - Can be one of 'UnicodeCodePoint' (default), 'Utf16CodePoint', or 'TextElements_v8'. - For additional information see https://aka.ms/text-analytics-offsets + :keyword str model_version: The model version to use for the analysis. + :keyword str string_index_type: Specifies the method used to interpret string offsets. + `UnicodeCodePoint`, the Python encoding, is the default. To override the Python default, + you can also pass in `Utf16CodePoint` or TextElements_v8`. For additional information + see https://aka.ms/text-analytics-offsets """ def __init__(self, **kwargs): @@ -1238,7 +1317,7 @@ def __init__(self, **kwargs): self.string_index_type = kwargs.get("string_index_type", "UnicodeCodePoint") def __repr__(self, **kwargs): - return "EntitiesRecognitionTask(model_version={}, string_index_type={})" \ + return "RecognizeEntitiesAction(model_version={}, string_index_type={})" \ .format(self.model_version, self.string_index_type)[:1024] def to_generated(self): @@ -1250,84 +1329,58 @@ def to_generated(self): ) -class EntitiesRecognitionTaskResult(DictMixin): - """EntitiesRecognitionTaskResult contains the results of a single Entities Recognition task, - including additional task metadata. +class RecognizePiiEntitiesAction(DictMixin): + """RecognizePiiEntitiesAction encapsulates the parameters for starting a long-running PII + Entities Recognition operation. - :ivar str name: The name of the task. - :ivar results: The results of the analysis. - :vartype results: list[~azure.ai.textanalytics.RecognizeEntitiesResult] - """ - - def __init__(self, **kwargs): - self.name = kwargs.get("name", None) - self.results = kwargs.get("results", []) - - def __repr__(self, **kwargs): - return "EntitiesRecognitionTaskResult(name={}, results={})" \ - .format(self.name, repr(self.results))[:1024] - - -class PiiEntitiesRecognitionTask(DictMixin): - """PiiEntitiesRecognitionTask encapsulates the parameters for starting a - long-running PII Entities Recognition operation. + If you just want to recognize pii entities in a list of documents, and not perform a batch + of long running actions on the input of documents, call method `recognize_pii_entities` instead + of interfacing with this model. - :ivar str model_version: The model version to use for the analysis. - :ivar str domain: An optional string to set the PII domain to include only a - subset of the entity categories. Possible values include 'PHI' or None. - :ivar str string_index_type: Specifies the method used to interpret string offsets. - Can be one of 'UnicodeCodePoint' (default), 'Utf16CodePoint', or 'TextElements_v8'. - For additional information see https://aka.ms/text-analytics-offsets + :keyword str model_version: The model version to use for the analysis. + :keyword str domain_filter: An optional string to set the PII domain to include only a + subset of the PII entity categories. Possible values include 'phi' or None. + :keyword str string_index_type: Specifies the method used to interpret string offsets. + `UnicodeCodePoint`, the Python encoding, is the default. To override the Python default, + you can also pass in `Utf16CodePoint` or TextElements_v8`. For additional information + see https://aka.ms/text-analytics-offsets """ def __init__(self, **kwargs): self.model_version = kwargs.get("model_version", "latest") - self.domain = kwargs.get("domain", None) + self.domain_filter = kwargs.get("domain_filter", None) self.string_index_type = kwargs.get("string_index_type", "UnicodeCodePoint") def __repr__(self, **kwargs): - return "PiiEntitiesRecognitionTask(model_version={}, domain={}, string_index_type={})" \ - .format(self.model_version, self.domain, self.string_index_type)[:1024] + return "RecognizePiiEntitiesAction(model_version={}, domain_filter={}, string_index_type={})" \ + .format(self.model_version, self.domain_filter, self.string_index_type)[:1024] def to_generated(self): return _v3_1_preview_3_models.PiiTask( parameters=_v3_1_preview_3_models.PiiTaskParameters( model_version=self.model_version, - domain=self.domain, + domain=self.domain_filter, string_index_type=self.string_index_type ) ) -class PiiEntitiesRecognitionTaskResult(DictMixin): - """PiiEntitiesRecognitionTaskResult contains the results of a single PII Entities Recognition task, - including additional task metadata. +class ExtractKeyPhrasesAction(DictMixin): + """ExtractKeyPhrasesAction encapsulates the parameters for starting a long-running key phrase + extraction operation - :ivar str name: The name of the task. - :ivar results: The results of the analysis. - :vartype results: list[~azure.ai.textanalytics.RecognizePiiEntitiesResult] - """ + If you just want to extract key phrases from a list of documents, and not perform a batch + of long running actions on the input of documents, call method `extract_key_phrases` instead + of interfacing with this model. - def __init__(self, **kwargs): - self.name = kwargs.get("name", None) - self.results = kwargs.get("results", []) - - def __repr__(self, **kwargs): - return "PiiEntitiesRecognitionTaskResult(name={}, results={})" \ - .format(self.name, repr(self.results))[:1024] - - -class KeyPhraseExtractionTask(DictMixin): - """KeyPhraseExtractionTask encapsulates the parameters for starting a long-running Key Phrase Extraction operation. - - :ivar str model_version: The model version to use for the analysis. + :keyword str model_version: The model version to use for the analysis. """ def __init__(self, **kwargs): self.model_version = kwargs.get("model_version", "latest") def __repr__(self, **kwargs): - return "KeyPhraseExtractionTask(model_version={})" \ + return "ExtractKeyPhrasesAction(model_version={})" \ .format(self.model_version)[:1024] def to_generated(self): @@ -1337,53 +1390,6 @@ def to_generated(self): ) ) - -class KeyPhraseExtractionTaskResult(DictMixin): - """KeyPhraseExtractionTaskResult contains the results of a single Key Phrase Extraction task, including additional - task metadata. - - :ivar str name: The name of the task. - :ivar results: The results of the analysis. - :vartype results: list[~azure.ai.textanalytics.ExtractKeyPhrasesResult] - """ - - def __init__(self, **kwargs): - self.name = kwargs.get("name", None) - self.results = kwargs.get("results", []) - - def __repr__(self, **kwargs): - return "KeyPhraseExtractionTaskResult(name={}, results={})" \ - .format(self.name, repr(self.results))[:1024] - - -class TextAnalysisResult(DictMixin): - """TextAnalysisResult contains the results of multiple text analyses performed on a batch of documents. - - :ivar entities_recognition_results: A list of objects containing results for all Entity Recognition tasks - included in the analysis. - :vartype entities_recognition_results: list[~azure.ai.textanalytics.EntitiesRecognitionTaskResult] - :ivar pii_entities_recognition_results: A list of objects containing results for all PII Entity Recognition - tasks included in the analysis. - :vartype pii_entities_recogition_results: list[~azure.ai.textanalytics.PiiEntitiesRecognitionTaskResult] - :ivar key_phrase_extraction_results: A list of objects containing results for all Key Phrase Extraction tasks - included in the analysis. - :vartype key_phrase_extraction_results: list[~azure.ai.textanalytics.KeyPhraseExtractionTaskResult] - """ - def __init__(self, **kwargs): - self.entities_recognition_results = kwargs.get("entities_recognition_results", []) - self.pii_entities_recognition_results = kwargs.get("pii_entities_recognition_results", []) - self.key_phrase_extraction_results = kwargs.get("key_phrase_extraction_results", []) - - def __repr__(self): - return "TextAnalysisResult(entities_recognition_results={}, pii_entities_recognition_results={}, \ - key_phrase_extraction_results={})" \ - .format( - repr(self.entities_recognition_results), - repr(self.pii_entities_recognition_results), - repr(self.key_phrase_extraction_results) - )[:1024] - - class RequestStatistics(DictMixin): def __init__(self, **kwargs): self.documents_count = kwargs.get("documents_count") diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_policies.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_policies.py index 3d0fca67ebcd..0db101c7f079 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_policies.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_policies.py @@ -18,14 +18,16 @@ def on_request(self, request): self._response_callback = request.context.options.pop("raw_response_hook", self._response_callback) def on_response(self, request, response): + if self._response_callback: data = ContentDecodePolicy.deserialize_from_http_generics(response.http_response) - statistics = data.get("statistics", None) - model_version = data.get("modelVersion", None) + if data: + statistics = data.get("statistics", None) + model_version = data.get("modelVersion", None) - if statistics or model_version: - batch_statistics = TextDocumentBatchStatistics._from_generated(statistics) # pylint: disable=protected-access - response.statistics = batch_statistics - response.model_version = model_version - response.raw_response = data - self._response_callback(response) + if statistics or model_version: + batch_statistics = TextDocumentBatchStatistics._from_generated(statistics) # pylint: disable=protected-access + response.statistics = batch_statistics + response.model_version = model_version + response.raw_response = data + self._response_callback(response) diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_request_handlers.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_request_handlers.py index 9f992ac5f6a9..2e02bfc49d30 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_request_handlers.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_request_handlers.py @@ -10,9 +10,11 @@ from ._models import ( DetectLanguageInput, TextDocumentInput, + RecognizeEntitiesAction, + RecognizePiiEntitiesAction, + AnalyzeBatchActionsType, ) - def _validate_input(documents, hint, whole_input_hint): """Validate that batch input has either all string docs or dict/DetectLanguageInput/TextDocumentInput, not a mix of both. @@ -65,6 +67,12 @@ def _validate_input(documents, hint, whole_input_hint): return request_batch +def _determine_action_type(action): + if isinstance(action, RecognizeEntitiesAction): + return AnalyzeBatchActionsType.RECOGNIZE_ENTITIES + if isinstance(action, RecognizePiiEntitiesAction): + return AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES + return AnalyzeBatchActionsType.EXTRACT_KEY_PHRASES def _check_string_index_type_arg(string_index_type_arg, api_version, string_index_type_default="UnicodeCodePoint"): string_index_type = None diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_response_handlers.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_response_handlers.py index 42df6bd801b0..9f3bad15b20c 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_response_handlers.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_response_handlers.py @@ -6,6 +6,7 @@ import json import functools +from collections import defaultdict from six.moves.urllib.parse import urlparse, parse_qsl from azure.core.exceptions import ( HttpResponseError, @@ -30,11 +31,12 @@ RecognizePiiEntitiesResult, PiiEntity, AnalyzeHealthcareResultItem, - TextAnalysisResult, - EntitiesRecognitionTaskResult, - PiiEntitiesRecognitionTaskResult, - KeyPhraseExtractionTaskResult, - RequestStatistics + AnalyzeBatchActionsResult, + RequestStatistics, + AnalyzeBatchActionsType, + AnalyzeBatchActionsError, + TextDocumentBatchStatistics, + _get_indices, ) from ._paging import AnalyzeHealthcareResult, AnalyzeResult @@ -193,36 +195,92 @@ def healthcare_result(health_result, results, *args, **kwargs): # pylint: disabl return AnalyzeHealthcareResultItem._from_generated(health_result) # pylint: disable=protected-access -def analyze_result(doc_id_order, obj, response_headers, tasks, **kwargs): # pylint: disable=unused-argument - return TextAnalysisResult( - entities_recognition_results=[ - EntitiesRecognitionTaskResult( - name=t.name, - results=entities_result(doc_id_order, t.results, response_headers, lro=True) - ) for t in tasks.entity_recognition_tasks - ] if tasks.entity_recognition_tasks else [], - pii_entities_recognition_results=[ - PiiEntitiesRecognitionTaskResult( - name=t.name, - results=pii_entities_result(doc_id_order, t.results, response_headers, lro=True) - ) for t in tasks.entity_recognition_pii_tasks - ] if tasks.entity_recognition_pii_tasks else [], - key_phrase_extraction_results=[ - KeyPhraseExtractionTaskResult( - name=t.name, - results=key_phrases_result(doc_id_order, t.results, response_headers, lro=True) - ) for t in tasks.key_phrase_extraction_tasks - ] if tasks.key_phrase_extraction_tasks else [] - ) - - def healthcare_extract_page_data(doc_id_order, obj, response_headers, health_job_state): # pylint: disable=unused-argument return (health_job_state.next_link, healthcare_result(doc_id_order, health_job_state.results, response_headers, lro=True)) +def _get_deserialization_callback_from_task_type(task_type): + if task_type == AnalyzeBatchActionsType.RECOGNIZE_ENTITIES: + return entities_result + if task_type == AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES: + return pii_entities_result + return key_phrases_result + +def _get_property_name_from_task_type(task_type): + if task_type == AnalyzeBatchActionsType.RECOGNIZE_ENTITIES: + return "entity_recognition_tasks" + if task_type == AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES: + return "entity_recognition_pii_tasks" + return "key_phrase_extraction_tasks" + +def _num_tasks_in_current_page(returned_tasks_object): + return ( + len(returned_tasks_object.entity_recognition_tasks or []) + + len(returned_tasks_object.entity_recognition_pii_tasks or []) + + len(returned_tasks_object.key_phrase_extraction_tasks or []) + ) + +def _get_task_type_from_error(error): + if "pii" in error.target.lower(): + return AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES + if "entity" in error.target.lower(): + return AnalyzeBatchActionsType.RECOGNIZE_ENTITIES + return AnalyzeBatchActionsType.EXTRACT_KEY_PHRASES + +def _get_mapped_errors(analyze_job_state): + """ + """ + mapped_errors = defaultdict(list) + if not analyze_job_state.errors: + return mapped_errors + for error in analyze_job_state.errors: + mapped_errors[_get_task_type_from_error(error)].append((_get_error_index(error), error)) + return mapped_errors + +def _get_error_index(error): + return _get_indices(error.target)[-1] + +def _get_good_result(current_task_type, index_of_task_result, doc_id_order, response_headers, returned_tasks_object): + deserialization_callback = _get_deserialization_callback_from_task_type(current_task_type) + property_name = _get_property_name_from_task_type(current_task_type) + response_task_to_deserialize = getattr(returned_tasks_object, property_name)[index_of_task_result] + document_results = deserialization_callback( + doc_id_order, response_task_to_deserialize.results, response_headers, lro=True + ) + return AnalyzeBatchActionsResult( + document_results=document_results, + action_type=current_task_type, + completed_on=response_task_to_deserialize.last_update_date_time, + ) + +def get_iter_items(doc_id_order, task_order, response_headers, analyze_job_state): + iter_items = [] + task_type_to_index = defaultdict(int) # need to keep track of how many of each type of tasks we've seen + returned_tasks_object = analyze_job_state.tasks + mapped_errors = _get_mapped_errors(analyze_job_state) + for current_task_type in task_order: + index_of_task_result = task_type_to_index[current_task_type] -def analyze_extract_page_data(doc_id_order, obj, response_headers, analyze_job_state): - return analyze_job_state.next_link, [analyze_result(doc_id_order, obj, response_headers, analyze_job_state.tasks)] + try: + # try to deserailize as error. If fails, we know it's good + # kind of a weird way to order things, but we can fail when deserializing + # the curr response as an error, not when deserializing as a good response. + + current_task_type_errors = mapped_errors[current_task_type] + error = next(err for err in current_task_type_errors if err[0] == index_of_task_result) + result = AnalyzeBatchActionsError._from_generated(error[1]) # pylint: disable=protected-access + except StopIteration: + result = _get_good_result( + current_task_type, index_of_task_result, doc_id_order, response_headers, returned_tasks_object + ) + iter_items.append(result) + task_type_to_index[current_task_type] += 1 + return iter_items + +def analyze_extract_page_data(doc_id_order, task_order, response_headers, analyze_job_state): + # return next link, list of + iter_items = get_iter_items(doc_id_order, task_order, response_headers, analyze_job_state) + return analyze_job_state.next_link, iter_items def lro_get_next_page(lro_status_callback, first_page, continuation_token, show_stats=False): @@ -251,12 +309,12 @@ def healthcare_paged_result(doc_id_order, health_status_callback, _, obj, respon statistics=RequestStatistics._from_generated(obj.results.statistics) if show_stats else None # pylint: disable=protected-access ) -def analyze_paged_result(doc_id_order, analyze_status_callback, _, obj, response_headers, show_stats=False): # pylint: disable=unused-argument +def analyze_paged_result(doc_id_order, task_order, analyze_status_callback, _, obj, response_headers, show_stats=False): # pylint: disable=unused-argument return AnalyzeResult( functools.partial(lro_get_next_page, analyze_status_callback, obj, show_stats=show_stats), - functools.partial(analyze_extract_page_data, doc_id_order, obj, response_headers), - statistics=RequestStatistics._from_generated(obj.statistics) \ - if show_stats and obj.statistics is not None else None # pylint: disable=protected-access + functools.partial(analyze_extract_page_data, doc_id_order, task_order, response_headers), + statistics=TextDocumentBatchStatistics._from_generated(obj.statistics) \ + if (show_stats and obj.statistics) else None # pylint: disable=protected-access ) def _get_deserialize(): diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_response_handlers_async.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_response_handlers_async.py index 4059f532f1eb..cb9d23fe7de2 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_response_handlers_async.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_response_handlers_async.py @@ -8,9 +8,10 @@ import functools from urllib.parse import urlparse, parse_qsl -from ._models import RequestStatistics +from azure.core.async_paging import AsyncList +from ._models import RequestStatistics, TextDocumentBatchStatistics from ._async_paging import AnalyzeHealthcareResultAsync, AnalyzeResultAsync -from ._response_handlers import healthcare_result, analyze_result +from ._response_handlers import healthcare_result, get_iter_items async def healthcare_extract_page_data_async(doc_id_order, obj, response_headers, health_job_state): # pylint: disable=unused-argument @@ -18,10 +19,6 @@ async def healthcare_extract_page_data_async(doc_id_order, obj, response_headers healthcare_result(doc_id_order, health_job_state.results, response_headers, lro=True)) -async def analyze_extract_page_data_async(doc_id_order, obj, response_headers, analyze_job_state): - return analyze_job_state.next_link, [analyze_result(doc_id_order, obj, response_headers, analyze_job_state.tasks)] - - async def lro_get_next_page_async(lro_status_callback, first_page, continuation_token, show_stats=False): if continuation_token is None: return first_page @@ -48,11 +45,16 @@ def healthcare_paged_result(doc_id_order, health_status_callback, response, obj, statistics=RequestStatistics._from_generated(obj.results.statistics) if show_stats else None # pylint: disable=protected-access ) +async def analyze_extract_page_data_async(doc_id_order, task_order, response_headers, analyze_job_state): + iter_items = get_iter_items(doc_id_order, task_order, response_headers, analyze_job_state) + return analyze_job_state.next_link, AsyncList(iter_items) -def analyze_paged_result(doc_id_order, analyze_status_callback, response, obj, response_headers, show_stats=False): # pylint: disable=unused-argument +def analyze_paged_result( + doc_id_order, task_order, analyze_status_callback, response, obj, response_headers, show_stats=False # pylint: disable=unused-argument +): return AnalyzeResultAsync( functools.partial(lro_get_next_page_async, analyze_status_callback, obj), - functools.partial(analyze_extract_page_data_async, doc_id_order, obj, response_headers), - statistics=RequestStatistics._from_generated(obj.statistics) \ + functools.partial(analyze_extract_page_data_async, doc_id_order, task_order, response_headers), + statistics=TextDocumentBatchStatistics._from_generated(obj.statistics) \ if show_stats and obj.statistics is not None else None # pylint: disable=protected-access ) diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_text_analytics_client.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_text_analytics_client.py index b5a4cab3c408..4eeb34cc9564 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_text_analytics_client.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_text_analytics_client.py @@ -19,7 +19,7 @@ from azure.core.tracing.decorator import distributed_trace from azure.core.exceptions import HttpResponseError from ._base_client import TextAnalyticsClientBase -from ._request_handlers import _validate_input, _check_string_index_type_arg +from ._request_handlers import _validate_input, _determine_action_type, _check_string_index_type_arg from ._response_handlers import ( process_http_response_error, entities_result, @@ -32,7 +32,14 @@ analyze_paged_result, _get_deserialize ) -from ._lro import TextAnalyticsOperationResourcePolling, TextAnalyticsLROPollingMethod + +from ._models import AnalyzeBatchActionsType + +from ._lro import ( + TextAnalyticsOperationResourcePolling, + TextAnalyticsLROPollingMethod, + AnalyzeBatchActionsLROPollingMethod, +) if TYPE_CHECKING: from azure.core.credentials import TokenCredential, AzureKeyCredential @@ -46,11 +53,11 @@ AnalyzeSentimentResult, DocumentError, RecognizePiiEntitiesResult, - EntitiesRecognitionTask, - PiiEntitiesRecognitionTask, - KeyPhraseExtractionTask, + RecognizeEntitiesAction, + RecognizePiiEntitiesAction, + ExtractKeyPhrasesAction, AnalyzeHealthcareResultItem, - TextAnalysisResult + AnalyzeBatchActionsResult, ) @@ -289,7 +296,7 @@ def recognize_pii_entities( # type: ignore :keyword bool show_stats: If set to true, response will contain document level statistics in the `statistics` field of the document-level response. :keyword domain_filter: Filters the response entities to ones only included in the specified domain. - I.e., if set to 'PHI', will only return entities in the Protected Healthcare Information domain. + I.e., if set to 'phi', will only return entities in the Protected Healthcare Information domain. See https://aka.ms/tanerpii for more information. :paramtype domain_filter: str or ~azure.ai.textanalytics.PiiEntityDomainType :keyword str string_index_type: Specifies the method used to interpret string offsets. @@ -722,13 +729,14 @@ def analyze_sentiment( # type: ignore except HttpResponseError as error: process_http_response_error(error) - def _analyze_result_callback(self, doc_id_order, raw_response, _, headers, show_stats=False): + def _analyze_result_callback(self, doc_id_order, task_order, raw_response, _, headers, show_stats=False): analyze_result = self._deserialize( self._client.models(api_version="v3.1-preview.3").AnalyzeJobState, # pylint: disable=protected-access raw_response ) return analyze_paged_result( doc_id_order, + task_order, self._client.analyze_status, raw_response, analyze_result, @@ -737,15 +745,13 @@ def _analyze_result_callback(self, doc_id_order, raw_response, _, headers, show_ ) @distributed_trace - def begin_analyze( # type: ignore + def begin_analyze_batch_actions( # type: ignore self, documents, # type: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]] - entities_recognition_tasks=None, # type: List[EntitiesRecognitionTask] - pii_entities_recognition_tasks=None, # type: List[PiiEntitiesRecognitionTask] - key_phrase_extraction_tasks=None, # type: List[KeyPhraseExtractionTask] + actions, # type: List[Union[RecognizeEntitiesAction, RecognizePiiEntitiesAction, ExtractKeyPhrasesAction]] **kwargs # type: Any - ): # type: (...) -> LROPoller[ItemPaged[TextAnalysisResult]] - """Start a long-running operation to perform a variety of text analysis tasks over a batch of documents. + ): # type: (...) -> LROPoller[ItemPaged[AnalyzeBatchActionsResult]] + """Start a long-running operation to perform a variety of text analysis actions over a batch of documents. :param documents: The set of documents to process as part of this batch. If you wish to specify the ID and language on a per-item basis you must @@ -755,11 +761,12 @@ def begin_analyze( # type: ignore :type documents: list[str] or list[~azure.ai.textanalytics.TextDocumentInput] or list[dict[str, str]] - :param tasks: A list of tasks to include in the analysis. Each task object encapsulates the parameters - used for the particular task type. - :type tasks: list[Union[~azure.ai.textanalytics.EntitiesRecognitionTask, - ~azure.ai.textanalytics.PiiEntitiesRecognitionTask, ~azure.ai.textanalytics.EntityLinkingTask, - ~azure.ai.textanalytics.KeyPhraseExtractionTask, ~azure.ai.textanalytics.SentimentAnalysisTask]] + :param actions: A heterogeneous list of actions to perform on the inputted documents. + Each action object encapsulates the parameters used for the particular action type. + The outputted action results will be in the same order you inputted your actions. + Duplicate actions in list not supported. + :type actions: + list[RecognizeEntitiesAction or RecognizePiiEntitiesAction or ExtractKeyPhrasesAction] :keyword str display_name: An optional display name to set for the requested analysis. :keyword str language: The 2 letter ISO 639-1 representation of language for the entire batch. For example, use "en" for English; "es" for Spanish etc. @@ -770,18 +777,22 @@ def begin_analyze( # type: ignore :keyword int polling_interval: Waiting time between two polls for LRO operations if no Retry-After header is present. Defaults to 30 seconds. :return: An instance of an LROPoller. Call `result()` on the poller - object to return an instance of TextAnalysisResult. + object to return a pageable heterogeneous list of the action results in the order + the actions were sent in this method. + :rtype: + ~azure.core.polling.LROPoller[~azure.core.paging.ItemPaged[ + ~azure.ai.textanalytics.AnalyzeBatchActionsResult]] :raises ~azure.core.exceptions.HttpResponseError or TypeError or ValueError or NotImplementedError: .. admonition:: Example: - .. literalinclude:: ../samples/sample_analyze.py + .. literalinclude:: ../samples/sample_analyze_batch_actions.py :start-after: [START analyze] :end-before: [END analyze] :language: python :dedent: 8 :caption: Start a long-running operation to perform a variety of text analysis - tasks over a batch of documents. + actions over a batch of documents. """ display_name = kwargs.pop("display_name", None) @@ -795,18 +806,22 @@ def begin_analyze( # type: ignore continuation_token = kwargs.pop("continuation_token", None) doc_id_order = [doc.get("id") for doc in docs.documents] + task_order = [_determine_action_type(action) for action in actions] try: analyze_tasks = self._client.models(api_version='v3.1-preview.3').JobManifestTasks( entity_recognition_tasks=[ - t.to_generated() for t in entities_recognition_tasks - ] if entities_recognition_tasks else [], + t.to_generated() for t in + [a for a in actions if _determine_action_type(a) == AnalyzeBatchActionsType.RECOGNIZE_ENTITIES] + ], entity_recognition_pii_tasks=[ - t.to_generated() for t in pii_entities_recognition_tasks - ] if pii_entities_recognition_tasks else [], + t.to_generated() for t in + [a for a in actions if _determine_action_type(a) == AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES] + ], key_phrase_extraction_tasks=[ - t.to_generated() for t in key_phrase_extraction_tasks - ] if key_phrase_extraction_tasks else [] + t.to_generated() for t in + [a for a in actions if _determine_action_type(a) == AnalyzeBatchActionsType.EXTRACT_KEY_PHRASES] + ] ) analyze_body = self._client.models(api_version='v3.1-preview.3').AnalyzeBatchInput( display_name=display_name, @@ -815,8 +830,10 @@ def begin_analyze( # type: ignore ) return self._client.begin_analyze( body=analyze_body, - cls=kwargs.pop("cls", partial(self._analyze_result_callback, doc_id_order, show_stats=show_stats)), - polling=TextAnalyticsLROPollingMethod( + cls=kwargs.pop("cls", partial( + self._analyze_result_callback, doc_id_order, task_order, show_stats=show_stats + )), + polling=AnalyzeBatchActionsLROPollingMethod( timeout=polling_interval, lro_algorithms=[ TextAnalyticsOperationResourcePolling(show_stats=show_stats) @@ -829,7 +846,7 @@ def begin_analyze( # type: ignore except ValueError as error: if "API version v3.0 does not have operation 'begin_analyze'" in str(error): raise ValueError( - "'begin_analyze' endpoint is only available for API version v3.1-preview.3" + "'begin_analyze_batch_actions' endpoint is only available for API version v3.1-preview.3" ) raise error diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/aio/_text_analytics_client_async.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/aio/_text_analytics_client_async.py index 02a336ac4eaa..fd93203a9956 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/aio/_text_analytics_client_async.py +++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/aio/_text_analytics_client_async.py @@ -18,7 +18,7 @@ from azure.core.tracing.decorator_async import distributed_trace_async from azure.core.exceptions import HttpResponseError from ._base_client_async import AsyncTextAnalyticsClientBase -from .._request_handlers import _validate_input, _check_string_index_type_arg +from .._request_handlers import _validate_input, _determine_action_type, _check_string_index_type_arg from .._response_handlers import ( process_http_response_error, entities_result, @@ -41,13 +41,14 @@ DocumentError, RecognizePiiEntitiesResult, AnalyzeHealthcareResultItem, - EntitiesRecognitionTask, - PiiEntitiesRecognitionTask, - KeyPhraseExtractionTask, - TextAnalysisResult + RecognizeEntitiesAction, + RecognizePiiEntitiesAction, + ExtractKeyPhrasesAction, + AnalyzeBatchActionsResult, + AnalyzeBatchActionsType, ) from .._lro import TextAnalyticsOperationResourcePolling -from .._async_lro import TextAnalyticsAsyncLROPollingMethod +from .._async_lro import AsyncAnalyzeBatchActionsLROPollingMethod, TextAnalyticsAsyncLROPollingMethod if TYPE_CHECKING: from azure.core.credentials_async import AsyncTokenCredential @@ -289,7 +290,7 @@ async def recognize_pii_entities( # type: ignore :keyword bool show_stats: If set to true, response will contain document level statistics in the `statistics` field of the document-level response. :keyword domain_filter: Filters the response entities to ones only included in the specified domain. - I.e., if set to 'PHI', will only return entities in the Protected Healthcare Information domain. + I.e., if set to 'phi', will only return entities in the Protected Healthcare Information domain. See https://aka.ms/tanerpii for more information. :paramtype domain_filter: str or ~azure.ai.textanalytics.PiiEntityDomainType :keyword str string_index_type: Specifies the method used to interpret string offsets. @@ -717,13 +718,14 @@ async def begin_cancel_analyze_healthcare( # type: ignore except HttpResponseError as error: process_http_response_error(error) - def _analyze_result_callback(self, doc_id_order, raw_response, _, headers, show_stats=False): + def _analyze_result_callback(self, doc_id_order, task_order, raw_response, _, headers, show_stats=False): analyze_result = self._deserialize( self._client.models(api_version="v3.1-preview.3").AnalyzeJobState, raw_response ) return analyze_paged_result( doc_id_order, + task_order, self._client.analyze_status, raw_response, analyze_result, @@ -732,15 +734,13 @@ def _analyze_result_callback(self, doc_id_order, raw_response, _, headers, show_ ) @distributed_trace_async - async def begin_analyze( # type: ignore + async def begin_analyze_batch_actions( # type: ignore self, documents, # type: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]] - entities_recognition_tasks=None, # type: List[EntitiesRecognitionTask] - pii_entities_recognition_tasks=None, # type: List[PiiEntitiesRecognitionTask] - key_phrase_extraction_tasks=None, # type: List[KeyPhraseExtractionTask] + actions, # type: List[Union[RecognizeEntitiesAction, RecognizePiiEntitiesAction, ExtractKeyPhrasesAction]] **kwargs # type: Any - ): # type: (...) -> AsyncLROPoller[AsyncItemPaged[TextAnalysisResult]] - """Start a long-running operation to perform a variety of text analysis tasks over a batch of documents. + ): # type: (...) -> AsyncLROPoller[AsyncItemPaged[AnalyzeBatchActionsResult]] + """Start a long-running operation to perform a variety of text analysis actions over a batch of documents. :param documents: The set of documents to process as part of this batch. If you wish to specify the ID and language on a per-item basis you must @@ -750,11 +750,12 @@ async def begin_analyze( # type: ignore :type documents: list[str] or list[~azure.ai.textanalytics.TextDocumentInput] or list[dict[str, str]] - :param tasks: A list of tasks to include in the analysis. Each task object encapsulates the parameters - used for the particular task type. - :type tasks: list[Union[~azure.ai.textanalytics.EntitiesRecognitionTask, - ~azure.ai.textanalytics.PiiEntitiesRecognitionTask, ~azure.ai.textanalytics.EntityLinkingTask, - ~azure.ai.textanalytics.KeyPhraseExtractionTask, ~azure.ai.textanalytics.SentimentAnalysisTask]] + :param actions: A heterogeneous list of actions to perform on the inputted documents. + Each action object encapsulates the parameters used for the particular action type. + The outputted action results will be in the same order you inputted your actions. + Duplicate actions in list not supported. + :type actions: + list[RecognizeEntitiesAction or RecognizePiiEntitiesAction or ExtractKeyPhrasesAction] :keyword str display_name: An optional display name to set for the requested analysis. :keyword str language: The 2 letter ISO 639-1 representation of language for the entire batch. For example, use "en" for English; "es" for Spanish etc. @@ -764,14 +765,17 @@ async def begin_analyze( # type: ignore :keyword bool show_stats: If set to true, response will contain document level statistics. :keyword int polling_interval: Waiting time between two polls for LRO operations if no Retry-After header is present. Defaults to 30 seconds. - :keyword str continuation_token: A continuation token to restart a poller from a saved state. - :return: An instance of an AsyncLROPoller. Call `result()` on the poller - object to return an instance of TextAnalysisResult. + :return: An instance of an LROPoller. Call `result()` on the poller + object to return a pageable heterogeneous list of the action results in the order + the actions were sent in this method. + :rtype: + ~azure.core.polling.AsyncLROPoller[~azure.core.async_paging.AsyncItemPaged[ + ~azure.ai.textanalytics.AnalyzeBatchActionsResult]] :raises ~azure.core.exceptions.HttpResponseError or TypeError or ValueError or NotImplementedError: .. admonition:: Example: - .. literalinclude:: ../samples/async_samples/sample_analyze_async.py + .. literalinclude:: ../samples/async_samples/sample_analyze_batch_actions_async.py :start-after: [START analyze_async] :end-before: [END analyze_async] :language: python @@ -791,18 +795,22 @@ async def begin_analyze( # type: ignore continuation_token = kwargs.pop("continuation_token", None) doc_id_order = [doc.get("id") for doc in docs.documents] + task_order = [_determine_action_type(action) for action in actions] try: analyze_tasks = self._client.models(api_version='v3.1-preview.3').JobManifestTasks( entity_recognition_tasks=[ - t.to_generated() for t in entities_recognition_tasks - ] if entities_recognition_tasks else [], + t.to_generated() for t in + [a for a in actions if _determine_action_type(a) == AnalyzeBatchActionsType.RECOGNIZE_ENTITIES] + ], entity_recognition_pii_tasks=[ - t.to_generated() for t in pii_entities_recognition_tasks - ] if pii_entities_recognition_tasks else [], + t.to_generated() for t in + [a for a in actions if _determine_action_type(a) == AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES] + ], key_phrase_extraction_tasks=[ - t.to_generated() for t in key_phrase_extraction_tasks - ] if key_phrase_extraction_tasks else [] + t.to_generated() for t in + [a for a in actions if _determine_action_type(a) == AnalyzeBatchActionsType.EXTRACT_KEY_PHRASES] + ] ) analyze_body = self._client.models(api_version='v3.1-preview.3').AnalyzeBatchInput( display_name=display_name, @@ -811,8 +819,10 @@ async def begin_analyze( # type: ignore ) return await self._client.begin_analyze( body=analyze_body, - cls=kwargs.pop("cls", partial(self._analyze_result_callback, doc_id_order, show_stats=show_stats)), - polling=TextAnalyticsAsyncLROPollingMethod( + cls=kwargs.pop("cls", partial( + self._analyze_result_callback, doc_id_order, task_order, show_stats=show_stats + )), + polling=AsyncAnalyzeBatchActionsLROPollingMethod( timeout=polling_interval, lro_algorithms=[ TextAnalyticsOperationResourcePolling(show_stats=show_stats) @@ -825,7 +835,7 @@ async def begin_analyze( # type: ignore except ValueError as error: if "API version v3.0 does not have operation 'begin_analyze'" in str(error): raise ValueError( - "'begin_analyze' endpoint is only available for API version v3.1-preview and up" + "'begin_analyze_batch_actions' endpoint is only available for API version v3.1-preview and up" ) raise error diff --git a/sdk/textanalytics/azure-ai-textanalytics/samples/README.md b/sdk/textanalytics/azure-ai-textanalytics/samples/README.md index 36ce89b9fbae..1f976af86ab7 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/samples/README.md +++ b/sdk/textanalytics/azure-ai-textanalytics/samples/README.md @@ -29,7 +29,7 @@ These sample programs show common scenarios for the Text Analytics client's offe |[sample_analyze_sentiment.py][analyze_sentiment] and [sample_analyze_sentiment_async.py][analyze_sentiment_async]|Analyze the sentiment of documents| |[sample_alternative_document_input.py][sample_alternative_document_input] and [sample_alternative_document_input_async.py][sample_alternative_document_input_async]|Pass documents to an endpoint using dicts| |[sample_analyze_healthcare.py][analyze_healthcare_sample] and [sample_analyze_healthcare_async.py][analyze_healthcare_sample_async]|Analyze healthcare entities| -|[sample_analyze.py][analyze_sample] and [sample_analyze_async.py][analyze_sample_async]|Batch multiple analyses together in a single request| +|[sample_analyze_batch_actions.py][analyze_sample] and [sample_analyze_batch_actions_async.py][analyze_sample_async]|Batch multiple analyses together in a single request| ## Prerequisites * Python 2.7, or 3.5 or later is required to use this package (3.5 or later if using asyncio) @@ -93,8 +93,8 @@ what you can do with the Azure Text Analytics client library. [sample_analyze_sentiment_with_opinion_mining_async]: https://github.com/Azure/azure-sdk-for-python/tree/master/sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_analyze_sentiment_with_opinion_mining_async.py [analyze_healthcare_sample]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples/sample_analyze_healthcare.py [analyze_healthcare_sample_async]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_analyze_healthcare_async.py -[analyze_sample]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples/sample_analyze.py -[analyze_sample_async]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_analyze_async.py +[analyze_sample]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples/sample_analyze_batch_actions.py +[analyze_sample_async]: https://github.com/Azure/azure-sdk-for-python/blob/master/sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_analyze_batch_actions_async.py [pip]: https://pypi.org/project/pip/ [azure_subscription]: https://azure.microsoft.com/free/ [azure_text_analytics_account]: https://docs.microsoft.com/azure/cognitive-services/cognitive-services-apis-create-account?tabs=singleservice%2Cwindows diff --git a/sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_analyze_async.py b/sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_analyze_batch_actions_async.py similarity index 67% rename from sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_analyze_async.py rename to sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_analyze_batch_actions_async.py index 80b62a5e527c..f0fbc51de7cc 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_analyze_async.py +++ b/sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_analyze_batch_actions_async.py @@ -7,15 +7,15 @@ # -------------------------------------------------------------------------- """ -FILE: sample_analyze_text.py +FILE: sample_analyze_batch_actions_async.py DESCRIPTION: This sample demonstrates how to submit a collection of text documents for analysis, which consists of a variety - of text analysis tasks, such as Entity Recognition, PII Entity Recognition, Entity Linking, Sentiment Analysis, - or Key Phrase Extraction. The response will contain results from each of the individual tasks specified in the request. + of text analysis actions, such as Entity Recognition, PII Entity Recognition, + or Key Phrase Extraction. The response will contain results from each of the individual actions specified in the request. USAGE: - python sample_analyze_text.py + python sample_analyze_batch_actions_async.py Set the environment variables with your own values before running the sample: 1) AZURE_TEXT_ANALYTICS_ENDPOINT - the endpoint to your Cognitive Services resource. @@ -32,9 +32,12 @@ async def analyze_async(self): # [START analyze_async] from azure.core.credentials import AzureKeyCredential from azure.ai.textanalytics.aio import TextAnalyticsClient - from azure.ai.textanalytics import EntitiesRecognitionTask, \ - PiiEntitiesRecognitionTask, \ - KeyPhraseExtractionTask + from azure.ai.textanalytics import ( + RecognizeEntitiesAction, + RecognizePiiEntitiesAction, + ExtractKeyPhrasesAction, + AnalyzeBatchActionsType + ) endpoint = os.environ["AZURE_TEXT_ANALYTICS_ENDPOINT"] key = os.environ["AZURE_TEXT_ANALYTICS_KEY"] @@ -54,22 +57,28 @@ async def analyze_async(self): ] async with text_analytics_client: - poller = await text_analytics_client.begin_analyze( + poller = await text_analytics_client.begin_analyze_batch_actions( documents, display_name="Sample Text Analysis", - entities_recognition_tasks=[EntitiesRecognitionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()] + actions=[ + RecognizeEntitiesAction(), + RecognizePiiEntitiesAction(), + ExtractKeyPhrasesAction() + ] ) result = await poller.result() - async for page in result: - for task in page.entities_recognition_results: - print("Results of Entities Recognition task:") - - docs = [doc for doc in task.results if not doc.is_error] - for idx, doc in enumerate(docs): + async for action_result in result: + if action_result.is_error: + raise ValueError( + "Action has failed with message: {}".format( + action_result.error.message + ) + ) + if action_result.action_type == AnalyzeBatchActionsType.RECOGNIZE_ENTITIES: + print("Results of Entities Recognition action:") + for idx, doc in enumerate(action_result.document_results): print("\nDocument text: {}".format(documents[idx])) for entity in doc.entities: print("Entity: {}".format(entity.text)) @@ -78,11 +87,9 @@ async def analyze_async(self): print("...Offset: {}".format(entity.offset)) print("------------------------------------------") - for task in page.pii_entities_recognition_results: - print("Results of PII Entities Recognition task:") - - docs = [doc for doc in task.results if not doc.is_error] - for idx, doc in enumerate(docs): + if action_result.action_type == AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES: + print("Results of PII Entities Recognition action:") + for idx, doc in enumerate(action_result.document_results): print("Document text: {}".format(documents[idx])) for entity in doc.entities: print("Entity: {}".format(entity.text)) @@ -90,11 +97,9 @@ async def analyze_async(self): print("Confidence Score: {}\n".format(entity.confidence_score)) print("------------------------------------------") - for task in page.key_phrase_extraction_results: - print("Results of Key Phrase Extraction task:") - - docs = [doc for doc in task.results if not doc.is_error] - for idx, doc in enumerate(docs): + if action_result.action_type == AnalyzeBatchActionsType.EXTRACT_KEY_PHRASES: + print("Results of Key Phrase Extraction action:") + for idx, doc in enumerate(action_result.document_results): print("Document text: {}\n".format(documents[idx])) print("Key Phrases: {}\n".format(doc.key_phrases)) print("------------------------------------------") diff --git a/sdk/textanalytics/azure-ai-textanalytics/samples/sample_analyze_batch_actions.py b/sdk/textanalytics/azure-ai-textanalytics/samples/sample_analyze_batch_actions.py new file mode 100644 index 000000000000..82ecbc9ce2f8 --- /dev/null +++ b/sdk/textanalytics/azure-ai-textanalytics/samples/sample_analyze_batch_actions.py @@ -0,0 +1,111 @@ +# coding: utf-8 + +# ------------------------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. See License.txt in the project root for +# license information. +# -------------------------------------------------------------------------- + +""" +FILE: sample_analyze_batch_actions.py + +DESCRIPTION: + This sample demonstrates how to submit a collection of text documents for analysis, which consists of a variety + of text analysis actions, such as Entity Recognition, PII Entity Recognition, + or Key Phrase Extraction. The response will contain results from each of the individual actions specified in the request. + +USAGE: + python sample_analyze_batch_actions.py + + Set the environment variables with your own values before running the sample: + 1) AZURE_TEXT_ANALYTICS_ENDPOINT - the endpoint to your Cognitive Services resource. + 2) AZURE_TEXT_ANALYTICS_KEY - your Text Analytics subscription key +""" + + +import os + + +class AnalyzeSample(object): + + def analyze(self): + # [START analyze] + from azure.core.credentials import AzureKeyCredential + from azure.ai.textanalytics import ( + TextAnalyticsClient, + RecognizeEntitiesAction, + RecognizePiiEntitiesAction, + ExtractKeyPhrasesAction, + PiiEntityDomainType, + ) + + endpoint = os.environ["AZURE_TEXT_ANALYTICS_ENDPOINT"] + key = os.environ["AZURE_TEXT_ANALYTICS_KEY"] + + text_analytics_client = TextAnalyticsClient( + endpoint=endpoint, + credential=AzureKeyCredential(key), + ) + + documents = [ + "We went to Contoso Steakhouse located at midtown NYC last week for a dinner party, and we adore the spot! \ + They provide marvelous food and they have a great menu. The chief cook happens to be the owner (I think his name is John Doe) \ + and he is super nice, coming out of the kitchen and greeted us all. We enjoyed very much dining in the place! \ + The Sirloin steak I ordered was tender and juicy, and the place was impeccably clean. You can even pre-order from their \ + online menu at www.contososteakhouse.com, call 312-555-0176 or send email to order@contososteakhouse.com! \ + The only complaint I have is the food didn't come fast enough. Overall I highly recommend it!" + ] + + poller = text_analytics_client.begin_analyze_batch_actions( + documents, + display_name="Sample Text Analysis", + actions=[ + RecognizeEntitiesAction(), + RecognizePiiEntitiesAction(domain_filter=PiiEntityDomainType.PHI), + ExtractKeyPhrasesAction() + ], + ) + + result = poller.result() + action_results = [action_result for action_result in list(result) if not action_result.is_error] + + first_action_result = action_results[0] + print("Results of Entities Recognition action:") + docs = [doc for doc in first_action_result.document_results if not doc.is_error] + + for idx, doc in enumerate(docs): + print("\nDocument text: {}".format(documents[idx])) + for entity in doc.entities: + print("Entity: {}".format(entity.text)) + print("...Category: {}".format(entity.category)) + print("...Confidence Score: {}".format(entity.confidence_score)) + print("...Offset: {}".format(entity.offset)) + print("------------------------------------------") + + second_action_result = action_results[1] + print("Results of PII Entities Recognition action:") + docs = [doc for doc in second_action_result.document_results if not doc.is_error] + + for idx, doc in enumerate(docs): + print("Document text: {}".format(documents[idx])) + for entity in doc.entities: + print("Entity: {}".format(entity.text)) + print("Category: {}".format(entity.category)) + print("Confidence Score: {}\n".format(entity.confidence_score)) + print("------------------------------------------") + + third_action_result = action_results[2] + print("Results of Key Phrase Extraction action:") + docs = [doc for doc in third_action_result.document_results if not doc.is_error] + + for idx, doc in enumerate(docs): + print("Document text: {}\n".format(documents[idx])) + print("Key Phrases: {}\n".format(doc.key_phrases)) + print("------------------------------------------") + + # [END analyze] + + +if __name__ == "__main__": + sample = AnalyzeSample() + sample.analyze() diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/recordings/test_analyze.test_all_successful_passing_dict_entities_task.yaml b/sdk/textanalytics/azure-ai-textanalytics/tests/recordings/test_analyze.test_all_successful_passing_dict_entities_task.yaml deleted file mode 100644 index 3a69c258fa0c..000000000000 --- a/sdk/textanalytics/azure-ai-textanalytics/tests/recordings/test_analyze.test_all_successful_passing_dict_entities_task.yaml +++ /dev/null @@ -1,532 +0,0 @@ -interactions: -- request: - body: '{"tasks": {"entityRecognitionTasks": [{"parameters": {"model-version": - "latest", "stringIndexType": "TextElements_v8"}}], "entityRecognitionPiiTasks": - [], "keyPhraseExtractionTasks": []}, "analysisInput": {"documents": [{"id": - "1", "text": "Microsoft was founded by Bill Gates and Paul Allen on April 4, - 1975.", "language": "en"}, {"id": "2", "text": "Microsoft fue fundado por Bill - Gates y Paul Allen el 4 de abril de 1975.", "language": "es"}, {"id": "3", "text": - "Microsoft wurde am 4. April 1975 von Bill Gates und Paul Allen gegr\u00fcndet.", - "language": "de"}]}}' - headers: - Accept: - - application/json, text/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '568' - Content-Type: - - application/json - User-Agent: - - azsdk-python-ai-textanalytics/5.1.0b5 Python/3.8.5 (macOS-10.13.6-x86_64-i386-64bit) - method: POST - uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze - response: - body: - string: '' - headers: - apim-request-id: - - dbc6e8e4-dcd4-4ce9-8919-b825c92d5144 - date: - - Wed, 27 Jan 2021 02:07:59 GMT - operation-location: - - https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/973fd47a-ec03-4a1b-a92e-52f3a1966ee3_637473024000000000 - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - transfer-encoding: - - chunked - x-content-type-options: - - nosniff - x-envoy-upstream-service-time: - - '24' - status: - code: 202 - message: Accepted -- request: - body: null - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - User-Agent: - - azsdk-python-ai-textanalytics/5.1.0b5 Python/3.8.5 (macOS-10.13.6-x86_64-i386-64bit) - method: GET - uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/973fd47a-ec03-4a1b-a92e-52f3a1966ee3_637473024000000000?showStats=True - response: - body: - string: '{"jobId":"973fd47a-ec03-4a1b-a92e-52f3a1966ee3_637473024000000000","lastUpdateDateTime":"2021-01-27T02:07:59Z","createdDateTime":"2021-01-27T02:07:59Z","expirationDateTime":"2021-01-28T02:07:59Z","status":"running","errors":[],"tasks":{"details":{"lastUpdateDateTime":"2021-01-27T02:07:59Z"},"completed":0,"failed":0,"inProgress":1,"total":1}}' - headers: - apim-request-id: - - b0ed9c1d-572a-490a-85ee-c8e95cd5bf80 - content-type: - - application/json; charset=utf-8 - date: - - Wed, 27 Jan 2021 02:08:03 GMT - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - transfer-encoding: - - chunked - x-content-type-options: - - nosniff - x-envoy-upstream-service-time: - - '37' - status: - code: 200 - message: OK -- request: - body: null - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - User-Agent: - - azsdk-python-ai-textanalytics/5.1.0b5 Python/3.8.5 (macOS-10.13.6-x86_64-i386-64bit) - method: GET - uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/973fd47a-ec03-4a1b-a92e-52f3a1966ee3_637473024000000000?showStats=True - response: - body: - string: '{"jobId":"973fd47a-ec03-4a1b-a92e-52f3a1966ee3_637473024000000000","lastUpdateDateTime":"2021-01-27T02:07:59Z","createdDateTime":"2021-01-27T02:07:59Z","expirationDateTime":"2021-01-28T02:07:59Z","status":"running","errors":[],"tasks":{"details":{"lastUpdateDateTime":"2021-01-27T02:07:59Z"},"completed":0,"failed":0,"inProgress":1,"total":1}}' - headers: - apim-request-id: - - f46a73cb-900b-4ca6-abf6-f567da9eab10 - content-type: - - application/json; charset=utf-8 - date: - - Wed, 27 Jan 2021 02:08:09 GMT - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - transfer-encoding: - - chunked - x-content-type-options: - - nosniff - x-envoy-upstream-service-time: - - '35' - status: - code: 200 - message: OK -- request: - body: null - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - User-Agent: - - azsdk-python-ai-textanalytics/5.1.0b5 Python/3.8.5 (macOS-10.13.6-x86_64-i386-64bit) - method: GET - uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/973fd47a-ec03-4a1b-a92e-52f3a1966ee3_637473024000000000?showStats=True - response: - body: - string: '{"jobId":"973fd47a-ec03-4a1b-a92e-52f3a1966ee3_637473024000000000","lastUpdateDateTime":"2021-01-27T02:07:59Z","createdDateTime":"2021-01-27T02:07:59Z","expirationDateTime":"2021-01-28T02:07:59Z","status":"running","errors":[],"tasks":{"details":{"lastUpdateDateTime":"2021-01-27T02:07:59Z"},"completed":0,"failed":0,"inProgress":1,"total":1}}' - headers: - apim-request-id: - - 59684911-0acb-4c1d-9845-5316c72e8803 - content-type: - - application/json; charset=utf-8 - date: - - Wed, 27 Jan 2021 02:08:14 GMT - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - transfer-encoding: - - chunked - x-content-type-options: - - nosniff - x-envoy-upstream-service-time: - - '37' - status: - code: 200 - message: OK -- request: - body: null - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - User-Agent: - - azsdk-python-ai-textanalytics/5.1.0b5 Python/3.8.5 (macOS-10.13.6-x86_64-i386-64bit) - method: GET - uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/973fd47a-ec03-4a1b-a92e-52f3a1966ee3_637473024000000000?showStats=True - response: - body: - string: '{"jobId":"973fd47a-ec03-4a1b-a92e-52f3a1966ee3_637473024000000000","lastUpdateDateTime":"2021-01-27T02:07:59Z","createdDateTime":"2021-01-27T02:07:59Z","expirationDateTime":"2021-01-28T02:07:59Z","status":"running","errors":[],"tasks":{"details":{"lastUpdateDateTime":"2021-01-27T02:07:59Z"},"completed":0,"failed":0,"inProgress":1,"total":1}}' - headers: - apim-request-id: - - 0359aca3-f22c-4814-9c8a-bff716e7d05b - content-type: - - application/json; 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charset=utf-8 date: - - Wed, 27 Jan 2021 02:16:43 GMT + - Tue, 02 Feb 2021 03:18:40 GMT strict-transport-security: - max-age=31536000; includeSubDomains; preload transfer-encoding: @@ -447,7 +447,41 @@ interactions: x-content-type-options: - nosniff x-envoy-upstream-service-time: - - '29' + - '33' + status: + code: 200 + message: OK +- request: + body: null + headers: + Accept: + - '*/*' + Accept-Encoding: + - gzip, deflate + Connection: + - keep-alive + User-Agent: + - azsdk-python-ai-textanalytics/5.1.0b5 Python/3.8.5 (macOS-10.13.6-x86_64-i386-64bit) + method: GET + uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/779f887f-f871-41aa-b683-073333cdd117_637478208000000000?showStats=True + response: + body: + string: '{"jobId":"779f887f-f871-41aa-b683-073333cdd117_637478208000000000","lastUpdateDateTime":"2021-02-02T03:17:42Z","createdDateTime":"2021-02-02T03:17:40Z","expirationDateTime":"2021-02-03T03:17:40Z","status":"running","errors":[],"tasks":{"details":{"lastUpdateDateTime":"2021-02-02T03:17:42Z"},"completed":0,"failed":0,"inProgress":1,"total":1}}' + headers: + apim-request-id: + - 903b9d02-f60f-4bb7-8caf-a3a90efef0f2 + content-type: + - application/json; charset=utf-8 + date: + - Tue, 02 Feb 2021 03:18:46 GMT + strict-transport-security: + - max-age=31536000; includeSubDomains; preload + transfer-encoding: + - chunked + x-content-type-options: + - nosniff + x-envoy-upstream-service-time: + - '31' status: code: 200 message: OK @@ -463,27 +497,27 @@ interactions: User-Agent: - azsdk-python-ai-textanalytics/5.1.0b5 Python/3.8.5 (macOS-10.13.6-x86_64-i386-64bit) method: GET - uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/33a55b3c-6f7b-4431-b692-a1564d53cef6_637473024000000000 + uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/779f887f-f871-41aa-b683-073333cdd117_637478208000000000?showStats=True response: body: - string: '{"jobId":"33a55b3c-6f7b-4431-b692-a1564d53cef6_637473024000000000","lastUpdateDateTime":"2021-01-27T02:15:42Z","createdDateTime":"2021-01-27T02:15:42Z","expirationDateTime":"2021-01-28T02:15:42Z","status":"succeeded","errors":[],"tasks":{"details":{"lastUpdateDateTime":"2021-01-27T02:15:42Z"},"completed":1,"failed":0,"inProgress":0,"total":1,"entityRecognitionPiiTasks":[{"lastUpdateDateTime":"2021-01-27T02:15:42.5081919Z","results":{"inTerminalState":true,"documents":[{"redactedText":"My - SSN is ***********.","id":"0","entities":[{"text":"859-98-0987","category":"U.S. + string: '{"jobId":"779f887f-f871-41aa-b683-073333cdd117_637478208000000000","lastUpdateDateTime":"2021-02-02T03:17:42Z","createdDateTime":"2021-02-02T03:17:40Z","expirationDateTime":"2021-02-03T03:17:40Z","status":"succeeded","errors":[],"tasks":{"details":{"lastUpdateDateTime":"2021-02-02T03:17:42Z"},"completed":1,"failed":0,"inProgress":0,"total":1,"entityRecognitionPiiTasks":[{"lastUpdateDateTime":"2021-02-02T03:17:42.359037Z","results":{"statistics":{"documentsCount":3,"validDocumentsCount":3,"erroneousDocumentsCount":0,"transactionsCount":3},"documents":[{"redactedText":"My + SSN is ***********.","id":"0","statistics":{"charactersCount":22,"transactionsCount":1},"entities":[{"text":"859-98-0987","category":"U.S. Social Security Number (SSN)","offset":10,"length":11,"confidenceScore":0.65}],"warnings":[]},{"redactedText":"Your ABA number - ********* - is the first 9 digits in the lower left hand corner - of your personal check.","id":"1","entities":[{"text":"111000025","category":"Phone + of your personal check.","id":"1","statistics":{"charactersCount":105,"transactionsCount":1},"entities":[{"text":"111000025","category":"Phone Number","offset":18,"length":9,"confidenceScore":0.8},{"text":"111000025","category":"ABA Routing Number","offset":18,"length":9,"confidenceScore":0.75},{"text":"111000025","category":"New Zealand Social Welfare Number","offset":18,"length":9,"confidenceScore":0.65},{"text":"111000025","category":"Portugal Tax Identification Number","offset":18,"length":9,"confidenceScore":0.65}],"warnings":[]},{"redactedText":"Is - ************** your Brazilian CPF number?","id":"2","entities":[{"text":"998.214.865-68","category":"Brazil + ************** your Brazilian CPF number?","id":"2","statistics":{"charactersCount":44,"transactionsCount":1},"entities":[{"text":"998.214.865-68","category":"Brazil CPF Number","offset":3,"length":14,"confidenceScore":0.85}],"warnings":[]}],"errors":[],"modelVersion":"2020-07-01"}}]}}' headers: apim-request-id: - - 22b6ef12-94d2-44bc-bdfe-b42560c27b99 + - 10323380-2759-417d-8818-a8412b9d9bf4 content-type: - application/json; charset=utf-8 date: - - Wed, 27 Jan 2021 02:16:48 GMT + - Tue, 02 Feb 2021 03:18:52 GMT strict-transport-security: - max-age=31536000; includeSubDomains; preload transfer-encoding: @@ -491,7 +525,7 @@ interactions: x-content-type-options: - nosniff x-envoy-upstream-service-time: - - '67' + - '63' status: code: 200 message: OK diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/recordings/test_analyze.test_all_successful_passing_text_document_input_entities_task.yaml b/sdk/textanalytics/azure-ai-textanalytics/tests/recordings/test_analyze.test_all_successful_passing_text_document_input_entities_task.yaml index 06ff3837d692..9cc5d1ca1733 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/tests/recordings/test_analyze.test_all_successful_passing_text_document_input_entities_task.yaml +++ b/sdk/textanalytics/azure-ai-textanalytics/tests/recordings/test_analyze.test_all_successful_passing_text_document_input_entities_task.yaml @@ -4,7 +4,7 @@ interactions: "latest", "stringIndexType": "TextElements_v8"}}], "entityRecognitionPiiTasks": [], "keyPhraseExtractionTasks": []}, "analysisInput": {"documents": [{"id": "1", "text": "Microsoft was founded by Bill Gates and Paul Allen on April 4, - 1975.", "language": "en"}, {"id": "2", "text": "Microsoft fue fundado por Bill + 1975", "language": "en"}, {"id": "2", "text": "Microsoft fue fundado por Bill Gates y Paul Allen el 4 de abril de 1975.", "language": "es"}, {"id": "3", "text": "Microsoft wurde am 4. April 1975 von Bill Gates und Paul Allen gegr\u00fcndet.", "language": "de"}]}}' @@ -16,7 +16,7 @@ interactions: Connection: - keep-alive Content-Length: - - '568' + - '567' Content-Type: - application/json User-Agent: @@ -28,11 +28,11 @@ interactions: string: '' headers: apim-request-id: - - d6d28511-1bff-4d8b-ac2f-1d6aa0bc3560 + - f74f575e-c65e-4792-a15a-aa052fd7d081 date: - - Wed, 27 Jan 2021 02:07:58 GMT + - Tue, 02 Feb 2021 03:25:45 GMT operation-location: - - https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/f885eb93-0e2d-49bb-a5be-92876b09761e_637473024000000000 + - https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/8e46fa87-ae8c-4ede-9b79-e3339541e5a0_637478208000000000 strict-transport-security: - max-age=31536000; includeSubDomains; preload transfer-encoding: @@ -40,7 +40,7 @@ interactions: x-content-type-options: - nosniff x-envoy-upstream-service-time: - - '32' + - '28' status: code: 202 message: Accepted @@ -56,17 +56,17 @@ interactions: User-Agent: - azsdk-python-ai-textanalytics/5.1.0b5 Python/3.8.5 (macOS-10.13.6-x86_64-i386-64bit) method: GET - uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/f885eb93-0e2d-49bb-a5be-92876b09761e_637473024000000000 + uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/8e46fa87-ae8c-4ede-9b79-e3339541e5a0_637478208000000000?showStats=True response: body: - string: '{"jobId":"f885eb93-0e2d-49bb-a5be-92876b09761e_637473024000000000","lastUpdateDateTime":"2021-01-27T02:07:59Z","createdDateTime":"2021-01-27T02:07:59Z","expirationDateTime":"2021-01-28T02:07:59Z","status":"running","errors":[],"tasks":{"details":{"lastUpdateDateTime":"2021-01-27T02:07:59Z"},"completed":0,"failed":0,"inProgress":1,"total":1}}' + string: '{"jobId":"8e46fa87-ae8c-4ede-9b79-e3339541e5a0_637478208000000000","lastUpdateDateTime":"2021-02-02T03:25:46Z","createdDateTime":"2021-02-02T03:25:46Z","expirationDateTime":"2021-02-03T03:25:46Z","status":"running","errors":[],"tasks":{"details":{"lastUpdateDateTime":"2021-02-02T03:25:46Z"},"completed":0,"failed":0,"inProgress":1,"total":1}}' headers: apim-request-id: - - d7ea45a4-2391-4d5c-a5fe-e7dfff3e4a33 + - ec400e9c-ae8a-41cb-a51e-3cc4176fbf52 content-type: - application/json; 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charset=utf-8 date: - - Wed, 27 Jan 2021 02:08:08 GMT + - Tue, 02 Feb 2021 03:25:56 GMT strict-transport-security: - max-age=31536000; includeSubDomains; preload transfer-encoding: @@ -108,7 +108,7 @@ interactions: x-content-type-options: - nosniff x-envoy-upstream-service-time: - - '35' + - '41' status: code: 200 message: OK @@ -124,17 +124,17 @@ interactions: User-Agent: - azsdk-python-ai-textanalytics/5.1.0b5 Python/3.8.5 (macOS-10.13.6-x86_64-i386-64bit) method: GET - uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/f885eb93-0e2d-49bb-a5be-92876b09761e_637473024000000000 + uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/8e46fa87-ae8c-4ede-9b79-e3339541e5a0_637478208000000000?showStats=True response: body: - string: '{"jobId":"f885eb93-0e2d-49bb-a5be-92876b09761e_637473024000000000","lastUpdateDateTime":"2021-01-27T02:07:59Z","createdDateTime":"2021-01-27T02:07:59Z","expirationDateTime":"2021-01-28T02:07:59Z","status":"running","errors":[],"tasks":{"details":{"lastUpdateDateTime":"2021-01-27T02:07:59Z"},"completed":0,"failed":0,"inProgress":1,"total":1}}' + string: '{"jobId":"8e46fa87-ae8c-4ede-9b79-e3339541e5a0_637478208000000000","lastUpdateDateTime":"2021-02-02T03:25:46Z","createdDateTime":"2021-02-02T03:25:46Z","expirationDateTime":"2021-02-03T03:25:46Z","status":"running","errors":[],"tasks":{"details":{"lastUpdateDateTime":"2021-02-02T03:25:46Z"},"completed":0,"failed":0,"inProgress":1,"total":1}}' headers: apim-request-id: - - 17da7db8-1cb6-453a-b51c-8b207b667213 + - 5b60fc57-55a7-466a-939b-8a968a5b3f4f content-type: - application/json; charset=utf-8 date: - - Wed, 27 Jan 2021 02:08:13 GMT + - Tue, 02 Feb 2021 03:26:00 GMT strict-transport-security: - max-age=31536000; includeSubDomains; preload transfer-encoding: @@ -142,7 +142,7 @@ interactions: x-content-type-options: - nosniff x-envoy-upstream-service-time: - - '61' + - '53' status: code: 200 message: OK @@ -158,17 +158,17 @@ interactions: User-Agent: - azsdk-python-ai-textanalytics/5.1.0b5 Python/3.8.5 (macOS-10.13.6-x86_64-i386-64bit) method: GET - uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/f885eb93-0e2d-49bb-a5be-92876b09761e_637473024000000000 + uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/8e46fa87-ae8c-4ede-9b79-e3339541e5a0_637478208000000000?showStats=True response: body: - string: '{"jobId":"f885eb93-0e2d-49bb-a5be-92876b09761e_637473024000000000","lastUpdateDateTime":"2021-01-27T02:07:59Z","createdDateTime":"2021-01-27T02:07:59Z","expirationDateTime":"2021-01-28T02:07:59Z","status":"running","errors":[],"tasks":{"details":{"lastUpdateDateTime":"2021-01-27T02:07:59Z"},"completed":0,"failed":0,"inProgress":1,"total":1}}' + string: '{"jobId":"8e46fa87-ae8c-4ede-9b79-e3339541e5a0_637478208000000000","lastUpdateDateTime":"2021-02-02T03:25:46Z","createdDateTime":"2021-02-02T03:25:46Z","expirationDateTime":"2021-02-03T03:25:46Z","status":"running","errors":[],"tasks":{"details":{"lastUpdateDateTime":"2021-02-02T03:25:46Z"},"completed":0,"failed":0,"inProgress":1,"total":1}}' headers: apim-request-id: - - 210d52d9-1205-4867-a1e2-215041776dc8 + - cb11c7e9-55ca-4c73-9a70-8f9715e453c5 content-type: - application/json; 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Make sure each document has a unique Id."}}' + string: '{"error":{"code":"InvalidRequest","message":"Invalid document in request.","innerError":{"code":"InvalidDocument","message":"Request + contains duplicated Ids. 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charset=utf-8 date: - - Wed, 27 Jan 2021 02:15:41 GMT + - Tue, 02 Feb 2021 03:19:53 GMT strict-transport-security: - max-age=31536000; includeSubDomains; preload transfer-encoding: @@ -1089,7 +939,7 @@ interactions: x-content-type-options: - nosniff x-envoy-upstream-service-time: - - '135' + - '158' status: code: 200 message: OK diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/recordings/test_analyze.test_output_same_order_as_input_multiple_tasks.yaml b/sdk/textanalytics/azure-ai-textanalytics/tests/recordings/test_analyze.test_output_same_order_as_input_multiple_tasks.yaml index 7fd6486ae8c3..7168a2a53069 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/tests/recordings/test_analyze.test_output_same_order_as_input_multiple_tasks.yaml +++ b/sdk/textanalytics/azure-ai-textanalytics/tests/recordings/test_analyze.test_output_same_order_as_input_multiple_tasks.yaml @@ -1,13 +1,12 @@ interactions: - request: - body: '{"tasks": {"entityRecognitionTasks": [{"parameters": {"model-version": - "latest", "stringIndexType": "TextElements_v8"}}], "entityRecognitionPiiTasks": - [{"parameters": {"model-version": "latest", "stringIndexType": "TextElements_v8"}}], - "keyPhraseExtractionTasks": [{"parameters": {"model-version": "latest"}}]}, - "analysisInput": {"documents": [{"id": "1", "text": "one", "language": "en"}, - {"id": "2", "text": "two", "language": "en"}, {"id": "3", "text": "three", "language": - "en"}, {"id": "4", "text": "four", "language": "en"}, {"id": "5", "text": "five", - "language": "en"}]}}' + body: '{"tasks": {"entityRecognitionTasks": [], "entityRecognitionPiiTasks": [{"parameters": + {"model-version": "latest", "stringIndexType": "UnicodeCodePoint"}}, {"parameters": + {"model-version": "bad", "stringIndexType": "UnicodeCodePoint"}}], "keyPhraseExtractionTasks": + [{"parameters": {"model-version": "latest"}}]}, "analysisInput": {"documents": + [{"id": "1", "text": "one", "language": "en"}, {"id": "2", "text": "two", "language": + "en"}, {"id": "3", "text": "three", "language": "en"}, {"id": "4", "text": "four", + "language": "en"}, {"id": "5", "text": "five", "language": "en"}]}}' headers: Accept: - application/json, text/json @@ -16,11 +15,11 @@ interactions: Connection: - keep-alive Content-Length: - - '579' + - '580' Content-Type: - application/json User-Agent: - - azsdk-python-ai-textanalytics/5.1.0b5 Python/3.8.5 (macOS-10.13.6-x86_64-i386-64bit) + - azsdk-python-ai-textanalytics/5.1.0b5 Python/3.9.1 (macOS-10.13.6-x86_64-i386-64bit) method: POST uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze response: @@ -28,11 +27,11 @@ interactions: string: '' headers: apim-request-id: - - 773590bd-d291-44a8-8f66-e5ed7747658a + - f41d24c2-cd05-4b45-8e48-f7aa1bfd7855 date: - - Wed, 27 Jan 2021 02:08:05 GMT + - Thu, 04 Feb 2021 21:06:53 GMT operation-location: - - https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/7c69fe99-d9eb-4a76-8fcd-640fcd31cde7_637473024000000000 + - https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/fc00d5d6-718a-499c-a44e-f996d556dcbd_637479936000000000 strict-transport-security: - max-age=31536000; includeSubDomains; preload transfer-encoding: @@ -40,7 +39,7 @@ interactions: x-content-type-options: - nosniff x-envoy-upstream-service-time: - - '23' + - '52' status: code: 202 message: Accepted @@ -54,19 +53,21 @@ interactions: Connection: - keep-alive User-Agent: - - azsdk-python-ai-textanalytics/5.1.0b5 Python/3.8.5 (macOS-10.13.6-x86_64-i386-64bit) + - azsdk-python-ai-textanalytics/5.1.0b5 Python/3.9.1 (macOS-10.13.6-x86_64-i386-64bit) method: GET - uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/7c69fe99-d9eb-4a76-8fcd-640fcd31cde7_637473024000000000 + uri: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/fc00d5d6-718a-499c-a44e-f996d556dcbd_637479936000000000 response: body: - string: '{"jobId":"7c69fe99-d9eb-4a76-8fcd-640fcd31cde7_637473024000000000","lastUpdateDateTime":"2021-01-27T02:08:06Z","createdDateTime":"2021-01-27T02:08:05Z","expirationDateTime":"2021-01-28T02:08:05Z","status":"running","errors":[],"tasks":{"details":{"lastUpdateDateTime":"2021-01-27T02:08:06Z"},"completed":1,"failed":0,"inProgress":2,"total":3,"keyPhraseExtractionTasks":[{"lastUpdateDateTime":"2021-01-27T02:08:06.814584Z","results":{"inTerminalState":true,"documents":[{"id":"1","keyPhrases":[],"warnings":[]},{"id":"2","keyPhrases":[],"warnings":[]},{"id":"3","keyPhrases":[],"warnings":[]},{"id":"4","keyPhrases":[],"warnings":[]},{"id":"5","keyPhrases":[],"warnings":[]}],"errors":[],"modelVersion":"2020-07-01"}}]}}' + string: '{"jobId":"fc00d5d6-718a-499c-a44e-f996d556dcbd_637479936000000000","lastUpdateDateTime":"2021-02-04T21:06:56Z","createdDateTime":"2021-02-04T21:06:53Z","expirationDateTime":"2021-02-05T21:06:53Z","status":"running","errors":[{"code":"InvalidRequest","message":"Job + task parameter value bad is not supported for model-version parameter for + job task type PersonallyIdentifiableInformation. 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Make sure each document has a unique Id."}}' + string: '{"error":{"code":"InvalidRequest","message":"Invalid document in request.","innerError":{"code":"InvalidDocument","message":"Request + contains duplicated Ids. 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charset=utf-8 - date: Wed, 27 Jan 2021 02:20:11 GMT - strict-transport-security: max-age=31536000; includeSubDomains; preload - transfer-encoding: chunked - x-content-type-options: nosniff - x-envoy-upstream-service-time: '172' - status: - code: 200 - message: OK - url: https://westus2.api.cognitive.microsoft.com/text/analytics/v3.1-preview.3/analyze/jobs/47d55652-6be9-4e82-844d-b45cfba42a4f_637473024000000000 -version: 1 diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/test_analyze.py b/sdk/textanalytics/azure-ai-textanalytics/tests/test_analyze.py index 05758e48194b..9f27e6e5349c 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/tests/test_analyze.py +++ b/sdk/textanalytics/azure-ai-textanalytics/tests/test_analyze.py @@ -9,6 +9,7 @@ import platform import functools import itertools +import datetime from azure.core.exceptions import HttpResponseError, ClientAuthenticationError from azure.core.credentials import AzureKeyCredential @@ -16,12 +17,13 @@ from testcase import TextAnalyticsClientPreparer as _TextAnalyticsClientPreparer from azure.ai.textanalytics import ( TextAnalyticsClient, - EntitiesRecognitionTask, - PiiEntitiesRecognitionTask, - KeyPhraseExtractionTask, + RecognizeEntitiesAction, + RecognizePiiEntitiesAction, + ExtractKeyPhrasesAction, TextDocumentInput, VERSION, TextAnalyticsApiVersion, + AnalyzeBatchActionsType, ) # pre-apply the client_cls positional argument so it needn't be explicitly passed below @@ -37,168 +39,64 @@ def _interval(self): @TextAnalyticsClientPreparer() def test_no_single_input(self, client): with self.assertRaises(TypeError): - response = client.begin_analyze("hello world", polling_interval=self._interval()) + response = client.begin_analyze_batch_actions("hello world", actions=[], polling_interval=self._interval()) - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() def test_all_successful_passing_dict_key_phrase_task(self, client): docs = [{"id": "1", "language": "en", "text": "Microsoft was founded by Bill Gates and Paul Allen"}, {"id": "2", "language": "es", "text": "Microsoft fue fundado por Bill Gates y Paul Allen"}] - response = client.begin_analyze( + response = client.begin_analyze_batch_actions( docs, - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], + actions=[ExtractKeyPhrasesAction()], show_stats=True, polling_interval=self._interval(), ).result() - results_pages = list(response) - self.assertEqual(len(results_pages), 1) + action_results = list(response) - task_results = results_pages[0].key_phrase_extraction_results - self.assertEqual(len(task_results), 1) + assert len(action_results) == 1 + action_result = action_results[0] - results = task_results[0].results - self.assertEqual(len(results), 2) + assert action_result.action_type == AnalyzeBatchActionsType.EXTRACT_KEY_PHRASES + assert len(action_result.document_results) == len(docs) - for phrases in results: - self.assertIn("Paul Allen", phrases.key_phrases) - self.assertIn("Bill Gates", phrases.key_phrases) - self.assertIn("Microsoft", phrases.key_phrases) - self.assertIsNotNone(phrases.id) - #self.assertIsNotNone(phrases.statistics) - - @pytest.mark.playback_test_only - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - def test_all_successful_passing_dict_entities_task(self, client): - docs = [{"id": "1", "language": "en", "text": "Microsoft was founded by Bill Gates and Paul Allen on April 4, 1975."}, - {"id": "2", "language": "es", "text": "Microsoft fue fundado por Bill Gates y Paul Allen el 4 de abril de 1975."}, - {"id": "3", "language": "de", "text": "Microsoft wurde am 4. April 1975 von Bill Gates und Paul Allen gegründet."}] - - response = client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - show_stats=True, - polling_interval=self._interval(), - ).result() - - results_pages = list(response) - self.assertEqual(len(results_pages), 1) - - task_results = results_pages[0].entities_recognition_results - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - self.assertEqual(len(results), 3) - - for doc in results: - self.assertEqual(len(doc.entities), 4) + for doc in action_result.document_results: + self.assertIn("Paul Allen", doc.key_phrases) + self.assertIn("Bill Gates", doc.key_phrases) + self.assertIn("Microsoft", doc.key_phrases) self.assertIsNotNone(doc.id) - # self.assertIsNotNone(doc.statistics) - for entity in doc.entities: - self.assertIsNotNone(entity.text) - self.assertIsNotNone(entity.category) - self.assertIsNotNone(entity.offset) - self.assertIsNotNone(entity.confidence_score) - - @pytest.mark.playback_test_only - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - def test_all_successful_passing_dict_pii_entities_task(self, client): - - docs = [{"id": "1", "text": "My SSN is 859-98-0987."}, - {"id": "2", "text": "Your ABA number - 111000025 - is the first 9 digits in the lower left hand corner of your personal check."}, - {"id": "3", "text": "Is 998.214.865-68 your Brazilian CPF number?"}] - - response = client.begin_analyze( - docs, - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - show_stats=True, - polling_interval=self._interval(), - ).result() - - results_pages = list(response) - self.assertEqual(len(results_pages), 1) - - task_results = results_pages[0].pii_entities_recognition_results - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - self.assertEqual(len(results), 3) - - self.assertEqual(results[0].entities[0].text, "859-98-0987") - self.assertEqual(results[0].entities[0].category, "U.S. Social Security Number (SSN)") - self.assertEqual(results[1].entities[0].text, "111000025") - # self.assertEqual(results[1].entities[0].category, "ABA Routing Number") # Service is currently returning PhoneNumber here - self.assertEqual(results[2].entities[0].text, "998.214.865-68") - self.assertEqual(results[2].entities[0].category, "Brazil CPF Number") - for doc in results: - self.assertIsNotNone(doc.id) - # self.assertIsNotNone(doc.statistics) - for entity in doc.entities: - self.assertIsNotNone(entity.text) - self.assertIsNotNone(entity.category) - self.assertIsNotNone(entity.offset) - self.assertIsNotNone(entity.confidence_score) - - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - def test_all_successful_passing_text_document_input_key_phrase_task(self, client): - docs = [ - TextDocumentInput(id="1", text="Microsoft was founded by Bill Gates and Paul Allen", language="en"), - TextDocumentInput(id="2", text="Microsoft fue fundado por Bill Gates y Paul Allen", language="es") - ] - - response = client.begin_analyze( - docs, - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - polling_interval=self._interval(), - ).result() - - results_pages = list(response) - self.assertEqual(len(results_pages), 1) - - key_phrase_task_results = results_pages[0].key_phrase_extraction_results - self.assertEqual(len(key_phrase_task_results), 1) - - results = key_phrase_task_results[0].results - self.assertEqual(len(results), 2) - - for phrases in results: - self.assertIn("Paul Allen", phrases.key_phrases) - self.assertIn("Bill Gates", phrases.key_phrases) - self.assertIn("Microsoft", phrases.key_phrases) - self.assertIsNotNone(phrases.id) + #self.assertIsNotNone(doc.statistics) @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() def test_all_successful_passing_text_document_input_entities_task(self, client): docs = [ - TextDocumentInput(id="1", text="Microsoft was founded by Bill Gates and Paul Allen on April 4, 1975.", language="en"), + TextDocumentInput(id="1", text="Microsoft was founded by Bill Gates and Paul Allen on April 4, 1975", language="en"), TextDocumentInput(id="2", text="Microsoft fue fundado por Bill Gates y Paul Allen el 4 de abril de 1975.", language="es"), - TextDocumentInput(id="3", text="Microsoft wurde am 4. April 1975 von Bill Gates und Paul Allen gegründet.", language="de") + TextDocumentInput(id="3", text="Microsoft wurde am 4. April 1975 von Bill Gates und Paul Allen gegründet.", language="de"), ] - response = client.begin_analyze( + response = client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], + actions=[RecognizeEntitiesAction()], + show_stats=True, polling_interval=self._interval(), ).result() - results_pages = list(response) - self.assertEqual(len(results_pages), 1) + action_results = list(response) - task_results = results_pages[0].entities_recognition_results - self.assertEqual(len(task_results), 1) + assert len(action_results) == 1 + action_result = action_results[0] - results = task_results[0].results - self.assertEqual(len(results), 3) + assert action_result.action_type == AnalyzeBatchActionsType.RECOGNIZE_ENTITIES + assert len(action_result.document_results) == len(docs) - for doc in results: + for doc in action_result.document_results: self.assertEqual(len(doc.entities), 4) self.assertIsNotNone(doc.id) + # self.assertIsNotNone(doc.statistics) for entity in doc.entities: self.assertIsNotNone(entity.text) self.assertIsNotNone(entity.category) @@ -207,156 +105,55 @@ def test_all_successful_passing_text_document_input_entities_task(self, client): @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() - def test_all_successful_passing_text_document_input_pii_entities_task(self, client): - docs = [ - TextDocumentInput(id="1", text="My SSN is 859-98-0987."), - TextDocumentInput(id="2", text="Your ABA number - 111000025 - is the first 9 digits in the lower left hand corner of your personal check."), - TextDocumentInput(id="3", text="Is 998.214.865-68 your Brazilian CPF number?") + def test_all_successful_passing_string_pii_entities_task(self, client): + + docs = ["My SSN is 859-98-0987.", + "Your ABA number - 111000025 - is the first 9 digits in the lower left hand corner of your personal check.", + "Is 998.214.865-68 your Brazilian CPF number?" ] - response = client.begin_analyze( + response = client.begin_analyze_batch_actions( docs, - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[RecognizePiiEntitiesAction()], + show_stats=True, polling_interval=self._interval(), ).result() - results_pages = list(response) - self.assertEqual(len(results_pages), 1) + action_results = list(response) - task_results = results_pages[0].pii_entities_recognition_results - self.assertEqual(len(task_results), 1) + assert len(action_results) == 1 + action_result = action_results[0] - results = task_results[0].results - self.assertEqual(len(results), 3) + assert action_result.action_type == AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES + assert len(action_result.document_results) == len(docs) - self.assertEqual(results[0].entities[0].text, "859-98-0987") - self.assertEqual(results[0].entities[0].category, "U.S. Social Security Number (SSN)") - self.assertEqual(results[1].entities[0].text, "111000025") + self.assertEqual(action_result.document_results[0].entities[0].text, "859-98-0987") + self.assertEqual(action_result.document_results[0].entities[0].category, "U.S. Social Security Number (SSN)") + self.assertEqual(action_result.document_results[1].entities[0].text, "111000025") # self.assertEqual(results[1].entities[0].category, "ABA Routing Number") # Service is currently returning PhoneNumber here - self.assertEqual(results[2].entities[0].text, "998.214.865-68") - self.assertEqual(results[2].entities[0].category, "Brazil CPF Number") - for doc in results: + self.assertEqual(action_result.document_results[2].entities[0].text, "998.214.865-68") + self.assertEqual(action_result.document_results[2].entities[0].category, "Brazil CPF Number") + for doc in action_result.document_results: self.assertIsNotNone(doc.id) + # self.assertIsNotNone(doc.statistics) for entity in doc.entities: self.assertIsNotNone(entity.text) self.assertIsNotNone(entity.category) self.assertIsNotNone(entity.offset) self.assertIsNotNone(entity.confidence_score) - @pytest.mark.playback_test_only - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - def test_passing_only_string_key_phrase_task(self, client): - docs = [ - u"Microsoft was founded by Bill Gates and Paul Allen", - u"Microsoft fue fundado por Bill Gates y Paul Allen" - ] - - response = client.begin_analyze( - docs, - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - polling_interval=self._interval(), - ).result() - - results_pages = list(response) - self.assertEqual(len(results_pages), 1) - - key_phrase_task_results = results_pages[0].key_phrase_extraction_results - self.assertEqual(len(key_phrase_task_results), 1) - - results = key_phrase_task_results[0].results - self.assertEqual(len(results), 2) - - self.assertIn("Paul Allen", results[0].key_phrases) - self.assertIn("Bill Gates", results[0].key_phrases) - self.assertIn("Microsoft", results[0].key_phrases) - self.assertIsNotNone(results[0].id) - @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() def test_bad_request_on_empty_document(self, client): docs = [u""] with self.assertRaises(HttpResponseError): - response = client.begin_analyze( + response = client.begin_analyze_batch_actions( docs, - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], + actions=[ExtractKeyPhrasesAction()], polling_interval=self._interval(), ) - @pytest.mark.playback_test_only - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - def test_passing_only_string_entities_task(self, client): - docs = [ - u"Microsoft was founded by Bill Gates and Paul Allen on April 4, 1975.", - u"Microsoft fue fundado por Bill Gates y Paul Allen el 4 de abril de 1975.", - u"Microsoft wurde am 4. April 1975 von Bill Gates und Paul Allen gegründet." - ] - - response = client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - polling_interval=self._interval(), - ).result() - - results_pages = list(response) - self.assertEqual(len(results_pages), 1) - - task_results = results_pages[0].entities_recognition_results - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - self.assertEqual(len(results), 3) - - self.assertEqual(len(results[0].entities), 4) - self.assertIsNotNone(results[0].id) - for entity in results[0].entities: - self.assertIsNotNone(entity.text) - self.assertIsNotNone(entity.category) - self.assertIsNotNone(entity.offset) - self.assertIsNotNone(entity.confidence_score) - - @pytest.mark.playback_test_only - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - def test_passing_only_string_pii_entities_task(self, client): - docs = [ - u"My SSN is 859-98-0987.", - u"Your ABA number - 111000025 - is the first 9 digits in the lower left hand corner of your personal check.", - u"Is 998.214.865-68 your Brazilian CPF number?" - ] - - response = client.begin_analyze( - docs, - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - polling_interval=self._interval(), - ).result() - - results_pages = list(response) - self.assertEqual(len(results_pages), 1) - - task_results = results_pages[0].pii_entities_recognition_results - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - self.assertEqual(len(results), 3) - - self.assertEqual(results[0].entities[0].text, "859-98-0987") - self.assertEqual(results[0].entities[0].category, "U.S. Social Security Number (SSN)") - self.assertEqual(results[1].entities[0].text, "111000025") - # self.assertEqual(results[1].entities[0].category, "ABA Routing Number") # Service is currently returning PhoneNumber here - self.assertEqual(results[2].entities[0].text, "998.214.865-68") - self.assertEqual(results[2].entities[0].category, "Brazil CPF Number") - - for i in range(3): - self.assertIsNotNone(results[i].id) - for entity in results[i].entities: - self.assertIsNotNone(entity.text) - self.assertIsNotNone(entity.category) - self.assertIsNotNone(entity.offset) - self.assertIsNotNone(entity.confidence_score) - @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() def test_payload_too_large(self, client): @@ -368,7 +165,6 @@ def test_document_warnings(self, client): # TODO: reproduce a warnings scenario for implementation pass - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() def test_output_same_order_as_input_multiple_tasks(self, client): @@ -380,75 +176,76 @@ def test_output_same_order_as_input_multiple_tasks(self, client): TextDocumentInput(id="5", text="five") ] - response = client.begin_analyze( + response = client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizePiiEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(model_version="bad"), + ], polling_interval=self._interval(), ).result() - results_pages = list(response) - self.assertEqual(len(results_pages), 1) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] + action_results = list(response) - for task_type in task_types: - task_results = getattr(results_pages[0], task_type) - self.assertEqual(len(task_results), 1) + assert len(action_results) == 3 + action_result = action_results[0] - results = task_results[0].results - self.assertEqual(len(results), 5) + assert action_results[0].action_type == AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES + assert action_results[1].action_type == AnalyzeBatchActionsType.EXTRACT_KEY_PHRASES + assert action_results[2].is_error + assert all([action_result for action_result in action_results if not action_result.is_error and len(action_result.document_results) == len(docs)]) - for idx, doc in enumerate(results): - self.assertEqual(str(idx + 1), doc.id) + for action_result in action_results: + if not action_result.is_error: + for idx, doc in enumerate(action_result.document_results): + self.assertEqual(str(idx + 1), doc.id) - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer(client_kwargs={ "text_analytics_account_key": "", }) def test_empty_credential_class(self, client): with self.assertRaises(ClientAuthenticationError): - response = client.begin_analyze( + response = client.begin_analyze_batch_actions( ["This is written in English."], - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(), + ], polling_interval=self._interval(), ) - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer(client_kwargs={ "text_analytics_account_key": "xxxxxxxxxxxx", }) def test_bad_credentials(self, client): with self.assertRaises(ClientAuthenticationError): - response = client.begin_analyze( + response = client.begin_analyze_batch_actions( ["This is written in English."], - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(), + ], polling_interval=self._interval(), ) - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() def test_bad_document_input(self, client): docs = "This is the wrong type" with self.assertRaises(TypeError): - response = client.begin_analyze( + response = client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(), + ], polling_interval=self._interval(), ) @@ -461,11 +258,13 @@ def test_mixing_inputs(self, client): u"You cannot mix string input with the above inputs" ] with self.assertRaises(TypeError): - response = client.begin_analyze( + response = client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(), + ], polling_interval=self._interval(), ).result() @@ -477,382 +276,184 @@ def test_out_of_order_ids_multiple_tasks(self, client): {"id": "19", "text": ":P"}, {"id": "1", "text": ":D"}] - response = client.begin_analyze( + response = client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask(model_version="bad")], # at this moment this should cause all documents to be errors, which isn't correct behavior but I'm using it here to test document ordering with errors. :) - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(model_version="bad"), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(), + ], polling_interval=self._interval(), ).result() - results_pages = list(response) - self.assertEqual(len(results_pages), 1) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] + action_results = list(response) + assert len(action_results) == 3 - in_order = ["56", "0", "19", "1"] + assert action_results[0].is_error + assert action_results[1].action_type == AnalyzeBatchActionsType.EXTRACT_KEY_PHRASES + assert action_results[2].action_type == AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES - for task_type in task_types: - task_results = getattr(results_pages[0], task_type) - self.assertEqual(len(task_results), 1) + action_results = [r for r in action_results if not r.is_error] + assert all([action_result for action_result in action_results if len(action_result.document_results) == len(docs)]) - results = task_results[0].results - # self.assertEqual(len(results), len(docs)) commenting out because of service error + in_order = ["56", "0", "19", "1"] - for idx, resp in enumerate(results): + for action_result in action_results: + for idx, resp in enumerate(action_result.document_results): self.assertEqual(resp.id, in_order[idx]) - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() def test_show_stats_and_model_version_multiple_tasks(self, client): + + def callback(resp): + if resp.raw_response: + a = "b" + docs = [{"id": "56", "text": ":)"}, {"id": "0", "text": ":("}, {"id": "19", "text": ":P"}, {"id": "1", "text": ":D"}] - response = client.begin_analyze( + poller = client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask(model_version="latest")], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask(model_version="latest")], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask(model_version="latest")], + actions=[ + RecognizeEntitiesAction(model_version="latest"), + ExtractKeyPhrasesAction(model_version="latest"), + RecognizePiiEntitiesAction(model_version="latest") + ], show_stats=True, polling_interval=self._interval(), - ).result() - - results_pages = list(response) - self.assertEqual(len(results_pages), 1) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - task_results = getattr(results_pages[0], task_type) - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - self.assertEqual(len(results), len(docs)) - - # self.assertEqual(results.statistics.document_count, 5) - # self.assertEqual(results.statistics.transaction_count, 4) - # self.assertEqual(results.statistics.valid_document_count, 4) - # self.assertEqual(results.statistics.erroneous_document_count, 1) - - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - def test_whole_batch_language_hint(self, client): - docs = [ - u"This was the best day of my life.", - u"I did not like the hotel we stayed at. It was too expensive.", - u"The restaurant was not as good as I hoped." - ] - - response = list(client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - language="en", - polling_interval=self._interval(), - ).result()) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - task_results = getattr(response[0], task_type) - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - for r in results: - self.assertFalse(r.is_error) - - @pytest.mark.playback_test_only - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - def test_whole_batch_dont_use_language_hint(self, client): - docs = [ - u"This was the best day of my life.", - u"I did not like the hotel we stayed at. It was too expensive.", - u"The restaurant was not as good as I hoped." - ] - - response = list(client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - language="", - polling_interval=self._interval(), - ).result()) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - task_results = getattr(response[0], task_type) - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - for r in results: - self.assertFalse(r.is_error) - - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - def test_per_item_dont_use_language_hint(self, client): - docs = [{"id": "1", "language": "", "text": "I will go to the park."}, - {"id": "2", "language": "", "text": "I did not like the hotel we stayed at."}, - {"id": "3", "text": "The restaurant had really good food."}] - - response = list(client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - polling_interval=self._interval(), - ).result()) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - task_results = getattr(response[0], task_type) - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - for r in results: - self.assertFalse(r.is_error) - - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - def test_whole_batch_language_hint_and_obj_input(self, client): - def callback(resp): - language_str = "\"language\": \"de\"" - language = resp.http_request.body.count(language_str) - self.assertEqual(language, 3) - - docs = [ - TextDocumentInput(id="1", text="I should take my cat to the veterinarian."), - TextDocumentInput(id="4", text="Este es un document escrito en Español."), - TextDocumentInput(id="3", text="猫は幸せ"), - ] - - response = list(client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - language="en", - polling_interval=self._interval(), - ).result()) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - task_results = getattr(response[0], task_type) - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - for r in results: - self.assertFalse(r.is_error) - - @pytest.mark.playback_test_only - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - def test_whole_batch_language_hint_and_dict_input(self, client): - docs = [{"id": "1", "text": "I will go to the park."}, - {"id": "2", "text": "I did not like the hotel we stayed at."}, - {"id": "3", "text": "The restaurant had really good food."}] - - response = list(client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - language="en", - polling_interval=self._interval(), - ).result()) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - task_results = getattr(response[0], task_type) - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - for r in results: - self.assertFalse(r.is_error) - - @pytest.mark.playback_test_only - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - def test_whole_batch_language_hint_and_obj_per_item_hints(self, client): - docs = [ - TextDocumentInput(id="1", text="I should take my cat to the veterinarian.", language="en"), - TextDocumentInput(id="2", text="Este es un document escrito en Español.", language="en"), - TextDocumentInput(id="3", text="猫は幸せ"), - ] + raw_response_hook=callback, + ) - response = list(client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - language="en", - polling_interval=self._interval(), - ).result()) + response = poller.result() + # assert response.statistics - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] + action_results = list(response) + assert len(action_results) == 3 + assert action_results[0].action_type == AnalyzeBatchActionsType.RECOGNIZE_ENTITIES + assert action_results[1].action_type == AnalyzeBatchActionsType.EXTRACT_KEY_PHRASES + assert action_results[2].action_type == AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES - for task_type in task_types: - task_results = getattr(response[0], task_type) - self.assertEqual(len(task_results), 1) + assert all([action_result for action_result in action_results if len(action_result.document_results) == len(docs)]) - results = task_results[0].results - for r in results: - self.assertFalse(r.is_error) + # for action_result in action_results: + # for doc in action_result.document_results: + # assert doc.statistics @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() - def test_whole_batch_language_hint_and_dict_per_item_hints(self, client): - docs = [{"id": "1", "language": "en", "text": "I will go to the park."}, - {"id": "2", "language": "en", "text": "I did not like the hotel we stayed at."}, - {"id": "3", "text": "The restaurant had really good food."}] - - response = list(client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - language="en", - polling_interval=self._interval(), - ).result()) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - task_results = getattr(response[0], task_type) - self.assertEqual(len(task_results), 1) + def test_poller_metadata(self, client): + docs = [{"id": "56", "text": ":)"}] - results = task_results[0].results - for r in results: - self.assertFalse(r.is_error) - - @pytest.mark.playback_test_only - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer(client_kwargs={ - "text_analytics_account_key": os.environ.get('AZURE_TEXT_ANALYTICS_KEY'), - "default_language": "en" - }) - def test_client_passed_default_language_hint(self, client): - docs = [{"id": "1", "text": "I will go to the park."}, - {"id": "2", "text": "I did not like the hotel we stayed at."}, - {"id": "3", "text": "The restaurant had really good food."}] - - response = list(client.begin_analyze( + poller = client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(model_version="latest") + ], + show_stats=True, polling_interval=self._interval(), - ).result()) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - tasks = getattr(response[0], task_type) # only expecting a single page of results here - self.assertEqual(len(tasks), 1) - self.assertEqual(len(tasks[0].results), 3) + ) - for r in tasks[0].results: - self.assertFalse(r.is_error) + response = poller.result() + + assert isinstance(poller.created_on, datetime.datetime) + poller._polling_method.display_name + assert isinstance(poller.expires_on, datetime.datetime) + assert poller.actions_failed_count == 0 + assert poller.actions_in_progress_count == 0 + assert poller.actions_succeeded_count == 1 + assert isinstance(poller.last_modified_on, datetime.datetime) + assert poller.total_actions_count == 1 + assert poller.id + + ### TODO: Commenting out language tests. Right now analyze only supports language 'en', so no point to these tests yet + + # @GlobalTextAnalyticsAccountPreparer() + # @TextAnalyticsClientPreparer() + # def test_whole_batch_language_hint(self, client): + # def callback(resp): + # language_str = "\"language\": \"fr\"" + # if resp.http_request.body: + # language = resp.http_request.body.count(language_str) + # self.assertEqual(language, 3) + + # docs = [ + # u"This was the best day of my life.", + # u"I did not like the hotel we stayed at. It was too expensive.", + # u"The restaurant was not as good as I hoped." + # ] + + # response = list(client.begin_analyze_batch_actions( + # docs, + # actions=[ + # RecognizeEntitiesAction(), + # ExtractKeyPhrasesAction(), + # RecognizePiiEntitiesAction() + # ], + # language="fr", + # polling_interval=self._interval(), + # raw_response_hook=callback + # ).result()) + + # for action_result in response: + # for doc in action_result.document_results: + # self.assertFalse(doc.is_error) + + # @GlobalTextAnalyticsAccountPreparer() + # @TextAnalyticsClientPreparer(client_kwargs={ + # "default_language": "en" + # }) + # def test_whole_batch_language_hint_and_obj_per_item_hints(self, client): + # def callback(resp): + # pass + # # if resp.http_request.body: + # # language_str = "\"language\": \"es\"" + # # language = resp.http_request.body.count(language_str) + # # self.assertEqual(language, 2) + # # language_str = "\"language\": \"en\"" + # # language = resp.http_request.body.count(language_str) + # # self.assertEqual(language, 1) + + # docs = [ + # TextDocumentInput(id="1", text="I should take my cat to the veterinarian.", language="es"), + # TextDocumentInput(id="2", text="Este es un document escrito en Español.", language="es"), + # TextDocumentInput(id="3", text="猫は幸せ"), + # ] + + # response = list(client.begin_analyze_batch_actions( + # docs, + # actions=[ + # RecognizeEntitiesAction(), + # ExtractKeyPhrasesAction(), + # RecognizePiiEntitiesAction() + # ], + # polling_interval=self._interval(), + # ).result()) + + # for action_result in response: + # for doc in action_result.document_results: + # assert not doc.is_error @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() def test_invalid_language_hint_method(self, client): - response = list(client.begin_analyze( + response = list(client.begin_analyze_batch_actions( ["This should fail because we're passing in an invalid language hint"], language="notalanguage", - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction() + ], polling_interval=self._interval(), ).result()) - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - tasks = getattr(response[0], task_type) # only expecting a single page of results here - self.assertEqual(len(tasks), 1) - - for r in tasks[0].results: - self.assertTrue(r.is_error) - - @pytest.mark.playback_test_only - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - def test_invalid_language_hint_docs(self, client): - response = list(client.begin_analyze( - [{"id": "1", "language": "notalanguage", "text": "This should fail because we're passing in an invalid language hint"}], - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - polling_interval=self._interval(), - ).result()) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - tasks = getattr(response[0], task_type) # only expecting a single page of results here - self.assertEqual(len(tasks), 1) - - for r in tasks[0].results: - self.assertTrue(r.is_error) + for action_result in response: + for doc in action_result.document_results: + assert doc.is_error @GlobalTextAnalyticsAccountPreparer() def test_rotate_subscription_key(self, resource_group, location, text_analytics_account, text_analytics_account_key): @@ -864,11 +465,11 @@ def test_rotate_subscription_key(self, resource_group, location, text_analytics_ {"id": "2", "text": "I did not like the hotel we stayed at."}, {"id": "3", "text": "The restaurant had really good food."}] - response = client.begin_analyze( + response = client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ], polling_interval=self._interval(), ).result() @@ -876,20 +477,20 @@ def test_rotate_subscription_key(self, resource_group, location, text_analytics_ credential.update("xxx") # Make authentication fail with self.assertRaises(ClientAuthenticationError): - response = client.begin_analyze( + response = client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ], polling_interval=self._interval(), ).result() credential.update(text_analytics_account_key) # Authenticate successfully again - response = client.begin_analyze( + response = client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ], polling_interval=self._interval(), ).result() self.assertIsNotNone(response) @@ -907,12 +508,13 @@ def callback(resp): {"id": "2", "text": "I did not like the hotel we stayed at."}, {"id": "3", "text": "The restaurant had really good food."}] - poller = client.begin_analyze( + poller = client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ], polling_interval=self._interval(), + raw_response_hook=callback ) self.assertIn("azsdk-python-ai-textanalytics/{} Python/{} ({})".format( @@ -922,74 +524,56 @@ def callback(resp): poller.result() # need to call this before tearDown runs even though we don't need the response for the test. - @pytest.mark.playback_test_only - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - def test_empty_document_failure(self, client): - docs = [{"id": "1", "text": ""}] - - with self.assertRaises(HttpResponseError): - response = client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - polling_interval=self._interval(), - ) - - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() def test_bad_model_version_error_single_task(self, client): # TODO: verify behavior of service docs = [{"id": "1", "language": "english", "text": "I did not like the hotel we stayed at."}] with self.assertRaises(HttpResponseError): - result = client.begin_analyze( + result = client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask(model_version="bad")], + actions=[ + RecognizeEntitiesAction(model_version="bad"), + ], polling_interval=self._interval(), ).result() - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() def test_bad_model_version_error_multiple_tasks(self, client): # TODO: verify behavior of service docs = [{"id": "1", "language": "english", "text": "I did not like the hotel we stayed at."}] - response = client.begin_analyze( + response = client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask(model_version="latest")], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask(model_version="bad")], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask(model_version="bad")], + actions=[ + RecognizeEntitiesAction(model_version="latest"), + ExtractKeyPhrasesAction(model_version="bad"), + RecognizePiiEntitiesAction(model_version="bad") + ], polling_interval=self._interval(), ).result() - results_pages = list(response) - self.assertEqual(len(results_pages), 1) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - tasks = getattr(results_pages[0], task_type) # only expecting a single page of results here - self.assertEqual(len(tasks), 1) - - for r in tasks[0].results: - self.assertTrue(r.is_error) # This is not the optimal way to represent this failure. We are discussing a solution with the service team. + action_results = list(response) + assert action_results[0].is_error == False + assert action_results[0].action_type == AnalyzeBatchActionsType.RECOGNIZE_ENTITIES + assert action_results[1].is_error == True + assert action_results[1].error.code == "InvalidRequest" + assert action_results[2].is_error == True + assert action_results[2].error.code == "InvalidRequest" - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() def test_bad_model_version_error_all_tasks(self, client): # TODO: verify behavior of service docs = [{"id": "1", "language": "english", "text": "I did not like the hotel we stayed at."}] with self.assertRaises(HttpResponseError): - response = client.begin_analyze( + response = client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask(model_version="bad")], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask(model_version="bad")], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask(model_version="bad")], + actions=[ + RecognizeEntitiesAction(model_version="bad"), + ExtractKeyPhrasesAction(model_version="bad"), + RecognizePiiEntitiesAction(model_version="bad") + ], polling_interval=self._interval(), ).result() @@ -998,11 +582,13 @@ def test_bad_model_version_error_all_tasks(self, client): # TODO: verify behavi def test_not_passing_list_for_docs(self, client): docs = {"id": "1", "text": "hello world"} with pytest.raises(TypeError) as excinfo: - client.begin_analyze( + client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction() + ], polling_interval=self._interval(), ) assert "Input documents cannot be a dict" in str(excinfo.value) @@ -1012,11 +598,13 @@ def test_not_passing_list_for_docs(self, client): def test_missing_input_records_error(self, client): docs = [] with pytest.raises(ValueError) as excinfo: - client.begin_analyze( + client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction() + ], polling_interval=self._interval(), ) assert "Input documents can not be empty or None" in str(excinfo.value) @@ -1025,7 +613,7 @@ def test_missing_input_records_error(self, client): @TextAnalyticsClientPreparer() def test_passing_none_docs(self, client): with pytest.raises(ValueError) as excinfo: - client.begin_analyze(None) + client.begin_analyze_batch_actions(None, None) assert "Input documents can not be empty or None" in str(excinfo.value) @GlobalTextAnalyticsAccountPreparer() @@ -1036,25 +624,26 @@ def test_duplicate_ids_error(self, client): # TODO: verify behavior of service {"id": "1", "text": "I did not like the hotel we stayed at."}] with self.assertRaises(HttpResponseError): - result = client.begin_analyze( + result = client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(), + ], polling_interval=self._interval(), ).result() - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() def test_pass_cls(self, client): def callback(pipeline_response, deserialized, _): return "cls result" - res = client.begin_analyze( + res = client.begin_analyze_batch_actions( documents=["Test passing cls to endpoint"], - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ], cls=callback, polling_interval=self._interval(), ).result() @@ -1066,39 +655,40 @@ def test_multiple_pages_of_results_returned_successfully(self, client): single_doc = "hello world" docs = [{"id": str(idx), "text": val} for (idx, val) in enumerate(list(itertools.repeat(single_doc, 25)))] # max number of documents is 25 - result = client.begin_analyze( + result = client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction() + ], show_stats=True, polling_interval=self._interval(), ).result() - pages = list(result) - self.assertEqual(len(pages), 2) # default page size is 20 + recognize_entities_results = [] + extract_key_phrases_results = [] + recognize_pii_entities_results = [] - # self.assertIsNotNone(result.statistics) # statistics not working at the moment, but a bug has been filed on the service to correct this. - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] + # do 2 pages of 3 task results + for idx, action_result in enumerate(result): + if idx % 3 == 0: + assert action_result.action_type == AnalyzeBatchActionsType.RECOGNIZE_ENTITIES + recognize_entities_results.append(action_result) + elif idx % 3 == 1: + assert action_result.action_type == AnalyzeBatchActionsType.EXTRACT_KEY_PHRASES + extract_key_phrases_results.append(action_result) + else: + assert action_result.action_type == AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES + recognize_pii_entities_results.append(action_result) + if idx < 3: # first page of task results + assert len(action_result.document_results) == 20 + else: + assert len(action_result.document_results) == 5 - expected_results_per_page = [20, 5] - - for idx, page in enumerate(pages): - for task_type in task_types: - task_results = getattr(page, task_type) - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - self.assertEqual(len(results), expected_results_per_page[idx]) - - for doc in results: - self.assertFalse(doc.is_error) - #self.assertIsNotNone(doc.statistics) + assert all([action_result for action_result in recognize_entities_results if len(action_result.document_results) == len(docs)]) + assert all([action_result for action_result in extract_key_phrases_results if len(action_result.document_results) == len(docs)]) + assert all([action_result for action_result in recognize_pii_entities_results if len(action_result.document_results) == len(docs)]) @GlobalTextAnalyticsAccountPreparer() @@ -1107,15 +697,13 @@ def test_too_many_documents(self, client): docs = list(itertools.repeat("input document", 26)) # Maximum number of documents per request is 25 with pytest.raises(HttpResponseError) as excinfo: - client.begin_analyze( + client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction() + ], polling_interval=self._interval(), ) assert excinfo.value.status_code == 400 - - - - diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/test_analyze_async.py b/sdk/textanalytics/azure-ai-textanalytics/tests/test_analyze_async.py index 49fe7f09b9c7..fbcb30765868 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/tests/test_analyze_async.py +++ b/sdk/textanalytics/azure-ai-textanalytics/tests/test_analyze_async.py @@ -3,7 +3,7 @@ # Copyright (c) Microsoft Corporation. # Licensed under the MIT License. # ------------------------------------ - +import datetime import os import pytest import platform @@ -22,9 +22,10 @@ TextDocumentInput, VERSION, TextAnalyticsApiVersion, - EntitiesRecognitionTask, - PiiEntitiesRecognitionTask, - KeyPhraseExtractionTask + RecognizeEntitiesAction, + RecognizePiiEntitiesAction, + ExtractKeyPhrasesAction, + AnalyzeBatchActionsType ) # pre-apply the client_cls positional argument so it needn't be explicitly passed below @@ -52,9 +53,8 @@ def _interval(self): @TextAnalyticsClientPreparer() async def test_no_single_input(self, client): with self.assertRaises(TypeError): - response = await client.begin_analyze("hello world", polling_interval=self._interval()) + response = await client.begin_analyze_batch_actions("hello world", actions=[], polling_interval=self._interval()) - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() async def test_all_successful_passing_dict_key_phrase_task(self, client): @@ -62,63 +62,57 @@ async def test_all_successful_passing_dict_key_phrase_task(self, client): {"id": "2", "language": "es", "text": "Microsoft fue fundado por Bill Gates y Paul Allen"}] async with client: - response = await (await client.begin_analyze( + response = await (await client.begin_analyze_batch_actions( docs, - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], + actions=[ExtractKeyPhrasesAction()], show_stats=True, polling_interval=self._interval() )).result() - results_pages = [] + action_results = [] async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_results = results_pages[0].key_phrase_extraction_results - self.assertEqual(len(task_results), 1) + action_results.append(p) + assert len(action_results) == 1 + action_result = action_results[0] - results = task_results[0].results - self.assertEqual(len(results), 2) + assert action_result.action_type == AnalyzeBatchActionsType.EXTRACT_KEY_PHRASES + assert len(action_result.document_results) == len(docs) - for phrases in results: - self.assertIn("Paul Allen", phrases.key_phrases) - self.assertIn("Bill Gates", phrases.key_phrases) - self.assertIn("Microsoft", phrases.key_phrases) - self.assertIsNotNone(phrases.id) - # self.assertIsNotNone(phrases.statistics) + for doc in action_result.document_results: + self.assertIn("Paul Allen", doc.key_phrases) + self.assertIn("Bill Gates", doc.key_phrases) + self.assertIn("Microsoft", doc.key_phrases) + self.assertIsNotNone(doc.id) + #self.assertIsNotNone(doc.statistics) - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() - async def test_all_successful_passing_dict_entities_task(self, client): + async def test_all_successful_passing_text_document_input_entities_task(self, client): docs = [ - {"id": "1", "language": "en", - "text": "Microsoft was founded by Bill Gates and Paul Allen on April 4, 1975."}, - {"id": "2", "language": "es", - "text": "Microsoft fue fundado por Bill Gates y Paul Allen el 4 de abril de 1975."}, - {"id": "3", "language": "de", - "text": "Microsoft wurde am 4. April 1975 von Bill Gates und Paul Allen gegründet."}] + TextDocumentInput(id="1", text="Microsoft was founded by Bill Gates and Paul Allen on April 4, 1975", language="en"), + TextDocumentInput(id="2", text="Microsoft fue fundado por Bill Gates y Paul Allen el 4 de abril de 1975.", language="es"), + TextDocumentInput(id="3", text="Microsoft wurde am 4. April 1975 von Bill Gates und Paul Allen gegründet.", language="de"), + ] async with client: - response = await (await client.begin_analyze( + poller = await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], + actions=[RecognizeEntitiesAction()], show_stats=True, - polling_interval=self._interval() - )).result() + polling_interval=self._interval(), + ) + response = await poller.result() - results_pages = [] + action_results = [] async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) + action_results.append(p) + assert len(action_results) == 1 + action_result = action_results[0] - task_results = results_pages[0].entities_recognition_results - self.assertEqual(len(task_results), 1) + assert action_result.action_type == AnalyzeBatchActionsType.RECOGNIZE_ENTITIES + assert len(action_result.document_results) == len(docs) - results = task_results[0].results - self.assertEqual(len(results), 3) - - for doc in results: + for doc in action_result.document_results: self.assertEqual(len(doc.entities), 4) self.assertIsNotNone(doc.id) # self.assertIsNotNone(doc.statistics) @@ -128,42 +122,39 @@ async def test_all_successful_passing_dict_entities_task(self, client): self.assertIsNotNone(entity.offset) self.assertIsNotNone(entity.confidence_score) - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() - async def test_all_successful_passing_dict_pii_entities_task(self, client): + async def test_all_successful_passing_string_pii_entities_task(self, client): - docs = [{"id": "1", "text": "My SSN is 859-98-0987."}, - {"id": "2", - "text": "Your ABA number - 111000025 - is the first 9 digits in the lower left hand corner of your personal check."}, - {"id": "3", "text": "Is 998.214.865-68 your Brazilian CPF number?"}] + docs = ["My SSN is 859-98-0987.", + "Your ABA number - 111000025 - is the first 9 digits in the lower left hand corner of your personal check.", + "Is 998.214.865-68 your Brazilian CPF number?" + ] async with client: - response = await (await client.begin_analyze( + response = await (await client.begin_analyze_batch_actions( docs, - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[RecognizePiiEntitiesAction()], show_stats=True, polling_interval=self._interval() )).result() - results_pages = [] + action_results = [] async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) + action_results.append(p) + assert len(action_results) == 1 + action_result = action_results[0] - task_results = results_pages[0].pii_entities_recognition_results - self.assertEqual(len(task_results), 1) + assert action_result.action_type == AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES + assert len(action_result.document_results) == len(docs) - results = task_results[0].results - self.assertEqual(len(results), 3) - - self.assertEqual(results[0].entities[0].text, "859-98-0987") - self.assertEqual(results[0].entities[0].category, "U.S. Social Security Number (SSN)") - self.assertEqual(results[1].entities[0].text, "111000025") + self.assertEqual(action_result.document_results[0].entities[0].text, "859-98-0987") + self.assertEqual(action_result.document_results[0].entities[0].category, "U.S. Social Security Number (SSN)") + self.assertEqual(action_result.document_results[1].entities[0].text, "111000025") # self.assertEqual(results[1].entities[0].category, "ABA Routing Number") # Service is currently returning PhoneNumber here - self.assertEqual(results[2].entities[0].text, "998.214.865-68") - self.assertEqual(results[2].entities[0].category, "Brazil CPF Number") - for doc in results: + self.assertEqual(action_result.document_results[2].entities[0].text, "998.214.865-68") + self.assertEqual(action_result.document_results[2].entities[0].category, "Brazil CPF Number") + for doc in action_result.document_results: self.assertIsNotNone(doc.id) # self.assertIsNotNone(doc.statistics) for entity in doc.entities: @@ -172,153 +163,6 @@ async def test_all_successful_passing_dict_pii_entities_task(self, client): self.assertIsNotNone(entity.offset) self.assertIsNotNone(entity.confidence_score) - @pytest.mark.playback_test_only - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - async def test_all_successful_passing_text_document_input_key_phrase_task(self, client): - docs = [ - TextDocumentInput(id="1", text="Microsoft was founded by Bill Gates and Paul Allen", language="en"), - TextDocumentInput(id="2", text="Microsoft fue fundado por Bill Gates y Paul Allen", language="es") - ] - - async with client: - response = await (await client.begin_analyze( - docs, - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - polling_interval=self._interval() - )).result() - - results_pages = [] - async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - key_phrase_task_results = results_pages[0].key_phrase_extraction_results - self.assertEqual(len(key_phrase_task_results), 1) - - results = key_phrase_task_results[0].results - self.assertEqual(len(results), 2) - - for phrases in results: - self.assertIn("Paul Allen", phrases.key_phrases) - self.assertIn("Bill Gates", phrases.key_phrases) - self.assertIn("Microsoft", phrases.key_phrases) - self.assertIsNotNone(phrases.id) - - @pytest.mark.playback_test_only - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - async def test_all_successful_passing_text_document_input_entities_task(self, client): - docs = [ - TextDocumentInput(id="1", text="Microsoft was founded by Bill Gates and Paul Allen on April 4, 1975.", - language="en"), - TextDocumentInput(id="2", text="Microsoft fue fundado por Bill Gates y Paul Allen el 4 de abril de 1975.", - language="es"), - TextDocumentInput(id="3", text="Microsoft wurde am 4. April 1975 von Bill Gates und Paul Allen gegründet.", - language="de") - ] - - async with client: - response = await (await client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - polling_interval=self._interval() - )).result() - - results_pages = [] - async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_results = results_pages[0].entities_recognition_results - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - self.assertEqual(len(results), 3) - - for doc in results: - self.assertEqual(len(doc.entities), 4) - self.assertIsNotNone(doc.id) - for entity in doc.entities: - self.assertIsNotNone(entity.text) - self.assertIsNotNone(entity.category) - self.assertIsNotNone(entity.offset) - self.assertIsNotNone(entity.confidence_score) - - @pytest.mark.playback_test_only - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - async def test_all_successful_passing_text_document_input_pii_entities_task(self, client): - docs = [ - TextDocumentInput(id="1", text="My SSN is 859-98-0987."), - TextDocumentInput(id="2", - text="Your ABA number - 111000025 - is the first 9 digits in the lower left hand corner of your personal check."), - TextDocumentInput(id="3", text="Is 998.214.865-68 your Brazilian CPF number?") - ] - - async with client: - response = await (await client.begin_analyze( - docs, - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - polling_interval=self._interval() - )).result() - - results_pages = [] - async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_results = results_pages[0].pii_entities_recognition_results - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - self.assertEqual(len(results), 3) - - self.assertEqual(results[0].entities[0].text, "859-98-0987") - self.assertEqual(results[0].entities[0].category, "U.S. Social Security Number (SSN)") - self.assertEqual(results[1].entities[0].text, "111000025") - # self.assertEqual(results[1].entities[0].category, "ABA Routing Number") # Service is currently returning PhoneNumber here - self.assertEqual(results[2].entities[0].text, "998.214.865-68") - self.assertEqual(results[2].entities[0].category, "Brazil CPF Number") - for doc in results: - self.assertIsNotNone(doc.id) - for entity in doc.entities: - self.assertIsNotNone(entity.text) - self.assertIsNotNone(entity.category) - self.assertIsNotNone(entity.offset) - self.assertIsNotNone(entity.confidence_score) - - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - async def test_passing_only_string_key_phrase_task(self, client): - docs = [ - u"Microsoft was founded by Bill Gates and Paul Allen", - u"Microsoft fue fundado por Bill Gates y Paul Allen" - ] - - async with client: - response = await (await client.begin_analyze( - docs, - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - polling_interval=self._interval() - )).result() - - results_pages = [] - async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - key_phrase_task_results = results_pages[0].key_phrase_extraction_results - self.assertEqual(len(key_phrase_task_results), 1) - - results = key_phrase_task_results[0].results - self.assertEqual(len(results), 2) - - self.assertIn("Paul Allen", results[0].key_phrases) - self.assertIn("Bill Gates", results[0].key_phrases) - self.assertIn("Microsoft", results[0].key_phrases) - self.assertIsNotNone(results[0].id) - @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() async def test_bad_request_on_empty_document(self, client): @@ -326,89 +170,12 @@ async def test_bad_request_on_empty_document(self, client): with self.assertRaises(HttpResponseError): async with client: - response = await (await client.begin_analyze( + response = await (await client.begin_analyze_batch_actions( docs, - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], + actions=[ExtractKeyPhrasesAction()], polling_interval=self._interval() )).result() - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - async def test_passing_only_string_entities_task(self, client): - docs = [ - u"Microsoft was founded by Bill Gates and Paul Allen on April 4, 1975.", - u"Microsoft fue fundado por Bill Gates y Paul Allen el 4 de abril de 1975.", - u"Microsoft wurde am 4. April 1975 von Bill Gates und Paul Allen gegründet." - ] - - async with client: - response = await (await client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - polling_interval=self._interval() - )).result() - - results_pages = [] - async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_results = results_pages[0].entities_recognition_results - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - self.assertEqual(len(results), 3) - - self.assertEqual(len(results[0].entities), 4) - self.assertIsNotNone(results[0].id) - for entity in results[0].entities: - self.assertIsNotNone(entity.text) - self.assertIsNotNone(entity.category) - self.assertIsNotNone(entity.offset) - self.assertIsNotNone(entity.confidence_score) - - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - async def test_passing_only_string_pii_entities_task(self, client): - docs = [ - u"My SSN is 859-98-0987.", - u"Your ABA number - 111000025 - is the first 9 digits in the lower left hand corner of your personal check.", - u"Is 998.214.865-68 your Brazilian CPF number?" - ] - - async with client: - response = await (await client.begin_analyze( - docs, - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - polling_interval=self._interval() - )).result() - - results_pages = [] - async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_results = results_pages[0].pii_entities_recognition_results - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - self.assertEqual(len(results), 3) - - self.assertEqual(results[0].entities[0].text, "859-98-0987") - self.assertEqual(results[0].entities[0].category, "U.S. Social Security Number (SSN)") - self.assertEqual(results[1].entities[0].text, "111000025") - # self.assertEqual(results[1].entities[0].category, "ABA Routing Number") # Service is currently returning PhoneNumber here - self.assertEqual(results[2].entities[0].text, "998.214.865-68") - self.assertEqual(results[2].entities[0].category, "Brazil CPF Number") - - for i in range(3): - self.assertIsNotNone(results[i].id) - for entity in results[i].entities: - self.assertIsNotNone(entity.text) - self.assertIsNotNone(entity.category) - self.assertIsNotNone(entity.offset) - self.assertIsNotNone(entity.confidence_score) - @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() async def test_output_same_order_as_input_multiple_tasks(self, client): @@ -421,36 +188,33 @@ async def test_output_same_order_as_input_multiple_tasks(self, client): ] async with client: - response = await (await client.begin_analyze( + response = await (await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizePiiEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(model_version="bad"), + ], polling_interval=self._interval() )).result() - results_pages = [] + action_results = [] async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] + action_results.append(p) - for task_type in task_types: - task_results = getattr(results_pages[0], task_type) - self.assertEqual(len(task_results), 1) + assert len(action_results) == 3 + action_result = action_results[0] - results = task_results[0].results - self.assertEqual(len(results), 5) + assert action_results[0].action_type == AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES + assert action_results[1].action_type == AnalyzeBatchActionsType.EXTRACT_KEY_PHRASES + assert action_results[2].is_error + assert all([action_result for action_result in action_results if not action_result.is_error and len(action_result.document_results) == len(docs)]) - for idx, doc in enumerate(results): - self.assertEqual(str(idx + 1), doc.id) + for action_result in action_results: + if not action_result.is_error: + for idx, doc in enumerate(action_result.document_results): + self.assertEqual(str(idx + 1), doc.id) - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer(client_kwargs={ "text_analytics_account_key": "", @@ -458,15 +222,16 @@ async def test_output_same_order_as_input_multiple_tasks(self, client): async def test_empty_credential_class(self, client): with self.assertRaises(ClientAuthenticationError): async with client: - response = await client.begin_analyze( + response = await (await client.begin_analyze_batch_actions( ["This is written in English."], - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(), + ], polling_interval=self._interval() - ) + )).result() - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer(client_kwargs={ "text_analytics_account_key": "xxxxxxxxxxxx" @@ -474,15 +239,16 @@ async def test_empty_credential_class(self, client): async def test_bad_credentials(self, client): with self.assertRaises(ClientAuthenticationError): async with client: - response = await client.begin_analyze( + response = await (await client.begin_analyze_batch_actions( ["This is written in English."], - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(), + ], polling_interval=self._interval() - ) + )).result() - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() async def test_bad_document_input(self, client): @@ -490,15 +256,16 @@ async def test_bad_document_input(self, client): with self.assertRaises(TypeError): async with client: - response = await client.begin_analyze( + response = await (await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(), + ], polling_interval=self._interval() - ) + )).result() - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() async def test_mixing_inputs(self, client): @@ -509,15 +276,16 @@ async def test_mixing_inputs(self, client): ] with self.assertRaises(TypeError): async with client: - response = await (await client.begin_analyze( + response = await (await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(), + ], polling_interval=self._interval() )).result() - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() async def test_out_of_order_ids_multiple_tasks(self, client): @@ -527,36 +295,33 @@ async def test_out_of_order_ids_multiple_tasks(self, client): {"id": "1", "text": ":D"}] async with client: - response = await (await client.begin_analyze( + response = await (await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask(model_version="bad")], - # at this moment this should cause all documents to be errors, which isn't correct behavior but I'm using it here to test document ordering with errors. :) - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(model_version="bad"), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(), + ], polling_interval=self._interval() )).result() - results_pages = [] + action_results = [] async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) + action_results.append(p) + assert len(action_results) == 3 - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] + assert action_results[0].is_error + assert action_results[1].action_type == AnalyzeBatchActionsType.EXTRACT_KEY_PHRASES + assert action_results[2].action_type == AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES - in_order = ["56", "0", "19", "1"] + action_results = [r for r in action_results if not r.is_error] - for task_type in task_types: - task_results = getattr(results_pages[0], task_type) - self.assertEqual(len(task_results), 1) + assert all([action_result for action_result in action_results if len(action_result.document_results) == len(docs)]) - results = task_results[0].results - self.assertEqual(len(results), len(docs)) + in_order = ["56", "0", "19", "1"] - for idx, resp in enumerate(results): + for action_result in action_results: + for idx, resp in enumerate(action_result.document_results): self.assertEqual(resp.id, in_order[idx]) @GlobalTextAnalyticsAccountPreparer() @@ -568,403 +333,148 @@ async def test_show_stats_and_model_version_multiple_tasks(self, client): {"id": "1", "text": ":D"}] async with client: - response = await (await client.begin_analyze( + response = await (await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask(model_version="latest")], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask(model_version="latest")], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask(model_version="latest")], + actions=[ + RecognizeEntitiesAction(model_version="latest"), + ExtractKeyPhrasesAction(model_version="latest"), + RecognizePiiEntitiesAction(model_version="latest") + ], show_stats=True, polling_interval=self._interval() )).result() - results_pages = [] + action_results = [] async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - task_results = getattr(results_pages[0], task_type) - self.assertEqual(len(task_results), 1) + action_results.append(p) + assert len(action_results) == 3 + assert action_results[0].action_type == AnalyzeBatchActionsType.RECOGNIZE_ENTITIES + assert action_results[1].action_type == AnalyzeBatchActionsType.EXTRACT_KEY_PHRASES + assert action_results[2].action_type == AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES - results = task_results[0].results - self.assertEqual(len(results), len(docs)) + assert all([action_result for action_result in action_results if len(action_result.document_results) == len(docs)]) # self.assertEqual(results.statistics.document_count, 5) # self.assertEqual(results.statistics.transaction_count, 4) # self.assertEqual(results.statistics.valid_document_count, 4) # self.assertEqual(results.statistics.erroneous_document_count, 1) - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() - async def test_whole_batch_language_hint(self, client): - docs = [ - u"This was the best day of my life.", - u"I did not like the hotel we stayed at. It was too expensive.", - u"The restaurant was not as good as I hoped." - ] + async def test_poller_metadata(self, client): + docs = [{"id": "56", "text": ":)"}] async with client: - response = await (await client.begin_analyze( + poller = await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - language="en", - polling_interval=self._interval() - )).result() - - results_pages = [] - async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - task_results = getattr(results_pages[0], task_type) - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - for r in results: - self.assertFalse(r.is_error) - - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - async def test_whole_batch_dont_use_language_hint(self, client): - docs = [ - u"This was the best day of my life.", - u"I did not like the hotel we stayed at. It was too expensive.", - u"The restaurant was not as good as I hoped." - ] - - async with client: - response = await (await client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - language="", - polling_interval=self._interval() - )).result() - - results_pages = [] - async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - task_results = getattr(results_pages[0], task_type) - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - for r in results: - self.assertFalse(r.is_error) - - @pytest.mark.playback_test_only - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - async def test_per_item_dont_use_language_hint(self, client): - docs = [{"id": "1", "language": "", "text": "I will go to the park."}, - {"id": "2", "language": "", "text": "I did not like the hotel we stayed at."}, - {"id": "3", "text": "The restaurant had really good food."}] - - async with client: - response = await (await client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - polling_interval=self._interval() - )).result() - - results_pages = [] - async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - task_results = getattr(results_pages[0], task_type) - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - for r in results: - self.assertFalse(r.is_error) - - @pytest.mark.playback_test_only - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - async def test_whole_batch_language_hint_and_obj_input(self, client): - async def callback(resp): - language_str = "\"language\": \"de\"" - language = resp.http_request.body.count(language_str) - self.assertEqual(language, 3) - - docs = [ - TextDocumentInput(id="1", text="I should take my cat to the veterinarian."), - TextDocumentInput(id="4", text="Este es un document escrito en Español."), - TextDocumentInput(id="3", text="猫は幸せ"), - ] - - async with client: - response = await (await client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - language="en", - polling_interval=self._interval() - )).result() - - results_pages = [] - async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - task_results = getattr(results_pages[0], task_type) - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - for r in results: - self.assertFalse(r.is_error) - - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - async def test_whole_batch_language_hint_and_dict_input(self, client): - docs = [{"id": "1", "text": "I will go to the park."}, - {"id": "2", "text": "I did not like the hotel we stayed at."}, - {"id": "3", "text": "The restaurant had really good food."}] - - async with client: - response = await (await client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - language="en", - polling_interval=self._interval() - )).result() - - results_pages = [] - async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - task_results = getattr(results_pages[0], task_type) - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - for r in results: - self.assertFalse(r.is_error) - - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - async def test_whole_batch_language_hint_and_obj_per_item_hints(self, client): - docs = [ - TextDocumentInput(id="1", text="I should take my cat to the veterinarian.", language="en"), - TextDocumentInput(id="2", text="Este es un document escrito en Español.", language="en"), - TextDocumentInput(id="3", text="猫は幸せ"), - ] - - async with client: - response = await (await client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - language="en", - polling_interval=self._interval() - )).result() - - results_pages = [] - async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - task_results = getattr(results_pages[0], task_type) - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - for r in results: - self.assertFalse(r.is_error) - - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - async def test_whole_batch_language_hint_and_dict_per_item_hints(self, client): - docs = [{"id": "1", "language": "en", "text": "I will go to the park."}, - {"id": "2", "language": "en", "text": "I did not like the hotel we stayed at."}, - {"id": "3", "text": "The restaurant had really good food."}] - - async with client: - response = await (await client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - language="en", - polling_interval=self._interval() - )).result() - - results_pages = [] - async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - task_results = getattr(results_pages[0], task_type) - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - for r in results: - self.assertFalse(r.is_error) - - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer(client_kwargs={ - "default_language": "en" - }) - async def test_client_passed_default_language_hint(self, client): - docs = [{"id": "1", "text": "I will go to the park."}, - {"id": "2", "text": "I did not like the hotel we stayed at."}, - {"id": "3", "text": "The restaurant had really good food."}] - - async with client: - response = await (await client.begin_analyze( - docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - polling_interval=self._interval() - )).result() - - results_pages = [] - async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - tasks = getattr(results_pages[0], task_type) - self.assertEqual(len(tasks), 1) - self.assertEqual(len(tasks[0].results), 3) - - for r in tasks[0].results: - self.assertFalse(r.is_error) - - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - async def test_invalid_language_hint_method(self, client): - async with client: - response = await (await client.begin_analyze( - ["This should fail because we're passing in an invalid language hint"], - language="notalanguage", - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - polling_interval=self._interval() - )).result() - - results_pages = [] - async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - tasks = getattr(results_pages[0], task_type) - self.assertEqual(len(tasks), 1) - - for r in tasks[0].results: - self.assertTrue(r.is_error) - - @GlobalTextAnalyticsAccountPreparer() - @TextAnalyticsClientPreparer() - async def test_invalid_language_hint_docs(self, client): - async with client: - response = await (await client.begin_analyze( - [{"id": "1", "language": "notalanguage", - "text": "This should fail because we're passing in an invalid language hint"}], - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - polling_interval=self._interval() - )).result() - - results_pages = [] - async for p in response: - results_pages.append(p) - self.assertEqual(len(results_pages), 1) - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - tasks = getattr(results_pages[0], task_type) - self.assertEqual(len(tasks), 1) + actions=[ + RecognizeEntitiesAction(model_version="latest") + ], + show_stats=True, + polling_interval=self._interval(), + ) - for r in tasks[0].results: - self.assertTrue(r.is_error) + response = await poller.result() + + assert isinstance(poller.created_on, datetime.datetime) + poller._polling_method.display_name + assert isinstance(poller.expires_on, datetime.datetime) + assert poller.actions_failed_count == 0 + assert poller.actions_in_progress_count == 0 + assert poller.actions_succeeded_count == 1 + assert isinstance(poller.last_modified_on, datetime.datetime) + assert poller.total_actions_count == 1 + assert poller.id + + ### TODO: Commenting out language tests. Right now analyze only supports language 'en', so no point to these tests yet + + # @GlobalTextAnalyticsAccountPreparer() + # @TextAnalyticsClientPreparer() + # async def test_whole_batch_language_hint(self, client): + # def callback(resp): + # language_str = "\"language\": \"fr\"" + # if resp.http_request.body: + # language = resp.http_request.body.count(language_str) + # self.assertEqual(language, 3) + + # docs = [ + # u"This was the best day of my life.", + # u"I did not like the hotel we stayed at. It was too expensive.", + # u"The restaurant was not as good as I hoped." + # ] + + # async with client: + # response = await (await client.begin_analyze_batch_actions( + # docs, + # actions=[ + # RecognizeEntitiesAction(), + # ExtractKeyPhrasesAction(), + # RecognizePiiEntitiesAction() + # ], + # language="fr", + # polling_interval=self._interval(), + # raw_response_hook=callback + # )).result() + + # async for action_result in response: + # for doc in action_result.document_results: + # self.assertFalse(doc.is_error) + + + # @GlobalTextAnalyticsAccountPreparer() + # @TextAnalyticsClientPreparer(client_kwargs={ + # "default_language": "en" + # }) + # async def test_whole_batch_language_hint_and_obj_per_item_hints(self, client): + # def callback(resp): + # if resp.http_request.body: + # language_str = "\"language\": \"es\"" + # language = resp.http_request.body.count(language_str) + # self.assertEqual(language, 2) + # language_str = "\"language\": \"en\"" + # language = resp.http_request.body.count(language_str) + # self.assertEqual(language, 1) + + # docs = [ + # TextDocumentInput(id="1", text="I should take my cat to the veterinarian.", language="es"), + # TextDocumentInput(id="2", text="Este es un document escrito en Español.", language="es"), + # TextDocumentInput(id="3", text="猫は幸せ"), + # ] + + # async with client: + # response = await (await client.begin_analyze_batch_actions( + # docs, + # actions=[ + # RecognizeEntitiesAction(), + # ExtractKeyPhrasesAction(), + # RecognizePiiEntitiesAction() + # ], + # language="en", + # polling_interval=self._interval() + # )).result() + + # async for action_result in response: + # for doc in action_result.document_results: + # assert not doc.is_error + + # @GlobalTextAnalyticsAccountPreparer() + # @TextAnalyticsClientPreparer() + # async def test_invalid_language_hint_method(self, client): + # async with client: + # response = await (await client.begin_analyze_batch_actions( + # ["This should fail because we're passing in an invalid language hint"], + # language="notalanguage", + # actions=[ + # RecognizeEntitiesAction(), + # ExtractKeyPhrasesAction(), + # RecognizePiiEntitiesAction() + # ], + # polling_interval=self._interval() + # )).result() + + # async for action_result in response: + # for doc in action_result.document_results: + # assert doc.is_error @GlobalTextAnalyticsAccountPreparer() async def test_rotate_subscription_key(self, resource_group, location, text_analytics_account, @@ -978,11 +488,11 @@ async def test_rotate_subscription_key(self, resource_group, location, text_anal {"id": "3", "text": "The restaurant had really good food."}] async with client: - response = await (await client.begin_analyze( + response = await (await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ], polling_interval=self._interval() )).result() @@ -990,28 +500,29 @@ async def test_rotate_subscription_key(self, resource_group, location, text_anal credential.update("xxx") # Make authentication fail with self.assertRaises(ClientAuthenticationError): - response = await (await client.begin_analyze( + response = await (await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ], polling_interval=self._interval() )).result() credential.update(text_analytics_account_key) # Authenticate successfully again - response = await (await client.begin_analyze( + response = await (await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ], polling_interval=self._interval() )).result() self.assertIsNotNone(response) + @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() async def test_user_agent(self, client): - async def callback(resp): + def callback(resp): self.assertIn("azsdk-python-ai-textanalytics/{} Python/{} ({})".format( VERSION, platform.python_version(), platform.platform()), resp.http_request.headers["User-Agent"] @@ -1022,20 +533,16 @@ async def callback(resp): {"id": "3", "text": "The restaurant had really good food."}] async with client: - poller = await client.begin_analyze( + poller = await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], - polling_interval=self._interval() + actions=[ + RecognizeEntitiesAction(), + ], + polling_interval=self._interval(), + raw_response_hook=callback, ) + await poller.wait() - self.assertIn("azsdk-python-ai-textanalytics/{} Python/{} ({})".format( - VERSION, platform.python_version(), platform.platform()), - poller._polling_method._initial_response.http_request.headers["User-Agent"] - ) - - await poller.result() # need to call this before tearDown runs even though we don't need the response for the test. @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() @@ -1044,47 +551,41 @@ async def test_bad_model_version_error_single_task(self, client): # TODO: verif with self.assertRaises(HttpResponseError): async with client: - result = await (await client.begin_analyze( + result = await (await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask(model_version="bad")], + actions=[ + RecognizeEntitiesAction(model_version="bad"), + ], polling_interval=self._interval() )).result() - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() async def test_bad_model_version_error_multiple_tasks(self, client): # TODO: verify behavior of service docs = [{"id": "1", "language": "english", "text": "I did not like the hotel we stayed at."}] async with client: - response = await(await - client.begin_analyze( + response = await (await + client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask(model_version="latest")], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask(model_version="bad")], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask(model_version="bad")], + actions=[ + RecognizeEntitiesAction(model_version="latest"), + ExtractKeyPhrasesAction(model_version="bad"), + RecognizePiiEntitiesAction(model_version="bad") + ], polling_interval=self._interval() )).result() - results_pages = [] + action_results = [] async for p in response: - results_pages.append(p) - - self.assertEqual(len(results_pages), 1) + action_results.append(p) - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - - for task_type in task_types: - tasks = getattr(results_pages[0], task_type) # only expecting a single page of results here - self.assertEqual(len(tasks), 1) - - for r in tasks[0].results: - self.assertTrue( - r.is_error) # This is not the optimal way to represent this failure. We are discussing this with the service team. + assert action_results[0].is_error == False + assert action_results[0].action_type == AnalyzeBatchActionsType.RECOGNIZE_ENTITIES + assert action_results[1].is_error == True + assert action_results[1].error.code == "InvalidRequest" + assert action_results[2].is_error == True + assert action_results[2].error.code == "InvalidRequest" @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() @@ -1093,11 +594,13 @@ async def test_bad_model_version_error_all_tasks(self, client): # TODO: verify with self.assertRaises(HttpResponseError): async with client: - result = await (await client.begin_analyze( + result = await (await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask(model_version="bad")], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask(model_version="bad")], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask(model_version="bad")], + actions=[ + RecognizeEntitiesAction(model_version="bad"), + ExtractKeyPhrasesAction(model_version="bad"), + RecognizePiiEntitiesAction(model_version="bad") + ], polling_interval=self._interval() )).result() @@ -1107,13 +610,15 @@ async def test_not_passing_list_for_docs(self, client): docs = {"id": "1", "text": "hello world"} with pytest.raises(TypeError) as excinfo: async with client: - await client.begin_analyze( + await (await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction() + ], polling_interval=self._interval() - ) + )).result() assert "Input documents cannot be a dict" in str(excinfo.value) @GlobalTextAnalyticsAccountPreparer() @@ -1122,13 +627,15 @@ async def test_missing_input_records_error(self, client): docs = [] with pytest.raises(ValueError) as excinfo: async with client: - await client.begin_analyze( + await (await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction() + ], polling_interval=self._interval() - ) + )).result() assert "Input documents can not be empty or None" in str(excinfo.value) @GlobalTextAnalyticsAccountPreparer() @@ -1136,7 +643,7 @@ async def test_missing_input_records_error(self, client): async def test_passing_none_docs(self, client): with pytest.raises(ValueError) as excinfo: async with client: - await client.begin_analyze(None, polling_interval=self._interval()) + await client.begin_analyze_batch_actions(None, None, polling_interval=self._interval()) assert "Input documents can not be empty or None" in str(excinfo.value) @GlobalTextAnalyticsAccountPreparer() @@ -1148,11 +655,13 @@ async def test_duplicate_ids_error(self, client): # TODO: verify behavior of se with self.assertRaises(HttpResponseError): async with client: - result = await (await client.begin_analyze( + result = await (await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(), + ], polling_interval=self._interval() )).result() @@ -1163,11 +672,11 @@ def callback(pipeline_response, deserialized, _): return "cls result" async with client: - res = await (await client.begin_analyze( + res = await (await client.begin_analyze_batch_actions( documents=["Test passing cls to endpoint"], - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ], cls=callback, polling_interval=self._interval() )).result() @@ -1181,11 +690,13 @@ async def test_multiple_pages_of_results_returned_successfully(self, client): enumerate(list(itertools.repeat(single_doc, 25)))] # max number of documents is 25 async with client: - result = await (await client.begin_analyze( + result = await (await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(), + ], show_stats=True, polling_interval=self._interval() )).result() @@ -1194,31 +705,29 @@ async def test_multiple_pages_of_results_returned_successfully(self, client): async for p in result: pages.append(p) - self.assertEqual(len(pages), 2) # default page size is 20 + recognize_entities_results = [] + extract_key_phrases_results = [] + recognize_pii_entities_results = [] - # self.assertIsNotNone(result.statistics) # statistics not working at the moment, but a bug has been filed on the service to correct this. + for idx, action_result in enumerate(pages): + if idx % 3 == 0: + assert action_result.action_type == AnalyzeBatchActionsType.RECOGNIZE_ENTITIES + recognize_entities_results.append(action_result) + elif idx % 3 == 1: + assert action_result.action_type == AnalyzeBatchActionsType.EXTRACT_KEY_PHRASES + extract_key_phrases_results.append(action_result) + else: + assert action_result.action_type == AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES + recognize_pii_entities_results.append(action_result) + if idx < 3: # first page of task results + assert len(action_result.document_results) == 20 + else: + assert len(action_result.document_results) == 5 - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] + assert all([action_result for action_result in recognize_entities_results if len(action_result.document_results) == len(docs)]) + assert all([action_result for action_result in extract_key_phrases_results if len(action_result.document_results) == len(docs)]) + assert all([action_result for action_result in recognize_pii_entities_results if len(action_result.document_results) == len(docs)]) - expected_results_per_page = [20, 5] - - for idx, page in enumerate(pages): - for task_type in task_types: - task_results = getattr(page, task_type) - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - self.assertEqual(len(results), expected_results_per_page[idx]) - - for doc in results: - self.assertFalse(doc.is_error) - # self.assertIsNotNone(doc.statistics) - - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() async def test_multiple_pages_of_results_with_errors_returned_successfully(self, client): @@ -1227,42 +736,26 @@ async def test_multiple_pages_of_results_with_errors_returned_successfully(self, enumerate(list(itertools.repeat(single_doc, 25)))] # max number of documents is 25 async with client: - result = await (await client.begin_analyze( + result = await (await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask(model_version="bad")], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(model_version="bad"), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(), + ], polling_interval=self._interval() )).result() pages = [] async for p in result: pages.append(p) - self.assertEqual(len(pages), 2) # default page size is 20 - - task_types = [ - "entities_recognition_results", - "key_phrase_extraction_results", - "pii_entities_recognition_results" - ] - expected_results_per_page = [20, 5] + for idx, action_result in enumerate(pages): + if idx % 3 == 0: + assert action_result.is_error + else: + assert all([doc for doc in action_result.document_results if not doc.is_error]) - for idx, page in enumerate(pages): - for task_type in task_types: - task_results = getattr(page, task_type) - self.assertEqual(len(task_results), 1) - - results = task_results[0].results - self.assertEqual(len(results), expected_results_per_page[idx]) - - for doc in results: - if task_type == "entities_recognition_results": - self.assertTrue(doc.is_error) - else: - self.assertFalse(doc.is_error) - - @pytest.mark.playback_test_only @GlobalTextAnalyticsAccountPreparer() @TextAnalyticsClientPreparer() async def test_too_many_documents(self, client): @@ -1270,11 +763,13 @@ async def test_too_many_documents(self, client): with pytest.raises(HttpResponseError) as excinfo: async with client: - await client.begin_analyze( + await (await client.begin_analyze_batch_actions( docs, - entities_recognition_tasks=[EntitiesRecognitionTask()], - key_phrase_extraction_tasks=[KeyPhraseExtractionTask()], - pii_entities_recognition_tasks=[PiiEntitiesRecognitionTask()], + actions=[ + RecognizeEntitiesAction(), + ExtractKeyPhrasesAction(), + RecognizePiiEntitiesAction(), + ], polling_interval=self._interval() - ) + )).result() assert excinfo.value.status_code == 400 diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/test_repr.py b/sdk/textanalytics/azure-ai-textanalytics/tests/test_repr.py index 3a675e9ef93e..843753d06702 100644 --- a/sdk/textanalytics/azure-ai-textanalytics/tests/test_repr.py +++ b/sdk/textanalytics/azure-ai-textanalytics/tests/test_repr.py @@ -6,6 +6,7 @@ # -------------------------------------------------------------------------- import pytest +import datetime from azure.ai.textanalytics import _models from azure.ai.textanalytics._generated.v3_1_preview_3 import models as _generated_models @@ -212,6 +213,55 @@ def sentence_sentiment(sentiment_confidence_scores, mined_opinion): assert repr(model) == model_repr return model, model_repr +@pytest.fixture +def recognize_pii_entities_result(pii_entity, text_analytics_warning, text_document_statistics): + model = _models.RecognizePiiEntitiesResult( + id="1", + entities=[pii_entity[0]], + redacted_text="***********", + warnings=[text_analytics_warning[0]], + statistics=text_document_statistics[0], + is_error=False + ) + model_repr = "RecognizePiiEntitiesResult(id=1, entities=[{}], redacted_text=***********, warnings=[{}], " \ + "statistics={}, is_error=False)".format( + pii_entity[1], text_analytics_warning[1], text_document_statistics[1] + ) + + assert repr(model) == model_repr + return model, model_repr + +@pytest.fixture +def recognize_entities_result(categorized_entity, text_analytics_warning, text_document_statistics): + model = _models.RecognizeEntitiesResult( + id="1", + entities=[categorized_entity[0]], + warnings=[text_analytics_warning[0]], + statistics=text_document_statistics[0], + is_error=False + ) + model_repr = "RecognizeEntitiesResult(id=1, entities=[{}], warnings=[{}], statistics={}, is_error=False)".format( + categorized_entity[1], text_analytics_warning[1], text_document_statistics[1] + ) + + assert repr(model) == model_repr + return model, model_repr + +@pytest.fixture +def extract_key_phrases_result(text_analytics_warning, text_document_statistics): + model = _models.ExtractKeyPhrasesResult( + id="1", + key_phrases=["dog", "cat", "bird"], + warnings=[text_analytics_warning[0]], + statistics=text_document_statistics[0], + is_error=False + ) + model_repr = "ExtractKeyPhrasesResult(id=1, key_phrases=['dog', 'cat', 'bird'], warnings=[{}], statistics={}, is_error=False)".format( + text_analytics_warning[1], text_document_statistics[1] + ) + + assert repr(model) == model_repr + return model, model_repr class TestRepr(): def test_text_document_input(self): @@ -272,36 +322,6 @@ def test_detect_language_result(self, detected_language, text_analytics_warning, assert repr(model) == model_repr - def test_recognize_entities_result(self, categorized_entity, text_analytics_warning, text_document_statistics): - model = _models.RecognizeEntitiesResult( - id="1", - entities=[categorized_entity[0]], - warnings=[text_analytics_warning[0]], - statistics=text_document_statistics[0], - is_error=False - ) - model_repr = "RecognizeEntitiesResult(id=1, entities=[{}], warnings=[{}], statistics={}, is_error=False)".format( - categorized_entity[1], text_analytics_warning[1], text_document_statistics[1] - ) - - assert repr(model) == model_repr - - def test_recognize_pii_entities_result(self, pii_entity, text_analytics_warning, text_document_statistics): - model = _models.RecognizePiiEntitiesResult( - id="1", - entities=[pii_entity[0]], - redacted_text="***********", - warnings=[text_analytics_warning[0]], - statistics=text_document_statistics[0], - is_error=False - ) - model_repr = "RecognizePiiEntitiesResult(id=1, entities=[{}], redacted_text=***********, warnings=[{}], " \ - "statistics={}, is_error=False)".format( - pii_entity[1], text_analytics_warning[1], text_document_statistics[1] - ) - - assert repr(model) == model_repr - def test_recognized_linked_entites_result(self, linked_entity, text_analytics_warning, text_document_statistics): model = _models.RecognizeLinkedEntitiesResult( id="1", @@ -316,20 +336,6 @@ def test_recognized_linked_entites_result(self, linked_entity, text_analytics_wa assert repr(model) == model_repr - def test_extract_key_phrases_result(self, text_analytics_warning, text_document_statistics): - model = _models.ExtractKeyPhrasesResult( - id="1", - key_phrases=["dog", "cat", "bird"], - warnings=[text_analytics_warning[0]], - statistics=text_document_statistics[0], - is_error=False - ) - model_repr = "ExtractKeyPhrasesResult(id=1, key_phrases=['dog', 'cat', 'bird'], warnings=[{}], statistics={}, is_error=False)".format( - text_analytics_warning[1], text_document_statistics[1] - ) - - assert repr(model) == model_repr - def test_analyze_sentiment_result( self, text_analytics_warning, text_document_statistics, sentiment_confidence_scores, sentence_sentiment ): @@ -366,3 +372,51 @@ def test_inner_error_takes_precedence(self): error = _models.TextAnalyticsError._from_generated(generated_error) assert error.code == "UnsupportedLanguageCode" assert error.message == "Supplied language not supported. Pass in one of: de,en,es,fr,it,ja,ko,nl,pt-PT,zh-Hans,zh-Hant" + + def test_analyze_batch_actions_result_recognize_entities(self, recognize_entities_result): + model = _models.AnalyzeBatchActionsResult( + document_results=[recognize_entities_result[0]], + is_error=False, + action_type=_models.AnalyzeBatchActionsType.RECOGNIZE_ENTITIES, + completed_on=datetime.datetime(1, 1, 1) + ) + + model_repr = ( + "AnalyzeBatchActionsResult(document_results=[{}], is_error={}, action_type={}, completed_on={})".format( + recognize_entities_result[1], False, "recognize_entities", datetime.datetime(1, 1, 1) + ) + ) + + assert repr(model) == model_repr + + def test_analyze_batch_actions_result_recognize_pii_entities(self, recognize_pii_entities_result): + model = _models.AnalyzeBatchActionsResult( + document_results=[recognize_pii_entities_result[0]], + is_error=False, + action_type=_models.AnalyzeBatchActionsType.RECOGNIZE_PII_ENTITIES, + completed_on=datetime.datetime(1, 1, 1) + ) + + model_repr = ( + "AnalyzeBatchActionsResult(document_results=[{}], is_error={}, action_type={}, completed_on={})".format( + recognize_pii_entities_result[1], False, "recognize_pii_entities", datetime.datetime(1, 1, 1) + ) + ) + + assert repr(model) == model_repr + + def test_analyze_batch_actions_result_extract_key_phrases(self, extract_key_phrases_result): + model = _models.AnalyzeBatchActionsResult( + document_results=[extract_key_phrases_result[0]], + is_error=False, + action_type=_models.AnalyzeBatchActionsType.EXTRACT_KEY_PHRASES, + completed_on=datetime.datetime(1, 1, 1) + ) + + model_repr = ( + "AnalyzeBatchActionsResult(document_results=[{}], is_error={}, action_type={}, completed_on={})".format( + extract_key_phrases_result[1], False, "extract_key_phrases", datetime.datetime(1, 1, 1) + ) + ) + + assert repr(model) == model_repr \ No newline at end of file diff --git a/shared_requirements.txt b/shared_requirements.txt index 67c224727868..216f23dd64b2 100644 --- a/shared_requirements.txt +++ b/shared_requirements.txt @@ -151,6 +151,7 @@ avro<2.0.0,>=1.10.0 #override azure-storage-file-datalake azure-storage-blob<13.0.0,>=12.7.0 #override azure-security-attestation msrest>=0.6.0 #override azure-security-attestation azure-core<2.0.0,>=1.8.2 +#override azure-data-tables msrest>=0.6.11 opencensus>=0.6.0 opencensus-ext-threading opencensus-ext-azure>=0.3.1 diff --git a/tools/azure-sdk-tools/pypi_tools/pypi.py b/tools/azure-sdk-tools/pypi_tools/pypi.py index 9eb28db8c0fe..59ab517167a7 100644 --- a/tools/azure-sdk-tools/pypi_tools/pypi.py +++ b/tools/azure-sdk-tools/pypi_tools/pypi.py @@ -1,4 +1,5 @@ from packaging.version import parse as Version +import sys import requests @@ -34,14 +35,35 @@ def project_release(self, package_name, version): response.raise_for_status() return response.json() - def get_ordered_versions(self, package_name): + def filter_packages_for_compatibility(self, package_name, version_set): + # only need the packaging.specifiers import if we're actually executing this filter. + from packaging.specifiers import SpecifierSet + + results = [] + + for version in version_set: + requires_python = self.project_release(package_name, version)["info"]["requires_python"] + if requires_python: + if Version('.'.join(map(str, sys.version_info[:3]))) in SpecifierSet(requires_python): + results.append(version) + else: + results.append(version) + + return results + + def get_ordered_versions(self, package_name, filter_by_compatibility = False): project = self.project(package_name) + versions = [ Version(package_version) for package_version in project["releases"].keys() ] versions.sort() + + if filter_by_compatibility: + return self.filter_packages_for_compatibility(package_name, versions) + return versions def get_relevant_versions(self, package_name): diff --git a/tools/azure-sdk-tools/setup.py b/tools/azure-sdk-tools/setup.py index 4e86afa3eadb..029526b18384 100644 --- a/tools/azure-sdk-tools/setup.py +++ b/tools/azure-sdk-tools/setup.py @@ -21,7 +21,8 @@ 'pyopenssl', 'azure-mgmt-resource', 'azure-mgmt-storage', - 'azure-mgmt-keyvault' + 'azure-mgmt-keyvault', + 'python-dotenv' ] setup(