diff --git a/appengine/search/snippets/snippets.py b/appengine/search/snippets/snippets.py new file mode 100644 index 000000000000..ceddb1ea568d --- /dev/null +++ b/appengine/search/snippets/snippets.py @@ -0,0 +1,287 @@ +# Copyright 2016 Google Inc. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from datetime import datetime + +from google.appengine.api import search + + +def simple_search(index): + index.search('rose water') + + +def search_date(index): + index.search('1776-07-04') + + +def search_terms(index): + # search for documents with pianos that cost less than $5000 + index.search("product = piano AND price < 5000") + + +def create_document(): + document = search.Document( + # Setting the doc_id is optional. If omitted, the search service will + # create an identifier. + doc_id='PA6-5000', + fields=[ + search.TextField(name='customer', value='Joe Jackson'), + search.HtmlField( + name='comment', value='this is marked up text'), + search.NumberField(name='number_of_visits', value=7), + search.DateField(name='last_visit', value=datetime.now()), + search.DateField( + name='birthday', value=datetime(year=1960, month=6, day=19)), + search.GeoField( + name='home_location', value=search.GeoPoint(37.619, -122.37)) + ]) + return document + + +def add_document_to_index(document): + index = search.Index('products') + index.put(document) + + +def add_document_and_get_doc_id(documents): + index = search.Index('products') + results = index.put(documents) + document_ids = [document.id for document in results] + return document_ids + + +def get_document_by_id(): + index = search.Index('products') + + # Get a single document by ID. + document = index.get("AZ125") + + # Get a range of documents starting with a given ID. + documents = index.get_range(start_id="AZ125", limit=100) + + return document, documents + + +def query_index(): + index = search.Index('products') + query_string = 'product: piano AND price < 5000' + + results = index.search(query_string) + + for scored_document in results: + print(scored_document) + + +def delete_all_in_index(index): + # index.get_range by returns up to 100 documents at a time, so we must + # loop until we've deleted all items. + while True: + # Use ids_only to get the list of document IDs in the index without + # the overhead of getting the entire document. + document_ids = [ + document.doc_id + for document + in index.get_range(ids_only=True)] + + # If no IDs were returned, we've deleted everything. + if not document_ids: + break + + # Delete the documents for the given IDs + index.delete(document_ids) + + +def async_query(index): + futures = [index.search_async('foo'), index.search_async('bar')] + results = [future.get_result() for future in futures] + return results + + +def query_options(): + index = search.Index('products') + query_string = "product: piano AND price < 5000" + + # Create sort options to sory on price and brand. + sort_price = search.SortExpression( + expression='price', + direction=search.SortExpression.DESCENDING, + default_value=0) + sort_brand = search.SortExpression( + expression='brand', + direction=search.SortExpression.DESCENDING, + default_value="") + sort_options = search.SortOptions(expressions=[sort_price, sort_brand]) + + # Create field expressions to add new fields to the scored documents. + price_per_note_expression = search.FieldExpression( + name='price_per_note', expression='price/88') + ivory_expression = search.FieldExpression( + name='ivory', expression='snippet("ivory", summary, 120)') + + # Create query options using the sort options and expressions created + # above. + query_options = search.QueryOptions( + limit=25, + returned_fields=['model', 'price', 'description'], + returned_expressions=[price_per_note_expression, ivory_expression], + sort_options=sort_options) + + # Build the Query and run the search + query = search.Query(query_string=query_string, options=query_options) + results = index.search(query) + for scored_document in results: + print(scored_document) + + +def query_results(index, query_string): + result = index.search(query_string) + total_matches = result.number_found + list_of_docs = result.results + number_of_docs_returned = len(list_of_docs) + return total_matches, list_of_docs, number_of_docs_returned + + +def query_offset(index, query_string): + offset = 0 + + while True: + # Build the query using the current offset. + options = search.QueryOptions(offset=offset) + query = search.Query(query_string=query_string, options=options) + + # Get the results + results = index.search(query) + + number_retrieved = len(results.results) + if number_retrieved == 0: + break + + # Add the number of documents found to the offset, so that the next + # iteration will grab the next page of documents. + offset += number_retrieved + + # Process the matched documents + for document in results: + print(document) + + +def query_cursor(index, query_string): + cursor = search.Cursor() + + while cursor: + # Build the query using the cursor. + options = search.QueryOptions(cursor=cursor) + query = search.Query(query_string=query_string, options=options) + + # Get the results and the next cursor + results = index.search(query) + cursor = results.cursor + + for document in results: + print(document) + + +def query_per_document_cursor(index, query_string): + cursor = search.Cursor(per_result=True) + + # Build the query using the cursor. + options = search.QueryOptions(cursor=cursor) + query = search.Query(query_string=query_string, options=options) + + # Get the results. + results = index.search(query) + + document_cursor = None + for document in results: + # discover some document of interest and grab its cursor, for this + # sample we'll just use the first document. + document_cursor = document.cursor + break + + # Start the next search from the document of interest. + if document_cursor is None: + return + + options = search.QueryOptions(cursor=document_cursor) + query = search.Query(query_string=query_string, options=options) + results = index.search(query) + + for document in results: + print(document) + + +def saving_and_restoring_cursor(cursor): + # Convert the cursor to a web-safe string. + cursor_string = cursor.web_safe_string + # Restore the cursor from a web-safe string. + cursor = search.Cursor(web_safe_string=cursor_string) + + +def add_faceted_document(index): + document = search.Document( + doc_id='doc1', + fields=[ + search.AtomField(name='name', value='x86')], + facets=[ + search.AtomFacet(name='type', value='computer'), + search.NumberFacet(name='ram_size_gb', value=8)]) + + index.put(document) + + +def facet_discovery(index): + # Create the query and enable facet discovery. + query = search.Query('name:x86', enable_facet_discovery=True) + results = index.search(query) + + for facet in results.facets: + print('facet {}.'.format(facet.name)) + for value in facet.values: + print('{}: count={}, refinement_token={}'.format( + value.label, value.count, value.refinement_token)) + + +def facet_by_name(index): + # Create the query and specify to only return the "type" and "ram_size_gb" + # facets. + query = search.Query('name:x86', return_facets=['type', 'ram_size_gb']) + results = index.search(query) + + for facet in results.facets: + print('facet {}'.format(facet.name)) + for value in facet.values: + print('{}: count={}, refinement_token={}'.format( + value.label, value.count, value.refinement_token)) + + +def facet_by_name_and_value(index): + # Create the query and specify to return the "type" facet with values + # "computer" and "printer" and the "ram_size_gb" facet with value in the + # ranges [0,4), [4, 8), and [8, max]. + query = search.Query( + 'name:x86', + return_facets=[ + search.FacetRequest('type', values=['computer', 'printer']), + search.FacetRequest('ram_size_gb', ranges=[ + search.FacetRange(end=4), + search.FacetRange(start=4, end=8), + search.FacetRange(start=8)]) + ]) + + results = index.search(query) + for facet in results.facets: + print('facet {}'.format(facet.name)) + for value in facet.values: + print('{}: count={}, refinement_token={}'.format( + value.label, value.count, value.refinement_token)) diff --git a/appengine/search/snippets/snippets_test.py b/appengine/search/snippets/snippets_test.py new file mode 100644 index 000000000000..e4e002118803 --- /dev/null +++ b/appengine/search/snippets/snippets_test.py @@ -0,0 +1,139 @@ +# Copyright 2016 Google Inc. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + + +from google.appengine.api import search +import pytest +import snippets + + +@pytest.fixture +def search_stub(testbed): + testbed.init_search_stub() + + +@pytest.fixture +def index(search_stub): + return search.Index('products') + + +@pytest.fixture +def document(): + return search.Document( + doc_id='doc1', + fields=[ + search.TextField(name='title', value='Meep: A biography')]) + + +def test_simple_search(index): + snippets.simple_search(index) + + +def test_search_date(index): + snippets.search_date(index) + + +def test_search_terms(index): + snippets.search_terms(index) + + +def test_create_document(): + assert snippets.create_document() + + +def test_add_document_to_index(index, document): + snippets.add_document_to_index(document) + assert index.get(document.doc_id) + + +def test_add_document_and_get_doc_id(index, document): + ids = snippets.add_document_and_get_doc_id([document]) + assert ids == [document.doc_id] + + +def test_get_document_by_id(index): + index.put(search.Document(doc_id='AZ124')) + index.put(search.Document(doc_id='AZ125')) + index.put(search.Document(doc_id='AZ126')) + + doc, docs = snippets.get_document_by_id() + + assert doc.doc_id == 'AZ125' + assert [x.doc_id for x in docs] == ['AZ125', 'AZ126'] + + +def test_query_index(index): + snippets.query_index() + + +def test_delete_all_in_index(index, document): + index.put(document) + snippets.delete_all_in_index(index) + assert not index.get(document.doc_id) + + +def test_async_query(index): + snippets.async_query(index) + + +def test_query_options(index): + snippets.query_options() + + +def test_query_results(index, document): + index.put(document) + total_matches, list_of_docs, number_of_docs_returned = ( + snippets.query_results(index, 'meep')) + + assert total_matches == 1 + assert list_of_docs + assert number_of_docs_returned == 1 + + +def test_query_offset(index, document): + index.put(document) + snippets.query_offset(index, 'meep') + + +def test_query_cursor(index, document): + index.put(document) + snippets.query_cursor(index, 'meep') + + +def test_query_per_document_cursor(index, document): + index.put(document) + snippets.query_per_document_cursor(index, 'meep') + + +def test_saving_and_restoring_cursor(index): + snippets.saving_and_restoring_cursor(search.Cursor()) + + +def test_add_faceted_document(index): + snippets.add_faceted_document(index) + + +def test_facet_discovery(index): + snippets.add_faceted_document(index) + snippets.facet_discovery(index) + + +def test_facet_by_name(index): + snippets.add_faceted_document(index) + snippets.facet_by_name(index) + + +def test_facet_by_name_and_value(index): + snippets.add_faceted_document(index) + snippets.facet_by_name_and_value(index)