osc-ingest-tools

python tools to assist with standardized data ingestion workflows

Installation, Usage, and Release Management

Install from PyPi

pip install osc-ingest-tools

Examples

>>> from osc_ingest_trino import *

>>> import pandas as pd

>>> data = [['tom', 10], ['nick', 15], ['juli', 14]]

>>> df = pd.DataFrame(data, columns = ['First Name', 'Age In Years']).convert_dtypes()

>>> df
  First Name  Age In Years
0        tom            10
1       nick            15
2       juli            14

>>> enforce_sql_column_names(df)
  first_name  age_in_years
0        tom            10
1       nick            15
2       juli            14

>>> enforce_sql_column_names(df, inplace=True)

>>> df
  first_name  age_in_years
0        tom            10
1       nick            15
2       juli            14

>>> df.info(verbose=True)
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 3 entries, 0 to 2
Data columns (total 2 columns):
 #   Column        Non-Null Count  Dtype
---  ------        --------------  -----
 0   first_name    3 non-null      string
 1   age_in_years  3 non-null      Int64
dtypes: Int64(1), string(1)
memory usage: 179.0 bytes

>>> p = create_table_schema_pairs(df)

>>> print(p)
    first_name varchar,
    age_in_years bigint

>>>

Adding custom type mappings to create_table_schema_pairs

>>> df = pd.DataFrame(data, columns = ['First Name', 'Age In Years'])

>>> enforce_sql_column_names(df, inplace=True)

>>> df.info(verbose=True)
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 3 entries, 0 to 2
Data columns (total 2 columns):
 #   Column        Non-Null Count  Dtype
---  ------        --------------  -----
 0   first_name    3 non-null      object
 1   age_in_years  3 non-null      int64
dtypes: int64(1), object(1)
memory usage: 176.0+ bytes

>>> p = create_table_schema_pairs(df, typemap={'object':'varchar'})

>>> print(p)
    first_name varchar,
    age_in_years bigint

>>>

Development

Patches may be contributed via pull requests to https://github.com/os-climate/osc-ingest-tools.

All changes must pass the automated test suite, along with various static checks.

Black code style and isort import ordering are enforced.

Enabling automatic formatting via pre-commit is recommended:

pip install black isort pre-commit
pre-commit install

To ensure compliance with static check tools, developers may wish to run;

pip install black isort
# auto-sort imports
isort .
# auto-format code
black .

Code can then be tested using tox:

=======
# run static checks and tests
tox
# run only tests
tox -e py3
# run only static checks
tox -e static
# run tests and produce a code coverage report
tox -e cov

Releasing

To release a new version of this library, authorized developers should;

• Prepare a signed release commit updating version in setup.py
• Tag the commit using Semantic Versioning prepended with "v"
• Push the tag

E.g.,

git commit -sm "Release v0.3.4"
git tag v0.3.4
git push --follow-tags

A Github workflow will then automatically release the version to PyPI.