The DKUtils python package was written to provide utility functions and classes that are used in DataKitchen recipes. It serves two main purposes.

1. Provide a Python API Client for interacting with the DataKitchen platform’s REST API (DataKitchenClient)
2. Provide utility classes and methods for interacting with tools commonly orchestrated in recipes in the DataKitchen platform (Alteryx, Jira, Gmail, etc.)

Building and testing this module is conveniently done using Make. Issue the make command to see a list of available targets (shown below for convenience). Note that any target can be suffixed with -ext to run that target inside a Docker container. This allows testing and development in a standard and portable environment. To develop inside a running docker container, use the bash-ext target. This will drop the user into a bash shell inside a running container.

Add '-ext' to any target to run it inside a docker container

Versioning:
    bump/major bump/minor bump/patch - bump the version

Utilities:
    bash         run bash - typically used in conjunction with -ext to enter a docker container
    scan_secrets scan source code for sensitive information

Linting:
    lint         run flake8 and yapf
    flake8       run flake8
    yapf         run yapf and correct issues in-place
    yapf-diff    run yapf and display diff between existing code and resolution if in-place is used

Testing:
    test         run all unit tests
    test_unit    run all unit tests
    clean_unit   remove files from last test run (e.g. report_dir, .coverage, etc.)
    tox          run unit tests in python 2 and 3
    clean_tox    clean tox files (e.g. .tox)

Documentation:
    docs         generate Sphinx documentation
    docs/html    generate Sphinx documentation
    docs/clean   remove generated Sphinx documentation

Build and Upload:
    build        generate distribution archives (i.e. *.tar.gz and *.whl)
    upload       upload distribution archives to PyPI
    clean_build  remove all the build files (i.e. build, dist, *.egg-info)

Cleanup:
    clean        run all the clean targets in one go
    clean_pyc    remove all *.pyc files

Pre-commit is also included to validate and flag commits that contain code that does not pass Flake8 and YAPF. To use, first install the python package pip install pre-commit and then run pre-commit install. All future commits will run these tools and deny commits that don't pass. When running YAPF, pre-commit will make in-place corrections to your code. Therefore, if it fails the YAPF validation on the first commit attempt, simply review the changed files, add, and commit again to resolve.