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CONTRIBUTING.rst

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Contributing

  1. Please sign one of the contributor license agreements below.
  2. Fork the repo, develop and test your code changes, add docs.
  3. Make sure that your commit messages clearly describe the changes.
  4. Send a pull request.

Here are some guidelines for hacking on gcloud-python.

Using a Development Checkout

You'll have to create a development environment to hack on gcloud-python, using a Git checkout:

  • While logged into your GitHub account, navigate to the gcloud-python repo on GitHub.

    https://github.com/GoogleCloudPlatform/gcloud-python

  • Fork and clone the gcloud-python repository to your GitHub account by clicking the "Fork" button.

  • Clone your fork of gcloud-python from your GitHub account to your local computer, substituting your account username and specifying the destination as "hack-on-gcloud". E.g.:

    $ cd ~
$ git clone git@github.com:USERNAME/gcloud-python.git hack-on-gcloud
$ cd hack-on-gcloud
# Configure remotes such that you can pull changes from the gcloud-python
# repository into your local repository.
$ git remote add upstream https://github.com:GoogleCloudPlatform/gcloud-python
# fetch and merge changes from upstream into master
$ git fetch upstream
$ git merge upstream/master

Now your local repo is set up such that you will push changes to your GitHub repo, from which you can submit a pull request.

  • Create a virtualenv in which to install gcloud-python:

    $ cd ~/hack-on-gcloud
$ virtualenv -ppython2.7 env

    Note that very old versions of virtualenv (virtualenv versions below, say, 1.10 or thereabouts) require you to pass a --no-site-packages flag to get a completely isolated environment.

    You can choose which Python version you want to use by passing a -p flag to virtualenv. For example, virtualenv -ppython2.7 chooses the Python 2.7 interpreter to be installed.

    From here on in within these instructions, the ~/hack-on-gcloud/env virtual environment you created above will be referred to as $VENV. To use the instructions in the steps that follow literally, use the export VENV=~/hack-on-gcloud/env command.

  • Install gcloud-python from the checkout into the virtualenv using setup.py develop. Running setup.py develop must be done while the current working directory is the gcloud-python checkout directory:

    $ cd ~/hack-on-gcloud
$ $VENV/bin/python setup.py develop

I'm getting weird errors... Can you help?

Chances are you have some dependency problems... If you're on Ubuntu, try installing the pre-compiled packages:

$ sudo apt-get install python-crypto python-openssl libffi-dev

or try installing the development packages (that have the header files included) and then pip install the dependencies again:

$ sudo apt-get install python-dev libssl-dev libffi-dev
$ pip install gcloud

Adding Features

In order to add a feature to gcloud-python:

  • The feature must be documented in both the API and narrative documentation (in docs/).
  • The feature must work fully on the following CPython versions: 2.6, and 2.7 on both UNIX and Windows.
  • The feature must not add unnecessary dependencies (where "unnecessary" is of course subjective, but new dependencies should be discussed).

Coding Style

  • PEP8 compliance, with exceptions defined in tox.ini. If you have tox installed, you can test that you have not introduced any non-compliant code via:

    $ tox -e lint

  • In order to make tox -e lint run faster, you can set some environment variables:

    export GCLOUD_REMOTE_FOR_LINT="upstream"
export GCLOUD_BRANCH_FOR_LINT="master"

    By doing this, you are specifying the location of the most up-to-date version of gcloud-python. The the suggested remote name upstream should point to the official GoogleCloudPlatform checkout and the the branch should be the main branch on that remote (master).

Exceptions to PEP8:

  • Many unit tests use a helper method, _callFUT ("FUT" is short for "Function-Under-Test"), which is PEP8-incompliant, but more readable. Some also use a local variable, MUT (short for "Module-Under-Test").

Running Tests

  • To run all tests for gcloud-python on a single Python version, run nosetests from your development virtualenv (See Using a Development Checkout above).

  • To run the full set of gcloud-python tests on all platforms, install tox (http://codespeak.net/~hpk/tox/) into a system Python. The tox console script will be installed into the scripts location for that Python. While cd'ed to the gcloud-python checkout root directory (it contains tox.ini), invoke the tox console script. This will read the tox.ini file and execute the tests on multiple Python versions and platforms; while it runs, it creates a virtualenv for each version/platform combination. For example:

    $ sudo /usr/bin/pip install tox
$ cd ~/hack-on-gcloud/
$ /usr/bin/tox

Running Regression Tests

  • To run regression tests you can execute:

    $ tox -e regression

    or run only regression tests for a particular package via:

    $ python regression/run_regression.py --package {package}

    This alone will not run the tests. You'll need to change some local auth settings and change some configuration in your project to run all the tests.

  • Regression tests will be run against an actual project and so you'll need to provide some environment variables to facilitate authentication to your project:

    • GCLOUD_TESTS_PROJECT_ID: Developers Console project ID (e.g. bamboo-shift-455).
    • GCLOUD_TESTS_DATASET_ID: The name of the dataset your tests connect to. This is typically the same as GCLOUD_TESTS_PROJECT_ID.
    • GOOGLE_APPLICATION_CREDENTIALS: The path to a JSON key file; see regression/app_credentials.json.sample as an example. Such a file can be downloaded directly from the developer's console by clicking "Generate new JSON key". See private key docs for more details.

  • Examples of these can be found in regression/local_test_setup.sample. We recommend copying this to regression/local_test_setup, editing the values and sourcing them into your environment:

    $ source regression/local_test_setup

  • For datastore tests, you'll need to create composite indexes with the gcloud command line tool:

    # Install the app (App Engine Command Line Interface) component.
$ gcloud components update app

# See https://cloud.google.com/sdk/crypto for details on PyOpenSSL and
# http://stackoverflow.com/a/25067729/1068170 for why we must persist.
$ export CLOUDSDK_PYTHON_SITEPACKAGES=1

# Authenticate the gcloud tool with your account.
$ SERVICE_ACCOUNT_EMAIL="some-account@developer.gserviceaccount.com"
$ P12_CREDENTIALS_FILE="path/to/keyfile.p12"
$ gcloud auth activate-service-account $SERVICE_ACCOUNT_EMAIL \
> --key-file=$P12_CREDENTIALS_FILE

# Create the indexes
$ gcloud preview datastore create-indexes regression/data/ \
> --project=$GCLOUD_TESTS_DATASET_ID

# Restore your environment to its previous state.
$ unset CLOUDSDK_PYTHON_SITEPACKAGES

  • For datastore query tests, you'll need stored data in your dataset. To populate this data, run:

    $ python regression/populate_datastore.py

  • If you make a mistake during development (i.e. a failing test that prevents clean-up) you can clear all regression data from your datastore instance via:

    $ python regression/clear_datastore.py

Test Coverage

  • The codebase must have 100% test statement coverage after each commit. You can test coverage via tox -e coverage, or alternately by installing nose and coverage into your virtualenv, and running setup.py nosetests --with-coverage. If you have tox installed:

    $ tox -e cover

Documentation Coverage and Building HTML Documentation

If you fix a bug, and the bug requires an API or behavior modification, all documentation in this package which references that API or behavior must be changed to reflect the bug fix, ideally in the same commit that fixes the bug or adds the feature.

To build and review docs (where $VENV refers to the virtualenv you're using to develop gcloud-python):

  1. After following the steps above in "Using a Development Checkout", install Sphinx and all development requirements in your virtualenv:

    $ cd ~/hack-on-gcloud
$ $VENV/bin/pip install Sphinx

  2. Change into the docs directory within your gcloud-python checkout and execute the make command with some flags:

    $ cd ~/hack-on-gcloud/gcloud-python/docs
$ make clean html SPHINXBUILD=$VENV/bin/sphinx-build

    The SPHINXBUILD=... argument tells Sphinx to use the virtualenv Python, which will have both Sphinx and gcloud-python (for API documentation generation) installed.

  3. Open the docs/_build/html/index.html file to see the resulting HTML rendering.

As an alternative to 1. and 2. above, if you have tox installed, you can build the docs via:

$ tox -e docs

Travis Configuration and Build Optimizations

All build scripts in the .travis.yml configuration file which have Python dependencies are specified in the tox.ini configuration. They are executed in the Travis build via tox -e {ENV} where {ENV} is the environment being tested.

By enumerating all Python dependencies in the tox configuration, we can use our custom gcloud-python-wheels wheelhouse to speed up builds. This project builds and stores pre-built Python wheels for every Python dependency our library and tests have.

If new tox environments are added to be run in a Travis build, they should either be:

  • listed in [tox].envlist as a default environment
  • added to the list in the Travis environment variable EXTRA_TOX_ENVS. This value is unencrypted in gcloud-python-wheels to make ongoing maintenance easier.

Shared Code with External Projects

In order to enable high-quality HTTP transfer of large data (for Cloud Storage), we have temporarily included some code from the apitools library.

We have chosen to partially include it, rather than include it as a dependency because

  • The library is not yet included on PyPI.
  • The library's protorpc dependency is not Python 3 friendly, so would block us from Python 3 support if fully included.

The included code in lives in the _gcloud_vendor directory. It is a snapshot of the e5a5c36e24926310712d20b93b4cdd02424a81f5 commit from the main project imported in 4c27079cf6d7f9814b36cfd16f3402455f768094. In addition to the raw import, we have customized (e.g. rewriting imports) for our library:

  • 334961054d875641d150eec4d6938f6f824ea655
  • 565750ee7d19742b520dd62e2a4ff38325987284
  • 67b06019549a4db8168ff4c5171c9d701ac94a15
  • f4a53ee64fad5f3d7f29a0341e6a72a060edfcc2

Supported Python Versions

We support:

We plan to support:

Supported versions can be found in our tox.ini config.

We explicitly decided not to support Python 2.5 due to decreased usage and lack of continuous integration support.

We also explicitly decided to support Python 3 beginning with version 3.3. Reasons for this include:

  • Encouraging use of newest versions of Python 3
  • Taking the lead of prominent open-source projects
  • Unicode literal support which allows for a cleaner codebase that works in both Python 2 and Python 3

Contributor License Agreements

Before we can accept your pull requests you'll need to sign a Contributor License Agreement (CLA):

  • If you are an individual writing original source code and you own the intellectual property, then you'll need to sign an individual CLA.
  • If you work for a company that wants to allow you to contribute your work, then you'll need to sign a corporate CLA.

You can sign these electronically (just scroll to the bottom). After that, we'll be able to accept your pull requests.