- Please sign one of the contributor license agreements below.
- Fork the repo, develop and test your code changes, add docs.
- Make sure that your commit messages clearly describe the changes.
- Send a pull request.
Here are some guidelines for hacking on gcloud-python.
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.
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 tovirtualenv
. 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$VENV
. To use the instructions in the steps that follow literally, use theexport VENV=~/hack-on-gcloud/env
command.Install gcloud-python from the checkout into the virtualenv using
setup.py develop
. Runningsetup.py develop
must be done while the current working directory is thegcloud-python
checkout directory:$ cd ~/hack-on-gcloud $ $VENV/bin/python setup.py develop
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
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).
PEP8 compliance, with exceptions defined in
tox.ini
. If you havetox
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 nameupstream
should point to the officialGoogleCloudPlatform
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").
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. Thetox
console script will be installed into the scripts location for that Python. Whilecd
'ed to the gcloud-python checkout root directory (it containstox.ini
), invoke thetox
console script. This will read thetox.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
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_DATASET_ID
: The name of the dataset your tests connect to.GCLOUD_TESTS_CLIENT_EMAIL
: The email for the service account you're authenticating withGCLOUD_TESTS_KEY_FILE
: The path to an encrypted key file. See private key docs for explanation on how to get a private key.
Examples of these can be found in
regression/local_test_setup.sample
. We recommend copying this toregression/local_test_setup
, editing the values and sourcing them into your environment:$ source regression/local_test_setup
The
GCLOUD_TESTS_KEY_FILE
value should point to a valid path (relative or absolute) on your system where the key file for your service account can be found.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. $ gcloud auth activate-service-account $GCLOUD_TESTS_CLIENT_EMAIL \ > --key-file=$GCLOUD_TESTS_KEY_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
The codebase must have 100% test statement coverage after each commit. You can test coverage via
tox -e coverage
, or alternately by installingnose
andcoverage
into your virtualenv, and runningsetup.py nosetests --with-coverage
. If you havetox
installed:$ tox -e cover
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):
After following the steps above in "Using a Development Checkout", install Sphinx and all development requirements in your virtualenv:
$ cd ~/hack-on-gcloud $ $VENV/bin/pip install Sphinx
Change into the
docs
directory within your gcloud-python checkout and execute themake
command with some flags:$ 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.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
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 ingcloud-python-wheels
to make ongoing maintenance easier.
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.