Contributing to Boto

Setting Up a Development Environment

While not strictly required, it is highly recommended to do development in a virtualenv. You can install virtualenv using pip:

$ pip install virtualenv

Once the package is installed, you’ll have a virtualenv command you can use to create a virtual environment:

$ virtualenv venv

You can then activate the virtualenv:

$ . venv/bin/activate

Note

You may also want to check out virtualenvwrapper, which is a set of extensions to virtualenv that makes it easy to manage multiple virtual environments.

A requirements.txt is included with boto which contains all the additional packages needed for boto development. You can install these packages by running:

$ pip install -r requirements.txt

Running the Tests

All of the tests for boto are under the tests/ directory. The tests for boto have been split into two main categories, unit and integration tests:

  • unit - These are tests that do not talk to any AWS services. Anyone should be able to run these tests without have any credentials configured. These are the types of tests that could be run in something like a public CI server. These tests tend to be fast.
  • integration - These are tests that will talk to AWS services, and will typically require a boto config file with valid credentials. Due to the nature of these tests, they tend to take a while to run. Also keep in mind anyone who runs these tests will incur any usage fees associated with the various AWS services.

To run all the unit tests, cd to the tests/ directory and run:

$ python test.py unit

You should see output like this:

$ python test.py unit
................................
----------------------------------------------------------------------
Ran 32 tests in 0.075s

OK

To run the integration tests, run:

$ python test.py integration

Note that running the integration tests may take a while.

Various integration tests have been tagged with service names to allow you to easily run tests by service type. For example, to run the ec2 integration tests you can run:

$ python test.py -t ec2

You can specify the -t argument multiple times. For example, to run the s3 and ec2 tests you can run:

$ python test.py -t ec2 -t s3

Warning

In the examples above no top level directory was specified. By default, nose will assume the current working directory, so the above command is equivalent to:

$ python test.py -t ec2 -t s3 .

Be sure that you are in the tests/ directory when running the tests, or explicitly specify the top level directory. For example, if you in the root directory of the boto repo, you could run the ec2 and s3 tests by running:

$ python tests/test.py -t ec2 -t s3 tests/

You can use nose’s collect plugin to see what tests are associated with each service tag:

$ python tests.py -t s3 -t ec2 --with-id --collect -v

Testing Details

The tests/test.py script is a lightweight wrapper around nose. In general, you should be able to run nosetests directly instead of tests/test.py. The tests/unit and tests/integration args in the commands above were referring to directories. The command line arguments are forwarded to nose when you use tests/test.py. For example, you can run:

$ python tests/test.py -x -vv tests/unit/cloudformation

And the -x -vv tests/unit/cloudformation are forwarded to nose. See the nose docs for the supported command line options, or run nosetests --help.

The only thing that tests/test.py does before invoking nose is to inject an argument that specifies that any testcase tagged with “notdefault” should not be run. A testcase may be tagged with “notdefault” if the test author does not want everyone to run the tests. In general, there shouldn’t be many of these tests, but some reasons a test may be tagged “notdefault” include:

  • An integration test that requires specific credentials.
  • An interactive test (the S3 MFA tests require you to type in the S/N and code).

Tagging is done using nose’s tagging plugin. To summarize, you can tag a specific testcase by setting an attribute on the object. Nose provides an attr decorator for convenience:

from nose.plugins.attrib import attr

@attr('notdefault')
def test_s3_mfs():
    pass

You can then run these tests be specifying:

nosetests -a 'notdefault'

Or you can exclude any tests tagged with ‘notdefault’ by running:

nosetests -a '!notdefault'

Conceptually, tests/test.py is injecting the “-a !notdefault” arg into nosetests.

Testing Supported Python Versions

Boto supports python 2.6 and 2.7. An easy way to verify functionality across multiple python versions is to use tox. A tox.ini file is included with boto. You can run tox with no args and it will automatically test all supported python versions:

$ tox
GLOB sdist-make: boto/setup.py
py26 sdist-reinst: boto/.tox/dist/boto-2.4.1.zip
py26 runtests: commands[0]
................................
----------------------------------------------------------------------
Ran 32 tests in 0.089s

OK
py27 sdist-reinst: boto/.tox/dist/boto-2.4.1.zip
py27 runtests: commands[0]
................................
----------------------------------------------------------------------
Ran 32 tests in 0.087s

OK
____ summary ____
  py26: commands succeeded
  py27: commands succeeded
  congratulations :)

Writing Documentation

The boto docs use sphinx to generate documentation. All of the docs are located in the docs/ directory. To generate the html documentation, cd into the docs directory and run make html:

$ cd docs
$ make html

The generated documentation will be in the docs/build/html directory. The source for the documentation is located in docs/source directory, and uses restructured text for the markup language.