Development Guidelines¶

Creating a Development Environment¶

First, you’ll need to clone Zipline by running:

$ git clone git@github.com:your-github-username/zipline.git

Then check out to a new branch where you can make your changes:

$ git checkout -b some-short-descriptive-name

If you don’t already have them, you’ll need some C library dependencies. You can follow the install guide to get the appropriate dependencies.

The following section assumes you already have virtualenvwrapper and pip installed on your system. Suggested installation of Python library dependencies used for development:

$ mkvirtualenv zipline
$ ./etc/ordered_pip.sh ./etc/requirements.txt
$ pip install -r ./etc/requirements_dev.txt
$ pip install -r ./etc/requirements_blaze.txt

Finally, you can build the C extensions by running:

$ python setup.py build_ext --inplace

To finish, make sure tests pass.

If you get an error running nosetests after setting up a fresh virtualenv, please try running

# where zipline is the name of your virtualenv
$ deactivate zipline
$ workon zipline

Development with Docker¶

If you want to work with zipline using a Docker container, you’ll need to build the Dockerfile in the Zipline root directory, and then build Dockerfile-dev. Instructions for building both containers can be found in Dockerfile and Dockerfile-dev, respectively.

Style Guide & Running Tests¶

We use flake8 for checking style requirements and nosetests to run Zipline tests. Our continuous integration tools will run these commands.

Before submitting patches or pull requests, please ensure that your changes pass when running:

$ flake8 zipline tests

In order to run tests locally, you’ll need TA-lib, which you can install on Linux by running:

$ wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz
$ tar -xvzf ta-lib-0.4.0-src.tar.gz
$ cd ta-lib/
$ ./configure --prefix=/usr
$ make
$ sudo make install

And for TA-lib on OS X you can just run:

$ brew install ta-lib

Then run pip install TA-lib:

$ pip install -r ./etc/requirements_talib.txt

You should now be free to run tests:

$ nosetests

Continuous Integration¶

We use Travis CI for Linux-64 bit builds and AppVeyor for Windows-64 bit builds.

Packaging¶

To learn about how we build Zipline conda packages, you can read this section in our release process notes.

Contributing to the Docs¶

If you’d like to contribute to the documentation on zipline.io, you can navigate to docs/source/ where each reStructuredText (.rst) file is a separate section there. To add a section, create a new file called some-descriptive-name.rst and add some-descriptive-name to appendix.rst. To edit a section, simply open up one of the existing files, make your changes, and save them.

We use Sphinx to generate documentation for Zipline, which you will need to install by running:

$ pip install -r ./etc/requirements_docs.txt

To build and view the docs locally, run:

# assuming you're in the Zipline root directory
$ cd docs
$ make html
$ {BROWSER} build/html/index.html

Commit messages¶

Standard prefixes to start a commit message:

BLD: change related to building Zipline
BUG: bug fix
DEP: deprecate something, or remove a deprecated object
DEV: development tool or utility
DOC: documentation
ENH: enhancement
MAINT: maintenance commit (refactoring, typos, etc)
REV: revert an earlier commit
STY: style fix (whitespace, PEP8, flake8, etc)
TST: addition or modification of tests
REL: related to releasing Zipline
PERF: performance enhancements

Some commit style guidelines:

Commit lines should be no longer than 72 characters. The first line of the commit should include one of the above prefixes. There should be an empty line between the commit subject and the body of the commit. In general, the message should be in the imperative tense. Best practice is to include not only what the change is, but why the change was made.

Example:

MAINT: Remove unused calculations of max_leverage, et al.

In the performance period the max_leverage, max_capital_used,
cumulative_capital_used were calculated but not used.

At least one of those calculations, max_leverage, was causing a
divide by zero error.

Instead of papering over that error, the entire calculation was
a bit suspect so removing, with possibility of adding it back in
later with handling the case (or raising appropriate errors) when
the algorithm has little cash on hand.

Formatting Docstrings¶

When adding or editing docstrings for classes, functions, etc, we use numpy as the canonical reference.