expan 0.3.3

Experiment Analysis Library

ExpAn: Experiment Analysis

A/B tests (a.k.a. Randomized Controlled Trials or Experiments) have been widely applied in different industries to optimize business processes and user experience. ExpAn (Experiment Analysis) is a Python library developed for the statistical analysis of such experiments and to standardise the data structures used.

The data structures and functionality of ExpAn are generic such that they can be used by both data scientists optimizing a user interface and biologists running wet-lab experiments. The library is also standalone and can be imported and used from within other projects and from the command line.

Major statistical functionalities include:

• feature check

• delta

• subgroup analysis

• trend

Table of Contents

• Quick start

  • Install

  • Some mock-up data

• Further documentation

• How to contribute

  • Style guide

  • Branching / Release

  • Versioning

  • Bumping Version

  • Travis CI and PyPI deployment

  • TODO

• License

Quick start

Install

To install you can simply run (pip >= 8.1.1 and setuptools >= 21.0.0 are required):

pip install expan

An alternative way to install is it to clone the repo and run:

python2 setup.py build
python2 setup.py install

And to test run:

python2 setup.py test

Some mock-up data

from expan.core.experiment import Experiment
from tests.tests_core.test_data import generate_random_data

exp = Experiment('B', *generate_random_data())
exp.delta()

Further documentation

ExpAn Description - details about the concept of the library and data structures.

ExpAn Introduction - a full jupyter (iPython) notebook. You can view it as slides with jupyter:

sh serve_intro_slides

Alternatives

There may be alternative libraries providing similar functionality, and these should be collected here. Very incomplete list so far…

• abba (https://github.com/thumbtack/abba)

Not an alternative, the Python part of this is simply a collection of some functions to handle binomial distributions.

How to contribute

Style guide

We follow PEP8 standards with the following exceptions:

• Use tabs instead of spaces - this allows all individuals to have visual depth of indentation they prefer, without changing the source code at all, and it is simply smaller

Branching / Release

We currently use the gitflow workflow. Feature branches are created from and merged back to the dev branch, and the master branch stores snapshots/releases of the dev branch.

See also the much simpler github flow here

Versioning

For the sake of reproducibility, always be sure to work with a release when doing the analysis!

We use semantic versioning (http://semver.org), and the current version of ExpAn is: v0.3.3.

The version is maintained in setup.cfg, and propagated from there to various files by the bumpversion program. The most important propagation destination is in version.py where it is held in the string __version__ with the form:

'{major}.{minor}.{patch}'

The __version__ string and a version() function is imported by core.__init__ and so is accessible to imported functions in expan.

The version(format_str) function generates version strings of any form. It can use git’s commit count and revision number to generate a long version string which may be useful for pip versioning? Examples: NB: caution using this… it won’t work if not in the original git repository.

>>> import core.binning
>>> core.version()
'v0.3.3'
>>> core.version('{major}.{minor}..{commits}')
'0.0..176'
>>> core.version('{commit}')
'a24730a42a4b5ae01bbdb05f6556dedd453c1767'

See: StackExchange 151558

Bumping Version

Can use bumpversion to maintain the __version__ in version.py:

$ bumpversion patch

or

$ bumpversion minor

This will update the version number, create a new tag in git, and commit the changes with a standard commit message.

When you have done this, you must push the commit and new tag to the repository with:

$ git push --tags

Travis CI and PyPI deployment

We use Travis CI for testing builds and deploying our PyPI package.

A build and test is triggered when a commit is pushed to either

• dev,

• master

• or a pull request branch to dev or master.

If you want to deploy to PyPI, then follow these steps:

• assuming you have a dev branch that is up to date, create a pull request from dev to master (a travis job will be started for the pull request)

• once the pull request is approved, merge it (another travis job will be started because a push to master happened)

• checkout master

• push tags to master (a third travis job will be started, but this time it will also push to PyPI because tags were pushed)

If you wish to skip triggering a CI task (for example when you change documentation), please include [ci skip] in your commit message.

TODO

• parallelization, eg. for the bootstrapping code

• Bayesian updating/early stopping

• multiple comparison correction, definitely relevant for delta and SGA, have to think about how to correct for time dependency in the trend analysis

• implement from_json and to_json methods in the Binning class, in order to convert the Python object to a json format for persisting in the Results metadata and reloading from a script

License

The MIT License (MIT)

Copyright © [2016] Zalando SE, https://tech.zalando.com

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

History

0.2.5

• Inclusion of cli in install

• many other minor changes since open-sourcing…

0.2.0 (2016-05-03)

• First opensource release to GitHub

0.1.0 (2016-04-29)

History

0.2.5

• Inclusion of cli in install

• many other minor changes since open-sourcing…

0.2.0 (2016-05-03)

• First opensource release to GitHub

0.1.0 (2016-04-29)

• Relatively stable version used by Zalando internally, prior to opensource release