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- fix broken docs links
- fix Markdown violations:
  - MD033/no-inline-html: Inline HTML [Element: br]
  - MD040/fenced-code-language: Fenced code blocks should have a language specified
  - MD014/commands-show-output: Dollar signs used before commands without showing output
  - substitute static badges with dynamic ones

---------

Co-authored-by: Alessandro D'Armiento <[email protected]>
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@spiaz @adarmiento
spiaz and adarmiento authored Jun 14, 2024
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[comment]: <> (Modify also docs/installation.rst if change the README.md)
[comment]: <> (Modify also LICENSE.rst if change the README.md)

PyBandits
=========

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![alt text](https://img.shields.io/badge/build-passing-brightgreen)
![alt text](https://img.shields.io/badge/docs-passing-brightgreen)
![alt text](https://img.shields.io/badge/coverage-82%25-green)
![alt text](https://img.shields.io/badge/version-0.0.2-blue)
![GitHub Actions Workflow Status](https://img.shields.io/github/actions/workflow/status/PlaytikaOSS/pybandits/continuous_integration.yml)
![PyPI - Version](https://img.shields.io/pypi/v/pybandits)
![PyPI - Python Version](https://img.shields.io/pypi/pyversions/pybandits)
![alt text](https://img.shields.io/badge/license-MIT-blue)

**PyBandits** is a ``Python`` library for Multi-Armed Bandit. It provides an implementation of stochastic Multi-Armed Bandit (sMAB) and contextual Multi-Armed Bandit (cMAB) based on Thompson Sampling.

<br/>

For the sMAB, we implemented a Bernoulli multi-armed bandit based on Thompson Sampling algorithm [Agrawal and Goyal, 2012](http://proceedings.mlr.press/v23/agrawal12/agrawal12.pdf). If context information is available we provide a generalisation of Thompson Sampling for cMAB [Agrawal and Goyal, 2014](https://arxiv.org/pdf/1209.3352.pdf) implemented with [PyMC3](https://peerj.com/articles/cs-55/), an open source probabilistic programming framework for automatic Bayesian inference on user-defined probabilistic models.


[comment]: <> (Paper)
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[comment]: <> (Our paper is available [here: add link])

<br/>


Installation
------------

This library is distributed on [PyPI](https://pypi.org/project/pybandits/) and can be installed with ``pip``.
The latest release is version ``0.0.2``. ``pybandits`` requires a Python version ``>= 3.8``.

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
$ pip install pybandits
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~bash
pip install pybandits
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The command above will automatically install all the dependencies listed in ``requirements.txt``. Please visit the
[installation](https://playtikaresearch.github.io/pybandits/installation.html)
[installation](https://playtikaoss.github.io/pybandits/installation.html)
page for more details.

<br/>


Getting started
---------------

A short example, illustrating it use. Use the sMAB model to predict actions and update the model based on rewards from the environment.

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~python
import numpy as np
import random
from pybandits.core.smab import Smab
Expand All @@ -69,75 +52,68 @@ for a in set(pred_actions):
smab.update(action_id=a, n_successes=n_successes[a], n_failures=n_failures[a])
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

<br/>

Documentation
-------------

For more information please read the full
[documentation](https://playtikaresearch.github.io/pybandits/pybandits.html)
[documentation](https://playtikaoss.github.io/pybandits/pybandits.html)
and
[tutorials](https://playtikaresearch.github.io/pybandits/tutorials.html).

<br/>
[tutorials](https://playtikaoss.github.io/pybandits/tutorials.html).

Info for developers
-------------------

PyBandits is supported by the [AI for gaming and entertainment apps](https://www.meetup.com/ai-for-gaming-and-entertainment-apps/) community.

The source code of the project is available on [GitHub](https://github.com/playtikaresearch/pybandits).
The source code of the project is available on [GitHub](https://github.com/playtikaoss/pybandits).

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
$ git clone https://github.com/playtikaresearch/pybandits.git
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~bash
git clone https://github.com/playtikaoss/pybandits.git
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

You can install the library and the dependencies with one of the following commands:

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
$ pip install . # install library + dependencies
$ pip install .[develop] # install library + dependencies + developer-dependencies
$ pip install -r requirements.txt # install dependencies
$ pip install -r requirements-dev.txt # install developer-dependencies
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~bash
pip install . # install library + dependencies
pip install .[develop] # install library + dependencies + developer-dependencies
pip install -r requirements.txt # install dependencies
pip install -r requirements-dev.txt # install developer-dependencies
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As suggested by the authors of ``pymc3`` and ``pandoc``, we highly recommend to install these dependencies with
``conda``:

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
$ conda install -c conda-forge pandoc
$ conda install -c conda-forge pymc3
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~bash
conda install -c conda-forge pandoc
conda install -c conda-forge pymc3
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To create the file ``pybandits.whl`` for the installation with ``pip`` run the following command:

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
$ python setup.py sdist bdist_wheel
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~bash
python setup.py sdist bdist_wheel
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To create the HTML documentation run the following commands:

~~~~~~~~~~~bash
cd docs
make html
~~~~~~~~~~~
$ cd docs
$ make html
~~~~~~~~~~~

<br/>

Run tests
---------

Tests can be executed with ``pytest`` running the following commands. Make sure to have the library installed before to
run any tests.

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~bash
cd tests
pytest -vv # run all tests
pytest -vv test_testmodule.py # run all tests within a module
pytest -vv test_testmodule.py -k test_testname # run only 1 test
pytest -vv -k 'not time' # run all tests but not exec time
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
$ cd tests
$ pytest -vv # run all tests
$ pytest -vv test_testmodule.py # run all tests within a module
$ pytest -vv test_testmodule.py -k test_testname # run only 1 test
$ pytest -vv -k 'not time' # run all tests but not exec time
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

<br/>

License
-------
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