Metadata-Version: 1.2
Name: mars-gym
Version: 0.1.0
Summary: Framework Code for the RecSys 2020 entitled 'MARS-Gym: A Gym framework to model, train, and evaluate recommendationsystems for marketplaces'.
Home-page: https://github.com/deeplearningbrasil/mars-gym
Author: MARS-Gym Authors
Author-email: mars-gym@googlegroups.com
License: MIT
Project-URL: Documentation, https://mars-gym.readthedocs.io/
Project-URL: Changelog, https://mars-gym.readthedocs.io/en/latest/changelog.html
Project-URL: Issue Tracker, https://github.com/deeplearningbrasil/mars-gym/issues
Description: ========
        Overview
        ========
        
        
        
        MARS-Gym (MArketplace Recommender Systems Gym), a benchmark framework for modeling, training, and evaluating RL-based recommender systems for marketplaces.
        
        .. figure:: images/img1.jpg
           :alt: MDP
        
        Three main components composes the framework:
        
        - Data Engineering Module: A highly customizable module where the consumer can ingest and process a massive amount of data for learning using spark jobs.
        - Simulation Module: Holds an extensible module built on top of PyTorch to design learning architectures. It also possesses an OpenAI’s Gym environment that ingests the processed dataset to run a multi-agent system that simulates the targeted marketplace.
        - Evaluation Module: Provides a set of distinct perspectives on the agent’s performance. It presents traditional recommendation metrics, off-policy evaluation metrics, and fairness indicators. This component is powered by a user-friendly interface to facilitate the analysis and comparison betweenagents
        
        .. figure:: images/img2.jpg
           :alt: Framework
        
           Framework
        
        Dependencies and Requirements
        -----------------------------
        
        -  python=3.6.7
        -  pandas=0.25.1
        -  matplotlib=2.2.2
        -  scipy=1.3.1
        -  numpy=1.17.0
        -  seaborn=0.8.1
        -  scikit-learn=0.21.2
        -  pytorch=1.2.0
        -  tensorboardx=1.6
        -  luigi=2.7.5
        -  tqdm=4.33
        -  requests=2.18.4
        -  jupyterlab=1.0.2
        -  ipywidgets=7.5.1
        -  diskcache=3.0.6
        -  pyspark=2.4.3
        -  psutil=5.2.2
        -  category\_encoders
        -  plotly=4.4.1
        -  imbalanced-learn==0.4.3
        -  torchbearer==0.5.1
        -  pytorch-nlp==0.4.1
        -  unidecode==1.1.1
        -  streamlit==0.52.2
        -  gym==0.15.4
        
        Free software: MIT license
        
        Installation
        ============
        
        ::
        
            pip install mars-gym
        
        You can also install the in-development version with::
        
            pip install https://github.com/deeplearningbrasil/mars-gym/archive/master.zip
        
        
        Documentation
        =============
        
        
        https://mars-gym.readthedocs.io/
        
        
        Development
        ===========
        
        To run the all tests run::
        
            tox
        
        Note, to combine the coverage data from all the tox environments run:
        
        .. list-table::
            :widths: 10 90
            :stub-columns: 1
        
            - - Windows
              - ::
        
                    set PYTEST_ADDOPTS=--cov-append
                    tox
        
            - - Other
              - ::
        
                    PYTEST_ADDOPTS=--cov-append tox
        
        
        Usage
        -----
        
        Simulate Example
        ----------------
        
        .. code:: bash
        
        
            mars-gym run interaction --project PROJECT \
            --n-factors N_FACTORS --learning-rate LR --optimizer OPTIMIZER \
            --epochs EPOCHS --obs-batch-size OBS_BATCH \
            --batch-size BATCH_SIZE --num-episodes NUM_EP \
            --bandit-policy BANDIT --bandit-policy-params BANDIT_PARAMS
        
        Evaluate Example
        ----------------
        
        .. code:: bash
        
        
            mars-gym evaluate iteraction \
             --model-task-id MODEL_TASK_ID --fairness-columns "[]" \
             --direct-estimator-class DE_CLASS
        
        Evaluation Module
        -----------------
        
        .. code:: bash
        
        
            mars-gym viz
        
        Cite
        ----
        
        Please cite the associated paper for this work if you use this code:
        
        ::
        
            @misc{santana2020marsgym,
                  title={MARS-Gym: A Gym framework to model, train, and evaluate Recommender Systems for Marketplaces}, 
                  author={Marlesson R. O. Santana and Luckeciano C. Melo and Fernando H. F. Camargo and Bruno Brandão and Anderson Soares and Renan M. Oliveira and Sandor Caetano},
                  year={2020},
                  eprint={2010.07035},
                  archivePrefix={arXiv},
                  primaryClass={cs.IR}
            }
        
        
        
        
        Changelog
        =========
        
        0.0.1 (2020-06-27)
        ------------------
        
        * First release on PyPI.
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.6
