Metadata-Version: 2.1
Name: margot
Version: 1.13
Summary: An algorithmic trading framework for PyData.
Home-page: https://github.com/pymargot/margot
Author: Rich Atkinson
Author-email: rich@airteam.com.au
License: apache-2.0
Description: [![](https://api.codacy.com/project/badge/Grade/1d42c486297a49158494e5f31b25793b)](https://app.codacy.com/manual/pymargot/margot?utm_source=github.com&utm_medium=referral&utm_content=pymargot/margot&utm_campaign=Badge_Grade_Dashboard)
        [![](https://travis-ci.org/pymargot/margot.svg?branch=master)](https://travis-ci.org/github/pymargot/margot)
        [![](https://readthedocs.org/projects/margot/badge/?version=latest)](https://margot.readthedocs.io/en/latest/?badge=latest)
        [![](https://codecov.io/gh/pymargot/margot/branch/master/graph/badge.svg)](https://codecov.io/gh/pymargot/margot)
        [![](https://img.shields.io/github/license/pymargot/margot)](https://github.com/pymargot/margot/blob/master/LICENSE)
        ![](https://img.shields.io/pypi/wheel/margot)
        ![](https://img.shields.io/pypi/pyversions/margot)
        [![](https://img.shields.io/pypi/v/margot)](https://pypi.org/project/margot/)
        
        
        # What is margot?
        Margot makes it super easy to backtest trading elgorithms. Firstly, Margot makes
        it super easy tocreate neat and tidy Pandas dataframes for time-series analysis.
        
        Margot manages data collection, caching, cleaning, feature generation,
        management and persistence using a clean, declarative API. If you've
        ever used Django you will find this approach similar to the Django ORM.
        
        Margot also provides a simple framework for writing and backtesting systematic
        trading algorithms.
        
        Results from margot's trading algorithms can be analysed using pyfolio.
        
        # Getting Started
        
            pip install margot
        
        Next you need to make sure you have a couple of important environment variables
        set::
        
            export ALPHAVANTAGE_API_KEY=YOUR_API_KEY
            export DATA_CACHE=PATH_TO_FOLDER_TO_STORE_HDF5_FILES
        
        Once you've done that, try running the code in the [notebook](notebook.margot.data).
        
        # Status
        This is still an early stage software project, and should not be used for live
        trading just yet.
        
        # Documentation
        
        The documentation is at [readthedocs](https://margot.readthedocs.io/en/latest/).
        
        # Contributing
        
        Feel free to make a pull request or chat about your idea first using [issues](https://github.com/atkinson/margot/issues).
        
        Dependencies are kept to a minimum. Generally if there's a way to do something
        in the standard library (or numpy / Pandas), let's do it that way rather than
        add another library. 
        
        # License
        Margot is licensed for use under Apache 2.0. For details see [the License](https://github.com/atkinson/margot/blob/master/LICENSE).
        
Keywords: quant,trading,systematic
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
