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
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
Requires-Dist: alpha-vantage
Requires-Dist: exchange-calendars
Requires-Dist: ftx
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: pyfolio
Requires-Dist: pytz
Requires-Dist: scipy
Requires-Dist: tables
Requires-Dist: versioneer

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# 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).


