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Victor Grau Serrat b39311de85 DOC: Resources page
2017-10-31 12:39:35 -06:00

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Resources
=========
- `Catalyst Whitepaper <https://www.enigma.co/enigma_catalyst.pdf>`_
Related 3rd Party APIs
^^^^^^^^^^^^^^^^^^^^^^
- `Zipline <http://www.zipline.io/appendix.html>`_ is a Pythonic Algorithmic
Trading Library, and the project Catalyst forked off in the spring of 2017.
- `Quantopian <https://www.quantopian.com/help>`_ provides a platform for
freelance quantitative analysts develop, test, and use trading algorithms to
buy and sell securities. They aim to create a crowd-sourced hedge fund by
fostering their community of freelance traders. Quantopian's backtesting and
live-trading engine is powered by *Zipline*.
- `Pandas <https://pandas.pydata.org/pandas-docs/stable/api.html>`_ is a Python
library providing high-performance, easy-to-use data structures and data
analysis tools. Catalyst relies heavily on pandas, and many API functions
return data as Pandas dataframes.
- `Numpy <https://docs.scipy.org/doc/numpy/reference/>`_ is the fundamental
package for scientific computing with Python. Some of the data computation
that your algorithms will need, will be optimized leveraging Numpy.
- `Matplotlib <https://matplotlib.org/1.5.3/api/index.html>`_ is a Python 2D
plotting library that many of examples rely on to plot the performance of
trading algorithms