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Merge pull request #206 from timkpaine/tkp/pkg
Update package for 2023, move to ruff for formatting, remove seaborn import styling side effect fixes #205
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@@ -9,26 +9,27 @@ test: | |
python -m pytest -vvv tests --cov=ffn --junitxml=python_junit.xml --cov-report=xml --cov-branch --cov-report term | ||
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lint: | ||
python -m flake8 ffn setup.py docs/source/conf.py | ||
python -m ruff ffn setup.py docs/source/conf.py | ||
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fix: | ||
python -m black ffn setup.py docs/source/conf.py | ||
python -m ruff format ffn setup.py docs/source/conf.py | ||
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clean: | ||
- rm -rf dist | ||
- rm -rf ffn.egg-info | ||
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dist: | ||
python setup.py sdist | ||
python -m build | ||
twine check dist/* | ||
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upload: clean dist | ||
twine upload dist/* | ||
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docs: | ||
docs: | ||
$(MAKE) -C docs/ clean | ||
$(MAKE) -C docs/ html | ||
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pages: | ||
pages: | ||
rm -rf $(TMPREPO) | ||
git clone -b gh-pages [email protected]:pmorissette/ffn.git $(TMPREPO) | ||
rm -rf $(TMPREPO)/* | ||
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@@ -38,7 +39,7 @@ pages: | |
git commit -a -m 'auto-updating docs';\ | ||
git push;\ | ||
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serve: | ||
serve: | ||
cd docs/build/html; \ | ||
python -m http.server 9087 | ||
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![](http://pmorissette.github.io/ffn/_static/logo.png) | ||
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[![Build Status](https://github.com/pmorissette/ffn/workflows/Build%20Status/badge.svg)](https://github.com/pmorissette/ffn/actions/) | ||
[![Codecov](https://codecov.io/gh/pmorissette/ffn/branch/master/graph/badge.svg)](https://codecov.io/pmorissette/ffn) | ||
[![PyPI Version](https://img.shields.io/pypi/v/ffn)](https://pypi.org/project/ffn/) | ||
[![PyPI License](https://img.shields.io/pypi/l/ffn)](https://pypi.org/project/ffn/) | ||
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# ffn - Financial Functions for Python | ||
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Alpha release - please let me know if you find any bugs! | ||
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If you are looking for a full backtesting framework, please check out [bt](https://github.com/pmorissette/bt). | ||
bt is built atop ffn and makes it easy and fast to backtest quantitative strategies. | ||
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## Overview | ||
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ffn is a library that contains many useful functions for those who work in **quantitative | ||
finance**. It stands on the shoulders of giants (Pandas, Numpy, Scipy, etc.) and provides | ||
a vast array of utilities, from performance measurement and evaluation to | ||
graphing and common data transformations. | ||
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```python | ||
import ffn | ||
returns = ffn.get('aapl,msft,c,gs,ge', start='2010-01-01').to_returns().dropna() | ||
returns.calc_mean_var_weights().as_format('.2%') | ||
aapl 62.54% | ||
c -0.00% | ||
ge 36.19% | ||
gs -0.00% | ||
msft 1.26% | ||
dtype: object | ||
``` | ||
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## Installation | ||
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The easiest way to install `ffn` is from the [Python Package Index](https://pypi.python.org/pypi/ffn/) | ||
using `pip`. | ||
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```bash | ||
pip install ffn | ||
``` | ||
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Since ffn has many dependencies, we strongly recommend installing the [Anaconda Scientific Python Distribution](https://store.continuum.io/cshop/anaconda/). This distribution comes with many of the required packages pre-installed, including pip. Once Anaconda is installed, the above command should complete the installation. | ||
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ffn should be compatible with Python 2.7 and Python 3. | ||
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## Documentation | ||
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Read the docs at http://pmorissette.github.io/ffn | ||
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- [Quickstart](http://pmorissette.github.io/ffn/quick.html) | ||
- [Full API](http://pmorissette.github.io/ffn/ffn.html) |
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