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README.md

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[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
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[![PyPI version](https://badge.fury.io/py/CausalPy.svg)](https://badge.fury.io/py/CausalPy)
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![GitHub Repo stars](https://img.shields.io/github/stars/pymc-labs/causalpy?style=social)
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![Read the Docs](https://img.shields.io/readthedocs/causalpy)
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![PyPI - Downloads](https://img.shields.io/pypi/dm/causalpy)
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A Python package focussing on causal inference in quasi-experimental settings. The package allows for sophisticated Bayesian model fitting methods to be used in addition to traditional OLS.
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causalpy/__init__.py

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import causalpy.pymc_models
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import causalpy.skl_experiments
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import causalpy.skl_models
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from causalpy.version import __version__
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from .data import load_data
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causalpy/version.py

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__version__ = "0.0.3"
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__version__ = "0.0.4"

manifest.in

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include requirements.txt
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include *.md *.rst
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include requirements.txt
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include LICENSE
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include requirements.txt

setup.py

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# get version
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sys.path.insert(0, os.path.abspath("../"))
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# sys.path.insert(0, os.path.abspath("../"))
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# from causalpy.version import __version__
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exec(open("causalpy/version.py").read())
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with open(REQUIREMENTS_FILE) as f:
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install_reqs = f.read().splitlines()

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