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setup.cfg
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setup.cfg
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[pycodestyle]
ignore=E402,W504
max-line-length=119
[pydocstyle]
; Use numpy style
convention=numpy
[metadata]
name = econml
author = Microsoft Corporation
description = This package contains several methods for calculating Conditional Average Treatment Effects
long_description = file: README.md
long_description_content_type = text/markdown
license = MIT
keywords = treatment-effect
url = https://github.com/Microsoft/EconML
project_urls =
Bug Tracker=https://github.com/Microsoft/EconML/Issues
Source Code=https://github.com/Microsoft/EconML
Documentation=https://econml.azurewebsites.net/
classifiers =
Programming Language :: Python :: 3.6
Programming Language :: Python :: 3.7
Programming Language :: Python :: 3.8
Programming Language :: Python :: 3.9
License :: OSI Approved :: MIT License
Operating System :: MacOS
Operating System :: Microsoft :: Windows
Operating System :: POSIX :: Linux
[options]
packages = find_namespace:
install_requires =
numpy
scipy > 1.4.0
scikit-learn > 0.22.0, < 1.2
sparse
joblib >= 0.13.0
statsmodels >= 0.10
pandas
shap >= 0.38.1, < 0.41.0
dowhy < 0.8
lightgbm
test_suite = econml.tests
tests_require =
pytest
pytest-xdist < 2.0.0
pytest-cov < 3.0.0
[options.extras_require]
automl =
; Disabled due to incompatibility with scikit-learn
; azureml-sdk[explain,automl] == 1.0.83
azure-cli
tf =
; This extra is not currently compatible with python 3.9 or above because of tensorflow breaking changes
keras < 2.4;python_version < '3.9'
tensorflow > 1.10, < 2.3;python_version < '3.9'
; Version capped due to tensorflow incompatibility
protobuf < 4
plt =
graphviz
matplotlib
all =
azure-cli
keras < 2.4
tensorflow > 1.10, < 2.3
; Version capped due to tensorflow incompatibility
protobuf < 4
matplotlib
[options.packages.find]
include =
econml
econml.*
exclude =
econml.tests
[options.package_data]
; include all CSV files as data
* = *.csv
*.jbl
; coverage configuration
[coverage:run]
omit = econml/tests/*
branch = True
; need to explicitly add support for multiprocessing for OrthoForest
concurrency =
thread
multiprocessing