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finance/py-alphalens: version 0.1.1

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Alphalens is a Python Library for performance analysis of predictive
(alpha) stock factors. Alphalens works great with the Zipline open
source backtesting library, and Pyfolio which provides performance and
risk analysis of financial portfolios.
This commit is contained in:
minskim 2017-09-16 21:31:35 +00:00
parent 7a46d90737
commit ca861fd437
4 changed files with 69 additions and 0 deletions
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finance/py-alphalens/DESCR Normal file
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Alphalens is a Python Library for performance analysis of predictive
(alpha) stock factors. Alphalens works great with the Zipline open
source backtesting library, and Pyfolio which provides performance and
risk analysis of financial portfolios.

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finance/py-alphalens/Makefile Normal file
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# $NetBSD: Makefile,v 1.1 2017/09/16 21:31:35 minskim Exp $
DISTNAME= alphalens-0.1.1
PKGNAME= ${PYPKGPREFIX}-${DISTNAME}
CATEGORIES= finance
MASTER_SITES= ${MASTER_SITE_GITHUB:=quantopian/}
GITHUB_PROJECT= alphalens
GITHUB_TAG= v0.1.1
MAINTAINER= minskim@NetBSD.org
HOMEPAGE= https://github.com/quantopian/alphalens/
COMMENT= Performance analysis of predictive stock factors
LICENSE= apache-2.0
DEPENDS+= ${PYPKGPREFIX}-matplotlib-[0-9]*:../../graphics/py-matplotlib
DEPENDS+= ${PYPKGPREFIX}-numpy-[0-9]*:../../math/py-numpy
DEPENDS+= ${PYPKGPREFIX}-pandas-[0-9]*:../../math/py-pandas
DEPENDS+= ${PYPKGPREFIX}-scipy-[0-9]*:../../math/py-scipy
DEPENDS+= ${PYPKGPREFIX}-seaborn-[0-9]*:../../graphics/py-seaborn
DEPENDS+= ${PYPKGPREFIX}-statsmodels-[0-9]*:../../math/py-statsmodels
.include "../../lang/python/egg.mk"
.include "../../mk/bsd.pkg.mk"

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finance/py-alphalens/PLIST Normal file
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@comment $NetBSD: PLIST,v 1.1 2017/09/16 21:31:35 minskim Exp $
${PYSITELIB}/${EGG_INFODIR}/PKG-INFO
${PYSITELIB}/${EGG_INFODIR}/SOURCES.txt
${PYSITELIB}/${EGG_INFODIR}/dependency_links.txt
${PYSITELIB}/${EGG_INFODIR}/requires.txt
${PYSITELIB}/${EGG_INFODIR}/top_level.txt
${PYSITELIB}/alphalens/__init__.py
${PYSITELIB}/alphalens/__init__.pyo
${PYSITELIB}/alphalens/__init__.pyc
${PYSITELIB}/alphalens/performance.pyo
${PYSITELIB}/alphalens/performance.pyc
${PYSITELIB}/alphalens/plotting.pyo
${PYSITELIB}/alphalens/plotting.pyc
${PYSITELIB}/alphalens/tears.pyo
${PYSITELIB}/alphalens/tears.pyc
${PYSITELIB}/alphalens/utils.pyo
${PYSITELIB}/alphalens/utils.pyc
${PYSITELIB}/alphalens/examples/ic_tear.png
${PYSITELIB}/alphalens/examples/predictive_vs_non-predictive_factor.ipynb
${PYSITELIB}/alphalens/examples/returns_tear.png
${PYSITELIB}/alphalens/examples/sector_tear.png
${PYSITELIB}/alphalens/examples/table_tear.png
${PYSITELIB}/alphalens/examples/tear_sheet_walk_through.ipynb
${PYSITELIB}/alphalens/performance.py
${PYSITELIB}/alphalens/plotting.py
${PYSITELIB}/alphalens/tears.py
${PYSITELIB}/alphalens/tests/__init__.py
${PYSITELIB}/alphalens/tests/__init__.pyo
${PYSITELIB}/alphalens/tests/__init__.pyc
${PYSITELIB}/alphalens/tests/test_performance.pyo
${PYSITELIB}/alphalens/tests/test_performance.pyc
${PYSITELIB}/alphalens/tests/test_utils.pyo
${PYSITELIB}/alphalens/tests/test_utils.pyc
${PYSITELIB}/alphalens/tests/test_performance.py
${PYSITELIB}/alphalens/tests/test_utils.py
${PYSITELIB}/alphalens/utils.py

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finance/py-alphalens/distinfo Normal file
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$NetBSD: distinfo,v 1.1 2017/09/16 21:31:35 minskim Exp $
SHA1 (alphalens-0.1.1.tar.gz) = 1d48a690c2fa740194ea1d496bc646108cabef7b
RMD160 (alphalens-0.1.1.tar.gz) = b3613b353d7703a607e738db2eb4bb15bc0e14a3
SHA512 (alphalens-0.1.1.tar.gz) = 08dcc25061afe05e0fe9da1aae1cbcf7f9782d9c392f05cc3304e02a750e1270f2612c1eb857db6d754774eb4e18cc1de9a9117b8210aed2af7ac9107dacd0ac
Size (alphalens-0.1.1.tar.gz) = 12304162 bytes