Repository: davidastephens/pandas-finance Branch: master Commit: d58e64f893a7 Files: 18 Total size: 42.9 KB Directory structure: gitextract_snlmun_9/ ├── .gitignore ├── .travis.yml ├── LICENSE.md ├── MANIFEST.in ├── README.rst ├── docs/ │ ├── Makefile │ ├── make.bat │ └── source/ │ ├── conf.py │ └── index.rst ├── pandas_finance/ │ ├── __init__.py │ ├── api.py │ └── tests/ │ ├── __init__.py │ ├── nosy.cfg │ └── test_api.py ├── requirements.txt ├── setup.cfg ├── setup.py └── tox.ini ================================================ FILE CONTENTS ================================================ ================================================ FILE: .gitignore ================================================ __pycache__ *.pyc *.egg-info .eggs .coverage build dist docs/build *.sqlite .idea/ ================================================ FILE: .travis.yml ================================================ sudo: false language: python env: - PYTHON=2.7 PANDAS=0.22 - PYTHON=3.5 PANDAS=0.21 - PYTHON=3.6 PANDAS=0.23.0 - PYTHON=3.6 PANDAS=0.25.0 - PYTHON=3.6 PANDAS="MASTER" matrix: allow_failures: - env: PYTHON=3.6 PANDAS="MASTER" - env: PYTHON=2.7 PANDAS=0.22 install: # You may want to periodically update this, although the conda update # conda line below will keep everything up-to-date. We do this # conditionally because it saves us some downloading if the version is # the same. - if [[ "$PYTHON" == "2.7" ]]; then wget http://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh -O miniconda.sh; else wget http://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh; fi - bash miniconda.sh -b -p $HOME/miniconda - export PATH="$HOME/miniconda/bin:$PATH" - hash -r - conda config --set always_yes yes --set changeps1 no - conda config --add channels pandas - conda update -q conda # Useful for debugging any issues with conda - conda info -a - conda create -q -n test-environment python=$PYTHON nose coverage setuptools html5lib lxml - source activate test-environment - if [[ "$PANDAS" == "MASTER" ]]; then conda install bottleneck numpy pytz python-dateutil; PRE_WHEELS="https://7933911d6844c6c53a7d-47bd50c35cd79bd838daf386af554a83.ssl.cf2.rackcdn.com"; pip install --pre --upgrade --timeout=60 -f $PRE_WHEELS pandas; else conda install bottleneck numpy pandas=$PANDAS; fi - pip install coveralls --quiet - conda list - python setup.py install script: - nosetests -v --with-coverage --cover-package=pandas_finance after_success: - coveralls ================================================ FILE: LICENSE.md ================================================ ======= License ======= pandas is distributed under a 3-clause ("Simplified" or "New") BSD license. Parts of NumPy, SciPy, numpydoc, bottleneck, which all have BSD-compatible licenses, are included. Their licenses follow the pandas license. pandas license ============== Copyright (c) 2011-2012, Lambda Foundry, Inc. and PyData Development Team All rights reserved. Copyright (c) 2008-2011 AQR Capital Management, LLC All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of the copyright holder nor the names of any contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDER AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. About the Copyright Holders =========================== AQR Capital Management began pandas development in 2008. Development was led by Wes McKinney. AQR released the source under this license in 2009. Wes is now an employee of Lambda Foundry, and remains the pandas project lead. The PyData Development Team is the collection of developers of the PyData project. This includes all of the PyData sub-projects, including pandas. The core team that coordinates development on GitHub can be found here: http://github.com/pydata. Full credits for pandas contributors can be found in the documentation. Our Copyright Policy ==================== PyData uses a shared copyright model. Each contributor maintains copyright over their contributions to PyData. However, it is important to note that these contributions are typically only changes to the repositories. Thus, the PyData source code, in its entirety, is not the copyright of any single person or institution. Instead, it is the collective copyright of the entire PyData Development Team. If individual contributors want to maintain a record of what changes/contributions they have specific copyright on, they should indicate their copyright in the commit message of the change when they commit the change to one of the PyData repositories. With this in mind, the following banner should be used in any source code file to indicate the copyright and license terms: #----------------------------------------------------------------------------- # Copyright (c) 2012, PyData Development Team # All rights reserved. # # Distributed under the terms of the BSD Simplified License. # # The full license is in the LICENSE file, distributed with this software. #----------------------------------------------------------------------------- Other licenses can be found in the LICENSES directory. ================================================ FILE: MANIFEST.in ================================================ include README.rst include LICENSE.md include pandas_finance/*.py include pandas_finance/tests/*.py include pandas_finance/tests/data/* ================================================ FILE: README.rst ================================================ pandas-finance ================= High level API for access to and analysis of financial data. .. image:: https://travis-ci.org/davidastephens/pandas-finance.svg?branch=master :target: https://travis-ci.org/davidastephens/pandas-finance .. image:: https://coveralls.io/repos/davidastephens/pandas-finance/badge.svg?branch=master :target: https://coveralls.io/r/davidastephens/pandas-finance .. image:: https://readthedocs.org/projects/pandas-finance/badge/?version=latest :target: http://pandas-finance.readthedocs.org/en/latest/ Installation ------------ Install via pip .. code-block:: shell $ pip install pandas-finance Usage ----- .. code-block:: python from pandas_finance import Equity aapl = Equity('AAPL') aapl.annual_dividend aapl.dividend_yield aapl.price aapl.options aapl.hist_vol(30) aapl.rolling_hist_vol(30) Data is automatically cached for 1 hr using requests_cache. 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The XML files are in %BUILDDIR%/xml. goto end ) if "%1" == "pseudoxml" ( %SPHINXBUILD% -b pseudoxml %ALLSPHINXOPTS% %BUILDDIR%/pseudoxml if errorlevel 1 exit /b 1 echo. echo.Build finished. The pseudo-XML files are in %BUILDDIR%/pseudoxml. goto end ) :end ================================================ FILE: docs/source/conf.py ================================================ # -*- coding: utf-8 -*- # # pandas-finance documentation build configuration file, created by # sphinx-quickstart on Sun Nov 22 14:31:26 2015. # # This file is execfile()d with the current directory set to its # containing dir. # # Note that not all possible configuration values are present in this # autogenerated file. # # All configuration values have a default; values that are commented out # serve to show the default. import sys import os # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. #sys.path.insert(0, os.path.abspath('.')) # -- General configuration ------------------------------------------------ # If your documentation needs a minimal Sphinx version, state it here. #needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = [ 'sphinx.ext.autodoc', 'sphinx.ext.doctest', 'sphinx.ext.viewcode', ] # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix of source filenames. source_suffix = '.rst' # The encoding of source files. #source_encoding = 'utf-8-sig' # The master toctree document. master_doc = 'index' # General information about the project. project = u'pandas-finance' copyright = u'2015, David Stephens' # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the # built documents. # # The short X.Y version. version = '0.1.0' # The full version, including alpha/beta/rc tags. release = '0.1.0' # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. #language = None # There are two options for replacing |today|: either, you set today to some # non-false value, then it is used: #today = '' # Else, today_fmt is used as the format for a strftime call. #today_fmt = '%B %d, %Y' # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. exclude_patterns = [] # The reST default role (used for this markup: `text`) to use for all # documents. #default_role = None # If true, '()' will be appended to :func: etc. cross-reference text. #add_function_parentheses = True # If true, the current module name will be prepended to all description # unit titles (such as .. function::). #add_module_names = True # If true, sectionauthor and moduleauthor directives will be shown in the # output. They are ignored by default. #show_authors = False # The name of the Pygments (syntax highlighting) style to use. pygments_style = 'sphinx' # A list of ignored prefixes for module index sorting. #modindex_common_prefix = [] # If true, keep warnings as "system message" paragraphs in the built documents. #keep_warnings = False # -- Options for HTML output ---------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. html_theme = 'default' # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. #html_theme_options = {} # Add any paths that contain custom themes here, relative to this directory. #html_theme_path = [] # The name for this set of Sphinx documents. If None, it defaults to # " v documentation". #html_title = None # A shorter title for the navigation bar. Default is the same as html_title. #html_short_title = None # The name of an image file (relative to this directory) to place at the top # of the sidebar. #html_logo = None # The name of an image file (within the static path) to use as favicon of the # docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 # pixels large. #html_favicon = None # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] # Add any extra paths that contain custom files (such as robots.txt or # .htaccess) here, relative to this directory. These files are copied # directly to the root of the documentation. #html_extra_path = [] # If not '', a 'Last updated on:' timestamp is inserted at every page bottom, # using the given strftime format. #html_last_updated_fmt = '%b %d, %Y' # If true, SmartyPants will be used to convert quotes and dashes to # typographically correct entities. #html_use_smartypants = True # Custom sidebar templates, maps document names to template names. #html_sidebars = {} # Additional templates that should be rendered to pages, maps page names to # template names. #html_additional_pages = {} # If false, no module index is generated. #html_domain_indices = True # If false, no index is generated. #html_use_index = True # If true, the index is split into individual pages for each letter. #html_split_index = False # If true, links to the reST sources are added to the pages. #html_show_sourcelink = True # If true, "Created using Sphinx" is shown in the HTML footer. Default is True. #html_show_sphinx = True # If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. #html_show_copyright = True # If true, an OpenSearch description file will be output, and all pages will # contain a tag referring to it. The value of this option must be the # base URL from which the finished HTML is served. #html_use_opensearch = '' # This is the file name suffix for HTML files (e.g. ".xhtml"). #html_file_suffix = None # Output file base name for HTML help builder. htmlhelp_basename = 'pandas-financedoc' # -- Options for LaTeX output --------------------------------------------- latex_elements = { # The paper size ('letterpaper' or 'a4paper'). #'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). #'pointsize': '10pt', # Additional stuff for the LaTeX preamble. #'preamble': '', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ ('index', 'pandas-finance.tex', u'pandas-finance Documentation', u'David Stephens', 'manual'), ] # The name of an image file (relative to this directory) to place at the top of # the title page. #latex_logo = None # For "manual" documents, if this is true, then toplevel headings are parts, # not chapters. #latex_use_parts = False # If true, show page references after internal links. #latex_show_pagerefs = False # If true, show URL addresses after external links. #latex_show_urls = False # Documents to append as an appendix to all manuals. #latex_appendices = [] # If false, no module index is generated. #latex_domain_indices = True # -- Options for manual page output --------------------------------------- # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ ('index', 'pandas-finance', u'pandas-finance Documentation', [u'David Stephens'], 1) ] # If true, show URL addresses after external links. #man_show_urls = False # -- Options for Texinfo output ------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ ('index', 'pandas-finance', u'pandas-finance Documentation', u'David Stephens', 'pandas-finance', 'One line description of project.', 'Miscellaneous'), ] # Documents to append as an appendix to all manuals. #texinfo_appendices = [] # If false, no module index is generated. #texinfo_domain_indices = True # How to display URL addresses: 'footnote', 'no', or 'inline'. #texinfo_show_urls = 'footnote' # If true, do not generate a @detailmenu in the "Top" node's menu. #texinfo_no_detailmenu = False ================================================ FILE: docs/source/index.rst ================================================ .. pandas-finance documentation master file, created by sphinx-quickstart on Sun Nov 22 14:31:26 2015. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. Welcome to pandas-finance's documentation! ========================================== Contents: .. toctree:: :maxdepth: 2 Indices and tables ================== * :ref:`genindex` * :ref:`modindex` * :ref:`search` ================================================ FILE: pandas_finance/__init__.py ================================================ __version__ = version = '0.1.3' from .api import Equity, Option, OptionChain ================================================ FILE: pandas_finance/api.py ================================================ import datetime import math import json import pandas as pd from pandas import DataFrame, Series from pandas_datareader.yahoo.quotes import YahooQuotesReader import yfinance as yf import pandas_datareader.data as pdr import requests_cache import empyrical TRADING_DAYS = 252 CACHE_HRS = 1 START_DATE = datetime.date(1990, 1, 1) QUERY_STRING = "https://query1.finance.yahoo.com/v10/finance/quoteSummary/{ticker}?lang=en-US®ion=US&modules={modules}&corsDomain=finance.yahoo.com" HEADERS = { "Connection": "keep-alive", "Expires": str(-1), "Upgrade-Insecure-Requests": str(1), # Google Chrome: "User-Agent": ( "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 " "(KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36" ), } _DEFAULT_PARAMS = { "lang": "en-US", "corsDomain": "finance.yahoo.com", ".tsrc": "finance", } class FixedYahooQuotesReader(YahooQuotesReader): def __init__(self, *args, crumb=None, **kwargs): super(FixedYahooQuotesReader, self).__init__(*args, **kwargs) self.crumb = crumb def params(self, symbol): params = super().params(symbol) params.update({"crumb": self.crumb}) return params def _read_lines(self, out): data = json.loads(out.read())["quoteResponse"]["result"][0] idx = data.pop('symbol') data["price"] = data["regularMarketPrice"] return Series(data) class Equity(object): def __init__(self, ticker, session=None): self.ticker = ticker self.yf_ticker = yf.Ticker(self.ticker) if session: self._session = session else: self._session = self._get_session() with self._session.cache_disabled(): self.crumb = self._session.get( 'https://query1.finance.yahoo.com/v1/test/getcrumb').text def _get_session(self): session = requests_cache.CachedSession( cache_name="pf-cache", backend="sqlite", expire_after=datetime.timedelta(hours=CACHE_HRS), ) session.headers.update(HEADERS) with session.cache_disabled(): session.get('https://fc.yahoo.com') return session @property def options(self): return OptionChain(self) @property def close(self): """Returns pandas series of closing price""" return self.trading_data["Close"] @property def adj_close(self): """Returns pandas series of closing price""" return self.trading_data["Adj Close"] @property def returns(self): return self.adj_close.pct_change() @property def trading_data(self): return self.yf_ticker.history(start=START_DATE) @property def actions(self): return pdr.get_data_yahoo_actions( self.ticker, session=self._session, start=START_DATE ) @property def dividends(self): dividends = self.yf_ticker.get_dividends() dividends.name = "Dividends" return dividends @property def splits(self): splits = self.yf_ticker.get_splits() splits.name = "Splits" return splits @property def annual_dividend(self): if "forwardAnnualDividendRate" in self.quotes.index: return self.quotes["forwardAnnualDividendRate"] elif "trailingAnnualDividendRate" in self.quotes.index: return self.quotes["trailingAnnualDividendRate"] else: return 0 @property def dividend_yield(self): return self.annual_dividend / self.price @property def price(self): return self.quotes["price"] @property def closed(self): "Market is closed or open" return self.quotes["marketState"].lower() == "closed" @property def currency(self): return self.quotes["currency"] @property def market_cap(self): return float(self.quotes["marketCap"]) @property def shares_os(self): return int(self.quotes["sharesOutstanding"]) def hist_vol(self, days, end_date=None): days = int(days) if end_date: data = self.returns[:end_date] else: data = self.returns data = data.iloc[-days:] return data.std() * math.sqrt(TRADING_DAYS) def rolling_hist_vol(self, days, end_date=None): days = int(days) if end_date: data = self.returns[:end_date] else: data = self.returns return data.rolling(days).std() * math.sqrt(TRADING_DAYS) @property def profile(self): response = self._session.get( QUERY_STRING.format(ticker=self.ticker, modules="assetProfile") ).json() asset_profile = response["quoteSummary"]["result"][0]["assetProfile"] del asset_profile["companyOfficers"] profile = pd.DataFrame.from_dict(asset_profile, orient="index")[0] profile.name = "" profile.index = [name.capitalize() for name in profile.index] rename = {"Fulltimeemployees": "Full Time Employees"} profile.rename(index=rename, inplace=True) return profile @property def quotes(self): return FixedYahooQuotesReader(self.ticker, session=self._session, crumb=self.crumb).read() @property def quote(self): return self.quotes @property def sector(self): return self.profile["Sector"] @property def industry(self): return self.profile["Industry"] @property def employees(self): return self.profile["Full Time Employees"] @property def name(self): return self.quotes["longName"] def alpha_beta(self, index, start=None, end=None): index_rets = Equity(index).returns rets = self.returns data = pd.DataFrame() data["Index"] = index_rets data["Rets"] = rets data = data.fillna(0) if start: data = data[start:] if end: data = data[start:end] return empyrical.alpha_beta(data["Rets"], data["Index"]) def beta(self, index, start=None, end=None): alpha, beta = self.alpha_beta(index, start, end) return beta def alpha(self, index, start=None, end=None): alpha, beta = self.alpha_beta(index, start, end) return alpha def vwap(self, end_date=None, days=30): days = int(days) if end_date: data = self.trading_data[:end_date] else: data = self.trading_data data = data.iloc[-days:] return (data["Close"] * data["Volume"]).sum() / data["Volume"].sum() def hist_vol_by_days(self, end_date=None, min_days=10, max_days=600): "Returns the historical vol for a range of trading days ending on end_date." min_days = int(min_days) max_days = int(max_days) if end_date: returns = self.returns[:end_date] else: returns = self.returns output = {} for i in range(min_days, max_days): output[i] = returns[-i:].std() * math.sqrt(TRADING_DAYS) return pd.Series(output) class Option(object): def __init__(self): pass class OptionChain(object): def __init__(self, underlying): self.underlying = underlying self._session = self.underlying._session self._pdr = pdr.Options(self.underlying.ticker, "yahoo", session=self._session) @property def all_data(self): return self._pdr.get_all_data() @property def calls(self): data = self.all_data mask = data.index.get_level_values("Type") == "calls" return data[mask] @property def puts(self): data = self.all_data mask = data.index.get_level_values("Type") == "puts" return data[mask] @property def near_puts(self): return self._pdr._chop_data(self.puts, 5, self.underlying.price) @property def near_calls(self): return self._pdr._chop_data(self.calls, 5, self.underlying.price) def __getattr__(self, key): if hasattr(self._pdr, key): return getattr(self._pdr, key) def __dir__(self): return sorted(set((dir(type(self)) + list(self.__dict__) + dir(self._pdr)))) ================================================ FILE: pandas_finance/tests/__init__.py ================================================ ================================================ FILE: pandas_finance/tests/nosy.cfg ================================================ #sample config file section for nosy # Including this file in the paths to check allows you to change # nose's behaviour on the fly. [nosy] # Paths to check for changed files; changes cause nose to be run base_path = ./ glob_patterns = *.py exclude_patterns = *_flymake.* extra_paths = nosy.cfg # Command line options to pass to nose options = # Command line arguments to pass to nose; e.g. part of test suite to run tests = ================================================ FILE: pandas_finance/tests/test_api.py ================================================ import datetime import unittest import pandas as pd from pandas_finance import Equity, OptionChain class TestEquity(unittest.TestCase): @classmethod def setUpClass(cls): cls.aapl = Equity("AAPL") cls.date = datetime.date(2013, 1, 25) cls.tsla = Equity("TSLA") def test_equity_price(self): self.assertAlmostEqual(self.aapl.close[self.date], 62.84, 2) def test_historical_vol(self): vol = self.aapl.hist_vol(30, end_date=self.date) self.assertAlmostEqual(vol, 0.484, 3) @unittest.skip("Yahoo options api broken") def test_options(self): self.assertIsInstance(self.aapl.options, OptionChain) def test_annual_dividend(self): self.assertEqual(self.aapl.annual_dividend, 3.00) self.assertEqual(self.tsla.annual_dividend, 0) def test_dividends(self): self.assertEqual(self.aapl.dividends[datetime.date(2015, 11, 5)], 0.52) def test_splits(self): self.assertAlmostEqual(self.aapl.splits[datetime.date(2014, 6, 9)], 0.142857, 5) def test_dividends_no_data(self): self.assertEqual(len(self.tsla.dividends), 0) def test_price(self): self.assertIsInstance(self.aapl.price, float) def test_sector(self): self.assertEqual(self.aapl.sector, "Technology") def test_employees(self): self.assertGreaterEqual(self.aapl.employees, 100000) def test_industry(self): self.assertEqual(self.aapl.industry, "Consumer Electronics") def test_name(self): self.assertEqual(self.aapl.name, "Apple Inc.") def test_quotes(self): self.assertIsInstance(self.aapl.quotes["price"], float) def test_quote(self): self.assertIsInstance(self.aapl.quote["price"], float) def test_shares_os(self): self.assertIsInstance(self.aapl.shares_os, int) def test_market_cap(self): self.assertIsInstance(self.aapl.market_cap, float) def test_closed(self): self.assertIsInstance(self.aapl.closed, bool) def test_currency(self): self.assertEqual(self.aapl.currency, "USD") def test_rolling_hist_vol(self): self.assertIsInstance(self.aapl.rolling_hist_vol(20), pd.Series) self.assertAlmostEqual(self.aapl.rolling_hist_vol(20)[self.date], 0.562, 3) def test_hist_vol_by_days(self): self.assertIsInstance(self.aapl.hist_vol_by_days(), pd.Series) self.assertAlmostEqual(self.aapl.hist_vol_by_days(self.date)[20], 0.562, 3) class TestOptionChain(unittest.TestCase): @classmethod @unittest.skip("Skip option tests due to broken yahoo api") def setUpClass(cls): cls.aapl = Equity("AAPL") cls.options = OptionChain(cls.aapl) def test_options(self): self.assertIsInstance(self.options.all_data, pd.DataFrame) def test_calls(self): self.assertIsInstance(self.options.calls, pd.DataFrame) self.assertTrue( (self.options.calls.index.get_level_values("Type") == "calls").all() ) def test_puts(self): self.assertIsInstance(self.options.puts, pd.DataFrame) self.assertTrue( (self.options.puts.index.get_level_values("Type") == "puts").all() ) def test_near_calls(self): self.assertIsInstance(self.options.near_calls, pd.DataFrame) self.assertTrue( (self.options.near_calls.index.get_level_values("Type") == "calls").all() ) def test_near_puts(self): self.assertIsInstance(self.options.near_puts, pd.DataFrame) self.assertTrue( (self.options.near_puts.index.get_level_values("Type") == "puts").all() ) class TestOption(unittest.TestCase): @classmethod @unittest.skip("Skip option tests due to broken yahoo api") def setUpClass(cls): cls.aapl = Equity("AAPL") cls.options = OptionChain(cls.aapl) def test_options(self): self.options.all_data ================================================ FILE: requirements.txt ================================================ pandas requests-cache pandas-datareader>=0.7.0 empyrical yfinance ================================================ FILE: setup.cfg ================================================ [bdist_wheel] universal = 1 ================================================ FILE: setup.py ================================================ #!/usr/bin/env python # -*- coding: utf-8 -*- from ast import parse import os from setuptools import setup, find_packages NAME = 'pandas-finance' def version(): """Return version string.""" with open(os.path.join(os.path.abspath(os.path.dirname(__file__)), 'pandas_finance', '__init__.py')) as input_file: for line in input_file: if line.startswith('__version__'): return parse(line).body[0].value.s def readme(): with open('README.rst') as f: return f.read() install_requires = [] with open("./requirements.txt") as f: install_requires = f.read().splitlines() setup( name=NAME, version=version(), description="High level API for access to and analysis of financial data.", long_description=readme(), license='BSD License', author='David Stephens', author_email='david@davidstephens.io', url='https://github.com/davidastephens/pandas-finance', classifiers=[ 'Development Status :: 1 - Planning', 'Environment :: Console', 'Intended Audience :: Science/Research', 'Operating System :: OS Independent', 'Programming Language :: Cython', 'Programming Language :: Python', 'Programming Language :: Python :: 2', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.2', 'Programming Language :: Python :: 3.3', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', 'Topic :: Scientific/Engineering', ], keywords='data', install_requires=install_requires, packages=find_packages(exclude=['contrib', 'docs', 'tests*']), test_suite='tests', zip_safe=False, ) ================================================ FILE: tox.ini ================================================ [tox] envlist=py{26,27,32,33,34} [testenv] commands= nosetests deps= nose [testenv:py26] deps= unittest2 {[testenv]deps}