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‎.gitignore‎

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# mypy
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.mypy_cache/
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*.sqlite
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.DS_Store
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‎.travis.yml‎

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sudo: false
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language: python
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matrix:
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fast_finish: true
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include:
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- os: linux
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env:
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- PYTHON=3.5 PANDAS=0.20.1
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- os: linux
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env:
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- PYTHON=3.6 PANDAS=0.20.1
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# In allow failures
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- os: linux
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env:
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- PYTHON=3.6 PANDAS="MASTER"
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allow_failures:
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- os: linux
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env:
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- PYTHON=3.6 PANDAS="MASTER"
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install:
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- pip install -qq flake8
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# You may want to periodically update this, although the conda update
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# conda line below will keep everything up-to-date. We do this
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# conditionally because it saves us some downloading if the version is
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# the same.
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- if [[ "$PYTHON" == "2.7" ]]; then
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wget http://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh -O miniconda.sh;
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else
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wget http://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh;
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fi
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- bash miniconda.sh -b -p $HOME/miniconda
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- export PATH="$HOME/miniconda/bin:$PATH"
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- hash -r
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- conda config --set always_yes yes --set changeps1 no
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- conda config --add channels pandas
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- conda update -q conda
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# Useful for debugging any issues with conda
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- conda info -a
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- conda create -q -n test-environment python=$PYTHON coverage setuptools pytest pytest-cov
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- source activate test-environment
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- if [[ "$PANDAS" == "MASTER" ]]; then
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conda install numpy pytz python-dateutil;
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PRE_WHEELS="https://7933911d6844c6c53a7d-47bd50c35cd79bd838daf386af554a83.ssl.cf2.rackcdn.com";
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pip install --pre --upgrade --timeout=60 -f $PRE_WHEELS pandas;
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else
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conda install pandas=$PANDAS;
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fi
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- pip install coveralls --quiet
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- conda list
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- python setup.py install
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script:
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- export EOD_HISTORICAL_API_KEY=$EOD_HISTORICAL_API_KEY
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- pytest -s --cov=eod_historical_data --cov-report xml:/tmp/cov-eod_historical_data.xml --junitxml=/tmp/eod_historical_data.xml
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- flake8 --version
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- flake8 eod_historical_data tests
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after_success:
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- coveralls

‎README.md‎

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[![Build Status](https://travis-ci.org/femtotrader/python-eodhistoricaldata.svg?branch=master)](https://travis-ci.org/femtotrader/python-eodhistoricaldata)
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# Python EOD Historical Data
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A library to download data from EOD historical data https://eodhistoricaldata.com/ using:
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- [Python](https://www.python.org/)
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- [Requests](http://docs.python-requests.org/) / [Requests-cache](http://requests-cache.readthedocs.io/)
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- [Pandas](http://pandas.pydata.org/)
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## Installation
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### Install latest development version
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```bash
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$ pip install git+https://github.com/femtotrader/python-eodhistoricaldata.git
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```
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or
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```bash
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$ git clone https://github.com/femtotrader/python-eodhistoricaldata.git
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$ python setup.py install
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```
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## Usage
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Environment variable `EOD_HISTORICAL_API_KEY` should be defined using:
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```bash
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export EOD_HISTORICAL_API_KEY="YOUR_API"
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```
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You can download data simply using
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```python
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In [1]: import pandas as pd
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In [2]: pd.set_option("max_rows", 10)
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In [3]: from eod_historical_data import get_eod_data
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In [4]: df = get_eod_data("AAPL", "US")
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In [5]: df
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Out[1]:
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Open High Low Close Adjusted_close \
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Date
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2000-01-03 3.7455 4.0179 3.6317 3.9978 3.9978
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2000-01-04 3.8661 3.9509 3.6138 3.6607 3.6607
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2000-01-05 3.7054 3.9487 3.6786 3.7143 3.7143
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2000-01-06 3.7902 3.8214 3.3929 3.3929 3.3929
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2000-01-07 3.4464 3.6071 3.4107 3.5536 3.5536
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... ... ... ... ... ...
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2017-05-26 154.0000 154.2400 153.3100 153.6100 153.6100
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2017-05-30 153.4200 154.4300 153.3300 153.6700 153.6700
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2017-05-31 153.9700 154.1700 152.3800 152.7600 152.7600
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2017-06-01 153.1700 153.3300 152.2200 153.1800 153.1800
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2017-06-02 153.6000 155.4500 152.8900 155.4500 155.4500
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Volume
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Date
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2000-01-03 133949200.0
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2000-01-04 128094400.0
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2000-01-05 194580400.0
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2000-01-06 191993200.0
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2000-01-07 115183600.0
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... ...
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2017-05-26 21927600.0
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2017-05-30 20126900.0
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2017-05-31 24451200.0
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2017-06-01 16274200.0
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2017-06-02 25163841.0
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[4382 rows x 6 columns]
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```
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but if you want to avoid too much data consumption, you can use a cache mechanism.
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```python
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In [1]: import datetime
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In [2]: import requests_cache
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In [3]: expire_after = datetime.timedelta(days=1)
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In [4]: session = requests_cache.CachedSession(cache_name='cache', backend='sqlite', expire_after=expire_after)
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In [5]: df = get_eod_data("AAPL", "US", session=session)
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```
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See [tests directory](https://github.com/femtotrader/python-eodhistoricaldata/tree/master/tests) for example of other API endpoints.
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## Credits
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- Idea to create this project [came from this issue](https://github.com/pydata/pandas-datareader/issues/315) (Thanks [@deios0](https://github.com/deios0) )
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- Code was inspired by [pandas-datareader](http://pandas-datareader.readthedocs.io/)

‎eod_historical_data/__init__.py‎

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from .data import (get_api_key, get_eod_data, get_dividends, # noqa
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get_exchange_symbols, get_exchanges, # noqa
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get_currencies, get_indexes) # noqa

‎eod_historical_data/_utils.py‎

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import requests
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import datetime
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import pandas as pd
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from pandas.io.common import urlencode
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from pandas.api.types import is_number
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def _init_session(session):
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"""
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Returns a requests.Session (or CachedSession)
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"""
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if session is None:
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return requests.Session()
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return session
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def _url(url, params):
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"""
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Returns long url with parameters
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http://mydomain.com?param1=...&param2=...
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"""
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if params is not None and len(params) > 0:
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return url + "?" + urlencode(params)
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else:
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return url
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class RemoteDataError(IOError):
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"""
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Remote data exception
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"""
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pass
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def _format_date(dt):
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"""
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Returns formated date
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"""
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if dt is None:
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return dt
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return dt.strftime("%Y-%m-%d")
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def _sanitize_dates(start, end):
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"""
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Return (datetime_start, datetime_end) tuple
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"""
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if is_number(start):
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# regard int as year
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start = datetime.datetime(start, 1, 1)
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start = pd.to_datetime(start)
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if is_number(end):
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# regard int as year
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end = datetime.datetime(end, 1, 1)
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end = pd.to_datetime(end)
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if start is not None and end is not None:
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if start > end:
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raise Exception("end must be after start")
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return start, end

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