Metadata-Version: 1.1
Name: iqfeed
Version: 0.4.1
Summary: IQFeed / DTN Data downloader
Home-page: http://github.com/tibkiss/iqfeed
Author: Tibor Kiss
Author-email: tibor.kiss@gmail.com
License: Apache License, Version 2.0
Description: IQFeed/DTN Downloader
        =====================
        
        This project provides command line tool and Python library to access DTN
        / IQFeed's historical data for equities. The provided command line tool
        ('iqfeed') is capable downloading 1 minute historical data from IQFeed
        client and store it in '.csv.gz' format.
        
        Prerequisites
        -------------
        
        -  Python 2.7 (`pypy <http://pypy.org>`__ is recommended), DocOpt, PyTZ,
           backports.functools\_lru\_cache
        -  IQFeed account
        -  IQFeed client (e.g. `bratchenko's
           'iqfeed-docker' <https://github.com/bratchenko/docker-iqfeed>`__)
        
        Installation
        ------------
        
        ``$ pip install iqfeed``
        
        Usage from command line
        -----------------------
        
        The provided ``iqfeed`` utility can be used to download CSV files from
        DTN / IQFeed.
        
        Help screen:
        
        ::
        
            iqfeed: Data downloader for Iqfeed/DTN
                 Tibor Kiss <tibor.kiss@gmail.com> - Copyright (c) 2012-2016 All rights reserved
        
            Usage:
              iqfeed process-file <filename> <start_year> <end_year> [-d DIR] [-i CON] [-t TZ] [-D]
              iqfeed download <instrument> <start_year> <end_year> [-d DIR] [-i CON] [-t TZ] [-D]
              iqfeed -h | --help
        
            Commands:
              download            Download the specified instrument
              get-from-file       Download instruments listed in the specified file
        
            Options:
              -d DIR --download-dir DIR   Directory where the files will be downloaded [default: .]
              -i CON --iqfeed CON         IQFeed host & port [default: localhost:9100]
              -t TZ --tz TZ               Time zone [default: US/Eastern]
              -D                          Debug mode
              -h                          Help screen
        
            Note:
            Date format for end_date and start_date: YYYYMMDD
        
        Start IQFeed client
        ~~~~~~~~~~~~~~~~~~~
        
        ``$ docker run -e LOGIN='<username>' -e PASSWORD='<password>' -p 5009:5010 -p 9100:9101 bratchenko/iqfeed``
        
        Download single instrument (SPY) for the time period 2010-2016
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        ``$ iqfeed download SPY 2010 2016``
        
        Download multiple instruments listed in a text file
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        ``$ iqfeed process-file russell-3000.lst 2016 2016``
        
        Usage from Python
        -----------------
        
        Use the following snippet to obtain list of Bar objects.
        
        .. code:: python
        
            import pytz
            from iqfeed import get_bars
        
            instrument = 'GLD'
            start_date = '20150101'
            end_date = '20151231'
            tz = pytz.timezone('US/Eastern')
            seconds_per_bar = 60  # For 1M data
            iqfeed_host = 'localhost'
            iqfeed_port = 9100
        
            bars = get_bars(instrument, start_date, end_date, tz, seconds_per_bar, iqfeed_host, iqfeed_port)
        
        The Bar object is a named tuple which holds the Open, High, Low, Close
        and Volume values for the given time:
        
        .. code:: python
        
            IQFeedBar(datetime=datetime.datetime(2015, 1, 2, 9, 30, tzinfo=<DstTzInfo 'US/Eastern' EST-1 day, 19:00:00 STD>), open=112.46, high=112.46, low=112.45, close=112.46, volume=192104)
        
        License
        -------
        
        `Apache License Version 2.0 <http://www.apache.org/licenses/>`__
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Office/Business :: Financial :: Investment
