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FX 1-Minute Dataset (+ Crude Oil and Stock indexes e.g. SP500)

API and dataset download for histdata.com.

Download the dataset

pip install -r requirements.txt
python download_all_fx_data.py

Expect it to take around 10 minutes if you have a fast internet connection.

API

Downloads Downloads

pip install histdata

Examples

from histdata import download_hist_data as dl
from histdata.api import Platform as P, TimeFrame as TF
  • Download tick data for 2019/06:
dl(year='2019', month='6', pair='eurusd', platform=P.GENERIC_ASCII, time_frame=TF.TICK_DATA)
  • Other possible calls:
dl(year='2019', month='6', pair='eurusd', platform=P.NINJA_TRADER, time_frame=TF.TICK_DATA_LAST)
dl(year='2019', month='6', pair='eurusd', platform=P.NINJA_TRADER, time_frame=TF.TICK_DATA_ASK)
dl(year='2019', month='6', pair='eurusd', platform=P.NINJA_TRADER, time_frame=TF.TICK_DATA_BID)
dl(year='2019', month='6', pair='eurusd', platform=P.NINJA_TRADER, time_frame=TF.ONE_MINUTE)
dl(year='2019', month='6', pair='eurusd', platform=P.GENERIC_ASCII, time_frame=TF.TICK_DATA)
dl(year='2019', month='6', pair='eurusd', platform=P.EXCEL, time_frame=TF.ONE_MINUTE)
dl(year='2019', month='6', pair='eurusd', platform=P.META_TRADER, time_frame=TF.ONE_MINUTE)
dl(year='2019', month='6', pair='eurusd', platform=P.META_STOCK, time_frame=TF.ONE_MINUTE)
dl(year='2018', month='6', pair='eurusd', platform=P.NINJA_TRADER, time_frame=TF.TICK_DATA_LAST)
dl(year='2018', month='6', pair='eurusd', platform=P.NINJA_TRADER, time_frame=TF.TICK_DATA_ASK)
dl(year='2018', month='6', pair='eurusd', platform=P.NINJA_TRADER, time_frame=TF.TICK_DATA_BID)

Data specification

This repository contains:

  • A dataset of all the FX prices (1-minute data) from 2000, in Generic ASCII.
    • More than 66 FX pairs
  • Contains some commodities:
    • WTI/USD = WEST TEXAS INTERMEDIATE in USD
    • BCO/USD = BRENT CRUDE OIL in USD
  • Contains some indexes:
    • SPX/USD = S&P 500 in USD
    • JPX/JPY = NIKKEI 225 in JPY
    • NSX/USD = NASDAQ 100 in USD
    • FRX/EUR = FRENCH CAC 40 in EUR
    • UDX/USD = US DOLLAR INDEX in USD
    • UKX/GBP = FTSE 100 in GBP
    • GRX/EUR = DAX 30 in EUR
    • AUX/AUD = ASX 200 in AUD
    • HKX/HKD = HAN SENG in HKD E - TX/EUR = EUROSTOXX 50 in EUR
  • A set of functions to download the historical prices yourself.

All the data is retrieved from: http://www.histdata.com/

Any file in a dataset is zipped and contains:

  • a CSV (semicolon separated file).
  • a status report (containing some meta data such as gaps).

Any CSV file looks like this:

20120201 000000;1.306600;1.306600;1.306560;1.306560;0
20120201 000100;1.306570;1.306570;1.306470;1.306560;0
20120201 000200;1.306520;1.306560;1.306520;1.306560;0
20120201 000300;1.306610;1.306610;1.306450;1.306450;0
20120201 000400;1.306470;1.306540;1.306470;1.306520;0
[...]

Headers are not included in the CSV files. They are:

DateTime Stamp;Bar OPEN Bid Quote;Bar HIGH Bid Quote;Bar LOW Bid Quote;Bar CLOSE Bid Quote;Volume

DateTime Stamp

Format: YYYYMMDD HHMMSS

Legend:

  • YYYY – Year
  • MM – Month (01 to 12)
  • DD – Day of the Month
  • HH – Hour of the day (in 24h format)
  • MM – Minute
  • SS – Second, in this case it will be always 00

TimeZone: Eastern Standard Time (EST) time-zone WITHOUT Day Light Savings adjustments

OPEN Bid Quote

The open (first) bid quote of the 1M bin.

HIGH Bid Quote

The highest bid quote of the 1M bin.

LOW Bid Quote

The lowest bid quote of the 1M bin.

CLOSE Bid Quote

The close (last) bid quote of the 1M bin.

Volume

Number of lots. Looks like it's always 0.

Metadata

Release files for histdata 1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for histdata 1.1
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Built distribution (wheel)

Table of built distributions (wheels) for histdata 1.1
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histdata-1.1-py3-none-any.whl Python 3 none any Details for histdata-1.1-py3-none-any.whl

Total release size: 17.8 kB

Release files / histdata-1.1.tar.gz

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Size 9.2 kB
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