66 Currency Pairs
Forex majors, crosses, commodities (WTI, Brent), and indices (S&P 500, Nikkei, DAX, and more).
Open Source
histdata
Download free Forex historical data from histdata.com and convert to Apache Parquet with zstd compression. 66 currency pairs, one command.
Python 3.10+Apache ParquetzstdMIT License66 Pairs
$ pip install git+https://github.com/StratCraftsAI/histdata.git
$ histdata --pairs EURUSD GBPUSD --year-start 2020 --year-end 2025
Downloading EURUSD 2020... OK
Downloading EURUSD 2021... OK
Downloading GBPUSD 2020... OK
...
✓ 12 Parquet files written to ./output/
Features
Everything you need to build a clean, local Forex dataset for quantitative research.
Apache Parquet Output
Parquet with zstd compression, ready for pandas, Polars, DuckDB, or any Arrow-compatible tool.
CLI Tool
Install once via pip, run from anywhere. One command to download years of data across multiple pairs.
Smart Year Handling
Past years download as single yearly ZIPs. Current year downloads month-by-month automatically.
Typed Schema
Clean OHLCV schema with timestamp[ms] and float64 columns. No manual parsing needed.
Zero Heavy Dependencies
Only requests, beautifulsoup4, and pyarrow. No heavy frameworks or complex setup required.
Pipeline
A simple four-step ETL process from raw web data to analysis-ready Parquet files.
1
Extract Token
→
2
Download ZIP
→
3
Parse CSV
→
4
Write Parquet
histdata.com → ZIP (CSV) → list[OHLCVRow] → Parquet (zstd)Supported Pairs
66 instruments across Forex, commodities, and global indices.
Forex 23
Majors
EURUSDGBPUSDUSDJPYUSDCHFUSDCADAUDUSDNZDUSDCrosses
EURAUDEURCADEURCHFEURGBPEURNZDGBPAUDGBPCADGBPCHFGBPNZDAUDNZDJPY Crosses
AUDJPYCADJPYCHFJPYEURJPYGBPJPYNZDJPYCommodities 2
BCOUSDBrent Crude Oil
WTIUSDWTI Crude Oil
Indices 9
AUXAUDASX 200
FRXEURCAC 40
GRXEURDAX 30
HKXHKDHang Seng
JPXJPYNikkei 225
NSXUSDNASDAQ 100
SPXUSDS&P 500
UDXUSDUS Dollar Index
UKXGBPFTSE 100
Output Schema
Typed Parquet columns ready for direct analysis. No post-processing required.
| Column | Type | Description |
|---|---|---|
| timestamp | timestamp[ms] | Bar open time (EST) |
| open | float64 | Open price |
| high | float64 | High price |
| low | float64 | Low price |
| close | float64 | Close price |
| volume | float64 | Tick volume |
Sourcehistdata.com — Free ASCII CSV, semicolon-delimited, no API key required
TimezoneEST (UTC-5, no DST adjustment)
FormatApache Parquet + zstd
Quick Start
Install from GitHub and start downloading data in seconds.
Installation
pip install git+https://github.com/StratCraftsAI/histdata.gitCLI Usage
# Download EURUSD 2020-2025 and convert to Parquet
histdata --pairs EURUSD --year-start 2020 --year-end 2025
# Multiple pairs
histdata --pairs EURUSD GBPUSD USDJPY --year-start 2015 --year-end 2025
# All 66 pairs
histdata --pairs all --year-start 2020 --year-end 2025Read with pandas
import pandas as pd
df = pd.read_parquet("output/EURUSD_M1.parquet")
print(df.head())
# timestamp open high low close volume
# 0 2023-01-02 17:00:00 1.07045 1.07048 1.07045 1.07048 0.0FAQ
Do I need an API key?
No. histdata.com provides free data without registration or API keys.
How long does a full download take?
Approximately 2 seconds per ZIP file (polite throttle). Downloading all 66 pairs for 5 years takes roughly 10-15 minutes.
Can I use this data with StratCraft?
Yes. The Parquet output follows the standard OHLCV schema and can be loaded directly into StratCraft as a data source.
What timezone are the timestamps in?
All timestamps are in EST (Eastern Standard Time, UTC-5). histdata.com does not apply DST adjustment.
Does it support tick data?
Yes. Pass --timeframe tick to download tick-level data instead of 1-minute bars.
Get Started
Free, open source, MIT licensed. One pip install away from clean Forex data.