pages.histdata.features.card1Title
pages.histdata.features.card1Desc
pages.histdata.hero.subtitle
pages.histdata.features.subtitle
pages.histdata.features.card1Desc
pages.histdata.features.card2Desc
pages.histdata.features.card3Desc
pages.histdata.features.card4Desc
pages.histdata.features.card5Desc
pages.histdata.features.card6Desc
pages.histdata.pipeline.subtitle
histdata.com → ZIP (CSV) → list[OHLCVRow] → Parquet (zstd)pages.histdata.pairs.subtitle
pages.histdata.schema.subtitle
| pages.histdata.schema.colName | pages.histdata.schema.colType | pages.histdata.schema.colDesc |
|---|---|---|
| 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 |
pages.histdata.quickstart.subtitle
pip install git+https://github.com/StratCraftsAI/histdata.git# 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 2025import 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 0.0pages.histdata.faq.a1
pages.histdata.faq.a2
pages.histdata.faq.a3
pages.histdata.faq.a4
pages.histdata.faq.a5
pages.histdata.cta.subtitle