Historical DEX trading data

The following datasets are available for historical DEX trading data. Sign up for a free API key to download the data.

Read the documentation how to get started with Trading Strategy Python library for algorithmic trading .

Available datasets

Name Tag Entries Size Format Last updated Links
Decentralised exchanges exchange_universe 5.6K 3.4 MB JSON
Trading pairs pair_universe 226.9K 28.5 MB Parquet
OHLCV candles, 1 minute candles_1m 593.1M 32.7 GB Parquet
OHLCV candles, 5 minutes candles_5m 357.3M 19.9 GB Parquet
OHLCV candles, 15 minutes candles_15m 229.0M 12.9 GB Parquet
OHLCV candles, 1 hour candles_1h 116.8M 6.6 GB Parquet
OHLCV candles, 4 hours candles_4h 53.1M 3.0 GB Parquet
OHLCV candles, daily candles_1d 16.5M 995.8 MB Parquet
OHLCV candles, weekly candles_7d 4.0M 254.0 MB Parquet
OHLCV candles, montly candles_30d 1.4M 93.6 MB Parquet
XY Liquidity, 1 minute liquidity_1m 589.3M 22.6 GB Parquet
XY Liquidity, 5 minutes liquidity_5m 352.5M 13.5 GB Parquet
XY Liquidity, 15 minutes liquidity_15m 225.5M 8.7 GB Parquet
XY Liquidity, 1 hour liquidity_1h 115.4M 4.5 GB Parquet
XY Liquidity, 4 hours liquidity_4h 52.8M 2.1 GB Parquet
XY Liquidity, daily liquidity_1d 16.9M 707.8 MB Parquet
XY Liquidity, weekly liquidity_7d 4.3M 194.2 MB Parquet
XY Liquidity, monthly liquidity_30d 1.5M 75.4 MB Parquet
Top momentum, daily top_movers_24h 500.0 656.5 KB JSON
AAVE v3 supply and borrow rates aave_v3 7.7M 696.2 MB Parquet
Uniswap trades uniswap_trades 2.0B 98.0 GB Parquet

Data logistics

Datasets are distributed in Parquet file format designed for data research. Parquet is a columnar data format for high performance in-memory datasets from Apache Arrow project.

Datasets are large. Datasets are compressed using Parquet built-in Snappy compression and may be considerably larger when expanded to RAM. We expect you to download the dataset, cache the resulting file on a local disk and perform your own strategy specific trading pair filtering before using the data. Uncompressed one minute candle data takes several gigabyte of memory.

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