crypto-lob-stream / README.md
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---
license: mit
task_categories:
- time-series-forecasting
tags:
- finance
- cryptocurrency
- order-book
- market-microstructure
- high-frequency
pretty_name: Binance BTC/ETH/SOL L2 Order Book & Trades
configs:
- config_name: depth
data_files: "depth/binance/*/*.parquet"
- config_name: trades
data_files: "trades/binance/*/*.parquet"
- config_name: snapshots
data_files: "snapshots/binance/*/*.parquet"
---
# Binance BTC/ETH/SOL - L2 Order Book, Trades & Snapshots
Continuous Level-2 order book (depth diffs), trades, and periodic full-book
snapshots for BTCUSDT, ETHUSDT, and SOLUSDT, captured from Binance's public
WebSocket feeds with [`crypto-lob-stream`](https://pypi.org/project/crypto-lob-stream/)
and published monthly as a contribution to open market-microstructure research.
Full depth-of-book data is paywalled or licensed for most asset classes; crypto
is the exception, where the raw feeds are genuinely public. This dataset exists
to lower that data barrier for independent researchers and students.
## Layout
```
depth/binance/{ASSET}/YYYY-MM.parquet # order book diff events
trades/binance/{ASSET}/YYYY-MM.parquet # executed trades
snapshots/binance/{ASSET}/*.parquet # full-book anchors for replay
```
Files are Snappy-compressed Parquet, compacted to one file per month per asset,
and carry an explicit `exchange` column - i.e. the native schema of the
`crypto-lob-stream` package, so its reconstruction helper works directly.
## Reconstructing the order book
Depth rows are diffs, not a standing book. Replay a snapshot plus every
subsequent diff, pruning to your intended depth after each update, to rebuild
the book at any instant. The package does this for you, ghost-level-safe:
```python
pip install crypto-lob-stream
from crypto_lob_stream import reconstruct
book = reconstruct("./depth", exchange="binance", asset="BTCUSDT")
bids, asks = book.top(n=10)
```
## Coverage & limitations
- **Reconstructable from 2026-06-03 onward.** Every depth file here carries
`first_update_id` / `last_update_id`, so the diff sequence can be replayed
against the snapshots. Earlier data lacks sequence ids and is not published.
- **Known gap — July 2026:** capture paused ~2026-07-05 20:56 to ~21:39 UTC
(~43 min) for all three symbols across depth and trades, due to a host
restart. A fresh snapshot was written on reconnect, so books before and
after the gap reconstruct cleanly; do not replay a diff sequence across it.
- Reconstruct each market on its own - never merge books across exchanges.
- Check the diff sequence for continuity before replaying across a boundary.