crypto-lob-stream 0.6.1

Stream Binance Level 2 order book and trade data to local disk or GCS.

crypto-lob-stream

Stream Binance Level 2 order book and trade data to local disk or Google Cloud Storage.

High-quality, granular LOB data is difficult to access openly. Most sources are paywalled, time-limited, or never publicly released. This package makes it easy for anyone to collect continuous, fully reconstructable order book and trade data for any Binance pair and store it in an open, analysis-ready format. Monthly snapshots are published freely on Hugging Face for the research community.

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Install

# Local output only
pip install crypto-lob-stream

# With Google Cloud Storage support
pip install crypto-lob-stream[gcs]

Requires Python 3.10+.

Windows users: if you see a warning that the Scripts directory is not on PATH, add it via System Settings > Environment Variables > Path. Until then, run with python -m crypto_lob_stream.cli instead of crypto-lob-stream.

---

Quickstart

Stream to local disk

from crypto_lob_stream import LOBStreamer

streamer = LOBStreamer(
    assets=["BTCUSDT", "ETHUSDT", "SOLUSDT"],
    output="local",
    output_dir="./lob_data",
)
streamer.run()

Stream to GCS

streamer = LOBStreamer(
    assets=["BTCUSDT"],
    output="gcs",
    bucket="my-gcs-bucket",
)
streamer.run()

Real-time callback

def on_trade(record):
    print(f"{record['asset']} {record['price']} x {record['quantity']}")

streamer = LOBStreamer(
    assets=["BTCUSDT"],
    output="local",
    on_trade=on_trade,
)
streamer.run()

CLI

# Local
crypto-lob-stream --assets BTCUSDT,ETHUSDT --output local --output-dir ./data

# GCS (after running setup)
crypto-lob-stream --assets BTCUSDT,ETHUSDT,SOLUSDT --output gcs

# Custom flush interval (seconds)
crypto-lob-stream --assets BTCUSDT --output local --flush-interval 60

---

GCS setup

If you want to stream to Google Cloud Storage, run the setup wizard once before your first stream. It saves your credentials so you never have to configure them again.

Step 1 -- Create a GCS bucket

Go to console.cloud.google.com, create a project, and create a bucket in your preferred region.

Step 2 -- Create a service account

In the GCP Console, go to IAM & Admin > Service Accounts. Create a new service account, assign it the Storage Object Admin role on your bucket, and download the JSON key file.

Step 3 -- Run the setup wizard

crypto-lob-stream setup

You will be prompted for your bucket name and the path to your JSON key file:

crypto-lob-stream -- GCS Setup
----------------------------------
GCS bucket name: my-bucket
Path to service account JSON key: ~/Downloads/my-key.json

Saved config to ~/.crypto_lob_stream/config.json
Testing connection to gs://my-bucket ... OK

Setup complete. You can now run:
  crypto-lob-stream --assets BTCUSDT,ETHUSDT --output gcs

Config is saved to ~/.crypto_lob_stream/config.json. From this point on, just run with --output gcs and credentials are applied automatically.

Check saved config

crypto-lob-stream config

Override credentials per run

crypto-lob-stream --assets BTCUSDT --output gcs --bucket other-bucket --credentials /path/to/other-key.json

---

Output structure

{output_dir}/
  trades/{asset}/YYYY-MM-DD-HH.parquet
  depth/{asset}/YYYY-MM-DD-HH.parquet
  snapshots/{asset}/YYYY-MM-DD-HHmmss.parquet

All files are Snappy-compressed Parquet. Files are flushed to disk or uploaded to GCS every 5 minutes by default.

---

Schemas

trades

Field	Type	Notes
timestamp_ms	int64	Event time (Unix ms)
asset	string	e.g. BTCUSDT
trade_id	int64	Binance trade ID
price	float64
quantity	float64
buyer_maker	bool	True if the buyer is the market maker

depth (diff events)

Field	Type	Notes
timestamp_ms	int64	Receipt time (Unix ms)
asset	string
side	string	bid or ask
price	float64
quantity	float64	0.0 means the level was removed
first_update_id	int64	U field from Binance diff event
last_update_id	int64	u field -- sequence number for replay ordering

snapshots

Field	Type	Notes
timestamp_ms	int64	Fetch time (Unix ms)
asset	string
side	string	bid or ask
price	float64
quantity	float64
last_update_id	int64	REST snapshot lastUpdateId -- anchor for diff replay

A REST snapshot is fetched from Binance (1000 levels per side) immediately after every WebSocket connection, including reconnects. This ensures there is always a valid anchor point for book reconstruction.

---

LOB reconstruction

To reconstruct the full order book at any point in time from stored data:

1. Load the nearest snapshots/ file whose timestamp_ms precedes your target window. The last_update_id column is the snapshot anchor.
2. Discard all depth diff rows where last_update_id <= snapshot_last_update_id.
3. Verify the first retained diff satisfies first_update_id <= snapshot_last_update_id + 1. If not, a gap exists -- use the next available snapshot.
4. Apply diffs in ascending last_update_id order. For each price level, set quantity to the diff value. Remove the level if quantity == 0.0.

To detect the schema version programmatically:

import pyarrow.parquet as pq

schema = pq.read_schema("depth/btcusdt/2026-06-03-15.parquet")
is_reconstructable = "last_update_id" in schema.names

---

LOBStreamer parameters

Parameter	Type	Default	Description
assets	list[str]	required	Binance symbols, e.g. ["BTCUSDT", "ETHUSDT"]
output	str	"local"	"local" or "gcs"
output_dir	str	"./lob_data"	Base directory for local output
bucket	str	None	GCS bucket name (required for GCS output if not saved via setup)
fallback_dir	str	"./lob_fallback"	Local directory for failed GCS uploads
flush_interval	int	300	Seconds between buffer flushes
on_trade	callable	None	Optional callback invoked per trade record
on_depth	callable	None	Optional callback invoked per depth record
log_dir	str	"./logs"	Directory for rotating log files

---

Data limitations

Depth files collected before 2026-06-03 14:38:49 UTC do not contain first_update_id or last_update_id and cannot be used for LOB reconstruction. They may still be useful for analysing the distribution of price-level updates and trade activity. Files from that timestamp onward are fully reconstructable.

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Hugging Face dataset

Monthly snapshots of data collected by this package are published at Hugging Face for free public use. Each release includes a dataset card noting the schema cutoff date and any known gaps.

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Contributing

Issues and pull requests are welcome. If you add support for a new exchange or output target, please include tests.

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License

MIT