Historic Data

Kuru publishes daily L2 order book snapshots for all markets as Parquet files on S3. These files are publicly accessible and can be used for backtesting, research, and analysis.

Bucket

s3://kuru-l2-snapshots/

Files are also accessible over HTTPS:

https://kuru-l2-snapshots.s3.amazonaws.com/

File Layout

Files are partitioned by market address and date:

market={market}/date={YYYY-MM-DD}/l2_book_snapshots.parquet

Example:

market=0xf39c4fd5465ea2dd7b0756cebc48a258b34febf3/date=2025-11-24/l2_book_snapshots.parquet

Schema

Each row in the Parquet file represents a single L2 snapshot:

Column	Type	Description
`id`	`string`	Unique snapshot identifier
`market`	`string`	Market contract address (lowercase)
`blockNumber`	`int64`	Block number at snapshot time
`timestamp`	`int64`	Block timestamp (Unix epoch seconds, UTC)
`bids`	`string`	JSON array of bid price levels
`asks`	`string`	JSON array of ask price levels
`bidCount`	`int32`	Number of bid levels in the snapshot
`askCount`	`int32`	Number of ask levels in the snapshot

Price levels in bids and asks use 1e18 price precision. Sizes are stored in the market’s size precision.

Reading with Python

import pandas as pd

df = pd.read_parquet(
    "https://kuru-l2-snapshots.s3.amazonaws.com/"
    "market=0xf39c4fd5465ea2dd7b0756cebc48a258b34febf3/"
    "date=2025-11-24/l2_book_snapshots.parquet"
)
print(df.head())

Or with pyarrow directly:

import pyarrow.parquet as pq
import pyarrow.fs as pafs

s3 = pafs.S3FileSystem(region="us-east-1", anonymous=True)
table = pq.read_table(
    "kuru-l2-snapshots/"
    "market=0xf39c4fd5465ea2dd7b0756cebc48a258b34febf3/"
    "date=2025-11-24/l2_book_snapshots.parquet",
    filesystem=s3,
)

Kuru Exchange API

Kuru Exchange WebSocket Streams

TypeScript SDK

Python SDK

Kuru Flow API

Smart Contracts

Historic Data

Bucket

File Layout

Schema

Reading with Python

​Bucket

​File Layout

​Schema

​Reading with Python

Bucket

File Layout

Schema

Reading with Python