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API for accessing Lake crypto market data

Project description

Lake API

Pypi package status Documentation status Build status

API for accessing Lake crypto market data.

Lake is a service providing historical cryptocurrency market data in high detail, including order book data, tick trades and 1m trade candles. It is tuned for convenient quant and machine-learning purposes and so offers high performance, caching and parallelization.

Usage

If you don’t have a paid plan with AWS credentials, you can access sample data:

import lakeapi

lakeapi.use_sample_data(anonymous_access = True)

df = lakeapi.load_data(
    table="book",
    start=None,
    end=None,
    symbols=["BTC-USDT"],
    exchanges=["BINANCE"],
)

With paid access, you can query any data:

import lakeapi

# Downloads SOL-USDT depth snapshots for last 2 days from Kucoin exchange
df = lakeapi.load_data(
    table="trades",
    start=datetime.datetime.now() - datetime.timedelta(days=2),
    end=None,
    symbols=["SOL-USDT"],
    exchanges=["KUCOIN"],
)

We recommend putting .lake_cache directory into .gitignore, because Lake API stores cache into this directory in the working directory.

History

0.6.0 (2023-08-14)

  • support for python3.11

0.5.0 (2023-05-21)

  • support for funding, open_interest and liquidations list_data

  • improve data type typing

0.4.5 (2023-01-09)

  • grow default cache size limit from 3 GB to 10 GB

0.4.3 (2022-12-09)

  • small documentation improvements

0.4.2 (2022-12-09)

  • fix trades_mpid issue

0.4.1 (2022-12-05)

  • fix warning messages in anonymous mode

0.4.0 (2022-11-19)

  • level_1 data added to typing

  • s3 user agent set to lakeapi

0.3.0 (2022-11-04)

  • Typing bugfix

  • Last modified filters for list_data

0.2.0 (2022-10-26)

  • New feature for listing available data.

0.1.3 (2022-10-13)

  • Corrupted cache bugfix

0.1.2 (2022-10-10)

  • Caching and requirements improvements.

0.1.1 (2022-10-09)

  • Python2.7 support and documentation improvements.

0.1.0 (2022-10-08)

  • First release on PyPI.

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