Skip to main content
Yanked

This release has been yanked by its maintainers, and will be ignored by installers, except when explicitly specified.
Consider using release 0.8.0 instead.
Reason given by maintainers: download_bulk silently returns incomplete results for dates from 2026-08-19 onward. Upgrade to 0.6.1.

CryptoHFTData Python SDK

PyPI version Python versions License: MIT

cryptohftdata is a Python SDK for downloading high-frequency cryptocurrency market data as pandas DataFrames.

It is designed for research scripts, notebooks, and production ingestion jobs that need a simple interface over the CryptoHFTData parquet dataset.

Installation

pip install cryptohftdata

Quick Start

No API key is needed to get started: without one, downloads use the free tier, which is rate limited to 60 requests per minute per IP, and the SDK logs a warning on each download call. For unlimited rate limits, create a free account at https://www.cryptohftdata.com/signup, then export CRYPTOHFTDATA_API_KEY or pass api_key= explicitly.

import cryptohftdata as chd

# Optional: unlimited rate limits with a free API key.
# chd.configure_client(api_key=os.environ["CRYPTOHFTDATA_API_KEY"])

exchange = chd.exchanges.BINANCE_FUTURES
symbols = chd.list_symbols(exchange, data_type="trades")

if "BTCUSDT" not in symbols:
    raise RuntimeError("BTCUSDT is not currently listed for Binance futures trades")

trades = chd.get_trades(
    symbol="BTCUSDT",
    exchange=exchange,
    start_date="2025-08-01",
    end_date="2025-08-01",
    max_workers=4,
)

print(trades.head())
print(f"rows={len(trades)} columns={list(trades.columns)}")

Authentication Model

  • list_symbols(), list_exchanges(), and get_exchange_info() query API metadata and can be used without an API key.
  • Dataset download helpers such as get_trades() and get_mark_price() download parquet files. Without an API key they use the free tier, which is rate limited to 60 requests per minute per IP and logs a warning on each call. With an API key, rate limits are unlimited.
  • The convenience helpers also accept client configuration kwargs such as api_key, base_url, timeout, max_retries, rate_limit, and use_jwt.

Native S3 Access

If you want raw flat-file access instead of DataFrame helpers, exchange your existing CryptoHFTData API key for short-lived R2 S3 credentials:

import os
import requests

response = requests.post(
    "https://api.cryptohftdata.com/s3-credentials",
    headers={"X-API-Key": os.environ["CRYPTOHFTDATA_API_KEY"]},
    timeout=30,
)
response.raise_for_status()

payload = response.json()
creds = payload["credentials"]

print(payload["bucket"])
print(payload["endpoint"])
print(payload["expires_at"])

You can then pass the returned credentials into boto3:

import boto3

s3 = boto3.client(
    "s3",
    endpoint_url=payload["endpoint"],
    region_name=payload["region"],
    aws_access_key_id=creds["access_key_id"],
    aws_secret_access_key=creds["secret_access_key"],
    aws_session_token=creds["session_token"],
)

objects = s3.list_objects_v2(Bucket=payload["bucket"])
for item in objects.get("Contents", []):
    print(item["Key"])

Public API

Convenience helpers

Use the top-level helpers when you want the shortest path from notebook code to DataFrame output:

import cryptohftdata as chd

chd.configure_client(api_key="your-api-key")

trades = chd.get_trades("BTCUSDT", chd.exchanges.BINANCE_FUTURES, "2025-08-01", "2025-08-01")
mark_price = chd.get_mark_price("BTCUSDT", chd.exchanges.BINANCE_FUTURES, "2025-08-01", "2025-08-01")

For finalized higher-time-frame data, get_candles() accepts any of 1m, 3m, 5m, 15m, 1h, 4h, 6h, or 1d:

candles = chd.get_candles(
    exchange=chd.exchanges.BINANCE_FUTURES,
    symbol="BTCUSDT",
    interval="4h",
    start="2025-01-01T00:00:00Z",
    end="2025-12-31T20:00:00Z",
    max_workers=8,
)

The start and end values are inclusive candle-open-time boundaries. The SDK uses the symbol manifest to fetch only overlapping monthly Parquet objects in parallel, verifies every object size and SHA-256, and fails closed if continuous coverage is incomplete, the collector watermark is stale, or the requested leading boundary was never source-attested. Set allow_partial=True only when partial history is acceptable.

Explicit client usage

Use CryptoHFTDataClient when you want explicit configuration, context-manager usage, or cache inspection:

from cryptohftdata import CryptoHFTDataClient, exchanges

with CryptoHFTDataClient(api_key="your-api-key", timeout=60, rate_limit=10) as client:
    info = client.get_exchange_info(exchanges.BYBIT_FUTURES)
    trades = client.get_trades(
        "ETHUSDT",
        exchanges.BYBIT_FUTURES,
        "2025-08-01",
        "2025-08-01",
        max_workers=2,
    )
    print(info["supported_data_types"])
    print(client.get_cache_info())

Data Sets

All dataset download helpers return pandas DataFrames. Column names can vary by exchange, but these are the typical shapes:

Helper Typical columns
get_candles() symbol, interval, open_time, close_time, open, high, low, close, base_volume, quote_volume
get_orderbook() timestamp, side, level, price, size
get_trades() timestamp, trade_id, price, quantity, side
get_ticker() timestamp, open, high, low, close, volume
get_mark_price() timestamp, mark_price, index_price, funding_rate, next_funding_time
get_open_interest() timestamp, symbol, exchange, open_interest
get_liquidations() timestamp, side, price, quantity, order_id

You can inspect the in-package schema reference if you want a structured summary at runtime:

from cryptohftdata import get_dataset_schema

schema = get_dataset_schema("trades")
print(schema.typical_columns)

Supported Exchanges

Use the SDK itself to discover supported exchanges and dataset coverage instead of hard-coding assumptions:

import cryptohftdata as chd

for exchange in chd.list_exchanges():
    info = chd.get_exchange_info(exchange)
    print(exchange, info["type"], info["supported_data_types"])

The package also exposes constants through chd.exchanges, for example:

  • chd.exchanges.BINANCE_SPOT
  • chd.exchanges.BINANCE_FUTURES
  • chd.exchanges.BYBIT_SPOT
  • chd.exchanges.BYBIT_FUTURES
  • chd.exchanges.KRAKEN_FUTURES

Error Handling

The most common exceptions are:

  • ValidationError for invalid symbols, exchange identifiers, or date ranges
  • ConfigurationError when a dataset download is attempted without an API key
  • AuthenticationError when credentials are rejected
  • APIError for API-side failures or malformed responses

Example:

import cryptohftdata as chd

try:
    chd.get_trades("BTCUSDT", chd.exchanges.BINANCE_FUTURES, "2025-08-02", "2025-08-01")
except chd.ValidationError as exc:
    print(f"invalid request: {exc}")

Examples and Docs

  • Example scripts live in sdk/python/examples/
  • Documentation source files live in sdk/python/docs/
  • Package docstrings are available through help(cryptohftdata) and help(cryptohftdata.CryptoHFTDataClient)

Development

From a source checkout:

cd sdk/python
pip install -e ".[dev,docs,test]"
pytest
sphinx-build -b html docs docs/_build/html

Support

Metadata

Release files for cryptohftdata 0.6.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for cryptohftdata 0.6.0
File Size Uploaded
cryptohftdata-0.6.0.tar.gz 101.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for cryptohftdata 0.6.0
File Interpreter ABI Platform
cryptohftdata-0.6.0-py3-none-any.whl Python 3 none any Details

Total release size: 159.4 kB

Release files / cryptohftdata-0.6.0.tar.gz

Download URL cryptohftdata-0.6.0.tar.gz
Size 101.3 kB
Tags Source
SHA-256 checksum
How to use checksums
404840adcb355addf1428c761ec240bec25616d4c003561878f2ad9f1cf767f4
BLAKE2b-256 checksum
How to use checksums
b507b7555522e227586dcd59605fa67d6434ffdfd0b2e79ce493191d000594ae
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.13.5

Release files / cryptohftdata-0.6.0-py3-none-any.whl

Download URL cryptohftdata-0.6.0-py3-none-any.whl
Size 58.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
af3e7d29591093a8b15c66c67033c34cfeb06272d87663fa44788c36217c7afa
BLAKE2b-256 checksum
How to use checksums
97770cff92931bd2f1f2d28c5cdce5802b0b08208b70d43b1ebd028ce8044e5e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.13.5

Release history Release notifications | RSS feed

0.8.0

2 release files

0.7.0

2 release files

0.6.1

2 release files

This release

0.6.0 This release

2 release files

0.4.0

2 release files

0.3.0

2 release files

0.2.2

2 release files

0.2.1

2 release files

0.2

2 release files

0.1.9

2 release files

0.1.8

2 release files

0.1.7

2 release files

0.1.6

2 release files

0.1.5

2 release files

0.1.4

2 release files

0.1.3

2 release files

0.1.2

2 release files

0.1.1

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page