dccd 2.3.3

Download Crypto Currency Data from different exchanges.

Download Crypto-Currency Data

Python package to download crypto-currency data (OHLCV, trades, order book) from multiple exchanges via REST and WebSocket APIs. Data can be saved to CSV, Excel, SQLite, PostgreSQL, or Parquet.

Installation

pip install dccd

With autonomous daemon support (APScheduler + PyYAML):

pip install "dccd[daemon]"

From source:

git clone https://github.com/ArthurBernard/Download_Crypto_Currencies_Data
cd Download_Crypto_Currencies_Data
pip install -e .

Supported exchanges

Exchange	REST OHLCV	REST Trades	REST Order Book	WS OHLCV	WS Trades	WS Order Book
Binance	✓	✓	✓		✓	✓
Coinbase	✓	✓ †	✓
Kraken	✓	✓	✓	✓	✓	✓
Bybit	✓	✓ †	✓		✓	✓
OKX	✓	✓	✓	✓	✓	✓
Bitfinex				✓ *	✓	✓
Bitmex					✓	✓

* Bitfinex WS OHLCV is aggregated from the trades stream via get_ohlc_bitfinex.
† Recent trades only (Bybit ≤ 1 000, Coinbase ≤ 100) — no deep historical pagination via the public REST API.

Presentation

Historical Downloader dccd.histo_dl
Download OHLCV data via REST APIs and save to disk. Supports chunked requests, automatic retry on rate-limit (HTTP 429), and incremental updates from the last saved timestamp.

Continuous Downloader dccd.continuous_dl
Stream real-time data (order book, trades) via WebSocket with automatic reconnection and configurable processing/saving callbacks.

Daemon dccd.daemon
Autonomous, server-side collector driven by a YAML config. Runs REST jobs on a schedule (APScheduler), opens WebSocket streams for real-time collection, and periodically syncs all local data to one or more remote destinations (NAS, S3, SFTP, …) via rclone. Multiple remotes and a configurable sync interval are supported; collection is never blocked by remote availability.

Output formats

Historical data can be saved as CSV, Excel (.xlsx), SQLite, PostgreSQL (via SQLAlchemy), or Parquet. All DataFrames are native polars.DataFrame. A pandas.DataFrame can be obtained via get_data(format='pandas').

Quick start

Historical data:

from dccd.histo_dl import FromBinance

obj = FromBinance('/path/to/data/', 'BTC', 3600, fiat='USDT')
obj.import_data(start='2024-01-01 00:00:00', end='2024-12-31 00:00:00')
obj.save(form='parquet')
df = obj.get_data()               # polars DataFrame (default)
df_pd = obj.get_data(format='pandas')  # pandas DataFrame (optional)

Incremental update (resume from last saved point):

obj.import_data(start='last', end='now').save(form='parquet')

Other exchanges:

from dccd.histo_dl import FromKraken, FromBybit, FromOKX

FromKraken('/path/', 'ETH', 3600).import_data(start='2024-01-01', end='now').save()
FromBybit('/path/', 'BTC', 86400).import_data(start='2024-01-01', end='now').save()
FromOKX('/path/', 'BTC', 3600).import_data(start='2024-01-01', end='now').save()

Trades (historical or recent):

from dccd.histo_dl import FromBinance, FromKraken

obj = FromBinance('/path/', 'BTC', 3600, fiat='USDT')
obj.import_trades(start='2024-01-01 00:00:00', end='2024-01-02 00:00:00')
obj.save_trades(form='csv')
df = obj.trades_df    # polars DataFrame — columns: TS, price, amount, type, tid

# Kraken also supports full history; Bybit/Coinbase return recent-only snapshots
FromKraken('/path/', 'BTC', 3600).import_trades(start='2024-01-01', end='2024-01-02').save_trades()

Order book snapshot:

from dccd.histo_dl import FromOKX

obj = FromOKX('/path/', 'BTC', 3600)
obj.import_orderbook(depth=50)
obj.save_orderbook(form='csv')
df = obj.orderbook_df    # columns: side, price, amount, count

Daemon (autonomous collector) — config.yml:

settings:
  data_path: /data/crypto/
  timezone: UTC

storage:
  remotes:
    - provider: rclone
      remote: "mynas:crypto/"
  sync_interval: 3600

histo_jobs:
  - exchange: binance
    pairs: [BTC/USDT, ETH/USDT]
    span: 3600
    format: parquet

stream_jobs:
  - exchange: binance
    pairs: [BTC/USDT]
    channels: [trades, book]
    time_step: 60

CLI quick start:

# Validate the config
dccd validate --config config.yml

# Backfill all OHLC history defined in config (resumable)
dccd backfill --config config.yml --start "2020-01-01 00:00:00"

# Dry run — estimate windows and time without downloading
dccd backfill --config config.yml --dry-run

# Backfill only one exchange
dccd backfill --config config.yml --exchange kraken

# One incremental batch per job, then exit (for cron)
dccd collect --config config.yml

# Continuous daemon (Ctrl-C to stop)
dccd start --config config.yml

# Add / remove a histo job in-place
dccd add --exchange kraken --pair ETH/USD --span 86400 --config config.yml
dccd remove --exchange kraken --pair ETH/USD --span 86400 --config config.yml

# Inspect all data on disk (OHLC, trades, orderbook)
dccd inventory --config config.yml

# Enable shell tab-completion (run once after install)
dccd --install-completion

--config is optional — dccd searches ./config.yml then ~/.config/dccd/config.yml when omitted.

Python API:

from dccd.daemon.config import load_config
from dccd.daemon.scheduler import run_once, build_histo_scheduler
from dccd.daemon.stream_manager import StreamManager

config = load_config('config.yml')

# One-shot: download all histo jobs once, then exit
run_once(config)

# Daemon mode: periodic REST + live WebSocket streams
scheduler = build_histo_scheduler(config)
scheduler.start()

mgr = StreamManager(config)
mgr.start()      # runs until mgr.stop() is called

Links

• PyPI: https://pypi.org/project/dccd/
• Documentation: https://download-crypto-currencies-data.readthedocs.io/
• Source: https://github.com/ArthurBernard/Download_Crypto_Currencies_Data
• Changelog: https://github.com/ArthurBernard/Download_Crypto_Currencies_Data/blob/master/CHANGELOG.md