dccd 2.3.2

Download Crypto Currency Data from different exchanges.

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

From pip:

$ 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

Note: --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