Dukascopy tick downloader and candle exporter for use in backtesting your trading strategies.
This tool downloads raw tick data from Dukascopy, converts it into clean, deterministic CSV candle files, and writes a metadata sidecar describing exactly how the data was produced.
It is designed to be run once per dataset, not repeatedly during backtests.
Install:
pip install tradedesk-dukascopyExport 5-minute candles for EURUSD:
tradedesk-dc-export --symbols EURUSD \
--from 2025-01-01 --to 2025-01-31 \
--resample 5min \
--out data \
--cache-dir /paperclip/tradedesk/marketdata \
--price-divisor 1000 \
--workers 1This produces:
data/
EURUSD_5MIN_bid.csv
EURUSD_5MIN_bid.csv.meta.json
EURUSD_5MIN_ask.csv
EURUSD_5MIN_ask.csv.meta.json
You can now point your backtest engine at the bid or ask CSV directly, depending on which price side you want to replay.
Dukascopy tick prices are stored as integers or scaled values depending on the instrument.
This tool applies price scaling once, at export time, using --price-divisor.
Examples:
| Instrument | Typical divisor |
|---|---|
| EURUSD | 1000 |
| USDJPY | 100000 |
| Indices | 1 or 10 |
If unsure, use probe mode:
tradedesk-dc-export --symbols GBPSEK \
--from 2025-07-01 --to 2025-07-01 \
--probeProbe mode prints sample ticks at different divisors without writing files.
GBPSEK: detected tick price format = int
GBPSEK @ 2025-07-01T00:00:00+00:00 (int): first 10 ticks
first tick raw: 2025-07-01T00:00:00.326000+00:00 bid_i 1297675 ask_i 1298619 vol 1.149999976158142
divisor 1: bid 1297675.000000 ask 1298619.000000
divisor 10: bid 129767.500000 ask 129861.900000
divisor 100: bid 12976.750000 ask 12986.190000
divisor 1000: bid 1297.675000 ask 1298.619000
divisor 10000: bid 129.767500 ask 129.861900
divisor 100000: bid 12.976750 ask 12.986190
using --price-divisor 1.0:
2025-07-01T00:00:00.326000+00:00 bid 1297675.0 ask 1298619.0 bid_vol 1.149999976158142
2025-07-01T00:00:01.128000+00:00 bid 1297800.0 ask 1298661.0 bid_vol 0.9200000166893005
2025-07-01T00:00:01.329000+00:00 bid 1297796.0 ask 1298621.0 bid_vol 0.9200000166893005
2025-07-01T00:00:03.335000+00:00 bid 1297796.0 ask 1298591.0 bid_vol 0.9200000166893005
2025-07-01T00:00:03.737000+00:00 bid 1297842.0 ask 1298695.0 bid_vol 1.149999976158142
2025-07-01T00:00:05.340000+00:00 bid 1297850.0 ask 1298655.0 bid_vol 0.9200000166893005
2025-07-01T00:00:06.542000+00:00 bid 1297862.0 ask 1298709.0 bid_vol 0.9200000166893005
2025-07-01T00:00:08.546000+00:00 bid 1297874.0 ask 1298709.0 bid_vol 0.9200000166893005
2025-07-01T00:00:10.556000+00:00 bid 1297877.0 ask 1298724.0 bid_vol 0.9200000166893005
2025-07-01T00:00:12.562000+00:00 bid 1297839.0 ask 1298684.0 bid_vol 1.149999976158142
This tool is intended to be used as a data preparation step, not as part of your backtest runtime loop:
- Download and export historical data once
- Commit or archive the output CSV + metadata if applicable
- Run fast, deterministic backtests against local files
When run, the tool will fetch new or missing raw data files from Dukascopy for the instrument(s) and periods that you specify. These are always compressed, hourly files. Once fetched, the files are converted to CSV format tick files and aggregated into daily files. When all 24 hour periods are available and the daily CSV file is written to the cache, the raw native files are discarded.
Dukascopy downloads are notoriously slow and unreliable due to rate limiting and limited resources available for their service. This tool has multiple strategies to address and work around those limitations, including retaining the raw files until a full daily file of CSV data can be written. Re-running the same tradedesk-dc-export is both safe and efficient - it will only attempt to fill in gaps and will finish very quickly where downloads or conversions are already cached.
For this to work well though, you should treat the cache directory as a permanent, not a transient store of local market data that can be added to over time. Best practice is to always specify a --cache-dir that points to your common market data trove wherever you use the tool from.
Each symbol export uses up to two downloader threads internally. --workers
controls how many symbols are exported concurrently, so the total request
concurrency can grow quickly.
Dukascopy becomes unreliable when too many requests are in flight. If you want
to stay near the safest limit of two concurrent download threads, keep
--workers 1. Re-running the same command is idempotent and is the intended way
to fill cache gaps caused by failed hours.
If you resample to an --out location, the tool writes separate bid and ask
OHLCV CSV files with UTC timestamps that include an explicit +00:00 offset:
timestamp,open,high,low,close,volume
2025-01-01 00:00:00+00:00,1.10342,1.10361,1.10311,1.10355,1234.0
- Timestamps are always UTC
- Prices are floats after applying the price divisor
- Volume is derived from tick volume
Every output CSV is accompanied by a metadata file describing how it was generated:
{
"data_type": "candles",
"generated_at": "2026-03-06T16:58:50.397630Z",
"params": {
"date_from": "2026-01-05",
"date_to": "2026-01-06",
"price_side": "bid",
"resample": "15MIN"
},
"price_divisor": 10.0,
"schema_version": "1",
"source": "dukascopy",
"symbol": "GBPUSD",
"timestamp_format": "iso8601_utc"
}This ensures datasets are self-describing and reproducible, even months later.
--resample requires --out. If you run the tool without --resample, it will
populate the --cache-dir with the cached source data and daily candles but it
will not emit the final range-level output CSVs in --out.
- Python 3.11+
- Internet access to Dukascopy datafeed
Licensed under the Apache License, Version 2.0. See: https://www.apache.org/licenses/LICENSE-2.0
Copyright 2026 Radius Red Ltd.
See CONTRIBUTING.md for guidelines on contributing to tradedesk-dukascopy.