FTX US
FTX US historical market data details - available currency pairs, data coverage and data collection specifics
FTX US historical data for all it's currency pairs is available since 2020-05-22 until 2022-11-13.
Downloadable CSV files
Historical CSV datasets for the first day of each month are available to download without API key. See downloadable CSV files documentation.
data type
symbol
date
How to download all FTX US datasets for all instruments
See full downloadable CSV files documentation with datasets format spec, data samples and more.
# requires Python >=3.6
# pip install tardis-dev
from tardis_dev import datasets, get_exchange_details
import logging
# optionally enable debug logs
# logging.basicConfig(level=logging.DEBUG)
exchange = 'ftx-us'
exchange_details = get_exchange_details(exchange)
# iterate over and download all data for every symbol
for symbol in exchange_details["datasets"]["symbols"]:
# alternatively specify datatypes explicitly ['trades', 'incremental_book_L2', 'quotes'] etc
# see available options https://docs.tardis.dev/downloadable-csv-files#data-types
data_types = symbol["dataTypes"]
symbol_id = symbol["id"]
from_date = symbol["availableSince"]
to_date = symbol["availableTo"]
# skip groupped symbols
if symbol_id in ['PERPETUALS', 'SPOT', 'FUTURES']:
continue
print(f"Downloading {exchange} {data_types} for {symbol_id} from {from_date} to {to_date}")
# each CSV dataset format is documented at https://docs.tardis.dev/downloadable-csv-files#data-types
# see https://docs.tardis.dev/downloadable-csv-files#download-via-client-libraries for full options docs
datasets.download(
exchange = exchange,
data_types = data_types,
from_date = from_date,
to_date = to_date,
symbols = [symbol_id],
# TODO set your API key here
api_key = "YOUR_API_KEY",
# path where CSV data will be downloaded into
download_dir = "./datasets",
)
See docs that shows all available download options (download path customization, filenames conventions and more).
API Access and data format
Historical data format is the same as provided by real-time FTX US WebSocket API with addition of local timestamps. If you'd like to work with normalized data format instead (same format for each exchange) see downloadable CSV files or official client libs that can perform data normalization client-side.
# pip install tardis-client
import asyncio
from tardis_client import TardisClient, Channel
tardis_client = TardisClient(api_key="YOUR_API_KEY")
async def replay():
# replay method returns Async Generator
messages = tardis_client.replay(
exchange="ftx-us",
from_date="2020-06-01",
to_date="2020-06-02",
filters=[Channel(name="orderbook", symbols=["BTC/USD"])]
)
# messages as provided by FTX US real-time stream
async for local_timestamp, message in messages:
print(message)
asyncio.run(replay())
See Python client docs.
Captured real-time channels
orderbookGrouped - available since 2020-07-21 As
orderbook
channel provides data only about the orderbook's best 100 orders on either side, grouped orderbooks channel supplies orderbook data with grouped (collapsed) prices allowing retrieving lower-granularity, higher-depth information about the orderbook. We setgrouping
param to currency pairs'priceIncrement
value multiplied by 10.
Market data collection details
Market data collection infrastructure for FTX US is located in GCP europe-west2 region (London, UK). Real-time market data is captured via multiple WebSocket connections.
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