FTX
FTX historical market data details - available instruments, data coverage and data collection specifics
FTX historical data for all it's instruments is available since 2019-08-01 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 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'
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 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",
from_date="2020-01-01",
to_date="2020-01-02",
filters=[Channel(name="orderbook", symbols=["BTC-PERP"])]
)
# messages as provided by FTX real-time stream
async for local_timestamp, message in messages:
print(message)
asyncio.run(replay())
See Python client docs.
Captured real-time channels
markets - available since 2020-05-22
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 instruments'priceIncrement
value multiplied by 10.instrument - generated channel, available since 2020-05-13 Since FTX does not offer currently real-time WebSocket instrument info channel with next funding rate, open interest or mark price data, we simulate it by fetching that info from FTX REST API (https://docs.ftx.com/#get-future and https://docs.ftx.com/#get-future-stats) every 3-5 seconds for each derivative instrument. Such messages are marked with
"channel":"instrument"
and"generated":true
fields anddata
field has the same format as REST API responses.
Market data collection details
Market data collection infrastructure for FTX since 2020-05-14 is located in GCP asia-northeast1 (Tokyo, Japan), before that it was located in GCP europe-west2 region (London, UK). Real-time market data is captured via multiple WebSocket connections.
Last updated