FTX US

FTX US historical market data details - available currency pairs, data coverage and data collection specifics

Delisted exchange.

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

trades

BTC-USD

2020-06-01

incremental_book_L2

BTC-USD

2020-06-01

quotes

BTC-USD

2020-06-01

trades

SPOT

2020-06-01

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).

// npm install tardis-dev
// requires node version >=12
const { downloadDatasets, getExchangeDetails } = require('tardis-dev')

;(async () => {
  const exchange = 'ftx-us'
  const exchangeDetails = await getExchangeDetails(exchange)

  // iterate over and download all data for every symbol
  for (const symbol of exchangeDetails.datasets.symbols) {
    // alternatively specify dataTypes explicitly ['trades', 'incremental_book_L2', 'quotes'] etc
    // see available options https://docs.tardis.dev/downloadable-csv-files#data-types
    const dataTypes = symbol.dataTypes
    const symbolId = symbol.id

    const from = symbol.availableSince
    const to = symbol.availableTo

    // skip groupped symbols
    if (['PERPETUALS', 'SPOT', 'FUTURES'].includes(symbolId)) {
      continue
    }

    console.log(`Downloading ${exchange} ${dataTypes} for ${symbolId} from ${from} to ${to}`)

    // 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
    await downloadDatasets({
      exchange,
      dataTypes,
      from,
      to,
      symbols: [symbolId],
      // TODO: set your API key here
      apiKey: 'YOUR_API_KEY',
      //  path where CSV data will be downloaded into
      downloadDir: './datasets'
    })
  }
})()

See docs that shows all available download options (download path customization, filenames conventions and more).

curl -o ftx_us_trades_2021-11-01_BTC-USD.csv.gz https://datasets.tardis.dev/v1/ftx-us/trades/2021/11/01/BTC-USD.csv.gz

See datasets API reference which allows downloading single file at once.

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.

// npm install tardis-dev
const { replay } = require('tardis-dev');

async function run() {
  try {
    const messages = replay({
      exchange: 'ftx-us',
      from: '2020-06-01',
      to: '2020-06-02',
      filters: [{ channel: 'orderbook', symbols: ['BTC/USD'] }],
      apiKey: 'YOUR_API_KEY'
    });

    // messages as provided by FTX US real-time stream
    for await (const { localTimestamp, message } of messages) {
      console.log(localTimestamp, message);
    }
  } catch (e) {
    console.error(e);
  }
}

run();

See Node.js client docs.

curl -g 'https://api.tardis.dev/v1/data-feeds/ftx-us?from=2020-06-01&filters=[{"channel":"orderbook","symbols":["BTC/USD"]}]&offset=0'

See HTTP API docs.

curl -g 'localhost:8000/replay?options={"exchange":"ftx-us","filters":[{"channel":"orderbook","symbols":["BTC/USD"]}],"from":"2020-06-01","to":"2020-06-02"}'

Tardis-machine is a locally runnable server that exposes API allowing efficiently requesting historical market data for whole time periods in contrast to HTTP API that provides data only in minute by minute slices.

See tardis-machine docs.

Captured real-time channels

Click any channel below to see HTTP API response with historical data recorded for it.

orderbook
trades
markets
orderbookGrouped - available since 2020-07-21 Asorderbook 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 set grouping 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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# 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", )

// npm install tardis-dev // requires node version >=12 const { downloadDatasets, getExchangeDetails } = require('tardis-dev') ;(async () => { const exchange = 'ftx-us' const exchangeDetails = await getExchangeDetails(exchange) // iterate over and download all data for every symbol for (const symbol of exchangeDetails.datasets.symbols) { // alternatively specify dataTypes explicitly ['trades', 'incremental_book_L2', 'quotes'] etc // see available options https://docs.tardis.dev/downloadable-csv-files#data-types const dataTypes = symbol.dataTypes const symbolId = symbol.id const from = symbol.availableSince const to = symbol.availableTo // skip groupped symbols if (['PERPETUALS', 'SPOT', 'FUTURES'].includes(symbolId)) { continue } console.log(`Downloading ${exchange} ${dataTypes} for ${symbolId} from ${from} to ${to}`) // 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 await downloadDatasets({ exchange, dataTypes, from, to, symbols: [symbolId], // TODO: set your API key here apiKey: 'YOUR_API_KEY', // path where CSV data will be downloaded into downloadDir: './datasets' }) } })()

# 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())

// npm install tardis-dev const { replay } = require('tardis-dev'); async function run() { try { const messages = replay({ exchange: 'ftx-us', from: '2020-06-01', to: '2020-06-02', filters: [{ channel: 'orderbook', symbols: ['BTC/USD'] }], apiKey: 'YOUR_API_KEY' }); // messages as provided by FTX US real-time stream for await (const { localTimestamp, message } of messages) { console.log(localTimestamp, message); } } catch (e) { console.error(e); } } run();