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Getting Started

Overview of the main ways Tardis.dev historical market data can be accessed programmatically
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​Python client  providing convenient access to tick-level historical market data

​efficient data replay API returning historical market data for whole time periods (in contrast to Tardis.dev HTTP API where single call returns data for single minute time period)

built-in data caching

market data in exchange-native format​
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​Node.js client providing convenient access to tick-level historical and real-time market data

​efficient data replay API returning historical market data for whole time periods (in contrast to Tardis.dev HTTP API where single call returns data for single minute time period)

consolidated real-time data streaming API connecting directly to exchanges' WebSocket APIs

​full limit order book reconstruction logic and customizable order book snapshots

built-in data caching

market data both in exchange-native and normalized formats​
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​Locally runnable tardis-machine server providing both HTTP and WebSocket endpoints

​efficient data replay API endpoints returning historical market data for whole time periods (in contrast to Tardis.dev HTTP API where single call returns data for single minute time period)

​WebSocket API providing historical market data replay from any given past point in time with the same data format and 'subscribe' logic as real-time exchanges' APIs - in many cases existing exchanges' WebSocket clients can be used to connect to this endpoint
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consolidated real-time WebSocket data streaming API endpoint

built-in data caching

market data both in exchange-native and normalized formats

customizable order book snapshots and trade bars data types

seamless switching between real-time data streaming and historical data replay​
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​HTTP API providing historical market data feed in minute by minute slices

Each API response returned as NDJSON (new line delimited JSON)  with addition of local timestamp at the beginning of each line

market data in exchange-native format​
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C++, Java, Rust, C#, Go and R clients - we have plans for adding dedicated clients for those languages, meanwhile following alternatives are available:

use HTTP API directly

use HTTP or WebSocket API of locally installed tardis-machine server

​download data in CSV format

We're always happy to help if you'd have any problems with the integration, contact us.
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See downloadable CSV files docs if you'd like to access historical CSV datasets with normalized data.
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Poloniex
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Python Client
Last modified 2yr ago