See downloadable CSV files documentation and related datasets API if you'd like to access historical tick-by-tick trades, order book snapshots, incremental order book L2 updates, options chains, quotes, derivative tickers and liquidations datasets in daily intervals split by exchange, data type and symbol. It may be faster and more native to your toolkit to access the historical data this way.
# empty lines in response are being used as markers
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# for disconnect events that occurred when collecting the data
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iflen(line)<=1:
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continue
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​
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parts = line.decode("utf-8").split(" ")
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local_timestamp = parts[0]
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message = json.loads(parts[1])
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# local_timestamp string marks message arrival timestamp
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# message is a message dict as provided by exchange real-time stream
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print(local_timestamp, message)
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​
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​
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get_data_feeds()
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See also Python client library with built-in data caching that provides more convenient access to tick-level historical market data — it returns data for the whole time periods in contrast to HTTP API where single call returns data for single minute time period.
// empty lines in response are being used as markers
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// for disconnect events that occurred when collecting the data
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if(line.length ===0){
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continue
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}
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​
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const parts = line.split(' ')
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const localTimestamp = parts[0]
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const message =JSON.parse(parts[1])
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// localTimestamp string marks message arrival timestamp
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// message is a message dict as provided by exchange real-time stream
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console.log(localTimestamp, message)
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}
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}
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​
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getDataFeeds()
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See also Node.js client library with built-in data caching that provides more convenient access to tick-level historical market data — it returns data for the whole time periods in contrast to HTTP API where single call returns data for single minute time period.