Get high resolution historical Bitcoin OHLCV from Amberdata using a jumping rather than sliding window.

jumping_window_ohlcv.py

dfs = []
n_days = 5

for i in range(n_days):
    print(f"Iteration: {i}")
    # get the start and end dates in timestamps
    startDate = results.timestamp.min() + timedelta(i-1)
    endDate = startDate + timedelta(1)
    
    # convert to UNIX format
    startDate = str(round(startDate.timestamp()*10**3))
    endDate = str(round(endDate.timestamp()*10**3))

    # the url for our endpoint
    url = "https://web3api.io/api/v2/market/ohlcv/btc_usd/historical"
    
    # our query
    querystring = {
        "timeInterval": "minutes", 
        "timeFormat": "iso",
        'startDate': startDate, 
        'endDate': endDate, 
        "exchange": "bitfinex"
    }
    
    # the API key
    headers = {'x-api-key': api_key["AMBERDATA_API_KEY"]}

    # the response for our query
    payload = get_response(url, headers, querystring)
    
    # we save the OHLCV data
    bfx = payload['data']['bitfinex']

    # get the columns and make a dataframe
    columns = payload['metadata']['columns']
    bfx_df = pd.DataFrame(bfx, columns=columns)
    # append the dataframe to a list
    dfs.append(bfx_df)

# combine the several days of OHLCV data
ohlcv = pd.concat(dfs)