Fix to issue #52

findatapy/market/datavendor.py

@@ -217,9 +217,6 @@ def translate_from_vendor_field(self, vendor_fields_list,
         # Otherwise used stored configuration files (every field needs to be
         # defined!)
         else:
-            if "-" in data_source:
-                data_source = data_source.split("-")[0]
-
             for vendor_field in vendor_fields_list:
                 try:
                     v = self.config.convert_vendor_to_library_field(

findatapy/market/datavendorcrypto.py

@@ -16,9 +16,12 @@
 #
 
 import pandas
-
+from pandas import json_normalize
+import requests
+from requests import get
 from findatapy.market.datavendor import DataVendor
 from findatapy.util import LoggerManager
+import datetime
 
 
 class DataVendorBitcoincharts(DataVendor):
@@ -31,31 +34,28 @@ def __init__(self):
 
     # implement method in abstract superclass
     def load_ticker(self, md_request):
+
         logger = LoggerManager().getLogger(__name__)
         md_request_vendor = self.construct_vendor_md_request(
             md_request)
-
         logger.info("Request data from Bitcoincharts")
-
-        data_website = 'http://api.bitcoincharts.com/v1/csv/' + \
-                       md_request_vendor.tickers[0] + '.csv.gz'
-        data_frame = pandas.read_csv(data_website,
-                                     names=['datetime', 'close', 'volume'])
-        data_frame = data_frame.set_index('datetime')
-        data_frame.index = pandas.to_datetime(data_frame.index, unit='s')
+        data_website = 'https://www.bitmex.com/api/v1/trade/bucketed?binSize=1d&partial=false&symbol=XBT&count=1000&reverse=false'
+        response = requests.get(data_website)
+        data_frame = json_normalize(response.json())
+        data_frame['timestamp'] = data_frame['timestamp'].apply(datetime.fromisoformat)
+        # data_frame = pandas.read_csv(data_website,
+        #                             names=['datetime', 'close', 'volume'])
+        data_frame = data_frame.set_index('timestamp')
+        data_frame = data_frame[['close', 'volume']]
+        # data_frame.index = pandas.to_datetime(data_frame.index, unit='s')
         data_frame.index.name = 'Date'
         data_frame = data_frame[
-            (data_frame.index >= md_request_vendor.start_date) & (
-                    data_frame.index <= md_request_vendor.finish_date)]
+            (data_frame.index >= md_request_vendor.start_date.tz_localize("UTC")) & (
+                    data_frame.index <= md_request_vendor.finish_date.tz_localize("UTC"))]
         #        data_frame = df[~df.index.duplicated(keep='last')]
-        if len(data_frame) == 0:
-            logger.warning(
-                "Warning: No data. Please change the start_date and finish_date.")
-
         data_frame.columns = [md_request.tickers[0] + '.close',
                               md_request.tickers[0] + '.volume']
         logger.info("Completed request from Bitcoincharts.")
-
         return data_frame
 
 

findatapy_examples/cryptodata_example.py

@@ -21,6 +21,7 @@
 if __name__ == "__main__":
     ###### below line CRUCIAL when running Windows, otherwise multiprocessing 
     # doesn"t work! (not necessary on Linux)
+
     from findatapy.util import SwimPool;
 
     SwimPool()
@@ -51,13 +52,13 @@
         # fields contains ["close","volume"]
         # return tick data
 
-        md_request = MarketDataRequest(start_date="11 Jan 2018",
-                                       finish_date="02 Feb 2018", cut="LOC",
+        md_request = MarketDataRequest(start_date="09 Sep 2024",
+                                       finish_date="10 Oct 2024", cut="LOC",
                                        freq="tick",
                                        data_source="bitcoincharts",
                                        category="crypto",
                                        fields=["close", "volume"],
-                                       tickers=["XBTUSD_itbit"])
+                                       tickers=["XBT"])
 
         df = market.fetch_market(md_request)
         print(df.head(5))