retrieve and concatenate results return from historical pricing parallel requests with events

thomas.ng

Based on this github example, i learn how to create parallel requests with events , where i need to retrieve snapshot data. However, I have a question,

1. how do i concatenate the results to form a larger dataframe ? Code below produce errors, as df_snap is referenced before assignment. Can someone show me the propoer way to concatenate results with index equal to the original dataframe, so i can reconcile / join the results with the original dataframe.

df_snap = pd.DataFrame()
def concat_response(response, definition, session):



      if response.is_success:

          df_snap = pd.concat([df_snap , response.data.df], axis=0)

      else:

          print(response.http_status) 
for idx, row in data.iterrows():

    asyncio.get_event_loop().create_task(

        historical_pricing.events.Definition(universe=row['ricCode'], fields=["TRDPRC_1","MID_PRICE"],start = row['GMT Time'], count = 1).get_data_async(on_response = concat_response, closure = str(idx))

    )

Jirapongse

@thomas.ng

Thank you for reaching out to us.

You can use the global keyword in the concat_response method.

df_snap = pd.DataFrame()
def concat_response(response, definition, session):
      global df_snap
      print(response.data.df)

      if response.is_success:

          df_snap = pd.concat([df_snap , response.data.df], axis=0)

      else:

          print(response.http_status)