How do I fix this error?
Error:
2020-10-20 05:40:08,286 -- pyeikon -- INFO -- Set App Key: None
2020-10-20 05:40:12,522 -- pyeikon -- INFO -- Response : 500 - {"code":500,"message":"Cannot find module \".\"","statusMessage":"Internal Server Error"}
2020-10-20 05:40:12,523 -- pyeikon -- INFO -- Port 9000 was retrieved from .portInUse file
2020-10-20 05:40:12,524 -- pyeikon -- INFO -- Try to handshake on url http://localhost:9000/api/handshake...
2020-10-20 05:40:12,612 -- pyeikon -- INFO -- Response : 400 - Handshake payload is invalid.
2020-10-20 05:40:12,613 -- pyeikon -- INFO -- Set Proxy port number to 9000
2020-10-20 05:40:12,613 -- pyeikon -- INFO -- Port 9000 on local proxy was detected
2020-10-20 05:40:12,614 -- pyeikon -- DEBUG -- Request:{'Entity': {'E': 'DataGrid_StandardAsync', 'W': {'requests': [{'instruments': ["lists('Inv Trust List')"], 'fields': [{'name': 'TR.RIC'}]}]}}}
2020-10-20 05:40:31,164 -- pyeikon -- DEBUG -- HTTP Response code: 200
2020-10-20 05:40:31,165 -- pyeikon -- DEBUG -- HTTP Response: {"ErrorCode":400,"ErrorMessage":"Backend error. 400 Bad Request"}
2020-10-20 05:40:31,166 -- pyeikon -- ERROR -- Backend error. 400 Bad Request
My code:
It downloads data via the Eikon API and exports them as a CSV each morning. I use Windows Task Scheduler to initiate the Batch file which runs the python file.
#WARNING: the Eikon terminal must be running in order to connect to the API
#import packages
import eikon as ek # the Eikon Python wrapper package
import pandas as pd
import numpy as np
import datetime
from datetime import timedelta, date, datetime
from pandas.tseries.offsets import BDay
import logging.config
#logs info for bug fixing
ek.set_log_level(logging.DEBUG)
#connects to Bill's Eikon terminal
ek.set_app_key('XXXX')
#retreive the RICs from Eikon
df_rics,e = ek.get_data("lists('Inv Trust List')","TR.RIC")
#convert that into a list and set as an object
ric_list = df_rics['Instrument'].tolist()
#Slice, loop and concatenate the retrieval request - must be done in order to avoid a backend request timeout which
#happens when we use too many RICs. n can be toggled below.
n = 10
df = pd.DataFrame()
for ric_chunk in [ric_list[i:i + n]
for i in range(0, len(ric_list), n)]:
tmp_df, e = ek.get_data(ric_chunk,
['TR.RNSFilerName',
'TR.RNSAnnouncedDate',
'TR.RNSTransactionType',
'TR.RNSARNumShrsTransacted',
'TR.RNSARPctOSTransacted',
'TR.RNSARTransactionPrice',
'TR.RNSARMktValTransaction',
'TR.RNSARTotShrsPostTrans',
'TR.RNSARPctOSPostTrans'])
df = tmp_df.append(df)
#set boundary dates of the download
end_date = date.today()
start_date = end_date - BDay(2)
#set those dates in the necessary string format
end_date_str = datetime.strftime(end_date, "%Y-%m-%d")
start_date_str = datetime.strftime(start_date, "%Y-%m-%d")
#denote dates in datetime format
df['RNS Announced Date'] = pd.to_datetime(df['RNS Announced Date'])
#set the date constraints as an object
mask = (df['RNS Announced Date'] >= start_date_str) & (df['RNS Announced Date'] < end_date_str)
#set the dataframe as only those with values inside the boundary dates
df = df.loc[mask]
#rename some of columns headings, some for compatability purposes - some programs don't like the '£' symbol
df.rename(columns={'RNS Announced Date': 'Transaction Date','RNS AR Price (at Transaction) - £': 'RNS AR Price (at Transaction) GBP',
'RNS AR Market Value of Transaction - £': 'RNS AR Market Value of Transaction - GBP'},
inplace=True)
#create file name and export as CSV
todays_date = date.today()
todays_date_str = datetime.strftime(todays_date, "%Y%m%d")
df.to_csv('Daily API Download_' + todays_date_str + '.csv')
