#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
 
#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 = 25
 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 compatibility 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')