Continuous 500 Internal Server Error and Gateway Time-out errors

Arries

Hi all, I have a few python models that have ran into updating issues in the past three weeks or so. On some days the models update just fine, but on other days (like today) I keep getting either an 500 Internal Server Error or a Gateway Time-out error.

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Here is a quick example of the code I am using to pull in the data:

lookback_days = 240 # You can change this number

today = dt.datetime.today()

start_date = (today - dt.timedelta(days=lookback_days)).strftime('%Y-%m-%d')

end_date = (today - dt.timedelta(days=1)).strftime('%Y-%m-%d') # Adjusted to get yesterday's date

pairs_rics = ['AUDCAD=R' , 'AUDCHF=R' , 'AUDNZD=R' , 'AUDJPY=R' , 'AUD=' ,

'CADCHF=R' , 'CADJPY=R' ,

'NZDCAD=R' , 'NZDCHF=R' , 'NZDJPY=R' , 'NZD=' ,

'EURAUD=R' , 'EURCAD=R' , 'EURCHF=R' , 'EURJPY=R' , 'EURNZD=R' , 'EURGBP=R' , 'EUR=' ,

'GBPAUD=R' , 'GBPCAD=R' , 'GBPCHF=R' , 'GBPJPY=R' , 'GBPNZD=R' , 'GBP=' ,

'CHFJPY=R' ,

'CHF=' , 'JPY=' , 'CAD=',

'US2YT=RR', 'DE2YT=RR', 'GB2YT=RR', 'JP2YT=RR', 'AU2YT=RR', 'NZ2YT=RR', 'CA2YT=RR', 'CH2YT=RR',

'US10YT=RR', 'DE10YT=RR', 'GB10YT=RR', 'JP10YT=RR', 'AU10YT=RR', 'NZ10YT=RR', 'CA10YT=RR', 'CH10YT=RR']

final_data = pd.DataFrame()

for pair in pairs_rics:

data = ek.get_timeseries(pair,

fields=["CLOSE"],

start_date=start_date,

end_date=today, # use end_date instead of today

interval='daily')

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I was told that I needed to reduce the amount of RICs and the lookback period, but even after limiting it to one RIC and just 5 lookback days I still got the same error.

Is there any advice on how I can solve this?

Someone told me I should consider moving away from the ek.get_timeseries and rather using rd.get_history but am struggling to find the same output compared to the other.

Any advice would be appreciated.

Regards.

jonathan.legrand

Hi @Arries,

Having a look at this article, I thought it best to try the below. Please let me know if it helps. Indeed, it is best with rd, but only via the Content Layer:

import datetime as dt
import pandas as pd
import refinitiv.data as rd
rd.open_session(config_name="C:/Example.DataLibrary.Python-main/Configuration/refinitiv-data.config.json") # https://github.com/LSEG-API-Samples/Example.DataLibrary.Python/blob/main/Configuration/refinitiv-data.config.json
rd.open_session("desktop.workspace")

lookback_days = 10
today = dt.datetime.today()
start_date = (today - dt.timedelta(days=lookback_days)).strftime('%Y-%m-%d')
end_date = (today - dt.timedelta(days=1)).strftime('%Y-%m-%d') # Adjusted to get yesterday's date

pairs_rics = [
    'AUDCAD=R' , 'AUDCHF=R' , 'AUDNZD=R' , 'AUDJPY=R' , 'AUD=' ,
    'CADCHF=R' , 'CADJPY=R' , 'NZDCAD=R' , 'NZDCHF=R' , 'NZDJPY=R' , 'NZD=' ,
    'EURAUD=R' , 'EURCAD=R' , 'EURCHF=R' , 'EURJPY=R' ,
    'EURNZD=R' , 'EURGBP=R' , 'EUR=' ,
    'GBPAUD=R' , 'GBPCAD=R' , 'GBPCHF=R' , 'GBPJPY=R' , 'GBPNZD=R' , 'GBP=' ,
    'CHFJPY=R' , 'CHF=' , 'JPY=' , 'CAD=',
    'US2YT=RR', 'DE2YT=RR', 'GB2YT=RR', 'JP2YT=RR', 'AU2YT=RR',
    'NZ2YT=RR', 'CA2YT=RR', 'CH2YT=RR',
    'US10YT=RR', 'DE10YT=RR', 'GB10YT=RR', 'JP10YT=RR',
    'AU10YT=RR', 'NZ10YT=RR', 'CA10YT=RR', 'CH10YT=RR']

def chunks(lst, n):
    """Yield successive n-sized chunks from lst."""
    _lst = []
    for i in range(0, len(lst), n):
        _lst.append(lst[i:i + n])
    return _lst

batched_rics = chunks(lst = pairs_rics, n = 10)

for i,j in enumerate(batched_rics):
    __optn_mrkt_price_gmt = rd.content.historical_pricing.summaries.Definition(
        universe=j,
        start=start_date,
        end=end_date,
        interval='P1D', # 'PT1M', 'PT10M', rd.content.historical_pricing.Intervals.DAILY
        fields=['TRDPRC_1', 'SETTLE', 'BID', 'ASK']).get_data().data.df # 'LST_TRD_PR', 'CF_LAST', 'CF_CLOSE', 'SETTLE', 'TRDPRC_1', 'BID', 'ASK'
    if i == 0:
        final_data = __optn_mrkt_price_gmt.T
    else:
        final_data = final_data.append(__optn_mrkt_price_gmt.T)
final_data = final_data.T
display(final_data)
rd.close_session()