Fetching Revenue, net income and Eps data.

I'm trying to retrieve the revenue, net income, and EPS data for around 4000 RICs, one RIC at a time, but I'm having trouble doing so. I'm able to get the data up to 100 but after that I get a 400 backend error message. I'm using Refinitiv Eikon's most recent version, 4.0.63. Additionally, I am not exceeding the limit according to the API docs.

The code screenshot I attempted with the Refinitiv Eikon version is posted below.

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Accepted answers

Jirapongse

@vishnu01

Thank you for reaching out to us.

According to the Eikon Data API Usage and Limits Guideline, this error indicates that the platform is overwhelmed.

You may catch this exception and then send the request again. Moreover, you can add the sleep code after sending each request.

All comments

Jirapongse

@vishnu01

Thank you for reaching out to us.

According to the Eikon Data API Usage and Limits Guideline, this error indicates that the platform is overwhelmed.

You may catch this exception and then send the request again. Moreover, you can add the sleep code after sending each request.

vishnu01

Hi, Thank you for the response. I added the the sleep code after sending the request but still the problem persist.

vishnu01

Hi, I converted the dataframe of 4063 rics into the chunks of 50. I used this code and added 2 time.sleep after one request and 5 sec sleep after one chunk. Still I'm getting the error . What is the best approch to resolve it.

import pandas as pd

# Initialize an empty DataFrame with column name 'split_ratio'

stock_split = pd.DataFrame(data=None)

try:

i = 0

for chunk in chunks:

for index, row in chunk.iterrows():

try:

df, err = ek.get_data(str(row['ric']), ['TR.CAAdjustmentFactor'], {'SDate': '2023-10-03', 'EDate': '2023-10-04'})

df.fillna(1, inplace=True)

df.rename(columns={'Adjustment Factor': 'split_ratio'}, inplace=True)

stock_split = pd.concat([stock_split, df], ignore_index=True)

except Exception as e:

print('Error:', e)

time.sleep(1)

i += 1

print(i, end=' ')

print('sleeping for 5 seconds before the next chunk...')

time.sleep(5)

except Exception as e:

print('Error:', e)

Jirapongse

@vishnu01

Can you share RICs? Therefore, I can test the code on my machine.

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