@gareth.teage

Thank you for reaching out to us.

To get 429 (too many requests), you need to send a lot of requests concurrently that exceeds the

Queued Extraction Request Limit defined in the DataScope Select Best Practices & Fair Usage Policy.

For example the code could like this:

import requests
import concurrent.futures
import time
import json


token = '<token>'


def get_status(url):


    payload = json.dumps({
  "ExtractionRequest": {
    "@odata.type": "#DataScope.Select.Api.Extractions.ExtractionRequests.HistoricalReferenceExtractionRequest",
    "ContentFieldNames": [
      "RIC",
      "ETH Expiry Date"
    ],
    "IdentifierList": {
      "@odata.type": "#DataScope.Select.Api.Extractions.ExtractionRequests.InstrumentIdentifierList",
      "InstrumentIdentifiers": [
        {
          "Identifier": "ESc1",
          "IdentifierType": "Ric"
        }
      ],
      "ValidationOptions": {
        "AllowHistoricalInstruments": True
      },
      "UseUserPreferencesForValidationOptions": False
    },
    "Condition": {
      "ReportDateRangeType": "Range",
      "QueryStartDate": "2000-01-01",
      "QueryEndDate": "2023-01-01"
    }
  }
})
    headers = {
      'Prefer': 'respond-async',
      'Content-Type': 'application/json',
      'Authorization': 'Token '+token
    }    


    response = requests.request("POST", url, headers=headers, data=payload)


    return response.status_code
    
    


url = "https://selectapi.datascope.refinitiv.com/RestApi/v1/Extractions/ExtractWithNotes"

tm1 = time.perf_counter()
with concurrent.futures.ThreadPoolExecutor(max_workers=100) as executor:

    futures = []
    for iter in range(1, 200):
        futures.append(executor.submit(get_status, url=url))

    for future in concurrent.futures.as_completed(futures):
        print(future.result())

tm2 = time.perf_counter()
print(f'Total time elapsed: {tm2-tm1:0.2f} seconds')