Batched way to get a 12:00UTC intraday price for ~1,800 instruments without 1 request per instrument

swanand

Hi all,

Setup

• LSEG Data Library for Python (lseg-data 2.1.1), Python 3.13
• Workspace desktop session (localhost:9000)
• Daily job; the session's quota is 10,000 requests/day and 5 requests/second

Use case
Once a day I need the price at exactly 12:00 UTC for about 1,800 equities and futures across European, US, Latin American and other exchanges. For each instrument I need the first 1-minute bar at or after 12:00:00 UTC (BID, ASK, TRDPRC_1).

What I do now

df = ld.get_history(

    universe=batch,                      # 50 RICs per call

    fields=["BID", "ASK", "TRDPRC_1"],

    interval="1min",

    start="2026-10-06T12:00:00Z",

    end="2026-10-06T12:05:00Z",

)

The problem
On a desktop session, get_history sends one HTTP request per instrument (GET .../historical-pricing/v1/views/intraday-summaries/<RIC>?interval=PT1M&...). Each one counts against the daily quota, so this step alone uses ~1,800 of the 10,000 daily requests.
For daily data I've already switched to ld.get_data with TR fields (TR.PriceClose, TR.BidPrice, TR.AskPrice with SDate/EDate). That is batched and costs 1 request per call.

Questions

1. Is there a supported way to get a 1-minute intraday bar (or the price as of a given timestamp) for many instruments in a single counted request? For example, an intraday-capable TR field or parameter for ld.get_data, or a multi-instrument intraday endpoint.
2. If the job runs at 12:00 UTC, would a real-time snapshot via ld.get_data (e.g. CF_BID, CF_ASK, CF_LAST) be a reliable, supported alternative? Does it count as 1 request per call, and are there any per-call instrument limits I should respect?
3. If neither is possible within the Data Library, is DataScope Select the recommended route for a daily intraday snapshot of this size?

Any pointers or examples would be much appreciated.

Thanks so much.

Jirapongse

@swanand

Thank you for reaching out to us.

1. The TR fields do not support historical intraday data. Therefore, to retrieve historical intraday data, you need to use the ld.get_history() method, which retrieves data from the Historical Pricing API. Please note that this Historical Pricing API supports only one RIC per request.
   
2. I checked and found that the LSEG Data Library for Python uses the Datagrid endpoint when retrieving snapshot data through the ld.get_data() method, which is the same service used to retrieve TR fields. Therefore, each ld.get_data() call is counted as a single request.
   
   However, if you do not have permission to access real-time data, the returned data may be delayed. In most cases, you can verify this by checking the DSPLY_NAME field. If the value ends with "/d", it indicates that the instrument is delayed. For example:
   
   
   
3. To pull historical intraday data for multiple RICs, you can use the Tick History product with the TickHistoryIntradaySummariesExtractionRequest request. Please contact your LSEG account team or sales team directly for more information.

To check the remaining usage limits for the LSEG Data Library for Python, please refer to the Check LSEG Data Library for Python Usage Limits Remaining article. This article describes how to monitor your current consumption and view the remaining quota available for your application.