How to pull the historical data for options in CODEBOOK using the chain RIC?

Question

Hi Team, our client is trying to pull the historical volume and price data in CODEBOOK for Google options using the chain RIC <0#GOOGL*.U>.

Here's the code we initially used:

import lseg.data as ld

from lseg.data.discovery import Chain

ld.open_session()

chain = Chain(name="0#GOOGL*.U")print(chain.constituents)

df = ld.get_history(

universe = chain.constituents[1:],

fields = ['TRDPRC_1','ACVOL_UNS'],

start = '2026-01-01',

end = '2026-06-02',

interval = '1d')

df = df.fillna(0)

df

Somehow, the code only reads the first part / pulls the constituents but not the volume and price data:

Here's the Excel formula:

=@RDP.HistoricalPricing($B$5:$B$1000,"TRDPRC_1;ACVOL_UNS","START:"&$B$2&" END:"&$B$3&" INTERVAL:P1D SOURCE:RFV",,"TSREPEAT:NO NULL:ZERO CH:IN;Fd RH:Timestamp",D4)

We'll appreciate it if you could check and advise.

Thank you very much!

Best Regards,

Yoy

Jirapongse · Answer

All retrieved data frame are in the df_list variable.

display(df_list)

yoy.delarama · Answer

Hi @Jirapongse and team, good day.

Tried the code suggested but I only got "5202" result and no volume/prices were retrieved:

import lseg.data as ld

from lseg.data.discovery import Chain

import pandas as pd

import time

ld.open_session()

chain = Chain(name="0#GOOGL*.U")

print(len(chain.constituents))

my_list = chain.constituents

chunk_size = 100

df_list = []

chunks = [my_list[i : i + chunk_size] for i in range(0, len(my_list), chunk_size)]

for chunk in chunks:df = ld.get_history(

universe = chunk,

fields = ['TRDPRC_1','ACVOL_UNS'],

start = '2026-01-01',

end = '2026-06-02',

interval = '1d')

df = df.fillna(0)

df_list.append(df)

time.sleep(2)

Jirapongse · Answer

@yoy.delarama

Thank you for reaching out to us.

The error is "429, Too many requests". This suggests that the API usage has surpassed its allowed limits.

The client may try splitting the request into multiple function calls instead of a single call. For example:

import lseg.data as ld
from lseg.data.discovery import Chain
import pandas as pd
import time

pd.set_option('future.no_silent_downcasting', True)
ld.open_session()

chain = Chain(name="0#GOOGL*.U")
print(len(chain.constituents))
my_list = chain.constituents
chunk_size = 100

df_list = []
chunks = [my_list[i : i + chunk_size] for i in range(0, len(my_list), chunk_size)]

for chunk in chunks:    
    df = ld.get_history(
        universe = chunk,
        fields = ['TRDPRC_1','ACVOL_UNS'],
        start = '2026-01-01',
        end = '2026-06-02',
        interval = '1d')
    df = df.fillna(0)
    df_list.append(df)
    time.sleep(2)

The client can also refer to the following articles.

* The Data Library for Python - Maximum Usage Reference Guide
* Check LSEG Data Library for Python Usage Limits Remaining

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