display(df)



Testing shows that get_history follows correctly however, get_data appears to put all real time fields at the end.

Directory 'T1' was setup by me. That's where I usually work. Can I just setup a 'My Notebooks' folder?

• The screenshot also demonstrates that an older Python file continues to display correctly with syntax highlighting (color-coded syntax), indicating that previously created files are unaffected.

• Steps performed:
1. Logged in to LSEG Workspace.
2. Opened Codebook.
3. Selected New File.
4. Chose Python Script.
5. Began writing code.

• The issue occurs across all newly created files/formats. Older files retain proper syntax highlighting, while all new code created since Saturday is interpreted as plain text.
• The user verified that the "Code" option was selected in the format dropdown, as demonstrated in the provided video.
• Expected behavior is for new Python scripts to display with standard syntax highlighting.
• The issue does not appear to be related to a display preference, and attempts to run the code did not produce any result.
• The problem is reproducible and has been occurring consistently since Saturday.

To clarify, the client is looking to automate the extraction of Share Reclassification information from ADVFIL. However, this functionality is not currently supported within Workspace, and there are no available capabilities in Excel that would enable the automated extraction of this information directly from the application.

Can you help me understand why this keeps happening?

e.g. storyId = 'urn:newsml:reuters.com:20260811:nASX8TmPfj:1'

The client is asking how to retrieve the PDF file or how to get the contents n the PDF with Python?

Thanks in advance.

1. Management Approach (Actively Managed or Passively Managed)
2. Index Replication Strategy

It was confirmed that there are currently no dedicated data fields or API fields available for these attributes.

However, the information is available within the Fund Screener (FSCREEN) application in Workspace. Is it possible to source the data from FSCREEN to API?

I am not able to open CodeBook as it crashes after trying to load (Spawn failed - the latest attempt to start your server failed). Login works normally and I have tried clearing cache, restarting. Relaunching does not help either.

If someone could help witht the issue, thanks :)

contract name like Dec26 etc

import lseg.data as ld

ld.open_session()

df = ld.get_history(
universe=[
"CFTCOTUSAMHY1",
"CFTCOTUSAMKY1",
"CFTCOTUSAMNY1",
"CFTCOTUSAMVY1",
"CFTCOTUSAY1",
"CFTCOTUSAMHY2",
"CFTCOTUSAMKY2",
"CFTCOTUSAMNY2",
"CFTCOTUSAMVY2",
"CFTCOTUSAY3",
"CFTCOTUSAY2",
"CFTCOTUSAMHY3",
"CFTCOTUSAMKY3",
"CFTCOTUSAMNY3",
"CFTCOTUSAY4",
"CFTCOTUSAY5",
"CFTCOTUSATOT"
],
fields=["MET_VAL","CLOSE"],
start="2000-01-01",
end="2026-08-26",
interval="1D"
)

print(df)

Thank you

Client requests how to develop in CODEBOOK to programmatically access a daily list of the latest (new) corporate bond issuances

We have seen content_search.ipynb under examples in codebk but unsure how to proceed with clients request

It behaves the same whether I open CodeBook from inside Workspace (the CodeBook app) or by going to the CodeBook URL directly.

ENVIRONMENT
Linux, Chromium 150. Workspace Web shows a "BROWSER NOT SUPPORTED" banner in this browser, so please do tell me if CodeBook is only supported on specific browsers and this is the cause - I would rather know that than keep troubleshooting.

QUESTION
Is this a known problem with CodeBook kernels, and what do I need to do to get code execution working again?

From Codebook Reuters API, Client need corporate guidance data for the entire US market.

Can he download Corporate guidance in batch?

Thank you

2. Is there a sample Python snippet for pulling an options chain (chain by underlying, with vol/OI/expiry) using lseg-data on a Desktop Session?

LP68378190
LP68037657
VAS.AX
IOZ.AX

"TR.FundIncDistribution;TR.FundExDate;TR.FundExDate;TR.FundRecordDate;TR.FundPayDate;TR.FundDiv;TR.FundDivCurr"

import lseg.data as ld
ld.open_session()
tickers = ['AZN.L', 'NXT.L', 'RIO.L', 'ULVR.L', 'BATS.L',           'SVT.L', 'EXPN.L', 'WTB.L', 'BNZL.L', 'GSK.L',           'PSN.L', 'BRBY.L', 'GLEN.L', 'RTO.L', 'BARC.L',           'MKS.L', 'SBRY.L', 'KGF.L', 'VOD.L', 'LLOY.L']
df_mktcap = ld.get_data(    universe=tickers,    fields=['TR.CompanyName', 'TR.CompanyMarketCap'])
print(df_mktcap.sort_values('Company Market Cap', ascending=False).to_string())
ld.close_session()

The code ran yesterday but has an issue today.

Checked and his USER-ID only has access to delayed RICs

We used /AZN.L, /NXT.L in the ticker section in the code but it still has the same issue. Can we confirm why is there an error?

rd.discovery.search(
view = rd.discovery.Views.EQUITY_QUOTES,
top = 10,
filter = "( SearchAllCategoryv2 eq 'Options')",
select = "DTSubjectName,AssetState,BusinessEntity,PI,SearchAllCategoryv3,SearchAllCategoryv2,SearchAllCategory,ExchangeName,CallPutOption,StrikePrice,ExpiryDate,RIC,UnderlyingQuoteRIC,UnderlyingIssuerName,UnderlyingRCSAssetCategoryLeaf"
)

I also need -> US Margin Debt

and then in CBOOK -> M2/ Margin Debt as chart

def refinitiv_get_news_body(row):
if row['status'] == "COMPLETED":
#print("body found locally")
return row["body"], "COMPLETED"

print(f"Requesting body for headling: {row['storyId']}")

return ld.news.get_story(row["storyId"]), “COMPLETED”

ld.open_session()

df_body = df_input.copy()

try:

for idx, row in df_body.iterrows():


    body, status = refinitiv_get_news_body(row)


    df_body.loc[idx, "body"] = body

    df_body.loc[idx, "status"] = status

except Exception as e:

logger. Error(f"Error: {e}”)

This is the ode I’m trying to run:

import refinitiv.data as rd

rd.open_session()

df = rd.get_history(universe =['aUSCPIAR','pUSCPI=M'],

                    start='2025-06-01',

                    end='2026-05-01')

df.sort_index(ascending=False)

This results in misaligned records, where additional education entries appear as separate rows with missing identifiers, making it impossible to reliably associate them with the correct individual. And, additional education records for one person, get instead put in the row of the next director or officer, misaligning all the rows to follow

Here is the code:

We also tried in CODEBK and it has the same issue. Can we assist on this?

Reaching out on behalf of client a professor in a University. 

I have shared the steps to client in getting his APP KEY so he can access the Workspace API via Codebook. 

Client followed the steps and got an API key. Then, he installed LSEG-data for Python and attempted a platform session using OAuth v1 Password Grant with my App Key, username and password.  The session fails during token refresh with:

Malformed JSON received during token refresh: '400 Bad Request'
[Error 400] - {}
session.open() returned: OpenState.Closed

Can you please confirm the below:

1. That clients App Key is enabled for LSEG Data Library for Python / platform access,
2. The exact User ID or Machine ID I should use for OAuth v1 Password Grant,
3. Whether the password is the same as my Workspace web password or a separate platform/Machine ID password,
4. Whether my account has the required Data Platform entitlement?
5. Any advice or recommendation?

I am trying to follow the help guidance of modeling an interest rate swap (currently in SWPR) in the CODEBK application. However, I think I must be doing something wrong because I am seeing a variance between the two. Can you help with what I am doing wrong? I reached out to the LSEG Help Desk who assisted with developing the query in Python (see .txt attachment). I am also including the output of SWPR which I am trying to model in codebook. Note I think I should be using MoneyMarket basis, so I will update this in the SWPR and Python code, however, the difference still remains.

Attached is their current approach (exported from Jupyter Notebook as a .txt file since the notebook cannot be attached directly). The existing script, which retrieves data for 10 companies across 8 points in time, currently takes around 30 minutes to complete.

Could you please review the code and provide recommendations on how they can improve performance and optimize data retrieval?

Please assist. Thank you.

In Codebook, the screener does not work when the field TR.NAICSNationalIndustryCode is included. For example, the commands

screener_output=Screener('U(IN(Equity(active,public,primary))), IN(TR.GICSSectorCode,"45"), IN(TR.NAICSNationalIndustryCode,"513210"), TOP(TR.H.EV(Curn=USD),7,nnumber),Curn=Native')

df=fundamental_and_reference.Definition(universe=[screener_output.expression],fields=['TR.CompanyName','TR.F.EV'], parameters={'curn':'USD','NULL':'Blank','Scale':6}).get_data()

return error code 800 (see 1st attachment).

When the parameter IN(TR.NAICSNationalIndustryCode,"513210") is removed, the code runs fine (see 2nd attachment).

Can this be corrected so that the screener works with the field TR.NAICSNationalIndustryCode as well?