why its not working ?

import os, time, pandas as pd
import refinitiv.data as rd
from refinitiv.data.content import filings as rfil

CSV_FILE_PATH = "/Users/prince/Downloads/nwsheet.csv"
COMPANY_NAME_COLUMN = "Company Name"
COMPANY_ID_COLUMN = "Identifier" # RICs like AAPL.OQ, RELI.NS, etc.
DOWNLOAD_DIR = "/Users/prince/Downloads/x"
START_YEAR, END_YEAR = 2015, 2023
LSEG_API_KEY = "" # or set env var RD_APP_KEY
ANNUAL_REPORT_CATEGORY_ID = 1 # MidLevelCategory: 1 == "Annual"

def ensure_dir(p):
if not os.path.exists(p):
os.makedirs(p)

def filings_query(ric: str, y: int) -> str:
# Filings query syntax uses field:value with AND
# Common fields: RIC, DateFrom, DateTo, MidLevelCategory
return f'RIC:{ric} AND DateFrom:{y}-01-01 AND DateTo:{y}-12-31 AND MidLevelCategory:{ANNUAL_REPORT_CATEGORY_ID}'

def main():
rd.open_session(app_key=LSEG_API_KEY) # or just rd.open_session() if RD_APP_KEY env var set
ensure_dir(DOWNLOAD_DIR)

try:
    df = pd.read_csv(CSV_FILE_PATH)
    ids = df[COMPANY_ID_COLUMN].astype(str).tolist()
    names = df[COMPANY_NAME_COLUMN].astype(str).tolist()
except FileNotFoundError:
    print(f"CSV not found: {CSV_FILE_PATH}")
    return
except KeyError as e:
    print(f"Missing column in CSV: {e}")
    return

print(f"Found {len(ids)} companies")

for ric, name in zip(ids, names):
    if not ric or ric == "nan":
        continue

    safe = name.replace(" ", "_").replace("/", "_")
    company_dir = os.path.join(DOWNLOAD_DIR, safe)
    ensure_dir(company_dir)
    print(f"\nProcessing {name} ({ric})")

    for year in range(START_YEAR, END_YEAR + 1):
        try:
            query = filings_query(ric, year)

            # 1) Search the Filings catalog
            search_resp = rfil.search(query=query, top=5)   # returns a DataFrame in .data.df
            results = getattr(search_resp, "data", None)
            df_res = getattr(results, "df", pd.DataFrame())

            if df_res.empty:
                print(f"  {year}: no annual report found")
                continue

            # Pick the best candidate (you can filter further on Title/Language if needed)
            row = df_res.iloc[0]
            doc_id = row.get("documentId") or row.get("DocumentId")  # naming differs across library versions
            title  = row.get("documentTitle") or row.get("DocumentTitle") or "Annual Report"

            if not doc_id:
                print(f"  {year}: search returned rows without documentId")
                continue

            out_path = os.path.join(company_dir, f"{safe}_Annual_Report_{year}.pdf")

            # 2) Download the document binary
            doc_resp = rfil.get_document(document_id=doc_id)   # returns .data.raw or .data.content depending on version
            binary = getattr(doc_resp.data, "raw", None) or getattr(doc_resp.data, "content", None)

            if not binary:
                print(f"  {year}: could not retrieve document content for {doc_id}")
                continue

            with open(out_path, "wb") as f:
                f.write(binary)
            print(f"  {year}: downloaded '{title}' -> {out_path}")

        except Exception as e:
            print(f"  {year}: error: {e}")

        time.sleep(0.75)  # be nice to the API

# close session (guard if none)
sess = rd.get_default_session()
if sess and getattr(sess, "is_open", False):
    rd.close_session()

if name == "main":
main()