LSEG Data Library

Access financial data from LSEG (London Stock Exchange Group), formerly Refinitiv, via the lseg.data Python library.

Quick Start

import lseg.data as ld

ld.open_session()

# Get fundamentals
df = ld.get_data(
    universe=['AAPL.O', 'MSFT.O'],
    fields=['TR.CompanyName', 'TR.Revenue', 'TR.EPS']
)

# Get historical prices
prices = ld.get_history(
    universe='AAPL.O',
    fields=['OPEN', 'HIGH', 'LOW', 'CLOSE', 'VOLUME'],
    start='2023-01-01',
    end='2023-12-31'
)

ld.close_session()

Authentication

Config file lseg-data.config.json:

{
  "sessions": {
    "default": "platform.ldp",
    "platform": {
      "ldp": {
        "app-key": "YOUR_APP_KEY",
        "username": "YOUR_MACHINE_ID",
        "password": "YOUR_PASSWORD"
      }
    }
  }
}

Or environment variables: RDP_USERNAME, RDP_PASSWORD, RDP_APP_KEY

Core APIs

API	Use Case	Example
`ld.get_data()`	Point-in-time data	Fundamentals, ESG scores
`ld.get_history()`	Time series	Historical prices, OHLCV
`symbol_conversion.Definition()`	ID mapping	RIC ↔ ISIN ↔ CUSIP

Key Field Prefixes

Prefix	Type	Example
`TR.`	Refinitiv fields	`TR.Revenue`, `TR.EPS`
`CF_`	Composite (real-time)	`CF_LAST`, `CF_BID`

RIC Symbology

Suffix	Exchange	Example
`.O`	NASDAQ	`AAPL.O`
`.N`	NYSE	`IBM.N`
`.L`	London	`VOD.L`
`.T`	Tokyo	`7203.T`

Rate Limits

Endpoint	Limit
`get_data()`	10,000 data points/request
`get_history()`	3,000 rows/request
Session	500 requests/minute

Additional Resources

Reference Files

references/fundamentals.md - Financial statement fields, ratios, estimates
references/esg.md - ESG scores, pillars, controversies
references/symbology.md - RIC/ISIN/CUSIP conversion
references/pricing.md - Historical prices, real-time data
references/screening.md - Stock screening with Screener object
references/troubleshooting.md - Common issues and solutions
references/wrds-comparison.md - LSEG vs WRDS data mapping

Example Files

examples/historical_pricing.ipynb - Historical price retrieval
examples/fundamentals_query.py - Fundamental data patterns
examples/stock_screener.ipynb - Dynamic stock screening

Scripts

scripts/test_connection.py - Validate LSEG connectivity

Local Sample Repositories

LSEG API samples at ~/resources/lseg-samples/:

Example.RDPLibrary.Python/ - Core API examples
Examples.DataLibrary.Python.AdvancedUsecases/ - Advanced patterns
Article.DataLibrary.Python.Screener/ - Stock screening

Date Awareness

Pattern from oh-my-opencode: When querying market data, use current date context.

Example for time series:

from datetime import datetime, timedelta

# Get recent market data
end_date = datetime.now()
start_date = end_date - timedelta(days=365)

# Adjust to exclude recent data (T-1 for market data availability)
end_date = end_date - timedelta(days=1)

df = ek.get_timeseries(
    "AAPL.O",
    fields=['CLOSE'],
    start_date=start_date.strftime('%Y-%m-%d'),
    end_date=end_date.strftime('%Y-%m-%d')
)

Remember: Market data typically has T-1 availability.

lseg-data

Contents