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Python SDK for London Strategic Edge real-time market data

Project description

lse-data

Python SDK for London Strategic Edge real-time market data.

Stream live prices for 4,000+ instruments including stocks, crypto, forex, indices, commodities, ETFs, and 81,000+ options contracts.

Install

pip install lse-data

Quick start

from lse import LSE

client = LSE(api_key="your_api_key")

for tick in client.stream(["BTC/USD", "AAPL", "EUR/USD"]):
    print(f"{tick.symbol}: ${tick.price}")

Get your API key at londonstrategicedge.com/data.

Features

  • Historical OHLCV candles for 4,000+ instruments (REST, no WebSocket needed)
  • Real-time WebSocket streaming with auto-reconnect
  • 4,000+ symbols: US/UK/EU/Asia stocks, crypto, forex, indices, commodities, ETFs
  • 81,000+ option contracts via subscribe_options()
  • Symbol catalog API for discovery before subscribing
  • Server-side symbol validation (invalid symbols rejected immediately)
  • Dynamic subscribe/unsubscribe at runtime
  • Graceful disconnect (from callbacks or other threads)
  • Sync and async interfaces
  • Callback and iterator patterns
  • Zero config, just an API key

Usage

Historical candles

Fetch OHLCV candles for any instrument. No WebSocket connection needed.

from lse import LSE

client = LSE(api_key="your_key")

# As a list of dicts
result = client.candles("XAU/USD", start="2021-01-01", end="2026-01-01", timeframe="1d")
print(f"{result['rows']} candles, plan: {result['plan']}")
for c in result["data"][-3:]:
    print(f"{c['timestamp']}  close={c['close']}")

# As a pandas DataFrame (pip install lse-data[pandas])
df = client.candles("AAPL", "2025-01-01", "2026-01-01", timeframe="1h", as_dataframe=True)
print(df.tail())

Supported timeframes: 1m, 5m, 15m, 30m, 1h, 2h, 4h, 1d

Works for all 4,000+ instruments: stocks, crypto, forex, ETFs, commodities, indices.

Stream ticks (simplest)

from lse import LSE

client = LSE(api_key="your_key")

for tick in client.stream(["BTC/USD", "ETH/USD", "AAPL"]):
    print(f"{tick.symbol:12s} ${tick.price:>12,.2f}")

Callback style

from lse import LSE

def on_tick(tick):
    print(f"{tick.symbol}: {tick.price}")

client = LSE(api_key="your_key")
client.on("tick", on_tick)
client.connect(symbols=["BTC/USD", "ETH/USD"])

Async streaming

import asyncio
from lse import LSE

async def main():
    client = LSE(api_key="your_key")
    async for tick in client.stream_async(["BTC/USD"]):
        print(tick)

asyncio.run(main())

Save to CSV

import csv, datetime
from lse import LSE

client = LSE(api_key="your_key")

with open("ticks.csv", "w", newline="") as f:
    writer = csv.writer(f)
    writer.writerow(["time", "symbol", "price", "bid", "ask"])

    for tick in client.stream(["BTC/USD", "ETH/USD"]):
        writer.writerow([
            datetime.datetime.now().isoformat(),
            tick.symbol, tick.price, tick.bid, tick.ask,
        ])

Tick object

Each tick has these fields:

Field Type Description
symbol str Instrument symbol (e.g. BTC/USD, AAPL)
price float Latest price
bid float Bid price (if available)
ask float Ask price (if available)
volume float Volume (if available)
timestamp float Unix timestamp
name str Human-readable name (e.g. Apple Inc.)

Events

When using the callback style with .on():

Event Callback args Description
tick Tick New price tick
connected (none) WebSocket connected
authenticated (none) API key accepted
disconnected (none) Connection lost (will auto-reconnect)
error str Error message

Symbol catalog

Query available instruments before subscribing. No WebSocket connection needed.

from lse import LSE

client = LSE(api_key="your_key")

# Get all available symbols
all_symbols = client.catalog()
print(f"{len(all_symbols)} instruments available")

# Filter by category: stock, crypto, forex, etf, commodity, index
stocks = client.catalog(category="stock")
crypto = client.catalog(category="crypto")

# Each entry has symbol, display_name, and category
for s in crypto[:5]:
    print(f"{s['symbol']:12s} {s['display_name']:20s} {s['category']}")

The catalog returns every subscribable instrument. Use it to build symbol pickers, validate user input, or discover what is available.

Available categories

Category Count Examples
stock ~3,987 AAPL, NVDA, TSLA, 0005.HK, 7203.T
forex ~62 EUR/USD, GBP/JPY, USD/CHF
crypto ~58 BTC/USD, ETH/USD, SOL/USD
etf ~25 SPY, QQQ, IWM, GLD
commodity ~23 XAU/USD, WTICO/USD, NATGAS/USD
index ~13 US30, NAS100, UK100

Options streaming

Subscribe to entire options chains by underlying. One call gives you every contract (calls + puts, all strikes, all expiries).

from lse import LSE

client = LSE(api_key="your_key")

def on_tick(tick):
    print(f"{tick.symbol}: ${tick.price:.2f}")

client.on("tick", on_tick)
client.subscribe_options(["AAPL", "TSLA"])
client.connect()

To stop receiving a chain:

client.unsubscribe_options(["TSLA"])

Unsubscribe

Remove symbols at runtime without disconnecting:

client.unsubscribe(["BTC/USD"])      # stop one symbol
client.subscribe(["SOL/USD"])        # add another

Disconnect

Stop the stream and exit cleanly. Works from callbacks or another thread:

tick_count = 0

def on_tick(tick):
    global tick_count
    tick_count += 1
    if tick_count >= 100:
        client.disconnect()  # connect()/stream() returns

client.on("tick", on_tick)
client.connect(symbols=["BTC/USD"])
print("Done, collected 100 ticks")

Async version:

await client.disconnect_async()

Requirements

  • Python 3.8+
  • websockets (installed automatically)

License

MIT

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