tasilab 0.1.0

Tasi Lab is the first API-native paper trading sandbox for the Saudi Stock Exchange, empowering developers to build, test, and deploy AI-driven trading strategies with zero financial risk.

Tasi Lab Python SDK

Tasi Lab is the first API-native paper trading sandbox for the Saudi Stock Exchange, empowering developers to build, test, and deploy AI-driven trading strategies with zero financial risk.

This package is the official Python client. Use it to pull historical TASI data, log backtests as experiments, and view results in the Tasi Lab dashboard.

• Dashboard: https://tasilab.com
• API docs: https://api.tasilab.com/docs

Install

pip install tasilab

Quick start

from tasilab import TasiLab

tasi = TasiLab(api_key="YOUR_API_KEY")

# 1. Pull historical bars (Tasi Lab caches them for you)
hist = tasi.get_historical("1120", "2024-01-01", "2025-12-31")

# 2. Run your strategy locally → list of trade dicts
trades = my_strategy(hist["bars"])

# 3. Log the run as a Tasi Lab experiment (auto-seals on exit)
with tasi.create_experiment(
    name="MACD 12/26/9 on Al Rajhi",
    symbol="1120",
    start_date="2024-01-01",
    end_date="2025-12-31",
    parameters={"fast": 12, "slow": 26, "signal": 9},
) as exp:
    exp.log_trades(trades)
    exp.log_metrics({"total_return_sar": 439.64, "win_rate": 0.412})

The with block automatically marks the experiment completed on clean exit and failed if an exception propagates, so experiments never get stuck in running.

Paper trading

The SDK also supports live paper-trading against the simulated exchange:

order = tasi.buy("2222", quantity=100)
portfolio = tasi.portfolio()

See https://tasilab.com for the full surface.

License

Proprietary — see https://tasilab.com for terms.