TickerDB for Python.
Simple client for the TickerDB HTTP API. Install with pip, initialize with your API key, and start pulling pre-computed market data immediately.
Install and call in seconds.
One pip install, one import, one line to initialize. Every method returns a dictionary with data and rate_limits.
pip install tickerdb
from tickerdb import TickerDB client = TickerDB("tdb_your_api_key") # Get a full summary for any ticker result = client.summary("AAPL") print(result["data"]["trend"]["direction"]) # "uptrend" print(result["data"]["momentum"]["rsi_zone"]) # "neutral_high"
Chain calls. Build context.
Pull a summary, use summary event mode for historical band transitions, then monitor your watchlist for changes. Each method returns market-state data you can branch on directly.
Track state changes effortlessly.
Most market data APIs return point-in-time snapshots. TickerDB tracks state transitions — your agent sees what changed, not just what is.
result = client.watchlist_changes()
{ "timeframe": "daily", "run_date": "2026-03-28", "changes": { "AAPL": [ { "field": "rsi_zone", "from": "neutral", "to": "oversold" }, { "field": "trend_direction", "from": "uptrend", "to": "downtrend" } ] }, "ticker_context": { "AAPL": { "last_changed_date": "2026-03-28" } }, "tickers_checked": 2, "tickers_changed": 1 }
What your agent sees.
Every tool returns categorical facts — not raw OHLCV data. Your agent can branch on "oversold" without needing to know what RSI > 70 means.
{ "ticker": "NVDA", "data_status": "eod", "as_of_date": "2026-04-11", "trend": { "direction": "strong_uptrend", "ma_alignment": "aligned_bullish" }, "momentum": { "rsi_zone": "overbought", "macd_state": "expanding_positive", "direction": "accelerating" }, "volatility": { "regime": "normal", "regime_trend": "stable" }, "fundamentals": { "valuation_zone": "fair_value", "pe_vs_historical_zone": "premium", "last_earnings_surprise": "beat" } }
What you can call.
Every method returns a dict with `data` and `rate_limits`. No raw data to parse, no indicator math to maintain.
Full technical + fundamental snapshot for a single asset.
Search across all assets with multi-field filters.
Discover all queryable fields and their types.
Batch EOD summaries for a portfolio.
State changes for your saved watchlist tickers.
Create a webhook for watchlist change alerts.
List the webhooks on your account.
Delete a webhook you no longer need.
Built for how code consumes data.
Market-state data, less parsing
Responses like "rsi_zone": "oversold" are ready to branch on. No indicator math, no threshold logic.
Plain dictionaries
Every method returns a dict. No ORM, no custom objects, no serialization steps. JSON in, dict out.
Pre-computed daily
No infrastructure to maintain. No cron jobs, no indicator math. TickerDB handles computation and syncing.