Part 01
Alert System with Python
Poll the API at regular intervals and fire webhooks when conditions are triggered:
Python Alert System with Python
from flask import Flask, jsonify
import requests, schedule, threading, time
app = Flask(__name__)
API_KEY = "YOUR_API_KEY"
BASE = "https://tickatlas.com/v1"
WEBHOOK_URL = "https://your-app.com/webhook" # or Discord/Slack URL
def check_alerts():
"""Check indicator conditions and fire webhooks."""
headers = {"X-API-Key": API_KEY}
symbols = ["EURUSD", "GBPUSD", "XAUUSD"]
for sym in symbols:
rsi = requests.get(f"{BASE}/indicator",
headers=headers,
params={"symbol": sym, "indicator": "RSI_14", "timeframe": "H1"}
).json()
value = rsi["data"]["value"]
if value < 30:
fire_alert(sym, "RSI OVERSOLD", value)
elif value > 70:
fire_alert(sym, "RSI OVERBOUGHT", value)
def fire_alert(symbol, condition, value):
"""Send alert via webhook."""
payload = {
"text": f"Alert: {symbol} - {condition} (RSI: {value:.1f})",
"symbol": symbol,
"condition": condition,
"value": value
}
requests.post(WEBHOOK_URL, json=payload)
print(f"Alert fired: {symbol} {condition}")
# Check every 5 minutes
schedule.every(5).minutes.do(check_alerts)
def run_scheduler():
while True:
schedule.run_pending()
time.sleep(30)
threading.Thread(target=run_scheduler, daemon=True).start()
check_alerts() # Run immediatelyPatterns
Popular Alert Conditions
RSI Extremes Alert when RSI crosses above 70 (overbought) or below 30 (oversold)
MACD Crossover Alert when MACD line crosses the signal line in either direction
Bollinger Band Touch Alert when price touches or crosses the upper/lower band
ADX Trend Start Alert when ADX crosses above 25 (new trend forming)
Before you go live
Production hardening
The code above is the happy path. These are the concerns that decide whether it survives contact with a real deployment.
1
Keep the key server-side. The API key authenticates with the X-API-Key header and must never reach a browser bundle. Proxy it, or use a public widget key, which is domain-scoped and revocable. Authentication
2
Handle 429 before you need to. Rate limits are per key and per minute. Back off on 429 rather than retrying immediately, and read the X-RateLimit-* headers on every response. Rate limits
3
Branch on the error code, not the message. Errors carry a stable machine-readable code; the human-readable text can change. Codes were unified in v3.15. Error handling
4
Expect gaps, and do not invent values. Markets close, feeds stall, and a retention window can reject a request outright. Surface an explicit unavailable state rather than substituting a zero or the last known price. Troubleshooting
5
Cache what you poll. Responses are already cached briefly upstream, so polling faster than the data changes spends credits without improving freshness. Cache on your side and poll on the cadence your timeframe actually updates. Pricing and credits
6
Watch retention per timeframe. History depth is set per timeframe, never per plan, so a request that works on D1 can fall outside the window on M1. Check the published windows before backfilling. Timeframes
7
Rotate keys and scope them. Issue a separate key per deployment so one can be revoked without taking the others down, and rotate on a schedule rather than after an incident. Authentication
8
Log the request, not the key. Record endpoint, parameters, status and latency so a failure is reproducible. Never log the key itself, and scrub it from error reports.
Reference map
Related Guides
Everything this guide touches, linked directly — so it never dead-ends.
Guide How to Build a Trading Bot Step-by-step Python bot with RSI + MACD strategy Open Guide Create a Market Screener Scan all symbols matching indicator criteria Open Indicator Relative Strength Index (RSI) The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and magnitude of price movements on a scale from 0 to 100. Open Topic Discord Trading Bot — Webhook Alert Setup Open