Building a Crypto Screener in Python

A python algo trading workflow doesn't start with trade execution. It starts with identifying opportunities. A crypto screener automatically scans hundreds of assets and filters them by your criteria, delivering a focused watchlist every day.

Fetching Market Data at Scale

Use the ccxt library to pull OHLCV data for all USDT-denominated pairs on Binance. Iterate through markets and fetch 100 bars of daily data for each:

import ccxt\nexchange = ccxt.binance()\nmarkets = [s for s in exchange.load_markets() if "/USDT" in s]\nfor symbol in markets:\n    ohlcv = exchange.fetch_ohlcv(symbol, "1d", limit=100)

Screening Criteria

Filter by: RSI below 30 (oversold), 20-day volume at 2x the 50-day average (volume breakout), price above 200-day SMA (uptrend filter). You can combine these into a scoring system for your crypto algo trading strategy universe selection.

Output

Generate a ranked list and send it to your Telegram bot every morning. Your automated crypto trading system can then focus execution only on the top-screened assets.