Code a Solana DEX Volume Screener

Volume precedes price. In this guide, we will use the Terminal Software API to build a Python screener that filters the Solana ecosystem for assets entering a "HOT" regime with surging ADX momentum.

Environment Setup

Ensure your Python environment is ready to handle JSON payloads and data manipulation.

pip install requests pandas

Connecting to the Crypto Radar

We will hit the /telemetry/v1/crypto endpoint. This stream delivers sub-second aggregation of market caps, 80H structural floors, and proprietary regime classifications.

import requests
import pandas as pd

HEADERS = {"Authorization": "Bearer term_live_YOUR_KEY_HERE"}
response = requests.get("https://api.terminalsoftware.online/v1/crypto/momentum", headers=HEADERS)

df = pd.DataFrame(response.json())

Momentum Filtration Logic

Institutional desks don't trade chop; they trade trend. We will write logic to filter out sideways price action and only return assets where the ADX is over 25 and the algorithmic status is marked as HOT.

# Filter for active momentum
breakout_assets = df[(df['adx'] > 25.0) & (df['regime_status'] == 'HOT')]

print(f"[{len(breakout_assets)}] ASSETS DETECTED IN HIGH-MOMENTUM REGIME:")

for _, coin in breakout_assets.iterrows():
    print(f"-> {coin['asset']} | Mark: ${coin['price']} | ADX: {coin['adx']} | 80H Ceiling: ${coin['ceiling_80h']}")
    
    # Example execution trigger
    if coin['price'] > coin['ceiling_80h']:
        print(f"   [!] ALERT: {coin['asset']} is breaking 80H structural resistance.")

This isolates the noise, allowing your execution bots to deploy capital only when mathematical momentum confirms a directional shift.