Quant & data trader

import os, requests, pandas as pd, time

API_KEY = os.environ["PREDEXON_API_KEY"]
BASE = "https://api.predexon.com"
HEADERS = {"x-api-key": API_KEY}

# 1. Find the highest-volume open market
top = requests.get(
    f"{BASE}/v2/polymarket/markets",
    headers=HEADERS,
    params={"status": "open", "sort": "volume", "limit": 1},
).json()["markets"][0]

condition_id = top["condition_id"]
token_id = top["outcomes"][0]["token_id"]  # "Yes" side
print(f"Backtesting: {top['title']}")

# 2. Pull 30 days of hourly candles (seconds for candles)
end_s = int(time.time())
start_s = end_s - 30 * 24 * 3600
candles = requests.get(
    f"{BASE}/v2/polymarket/candlesticks/{condition_id}",
    headers=HEADERS,
    params={"interval": 60, "start_time": start_s, "end_time": end_s},
).json()
candles_df = pd.DataFrame(candles)
print(f"Candles: {len(candles_df)} bars")

# 3. Pull the trade tape (seconds for trades)
trades = requests.get(
    f"{BASE}/v2/polymarket/trades",
    headers=HEADERS,
    params={"token_id": token_id, "start_time": start_s, "end_time": end_s, "limit": 1000},
).json()
print(f"Trades: {len(trades)}")

# 4. Walk historical orderbook snapshots (milliseconds for orderbook)
end_ms = end_s * 1000
start_ms = start_s * 1000
snapshots, cursor = [], start_ms
while cursor < end_ms:
    page = requests.get(
        f"{BASE}/v2/polymarket/orderbooks",
        headers=HEADERS,
        params={"token_id": token_id, "start_time": cursor, "end_time": end_ms, "limit": 200},
    ).json()
    if not page: break
    snapshots.extend(page)
    cursor = page[-1]["timestamp"] + 1
print(f"Orderbook snapshots: {len(snapshots)}")