Orderbook replay

{
  "timestamp": 1736294400000,
  "token_id": "82855...",
  "condition_id": "0x...",
  "bids": [{ "price": "0.62", "size": "5000" }, ...],
  "asks": [{ "price": "0.63", "size": "3000" }, ...]
}

import requests, time

API_KEY = "YOUR_API_KEY"
BASE = "https://api.predexon.com"
HEADERS = {"x-api-key": API_KEY}

TOKEN_ID = "82855..."          # the outcome you're backtesting
START_MS = 1736294400000       # 2026-01-08 00:00 UTC
END_MS   = 1736380800000       # 2026-01-09 00:00 UTC

cursor = START_MS
while cursor < END_MS:
    snaps = 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 snaps:
        break

    for s in snaps:
        # your strategy sees the book exactly as it was at s["timestamp"]
        best_bid = float(s["bids"][0]["price"]) if s["bids"] else 0
        best_ask = float(s["asks"][0]["price"]) if s["asks"] else 1
        spread   = best_ask - best_bid
        # decide(s, best_bid, best_ask, spread)

    cursor = snaps[-1]["timestamp"] + 1

def simulate_market_buy(snapshot, usd_to_spend):
    spent, filled = 0.0, 0.0
    for level in snapshot["asks"]:
        price = float(level["price"])
        size  = float(level["size"])
        level_cost = price * size
        if spent + level_cost <= usd_to_spend:
            spent  += level_cost
            filled += size
        else:
            remaining_usd = usd_to_spend - spent
            partial_size  = remaining_usd / price
            spent  += remaining_usd
            filled += partial_size
            break
    avg_price = spent / filled if filled else None
    return {"filled_shares": filled, "avg_price": avg_price, "usd_spent": spent}