How to Build a Polymarket Trading Bot in Python (2026)

Polymarket's order book is fully programmatic — everything you can do in the UI, a bot can do through the CLOB API. This tutorial walks through the whole stack: wallet setup, the py-clob-client SDK, reading markets, placing orders, and a strategy skeleton you can extend. At the end, we'll cover the one thing most bot tutorials skip: where your edge actually comes from.

Not financial advice. Trading bots can lose money quickly. Test with small amounts, and always verify market resolution criteria before trading.

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What You'll Need

• Python 3.9+
• A Polygon wallet (its private key) funded with USDC on Polygon plus a small amount of POL for gas
• The official Polymarket Python client: pip install py-clob-client

Unlike reading market data (which needs no auth at all), trading on Polymarket requires wallet-based authentication — orders are signed with your key and settle on-chain.

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Step 1: Connect and Derive API Credentials

Polymarket's CLOB uses two auth layers: your wallet key (L1) signs a message to derive API credentials (L2) used for order endpoints.

from py_clob_client.client import ClobClient

HOST = "https://clob.polymarket.com"
PRIVATE_KEY = "0x..."  # your wallet key — use env vars, never hardcode
CHAIN_ID = 137         # Polygon mainnet

client = ClobClient(HOST, key=PRIVATE_KEY, chain_id=CHAIN_ID)
client.set_api_creds(client.create_or_derive_api_creds())

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Step 2: Find a Market to Trade

Use the Gamma API to discover markets, then grab the CLOB token IDs:

import json, requests

events = requests.get(
    "https://gamma-api.polymarket.com/events",
    params={"limit": 5, "active": "true", "closed": "false", "order": "volume", "ascending": "false"},
).json()

market = events[0]["markets"][0]
token_ids = json.loads(market["clobTokenIds"])  # [yes_token, no_token]
yes_token = token_ids[0]
print(market["question"], "| Yes token:", yes_token)

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Step 3: Read the Order Book

book = client.get_order_book(yes_token)
best_bid = float(book.bids[0].price) if book.bids else None
best_ask = float(book.asks[0].price) if book.asks else None
print(f"Best bid: {best_bid} | Best ask: {best_ask}")

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Step 4: Place (and Cancel) an Order

from py_clob_client.clob_types import OrderArgs
from py_clob_client.order_builder.constants import BUY

order = client.create_order(OrderArgs(
    price=0.45,   # 45¢
    size=10.0,    # 10 shares
    side=BUY,
    token_id=yes_token,
))
resp = client.post_order(order)
print(resp)

# client.cancel(order_id=resp["orderID"])  # cancel anytime

A limit buy at 45¢ on a Yes token pays out $1 per share if the market resolves Yes. That's the whole game: buy probability cheap, sell it dear.

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Step 5: The Strategy Loop

Every trading bot reduces to the same skeleton:

import time

def get_signal(market) -> str:
    """Return 'buy', 'sell', or 'hold'. This is where your edge lives."""
    ...

while True:
    for market in watchlist:
        signal = get_signal(market)
        if signal == "buy" and within_risk_limits(market):
            place_order(market)
    time.sleep(POLL_INTERVAL)  # or use WebSockets and react to events

Non-negotiable risk controls before you run anything live: a max position size per market, a max total exposure, a kill switch, and logging for every decision. Polymarket also enforces rate limits, so prefer WebSocket streams over tight polling loops.

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Where Does the Edge Come From?

This is the part most tutorials hand-wave. A bot that only sees Polymarket has no reference point — it knows the price, but not whether the price is wrong. The most reliable signals in prediction markets come from comparing venues:

• Cross-platform price gaps. If Kalshi has the same event at 52¢ and Polymarket at 46¢, one of them is mispriced — or you've found an arbitrage.
• Smart money flow. Wallets with strong track records moving size is information.
• Speed on news. Prices adjust at different rates on different platforms.

Building that yourself means integrating Kalshi (RSA-signed requests), PredictIt, ProphetX, and others, then solving entity resolution — matching presidential-2028 to PRES-2028-DEM across naming schemes, at scale.

Or you make one call:

import requests

resp = requests.get(
    "https://prediction.com/api/v2/search",
    params={"q": "presidential election"},
    headers={"X-API-Key": "YOUR_API_KEY"},
)
# One response: the same event's price on Polymarket, Kalshi, PredictIt, ProphetX & more

The Prediction HuntPrediction.com API handles the multi-platform plumbing — 6 platforms, automatic event matching, plus WebSocket channels for prices, smart-money alerts, and cross-platform arbitrage signals. There are ready-to-run starter scripts, including an arb alert bot, and the free tier (1,000 req/month) is enough to prototype a signal layer.

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Common Pitfalls

• clobTokenIds and outcomePrices are JSON strings, not arrays. Parse them.
• Insufficient allowances. Your wallet must approve USDC spending for the exchange contracts before orders will post.
• Ignoring resolution criteria. Two "identical" markets can resolve differently. Read the rules.
• Testing in production. Start with tiny size. There is no Polymarket paper-trading environment (Kalshi has one; Prediction HuntPrediction.com also offers a paper portfolio).

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FAQ

Is running a Polymarket bot allowed? Programmatic trading via the official CLOB API is supported — that's what the API is for. Check Polymarket's terms and your local regulations regarding platform access.

Do I need an API key? No separate key — credentials are derived from your wallet's private key via py-clob-client.

Can I backtest? Yes — pull historical prices from the CLOB /prices-history endpoint or use a historical data source covering multiple platforms.

Give your bot eyes on every platform. Get a free Prediction HuntPrediction.com API key and stream cross-platform prices, smart money, and arb alerts into your strategy.