← 返回
数据分析 Key 中文

Polymarket Real Time Trades Stream

Real-time streaming Polymarket prediction trades on Polygon (matic) with live USD pricing. Subscribe to a live stream of Polymarket prediction market trades...
实时流式传输Polygon链上的Polymarket预测交易,提供实时美元定价。
divyn
数据分析 clawhub v1.0.5 3 版本 99834.2 Key: 需要
★ 0
Stars
📥 602
下载
💾 21
安装
3
版本
#latest

概述

Polymarket Prediction Trades — real-time streaming on Polygon

This skill gives you a real-time streaming Polymarket prediction trade feed over WebSocket on Polygon (matic). Every event is a successful prediction trade with outcome token amounts, collateral in USD, price in USD, buyer/seller addresses, market question, outcome label (e.g. "Up" / "Down"), and transaction hash.

Trades are filtered to TransactionStatus.Success: true. The stream uses Bitquery's EVM.PredictionTrades subscription so downstream code can build dashboards, track order flow, or monitor specific markets.

Official docs: Polymarket API — Get Prices, Trades & Market Data (Bitquery).


What to consider before installing

This skill's code implements the described Polymarket stream and contacts only Bitquery. Before installing:

  1. Required credential: This skill requires BITQUERY_API_KEY (your Bitquery API token). The registry metadata must declare this credential so installers are prompted to provide it. Verify the registry entry lists BITQUERY_API_KEY as a required environment variable.
  1. ⚠️ Critical security risk — Token in WebSocket URL: Bitquery's API does not support header-based auth or any method other than embedding the token in the WebSocket URL as ?token=.... This is an inherent design limitation of the API, not a bug in this skill. However, it creates a significant leakage risk:
    • The token will always be present in the connection URL in memory and in any logs or captured network traffic
    • If the URL is printed, logged, captured in shell history, IDE history, proxy logs, firewall logs, or monitoring systems, the token is exposed
    • Once exposed, anyone with the token can impersonate your account and consume your quota
    • Mitigation: Store the key only in a secure environment variable; never print or log the full URL; rotate the key immediately if you suspect exposure; run in a sandboxed environment (virtualenv/container) to limit logging surface
  1. Sandbox first: Before using this skill in production or in shared environments, test it in an isolated environment (virtualenv, container, or dedicated machine) to confirm the logging behavior and ensure the URL is not captured by system monitoring or logging tools you have enabled.
  1. Source and publisher: Verify the publisher's identity and source control access. Review the code in scripts/stream_polymarket.py to confirm the script does not log the full URL before use.

Security Checklist

Before running this skill, confirm:

  • [ ] You have set BITQUERY_API_KEY in your environment: export BITQUERY_API_KEY=your_token_here
  • [ ] You are running in a sandboxed or isolated environment (virtualenv, Docker, or dedicated machine)
  • [ ] Logging and shell history are disabled or monitored to prevent URL capture: check HISTFILE, .bash_history, system logs, IDE debug output
  • [ ] You understand that the WebSocket URL will contain your API token in plaintext in memory
  • [ ] You have a plan to rotate your key if it is ever exposed
  • [ ] You will not print, log, or commit the full URL to any file or logging system

If any of these cannot be confirmed, do not proceed with this skill until those conditions are met.


Prerequisites

  • Environment: BITQUERY_API_KEY — your Bitquery API token (required).

⚠️ URL-only authentication (Bitquery API limitation): Bitquery's streaming endpoint accepts the token only in the WebSocket URL as a query parameter (?token=...). It does not support header-based auth or Bearer tokens. This design choice means:

  • The token is embedded in the connection URL and will be present in memory, network traces, and any logs that capture the full URL
  • Never print, log, or emit the full WebSocket URL in any context
  • Always construct the URL from the environment variable and pass it only to the WebSocket transport
  • If the URL appears in shell history, logs, IDE debugger, or network monitoring, the token is compromised
  • Rotate your API key immediately if you suspect it was logged or captured
  • Run this script only in controlled environments where logging and monitoring are configured securely
  • Runtime: Python 3.8+ and pip. Install the dependency: pip install 'gql[websockets]'.

Trader Use Cases

These are the key reasons a trader would use this feed:

1. Order flow / market activity

Monitor every filled order: buyer, seller, collateral in USD, price in USD, and outcome (Yes/No or Up/Down). Identify which markets are most active and which side (buy vs sell) is dominant.

2. Whale / large-trade detection

Filter by CollateralAmountInUSD or Amount to surface large prediction-market trades. Useful for following smart-money flow into specific outcomes.

3. Market-specific monitoring

Use Question.MarketId, Question.Title, or Question.Id to filter the stream to a single market (e.g. "Ethereum Up or Down - March 10") and track all trades for that market in real time.

4. Outcome imbalance

Aggregate trades by Outcome.Label (e.g. "Up" vs "Down") and IsOutcomeBuy to see net buying pressure per outcome — useful for sentiment or momentum.

5. Resolution source / data markets

Use Question.ResolutionSource and Question.Title to focus on data or oracle-driven markets (e.g. Chainlink streams) and monitor trading around resolution.

6. Entry / exit timing

Stream PriceInUSD and CollateralAmountInUSD per trade to see where size is trading and at what price — helps time entries and exits in prediction markets.

7. Protocol / marketplace verification

Marketplace.ProtocolName and ProtocolFamily (e.g. "polymarket", "Gnosis_CTF") confirm the trade is from Polymarket on Polygon; use to avoid mixing with other protocols.

8. Audit trail

Each event includes Transaction.Hash, Block.Time, Call.Signature.Name (e.g. "matchOrders"), and Log.Signature.Name (e.g. "OrderFilled") for full on-chain audit.


Step 1 — Check API Key

import os
api_key = os.getenv("BITQUERY_API_KEY")
if not api_key:
    print("ERROR: BITQUERY_API_KEY environment variable is not set.")
    print("Run: export BITQUERY_API_KEY=your_token")
    exit(1)

If the key is missing, tell the user and stop. Do not proceed without it.


Step 2 — Run the stream

Install the WebSocket dependency once:

pip install 'gql[websockets]'

Use the streaming script:

python ~/.openclaw/skills/polymarket-prediction-trades/scripts/stream_polymarket.py

Optional: stop after N seconds:

python ~/.openclaw/skills/polymarket-prediction-trades/scripts/stream_polymarket.py --timeout 60

Or subscribe inline with Python:

import asyncio, os
from gql import Client, gql
from gql.transport.websockets import WebsocketsTransport

async def main():
    token = os.environ["BITQUERY_API_KEY"]
    url = f"wss://streaming.bitquery.io/graphql?token={token}"
    transport = WebsocketsTransport(
        url=url,
        headers={"Sec-WebSocket-Protocol": "graphql-ws"},
    )
    async with Client(transport=transport) as session:
        sub = gql("""
            subscription MyQuery {
              EVM(network: matic) {
                PredictionTrades(where: { TransactionStatus: { Success: true } }) {
                  Block { Time }
                  Call { Signature { Name } }
                  Log { Signature { Name } SmartContract }
                  Trade {
                    OutcomeTrade {
                      Buyer
                      Seller
                      Amount
                      CollateralAmount
                      CollateralAmountInUSD
                      OrderId
                      Price
                      PriceInUSD
                      IsOutcomeBuy
                    }
                    Prediction {
                      CollateralToken { Name Symbol SmartContract AssetId }
                      ConditionId
                      OutcomeToken { Name Symbol SmartContract AssetId }
                      Marketplace { SmartContract ProtocolVersion ProtocolName ProtocolFamily }
                      Question { Title ResolutionSource Image MarketId Id CreatedAt }
                      Outcome { Id Index Label }
                    }
                  }
                  Transaction { From Hash }
                }
              }
            }
        """)
        async for result in session.subscribe(sub):
            for trade in (result.get("EVM") or {}).get("PredictionTrades") or []:
                q = (trade.get("Trade") or {}).get("Prediction") or {}
                q = q.get("Question") or {}
                ot = (trade.get("Trade") or {}).get("OutcomeTrade") or {}
                pred = (trade.get("Trade") or {}).get("Prediction") or {}
                outcome = pred.get("Outcome") or {}
                print(
                    f"{q.get('Title', '?')} | "
                    f"Outcome: {outcome.get('Label', '?')} | "
                    f"${float(ot.get('CollateralAmountInUSD') or 0):.2f}"
                )

asyncio.run(main())

Step 3 — Key fields on every trade

FieldWhat it means for traders
-----------------------------------
Trade.OutcomeTrade.BuyerTaker buyer address
Trade.OutcomeTrade.SellerMaker seller address
Trade.OutcomeTrade.AmountOutcome token amount (raw)
Trade.OutcomeTrade.CollateralAmountCollateral token amount
Trade.OutcomeTrade.CollateralAmountInUSDNotional in USD — use for size/whale filter
Trade.OutcomeTrade.OrderIdOrder identifier
Trade.OutcomeTrade.PricePrice in collateral (0–1 typical for binary)
Trade.OutcomeTrade.PriceInUSDPrice in USD — entry/exit reference
Trade.OutcomeTrade.IsOutcomeBuyTrue = buyer bought the outcome (Yes/Up)
Trade.Prediction.Question.TitleMarket question (e.g. "Ethereum Up or Down - ...")
Trade.Prediction.Question.MarketIdMarket ID for filtering
Trade.Prediction.Question.ResolutionSourceResolution source (e.g. Chainlink URL)
Trade.Prediction.Outcome.LabelOutcome label (e.g. "Up", "Down")
Trade.Prediction.Marketplace.ProtocolNamee.g. "polymarket"
Block.TimeTrade timestamp (ISO)
Transaction.HashOn-chain tx hash for audit
Call.Signature.Namee.g. "matchOrders"
Log.Signature.Namee.g. "OrderFilled"

Step 4 — Format output for traders

When presenting prediction trades to a trader, use this layout:

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Polymarket  [matic]  Protocol: polymarket (Gnosis_CTF)
Time: 2026-03-10T13:21:11Z  Tx: 0x9566...f2da
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Question: Ethereum Up or Down - March 10, 9:15AM-9:30AM ET
MarketId: 1537455  |  Outcome: Down  (Index 1)
Resolution: https://data.chain.link/streams/eth-usd
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
OutcomeTrade
  Side:       BUY outcome (IsOutcomeBuy: true)
  Buyer:      0x22dc...91bb  →  Seller: 0x86a2...73a8
  Collateral: 0.316471 USDC  (USD: $0.32)
  Price:      0.632942  (USD: $0.633)
  Amount:     500000 (outcome tokens)
  OrderId:    44433632...
Call: matchOrders  |  Log: OrderFilled @ 0x4bfb...982e
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Error handling

  • Missing BITQUERY_API_KEY: Tell user to export the variable and stop
  • WebSocket connection failed / 401: Token invalid or expired (auth is via URL ?token= only — do not pass the token in headers)
  • Subscription errors in payload: Log the error and stop cleanly (send complete, close transport)
  • No events received: Polygon prediction activity can be bursty; wait a few seconds or check that Polymarket has recent activity on matic
  • Empty PredictionTrades: Ensure filter is TransactionStatus: { Success: true } and network is matic

Reference

版本历史

共 3 个版本

  • v1.0.5 当前
    2026-03-29 17:04 安全 安全
  • v1.0.2
    2026-03-26 22:20
  • v1.0.3
    2026-03-19 04:25

安全检测

腾讯云安全 (Keen)

安全,无风险
查看报告

腾讯云安全 (Sanbu)

安全,无风险
查看报告

🔗 相关推荐

developer-tools

Reliable Pumpfun Price Feed

divyn
Solana上的PumpFun代币实时流数据,包含每枚代币的实时USD价格。可通过WebSocket订阅直播流。
★ 0 📥 599
data-analysis

A股量化 AkShare

mbpz
A股量化数据分析工具,基于AkShare库获取A股行情、财务数据、板块信息等。用于回答关于A股股票查询、行情数据、财务分析、选股等问题。
★ 165 📥 60,016
data-analysis

Data Analysis

ivangdavila
{"answer":"数据分析与可视化。查询数据库、生成报告、自动化电子表格,将原始数据转化为清晰可行的见解。适用于:(1) 您……"}
★ 198 📥 65,120