CTP Direct Data Connector

CTP Direct Data is useful when a futures workflow needs to pull market data, order flow, and account state from a broker's CTP interface into a local engineering pipeline. Many quant setups do not just need a script that can connect to CTP; they also need to handle market subscription, order reports, position and funds queries, data persistence, and real-time distribution, especially across the configuration differences between SimNow testing and live penetration environments.

What It Solves

The skill wraps CTP as a reusable data and trading connector. On the market side, it supports Tick, depth, and K-line data. On the trading side, it covers placing orders, canceling orders, querying orders, fills, positions, and funds. For output, it supports CSV/JSON files, database storage, and real-time streaming through ZeroMQ or WebSocket. In a strategy project, it behaves more like a local data pipeline than a one-off API call.

How It Works

The core capabilities are split into modules: CTPMarketData handles market data, CTPTrader handles trading, and data models normalize returned structures. Configuration is managed through config/ctp_config.yaml plus environment variables, with sensitive fields recommended to be injected as ${ENV_VAR} to avoid plaintext passwords or auth_code. The typical run path is: log in to market and trading front ends, subscribe to contracts, receive reports, then write data to storage or push it to downstream services. For backtesting, persisted market data can be used directly as historical input. For live or near-realtime use, ZeroMQ/WebSocket can distribute data to strategy, monitoring, or visualization components.

Scope and Caveats

It is suitable for SimNow and the user's own live accounts, not for bypassing broker permissions or engaging in unauthorized trading. Before live use, verify app_id, auth_code, broker_id, front-end addresses, and complete penetration authentication. Connection failures usually require checking network reachability, credentials, trading hours, contract code casing, and login state. In production, pay attention to log masking, .env version control, pinned dependencies, and storage permissions.