$ show quant-king299/EasyXT
EasyXT is a comprehensive quantitative trading toolkit for Chinese A-share markets, built on top of the Xuntou QMT broker platform. It provides a modular ecosystem that includes data management (multi-source with automatic fallback via DuckDB, Tushare, BaoStock, QMT DAT files, etc.), factor research (Alpha101/Alpha191 engines, IC/IR analysis, layered backtesting, Fama-French factors), backtesting engines (vectorized and event-driven with T+1 enforcement), live trading capabilities (auto-login, signal bridges, real-time quote providers, WebSocket push, monitoring), and multiple strategy implementations (grid trading, small-cap, convertible bonds, Xueqiu portfolio following). The system also features a PyQt5 desktop GUI and a Streamlit web app for factor analysis and strategy configuration. While primarily an application framework for executing trading strategies, it contains significant data research components for alpha factor development and performance analysis, making it a hybrid tool with a focus on production deployment. The codebase is large and actively maintained, with well-designed abstractions like data source adapters, cache backends, and a config manager, but also exhibits some duplication, hardcoded paths, and mixed Chinese/English naming that may hinder portability.
The LLM identified 5 files worth highlighting for reuse:
A robust DuckDB connection manager implementing a singleton pattern with read/write connection splitting, automatic retry with backoff, and context manager support. It provides a unified interface for obtaining connections, ensuring thread safety and resource cleanup. This component is self-contained and could be extracted as a standalone library for any Python project using DuckDB, especially those requiring high concurrency and resilience.
A multi-level configuration manager that supports system, user, session, and runtime layers with nested dict access and automatic file persistence. It uses dataclasses for typed configuration, thread-safe reads, and provides methods for deep merge, validation, and export/import. This pattern is reusable as a general-purpose configuration library for any Python application needing hierarchical, file-backed settings.
A collection of in-memory cache implementations (LRU, LFU, FIFO) with optional serialization, compression, TTL-based expiry, and a background cleanup thread. Each cache subclass exposes a clean API (get, set, delete, stats) and can be used independently. The design is generic and can be reused as a high-performance caching layer in any Python application, with easy extension to other eviction policies.
A base class for implementing quantitative trading strategies, providing reusable infrastructure for position handling, market code normalization, cookie loading, dataframe formatting, and stock list retrieval. It follows the template method pattern: subclasses implement specific logic (e.g., signal generation) while inheriting data merging, risk checks, and execution helpers. This component can be extracted and used as a foundation for any broker-agnostic strategy framework.
A standalone module for computing Information Coefficient (IC) and Rank IC measures for factor evaluation, supporting multiple period types (daily, weekly, monthly) and generating statistical summaries including t-tests and cumulative IC plots. It is well-structured with clear data inputs (factor values, forward returns) and outputs (DataFrame with IC series, mean, std, IR). This can be reused in any factor research pipeline without dependency on the rest of the EasyXT codebase.