This repository implements a Python library for performing technical analysis of stock price data based on 'Chan Theory' (缠论). It calculates core elements such as strokes (笔), segments (线段), central hubs (中枢), and buy/sell points (买卖点) from K-line (OHLC) data. The system supports multiple data sources (BaoStock, AKShare, CSV, CCXT) and multiple timeframes (day, week, month, minute). The architecture is modular: the central CChan class orchestrates the analysis, with submodules for strokes (Bi), segments (Seg), hubs (ZS), buy/sell points (BuySellPoint), mathematical indicators (Math), plotting (Plot), and data access (DataAPI). Key entry points include main.py for demonstration, App/ashare_bsp_scanner_gui.py for a GUI-based stock scanner, and the CChan class for programmatic use. Data flows from user-provided stock codes and time ranges through the data API, then through the analysis pipeline (K-line combination, stroke detection, segment calculation, hub identification, buy/sell point detection), and finally outputs results that can be plotted or accessed via object properties. External dependencies include baostock, akshare, ccxt, matplotlib, numpy, pandas, and requests.