A-Share Data Analysis Tools

Why I built it

I used these projects to turn recurring market-data questions into reusable views and to understand how unstable upstream interfaces affect data tools. The outputs are for observation and review, not trading recommendations.

Links

What it includes

• Presents intraday prices, tick transactions, large-order behavior, technical indicators, basic fundamentals, flow estimates, and risk statistics in Streamlit views.
• Keeps data access, field normalization, analysis, charts, and page logic in separate modules so changing an AKShare field does not require rewriting the whole app.
• Parses documented AKShare stock endpoints and runs each check in a separate process with timeout, retries, rate control, and resume support.
• Writes searchable HTML plus CSV, JSON, and XLSX reports so failed endpoints can be reviewed rather than reduced to one pass/fail count.

What I worked on

• Defined the questions each tool should answer and used AI assistance to implement and reorganize data fetching, cleaning, indicators, charts, and interface-checking workflows.
• Reviewed generated code and reports against real AKShare responses, including alternate field names, empty data, timeouts, upstream failures, and cached results.
• Separated experimental anomaly detection and classification examples from the main dashboards, and kept all financial wording at the level of observation rather than prediction.