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How to self-host an A-share quant workbench in one container with Tick Stock Panel

Pull the published image and run strategies, scans and dashboards locally with your data on your disk.

Short answer: Install Docker; then run the one-line docker run command from the README quick start, which pulls the ghcr.io/shy3130/tick-stock-panel image and mounts a local data folder; open the workbench on localhost at the port given in the quick start. All steps.

  • Top pick
  • Money
  • Beginner
  • 20 minutes
  • From the README
  • Any agent

Who it is forA developer studying China A-shares who does not want cloud platforms holding their data.

The problemPatched together scripts and paid terminals make it hard to keep data, strategies and backtests consistent.

The outcomeA local web workbench with dashboard, screener, backtest, mining and monitoring pages, data stored as local Parquet.

What you need first

  • Docker (one container, no external database)
  • Optional: a TickFlow API key or another plugged in data source
  • Optional: an OpenAI compatible LLM endpoint for strategy generation and the chat assistant

Steps

  1. Install Docker
  2. Run the one-line docker run command from the README quick start, which pulls the ghcr.io/shy3130/tick-stock-panel image and mounts a local data folder
  3. Open the workbench on localhost at the port given in the quick start
  4. Copy .env.example to .env if you need a data source key or LLM settings

Prompt for your agent

Deploy shy3130/tick-stock-panel locally with the published Docker image from its README quick start, keep data in a mounted folder, and tell me which pages load and which data source mode it is in.

Caveat. It targets China A-shares only and the README says it is for learning and research, not an investment or market watching tool. Not financial advice: paper trade first, and remember you can lose money.

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Using the Deduped MCP, get the setup steps for shy3130/tick-stock-panel and "Self-host an A-share quant workbench in one container"

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