zhulinsen/daily_stock_analysis

Analysis updated 2026-06-20

★ 34,255PythonAudience · dataComplexity · 3/5LicenseSetup · moderate

Mindmap

mindmap
  root((Daily Stock Analysis))
    Data Sources
      AkShare Tushare
      YFinance
      News APIs
      Social sentiment
    AI Models
      Gemini Claude
      OpenAI DeepSeek
      Local Ollama
    Output Channels
      WeChat Work
      Feishu Lark
      Telegram Slack
      Email
    Deployment
      GitHub Actions
      Docker
      Local

mindmap root((Daily Stock Analysis)) Data Sources AkShare Tushare YFinance News APIs Social sentiment AI Models Gemini Claude OpenAI DeepSeek Local Ollama Output Channels WeChat Work Feishu Lark Telegram Slack Email Deployment GitHub Actions Docker Local

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What do people build with it?

USE CASE 1

Receive a daily AI-generated buy/sell analysis for your Chinese and US stock watchlist automatically in Slack or Telegram.

USE CASE 2

Run the full stock analysis pipeline for free on GitHub Actions on a schedule without a dedicated server.

USE CASE 3

Generate a daily market overview of index performance, sector leaders, and sentiment for A-share and US markets.

What is it built with?

PythonGitHub ActionsDockerAkShareTushareYFinance

How does it compare?

	zhulinsen/daily_stock_analysis	stanfordnlp/dspy	python-poetry/poetry
Stars	34,255	34,238	34,273
Language	Python	Python	Python
Setup difficulty	moderate	moderate	easy
Complexity	3/5	3/5	2/5
Audience	data	developer	developer

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 1h+

Requires API keys for stock data providers and an AI model, plus a messaging bot token, free to run on GitHub Actions.

Use, copy, modify, and distribute freely for any purpose, including commercial use, as long as you keep the copyright notice.

In plain English

Daily Stock Analysis is a Python project that automates daily AI-powered analysis of stocks in the Chinese A-share market, Hong Kong H-share market, and US markets. The problem it solves is that tracking multiple stocks across different markets, aggregating price data, news, sentiment, and fundamental information, and producing a structured investment opinion each day is extremely time-consuming if done manually. This tool automates the entire pipeline and delivers a concise decision dashboard to messaging apps on a schedule. The system works by fetching market data from multiple sources, stock price and technical indicator providers like AkShare, Tushare, and YFinance, and combining them with real-time news search (via APIs like SerpAPI, Tavily, or Brave Search), social sentiment signals, and company announcements. It feeds this combined information to a large language model (configurable to use Gemini, Claude, OpenAI-compatible models, DeepSeek, or local Ollama models) which generates a structured analysis for each stock including a one-sentence conclusion, a score, suggested buy/sell levels, risk alerts, and an action checklist. It also generates a daily market overview covering index performance, sector leaders, and market breadth. The output is pushed automatically to notification channels including WeChat Work bots, Feishu (Lark) bots, Telegram, Discord, Slack, and email. The whole pipeline is designed to run for free on GitHub Actions on a schedule, requiring no server, though Docker and local deployment options are also supported. You would use this project if you actively follow a watchlist of Chinese and US stocks and want a daily AI-generated briefing delivered to your team chat or inbox without doing the aggregation yourself. The project is MIT-licensed Python code running on Python 3.10 or newer.

Copy-paste prompts

Prompt 1

Set up daily_stock_analysis to track 10 Chinese A-share stocks and 5 US stocks. Write the config file with these tickers, using Gemini for AI analysis and Slack for notifications.

Prompt 2

Configure daily_stock_analysis to use a local Ollama model instead of a cloud AI API so all stock analysis stays private on my machine.

Prompt 3

Write the GitHub Actions workflow YAML to run daily_stock_analysis every weekday at 8am UTC, with all API keys stored as GitHub Secrets.

Prompt 4

Show me how to add new stocks to my daily_stock_analysis watchlist and customize the AI prompt to focus on dividend yield and earnings momentum.

Frequently asked questions

What is daily_stock_analysis?

Daily Stock Analysis automates AI-powered daily briefings for Chinese A-share, Hong Kong, and US stocks, fetching price data, news, and sentiment, then delivering a structured buy/sell analysis to messaging apps like Slack or WeChat on a schedule.

What language is daily_stock_analysis written in?

Mainly Python. The stack also includes Python, GitHub Actions, Docker.

What license does daily_stock_analysis use?

Use, copy, modify, and distribute freely for any purpose, including commercial use, as long as you keep the copyright notice.

How hard is daily_stock_analysis to set up?

Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.

Who is daily_stock_analysis for?

Mainly data.

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