{"id":23394138,"url":"https://github.com/lizardcat/stocksasa","last_synced_at":"2025-07-26T02:39:36.804Z","repository":{"id":250966836,"uuid":"836000641","full_name":"lizardcat/stocksasa","owner":"lizardcat","description":"Stocksasa is a Python stock trend prediction system powered by AI","archived":false,"fork":false,"pushed_at":"2025-04-04T00:21:06.000Z","size":151,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-04T00:26:19.627Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/lizardcat.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":".github/CODEOWNERS","security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-07-31T00:51:52.000Z","updated_at":"2025-04-04T00:21:09.000Z","dependencies_parsed_at":null,"dependency_job_id":"5d44dba1-3657-4c9c-9ea5-1fdbfc53806a","html_url":"https://github.com/lizardcat/stocksasa","commit_stats":null,"previous_names":["lizardcat/stocksasa"],"tags_count":0,"template":false,"template_full_name":"streamlit/gdp-dashboard-template","purl":"pkg:github/lizardcat/stocksasa","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lizardcat%2Fstocksasa","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lizardcat%2Fstocksasa/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lizardcat%2Fstocksasa/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lizardcat%2Fstocksasa/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lizardcat","download_url":"https://codeload.github.com/lizardcat/stocksasa/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lizardcat%2Fstocksasa/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":267108996,"owners_count":24037615,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-07-26T02:00:08.937Z","response_time":62,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-12-22T06:12:55.841Z","updated_at":"2025-07-26T02:39:36.723Z","avatar_url":"https://github.com/lizardcat.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Stocksasa - A Simple AI Market Trend Prediction App\n\n**Stocksasa** is a stock trend prediction system powered by AI. It uses historical market data, technical indicators, and macroeconomic event analysis (like tariffs and interest rate changes) to predict whether a stock or index is likely to go up or down the next day.\n\nBuilt with:\n- Python \n- Streamlit for interactive UI\n- Random Forest Classifier for AI predictions\n- yFinance for market data\n- NewsAPI for real-time economic events (optional)\n\n## Features\n\n- Predicts up/down movement for any stock or index (only 12 are implemented currently but more can be added)\n- Visualizes recent trends and AI predictions\n- Learns from technical indicators + global event flags\n- Export historical data as CSV\n- Automatically update macroeconomic events with `update_events.py`\n\n## Live Demo\n\nYou can see a live demo of the app on Streamlit here: https://stocksasa.streamlit.app/\n\n## Screenshots \n### 1. Current Market Outlook\n![](/assets/stocksasa_1.png)\n\n### 2. AI Market Prediction for S\u0026P500\n![](/assets/stocksasa_2.png)\n\n## Installation\n\nClone the repo and install requirements:\n\n```bash\ngit clone https://github.com/lizardcat/stocksasa.git\n\ncd stocksasa\n\n# Create virtual environment\npython -m venv .venv\nsource .venv/bin/activate  # Windows: .venv\\Scripts\\activate\n\n# Install packages\npip install -r requirements.txt\n```\n\n## API Key Setup (for NewsAPI)\n\nTo use live news updates, you’ll need a free API key from [NewsAPI.org](https://newsapi.org/).\n\n- Create a file named .env in the root of your project.\n\n- Inside that file, add your own NewsAPI key like this:\n\n```\nNEWSAPI_KEY=your_actual_api_key_here\n```\n\nReplace `your_newsapi_key_here` with your personal API key from https://newsapi.org.\nThis file is ignored by Git and will stay private.\n\n## How to Use\n\n### 1. Train the model:\n```bash\npython main.py\n```\n\n### 2. Run the Streamlit app:\n```bash\nstreamlit run app.py\n```\n\n### 3. Update events from live news:\n```bash\npython update_events.py\n```","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flizardcat%2Fstocksasa","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flizardcat%2Fstocksasa","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flizardcat%2Fstocksasa/lists"}