Blue Sky Social Media Data Collector

This project is designed to collect, store, and process data from Blue Sky social media. The goal is to create a comprehensive toolset for interacting with the Blue Sky API, enabling users to gather insights and perform various operations on social media data.

Project Structure

The main scripts you need are :

• store_bsky_data_in_db.py: A script to continuously collect posts from the Blue Sky timeline and store them in a SQLite database.
• main.py: The main application file that sets up a web interface for analyzing Blue Sky feed data using AI.
• useful_info.md: Contains useful links and resources for getting started with Blue Sky development.
• .env: Configuration file for storing environment variables and API keys.

others are just for experimenting with the data and the api:

• scripbles.ipynb: A Jupyter Notebook for experimenting with the Blue Sky API, testing data collection methods, and analyzing collected data.
• get_a_list_of_posts.py: A script to retrieve and display posts from the user's timeline.
• post_a_message.py: A script to post a message to Blue Sky and interact with posts (e.g., liking a post).

Setup Instructions

1. Clone the Repository

   git clone https://github.com/resolver101757/blue_sky_data
   cd bluesky-data-collector

2. Install Dependencies

   Ensure you have Python 3.12.2 or later installed. Then, install the required packages:

   pip install -r requirements.txt

3. Environment Variables

   Create a .env file in the root directory and add your credentials:

   username=your_bluesky_username
   password=your_bluesky_password
   google_api_key=your_google_api_key
   

4. Run the Scripts

   • To run the main application:

     python main.py

Features

• Collect and store posts from Blue Sky in a SQLite database
• Post messages to Blue Sky
• Web interface for analyzing Blue Sky feed using AI (powered by Google's Gemini model)
• Jupyter Notebook for data exploration and experimentation

Future Development

• Implement more advanced data processing and analysis techniques
• Enhance the web interface with more features and visualizations
• Improve error handling and logging
• Add user authentication for the web interface
• Implement real-time data streaming capabilities

Contributing

Contributions are welcome! Please fork the repository and submit a pull request with your changes.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For questions or suggestions, please open an issue on the GitHub repository.