Skip to content

README.md

Latest commit

 

History

History
131 lines (107 loc) · 3.88 KB

README.md

File metadata and controls

131 lines (107 loc) · 3.88 KB

Python Learning Repository

A collection of Python modules and utilities demonstrating best practices in Python development.

Modules

coding_habits.py

Contains practical examples of Python best practices, including:

  • Data types and their properties (immutable vs mutable, usage examples)
  • String formatting with f-strings
  • Path manipulation with pathlib
  • File operations
  • Exception handling
  • Using default parameters safely
  • Comprehensions (list, dict, set, generator)
  • Type checking with isinstance
  • Comparing singletons (None, True, False)
  • Advanced iteration techniques (enumerate, zip, reversed)
  • Performance timing with time.perf_counter()
  • Logical operators (and, or) behavior
  • Named tuples and dataclasses

logger.py

A custom JSON logging implementation with:

  • Custom JSON formatter (MyJSONFormatter)
  • Log filtering (NonErrorFilter)
  • Structured logging support with proper formatting
  • Built-in attribute handling

logging_config.json

Configuration for the logging system:

  • Multiple formatters (simple text and JSON)
  • Different handlers (stderr, rotating file)
  • Queue-based async logging
  • Log level settings

main.py

Example application demonstrating the logging system:

  • Configuration loading from JSON
  • Multiple log levels (DEBUG, INFO, WARNING, ERROR, CRITICAL)
  • Exception logging with traceback
  • Queue-based logging with listener
  • Proper cleanup using atexit

Setup

  1. Clone the repository
git clone https://github.com/yourusername/python_learning.git
cd python_learning
  1. Create a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
  1. Install dependencies
pip install -r requirements.txt
  1. Run the main application
python main.py

Logging System

The logging system is configured via logging_config.json which defines:

  • Formatters: simple text and a custom JSON formatter
  • Handlers: stderr (for warnings and above) and rotating file handler
  • Queue-based async logging for thread safety

Log files are stored in the logs/ directory in JSON Lines format (.jsonl).

Each log entry contains:

  • Level (DEBUG, INFO, etc.)
  • Message content
  • Timestamp (ISO format with timezone)
  • Logger name
  • Module, function, and line number
  • Thread information

Project Structure

python_learning/
│
├── coding_habits.py         # Python best practices examples
├── logger.py                # Custom JSON logging implementation
├── logging_config.json      # Logging configuration
├── main.py                  # Example application with logging demo
│
├── logs/                    # Log file directory
│   └── logger.log.jsonl     # JSON Line formatted logs
│
├── personal_files/          # Directory for personal files (contents ignored by Git)
│   └── .gitkeep             # Empty file to maintain directory structure
│
├── requirements.txt         # Project dependencies (not yet created)
├── .gitignore               # Git ignore patterns
└── README.md                # Project documentation

Personal Files

The repository includes a personal_files/ directory whose structure is tracked by Git, but contents are ignored (via .gitignore). You can use this directory to store:

  • Personal notes
  • Configuration files with credentials
  • Local development settings
  • Test data and examples
  • Any other files that shouldn't be committed to version control

The directory structure itself is maintained in Git using a .gitkeep placeholder file.

Future Improvements

Potential areas for expansion:

  • Add more advanced Python patterns and techniques
  • Create unit tests for modules
  • Add a CLI interface
  • Implement async/await examples
  • Add type checking with mypy
  • Create example of packaging Python code

Contributing

Feel free to add more examples of Python best practices or improvements to the existing code.