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The full curriculum covers topics such as object-oriented programming, databases, REST APIs, and web technologies, but this repo focuses exclusively on the Python fundamentals portion of the program and intentionally omits any SQL work.\n\n## Python Learning Goals\n- Basic syntax, variables, and data types\n- Control flow with conditions and loops\n- Functions, modules, and standard libraries\n- File I/O and error handling\n- Introductory object-oriented programming concepts\n- Simple web programming with Flask later in the course\n\n## Prerequisites\n- Python 3.12 or later\n- Recommended tools: a code editor (e.g., VS Code, PyCharm) and Git\n\n## Getting Started\n1. Clone the repository and change into the directory\n   ```bash\n   git clone https://github.com/cihat-kose/python-learning-path.git\n   cd python-learning-path\n   ```\n2. Create and activate a virtual environment\n   ```bash\n   python -m venv .venv\n   source .venv/bin/activate  # Windows: .venv\\Scripts\\activate\n   ```\n3. Install any required packages (none at the moment)\n4. Run an exercise file with `python oppgavene/oppgaver_uke34.py`\n\n## Folder Structure\n- `oppgaver_uke34.py` – exercises for week 34\n- `oppgavene/` – supplementary materials\n\n## Contributing\nParticipants are welcome to extend the exercises or submit improvements:\n1. Fork the repository\n2. Create a feature branch\n3. Commit and push your changes\n4. Open a pull request for review\n\n## Future Improvements\n- Add automated tests to validate exercise solutions\n- Organize exercises into separate folders per week\n- Introduce code style tools such as `black` or `flake8`\n- Provide example solutions and additional documentation\n\n## License\nThis project is distributed under the [MIT License](LICENSE).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcihat-kose%2Fpython-learning-path","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcihat-kose%2Fpython-learning-path","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcihat-kose%2Fpython-learning-path/lists"}