This repository contains a collection of materials for teaching/learning Python 3 (3.5+).

• Have Python 3.5 or newer installed. You can check the version by typing python3 --version in your command line. You can download the latest Python version from here.
• Have Jupyter Notebook installed.

If you can not access Python and/or Jupyter Notebook on your machine, you can still follow the web based materials. However, you should be able to use Jupyter Notebook in order to complete the exercises.

1. Clone or download this repository.
2. Run jupyter notebook command in your command line in the repository directory.
3. Jupyter Notebook session will open in the browser and you can start navigating through the materials.

See contributing guide.

1. Strings [notebook] [exercise]
2. Numbers [notebook] [exercise]
3. Conditionals [notebook] [exercise]
4. Lists [notebook] [exercise]
5. Dictionaries [notebook] [exercise]
6. For loops [notebook] [exercise]
7. Functions [notebook] [exercise]
8. Testing with pytest - part 1 [notebook] [exercise]
9. Recap exercise 1 [exercise]
10. File I\O [notebook] [exercise]
11. Classes [notebook] [exercise]
12. Exceptions [notebook] [exercise]
13. Modules and packages [notebook]
14. Debugging [notebook] [exercise]
15. Goodies of the Standard Library - part 1 [notebook] [exercise]
16. Testing with pytest - part 2 [notebook] [exercise]
17. Virtual environment [notebook]
18. Project structure [notebook]
19. Recap exercise 2 [exercise]

Python is a powerful language which contains many features not presented in most other programming languages. Idiomatic section will cover some of these Pythonic features in detail. These materials are especially useful for people with background in other programming languages.

1. Idiomatic loops [notebook]
2. Idiomatic dictionaries [notebook]
3. Idiomatic Python - miscellaneous part 1 [notebook]
4. Idiomatic Python - miscellaneous part 2 [notebook]
5. Idiomatic Python exercise [exercise]

1. Efficient use of fixtures [notebook]
2. Other tips and tricks

A list of best development practices for Python projects. Most of the practices listed here are also applicable for other languages, however the presented tooling focuses mainly on Python.

1. Best practices [notebook]

1. Goodies of the Standard Library - part 2 [notebook] [exercise]

• Sets
• Generators
• Decorators
• Context managers
• Playing with attributes
• *, *args, **kwargs
• Command line arguments with click
• OOP - inheritance
• OOP - Abstract Base Classes
• OOP - attrs
• Testing with mocks
• Structuring your tests

• requests
• testing requests with responses
• beautifulsoup4
• selenium

• SQLAlchemy

• excel
  • openpyxl
• pdf
  • pdfrw / PyPDF2

• Logo: Abdur-Rahmaan Janhangeer, @Abdur-rahmaanJ