Sandbox and Python Learning Cheat Sheet

I started learning Python3 with documentation on the official site. I liked the code samples, but unfortunately they were not interactive there. I wanted to try to execute the code on my own, with different inputs and look at the output. It is also easier for me personally to remember the constructions of a language if I typed them several times manually. Python console for this is great, but I also wanted to have a kind of cheat sheet, which I could return to when writing programs in the future, if, for example, a question arises how to write a for loop, etc. in Python. And the last straw was the desire to automatically check the style of writing code in accordance with existing standards . It was too lazy to read and delve into them, so I wanted to check the code automatically and tell me what mistakes I was making and how to fix them.

As a result, I poured all my experiments on GitHub .

The repository is a collection of Python scripts , divided into categories . Each script contains code samples, with comments and usage examples, as well as with links for further more detailed reading and study of each topic.

As a result, the repository turned out to be a sandbox because users have the opportunity to change or add code, look at how it works and use the tests to verify its correctness (using assertion . It is also possible to check the code compliance with modern standards . Together this should help users learn the language more interactively and from the very beginning maintain a good purity of the code.

The repository also, in my opinion, is a cheat sheet in the sense that you can return to it and recall the basic constructs of the language , methods of objects, and the like. Also, due to the fact that the code is punctuated with assertion users, users can check the expected result of the functions without starting them.

How to use this repository

Each Python script in the repository has the following structure:

 """Lists <---    # @see: https://www.learnpython.org/en/Lists <--          ,    ( -  Lists). """ def test_list_type(): """   - ( " "  " ").     ... """ # Here is an example of how to build a list. <-- ,   squares = [1, 4, 9, 16, 25] # Lists can be indexed and sliced. # Indexing returns the item. assert squares[0] == 1 # <-- Assertion,    . # Slicing returns a new list. assert squares[-3:] == [9, 16, 25] # <-- Assertion,    . 

Therefore, the process of using the repository may be as follows:

• Find a topic of interest that you want to explore or remember.
• Read the comments, if necessary, follow the link with a more detailed explanation of the topic.
• Get acquainted with the code examples and "assessments".
• Modify or add code and see how it will work.
• Run tests and check the style of writing code .

Repository sections

1. Getting Started
   
   • What is python
   • Python Syntax
   • Variable
2. Operators
   
   • Arithmetic Operators ( + , - , * , / , // , % , ** )
   • Bitwise Operators ( & , | , ^ , >> , << , ~ )
   • Assignment Operators ( = , += , -= , /= , //= etc.)
   • Comparison Operator ( == != , > , < , >= , <= )
   • Logical Operators ( and , or , not )
   • Identity Operators ( is , is not )
   • Membership Operators ( in , not in )
3. Data types
   
   • Numbers (including booleans)
   • Strings and their methods
   • Lists and their methods (including list comprehensions)
   • Tuples
   • Sets and their methods
   • Dictionaries
   • Type casting
4. Control flow
   
   • The if statement
   • The for statement (and range() function)
   • The while statement
   • The try statements
   • The break statement
   • The continue statement
5. Functions
   
   • Function Definition ( def and return statements)
   • Default Argument Values
   • Keyword arguments
   • Arbitrary Argument Lists
   • Unpacking Argument Lists ( * and ** statements)
   • Lambda Expressions ( lambda statement)
   • Documentation Strings
   • Function annotations
6. Classes
   
   • Class Definition ( class statement)
   • Class objects
   • Instance Objects
   • Method objects
   • Class and Instance Variables
   • Inheritance
   • Multiple inheritance
7. Modules
   
   • Modules ( import statement)
   • Packages
8. Errors and Exceptions
   
   • Handling Exceptions ( try statement)
   • Raising Exceptions ( raise statement)
9. Files
   
   • Reading and Writing ( with statement)
   • Methods of File Objects
10. Additions
    
    • The pass statement
    • Generators ( yield statement)
11. Brief Tour of the Standard Libraries
    
    • Serialization ( json library)
    • File Wildcards ( glob library)
    • String Pattern Matching ( re library)
    • Mathematics ( math , random , statistics libraries)
    • Dates and Times ( datetime library)
    • Data Compression ( zlib library)

I hope you find this repository useful.