chunxli / PythonSkillEnhancement

This repository is a comprehensive track of my journey from understanding the basics to mastering the advanced aspects of Python programming. It's designed as a structured path to enhance my Python skills, covering intermediate to advanced topics

Python Basics To-Do List

• Introduction to Python

  • Install Python and set up the development environment
  • Understand Python syntax and script execution
  • Practice with basic Python REPL commands

• Variables and Data Types

  • Learn about data types: int, float, str, bool
  • Understand variables and how to assign values
  • Practice type conversion

• Operators

  • Explore arithmetic operators
  • Understand comparison operators
  • Use logical operators
  • Practice assignment operators

• Strings

  • Manipulate strings (concatenation, slicing, and methods)
  • Understand string formatting
  • Practice with common string functions

• Control Flow

  • Write if, elif, and else statements
  • Practice with for loops
  • Utilize while loops
  • Understand break and continue

• Functions

  • Define and call functions
  • Understand parameters and return values
  • Explore scope and global variables
  • Use built-in functions and modules

• Lists

  • Create and manipulate lists
  • Understand list methods and slicing
  • Practice list comprehensions

• Dictionaries

  • Work with dictionaries and understand key-value pairs
  • Explore dictionary methods
  • Practice iterating over dictionaries

• Tuples and Sets

  • Learn to use tuples and understand their immutability
  • Create and manipulate sets
  • Understand set operations

• Input and Output

  • Use input() to gather user input
  • Practice output formatting
  • Read from and write to files

• Error Handling

  • Understand try-except blocks
  • Use exceptions for error handling
  • Explore finally and else in error handling

Intermediate Python To-Do List

• Object-Oriented Programming (OOP)

  • Understand classes and objects
  • Master inheritance and polymorphism
  • Explore method overriding and data encapsulation

• Functional Programming

  • Use lambda functions
  • Implement map, reduce, and filter
  • Understand closures and decorators

• Comprehensions

  • Practice list comprehensions
  • Use dictionary and set comprehensions

• Data Structures

  • Explore tuples, sets, and frozensets
  • Implement advanced operations with dictionaries
  • Understand stack, queue, and linked lists in Python

• Modules and Packages

  • Create and use modules
  • Organize code with packages
  • Explore Python Standard Library modules

• Error Handling and Exceptions

  • Use try-except blocks
  • Implement multiple exception clauses
  • Utilize finally and else in exception handling

• File Operations

  • Read from and write to files
  • Manage file context with with statement
  • Explore different file operation modes

• Iterators and Generators

  • Create custom iterators
  • Use generator functions and expressions
  • Understand the yield statement

• Regular Expressions

  • Practice basic pattern matching
  • Use metacharacters and quantifiers
  • Grouping and capturing data

Advanced Python To-Do List

• Concurrency and Parallelism

  • Explore threading and multiprocessing
  • Use asyncio for asynchronous programming
  • Understand concurrent.futures

• Advanced Data Manipulation

  • Master Pandas for data analysis
  • Explore NumPy for numerical data
  • Visualize data with Matplotlib or Seaborn

• Web Development Frameworks

  • Build a basic web app with Flask
  • Develop a Django project
  • Understand RESTful API development

• Unit Testing and Test-Driven Development (TDD)

  • Write unit tests with unittest and pytest
  • Practice TDD workflow
  • Explore mocking and patching in tests

• Design Patterns

  • Study the Singleton, Factory, and Observer patterns
  • Implement MVC architecture in a project
  • Explore Behavioral, Creational, and Structural patterns

• Performance Optimization

  • Profile Python code
  • Optimize with Cython or JIT compilers
  • Use caching techniques effectively

• Advanced Libraries and APIs

  • Work with external APIs
  • Explore libraries for specific domains (e.g., SciPy for scientific computing)
  • Integrate Python with other services and databases

• Software Packaging and Distribution

  • Create a Python package
  • Publish a package to PyPI
  • Understand versioning and dependencies

Typical layout for a Python project

my_project/
│
├── README.md                   # Project overview, installation, and usage
├── requirements.txt            # The dependencies file for reproducing the analysis environment, typically for pip
├── setup.py                    # Makes project pip installable (pip install -e .) so my_project can be imported
├── my_project/                 # Source package for the project
│   ├── __init__.py             # Initializes the Python package
│   ├── module1.py              # Python module with functions, classes, etc.
│   ├── module2.py
│   └── subpackage1/            # Sub-package for organization
│       ├── __init__.py
│       ├── submodule1.py
│       └── submodule2.py
├── tests/                      # Directory for unit tests
│   ├── __init__.py
│   ├── test_module1.py
│   └── test_module2.py
├── docs/                       # Documentation files
│   ├── conf.py                 # Sphinx configuration file
│   └── index.rst               # For Sphinx documentation
├── data/                       # For storing data used in the project
├── scripts/                    # For standalone scripts within the project
│   └── script.py
└── notebooks/                  # Jupyter notebooks for experiments and analysis
    └── exploration.ipynb