Setting Up the Python Environment - Course Outline

Описание: #python #setup #environment #programming
Welcome to the first section of our Python course, 'Setting Up the Python Environment.'
This section is designed to equip you with the essential tools and knowledge needed to start your Python development journey.
By the end of this section, you'll have Python installed on your computer, you'll be familiar with different IDEs, and you'll have Visual Studio Code set up, and ready to go with all the best extensions.
You'll also know how to set up and use virtual environments, which are essential for managing dependencies in your projects.
Let's dive into what we'll cover in each lecture of this section.
In the first lecture, we'll learn how to install Python on a Windows system.
Next, we'll cover installing Python on macOS. We'll install 'Homebrew' and use it to install Python.
For our Linux users, we'll go through the steps to get Python up and running in a separate lecture. We'll update the package list and install Python using the package manager.
Then, we'll explore various Integrated Development Environments that you can use for Python development.
We'll review PyCharm, known for its powerful features like code completion and inspections, and integrated version control.
Then, we'll look at Spyder, which is great for data science with its integration with IPython and scientific libraries.
We'll also discuss Jupyter Notebook, which allows for interactive coding and visualization.
Finally, we'll introduce Visual Studio Code, a lightweight yet powerful editor with extensive extensions.
Visual Studio Code (VS Code) will be our main editor throughout this course. We'll cover the installation process for different operating systems.
To further enhance our productivity in VS Code, we'll look at some of the best extensions for Python development.
We'll start with the Python extension by Microsoft, which offers advanced features like IntelliSense and debugging.
Then, we'll explore Pylance for fast and feature-rich IntelliSense, the Python Debugger for efficient troubleshooting, Python Type Hint for adding type hints, and Python Path for managing Python paths.
We'll also cover Black Formatter for automatic code formatting, Material Icon Theme for a better visual experience, and Numbered Bookmarks for easier navigation within your code.
Finally, we'll learn how to set up and use virtual environments in Python. We will cover creating a virtual environment to isolate project dependencies, and how to activate and deactivate the environment.
And that's our plan for this section. By the end of these lectures, you'll be fully equipped with the tools and knowledge needed to start coding in Python.