Lesson 6 of 70 – Python Development Environment
8.4%

Python Development Environment

A development environment is a collection of tools used to write, edit, run, test, and debug Python programs. Python programs can be written using a simple text editor, a code editor, or a complete Integrated Development Environment (IDE).

Note: Beginners can start with Python IDLE or Visual Studio Code. As you gain experience, you can explore professional IDEs such as PyCharm and tools such as Jupyter Notebook.
What is a Development Environment?

A development environment provides the tools required to create and execute software programs.

For Python development, an environment may include a Python interpreter, code editor, terminal, debugger, package manager, and project files.

  • Code Editor
  • Python Interpreter
  • Terminal
  • Debugger
  • Package Manager
  • Project Folder
Python Interpreter

The Python interpreter executes Python programs. It is the core component required to run Python code.

Example:
print("Hello Python")

When this code is executed, the Python interpreter processes the program and displays the output.

Output:
Hello Python
Code Editor

A code editor is a program used to write and edit source code. A good Python code editor provides features such as syntax highlighting, indentation support, code completion, and error detection.

Popular code editors include:

  • Visual Studio Code
  • Sublime Text
  • Notepad++

Visual Studio Code is a popular choice because it supports Python through extensions and provides many useful development features.

Python IDLE

IDLE stands for Integrated Development and Learning Environment. It is included with many Python installations and provides a simple environment for learning Python.

IDLE provides a Python shell and a basic editor for creating Python files.

Example:
print("Welcome to Python IDLE")
Visual Studio Code

Visual Studio Code, commonly called VS Code, is a lightweight source-code editor that can be configured for Python development.

Useful Python development features include:

  • Syntax highlighting
  • Code completion
  • Debugging
  • Integrated terminal
  • Extensions
  • Source control integration
  • Project management

To work with Python effectively in VS Code, install Python on your computer and install the appropriate Python extension.

Installing Python Extension in VS Code

VS Code can be extended with additional functionality using extensions.

  1. Open Visual Studio Code.
  2. Open the Extensions panel.
  3. Search for the Python extension.
  4. Choose the Python extension provided by Microsoft.
  5. Click Install.
  6. Restart VS Code if required.

After installation, VS Code can provide Python-specific editing and development features.

Creating Your First Python Project

It is a good practice to keep the files of each Python project inside a separate folder.

Example Project Structure:
python_project/
    main.py

The main.py file can contain the main Python program.

Example:
print("My First Python Project")
Using the Terminal

The terminal allows you to execute Python programs and other commands without using a graphical interface.

Open the terminal in your project folder and run:

python main.py

On systems where Python 3 is invoked using python3, use:

python3 main.py
Output:
My First Python Project
Python Virtual Environment

A virtual environment creates an isolated Python environment for a project. It allows a project to use its own installed packages without affecting other Python projects.

A virtual environment can be created using:

python -m venv myenv

On systems where Python 3 is invoked with python3:

python3 -m venv myenv
Activating a Virtual Environment

The activation command depends on the operating system and shell.

Windows Command Prompt:
myenv\Scripts\activate
Windows PowerShell:
.\myenv\Scripts\Activate.ps1
Linux / macOS:
source myenv/bin/activate

After activation, packages installed using pip are normally installed inside the virtual environment.

Package Management with pip

Python packages can be installed using pip, the commonly used Python package installer.

Example:
python -m pip install requests

The command installs the Requests package into the active Python environment.

Check Installed Packages:
python -m pip list
Jupyter Notebook

Jupyter Notebook provides an interactive environment where code, text, data, and visualizations can be combined in a notebook.

It is commonly used for:

  • Data analysis
  • Data visualization
  • Scientific computing
  • Machine learning
  • Python learning

Jupyter is especially useful when you want to execute code in small sections and immediately see the results.

PyCharm

PyCharm is an Integrated Development Environment designed for Python development.

It provides features such as code completion, debugging, project management, testing, and integration with Python development tools.

PyCharm is useful for developers who want a dedicated Python development environment.

Choosing a Python Development Tool
Tool Suitable For
IDLE Beginners and basic Python practice
VS Code General Python development
PyCharm Professional Python development
Jupyter Notebook Data analysis and interactive programming
Recommended Environment for Beginners

For beginners learning Python programming, the following setup is sufficient:

  • Python 3
  • Visual Studio Code
  • Python extension for VS Code
  • Integrated terminal
  • pip
  • Virtual environments for projects

This setup provides everything needed to learn Python and build practical projects.

Key Points
  • A development environment provides tools for writing and running programs.
  • The Python interpreter executes Python programs.
  • IDLE is a simple Python development environment.
  • VS Code can be configured for Python development.
  • PyCharm is a dedicated Python IDE.
  • Jupyter Notebook provides an interactive programming environment.
  • The terminal can be used to run Python programs.
  • Virtual environments isolate project dependencies.
  • pip is commonly used to install Python packages.
  • Python projects should be organized into separate folders.

🧠 Quick Quiz

Which tool is commonly used as a code editor for Python development?