Python IDEs and Tools

You can write Python in any text editor, but a good editor or IDE (Integrated Development Environment) makes you far more productive: it highlights errors as you type, completes code, runs and debugs programs, and manages virtual environments.

This lesson compares the most popular tools — VS Code, PyCharm, Jupyter, IDLE, Thonny and online environments — shows how to run Python code in each style (script, REPL, notebook), and recommends a setup for beginners and professionals.

Popular Editors and IDEs

Each tool suits a different style of work:

VS Code — free, lightweight editor; with the Python and Pylance extensions it offers IntelliSense, debugging, testing, Jupyter notebooks and environment selection. The most popular choice today.
PyCharm — a full IDE by JetBrains with deep refactoring, database tools and Django/FastAPI support. The free version covers most needs.
Jupyter Notebook / JupyterLab — mix code, output, charts and notes in cells; the standard for data analysis and teaching.
IDLE — installed with Python; simple but limited.
Thonny — a beginner-friendly IDE that shows variables and step-by-step execution.
Online — Webnest Codelab, Google Colab (free notebooks with GPUs), Replit.

Three Ways to Run Python

Scripts: save code in app.py and run python app.py. REPL (interactive shell): type python and execute lines one by one — great for experiments. Notebooks: run cells in Jupyter and keep results next to the code — great for data exploration. Professional projects are scripts and packages; notebooks are for exploration and reporting.

Recommended Setup

Install Python from python.org (or with a version manager), install VS Code with the Python extension, create a virtual environment per project, and add a formatter/linter such as Ruff. Learn a few debugger basics early: breakpoints, stepping, and watching variables will save you hours of print debugging.

Examples

Using the interactive REPL

Python

$ python
>>> 2 ** 10
1024
>>> name = "Webnest"
>>> name.upper()
'WEBNEST'
>>> help(len)          # built-in help for any object
>>> exit()

Output

(The REPL evaluates each line immediately and prints the value of expressions.)

A script you can run and debug in any IDE

Python

def average(numbers):
    total = sum(numbers)          # set a breakpoint here in VS Code or PyCharm
    return total / len(numbers)

marks = [78, 92, 85]
print("Average:", round(average(marks), 2))

Output

Average: 85.0

Common Mistakes

Selecting the wrong interpreter in the IDE, so installed packages "cannot be found".
Building whole applications in notebooks, where hidden cell order makes code hard to reuse and test.
Using only print debugging and never learning breakpoints.
Installing many IDE plugins that conflict instead of a small, reliable setup.

Key Points to Remember

VS Code (with Python extension) and PyCharm are the most popular Python development tools.
Jupyter notebooks are ideal for data exploration; scripts and packages for applications.
Run Python as scripts, in the REPL, or in notebooks.
Always select the project's virtual environment as the interpreter.
Learn the debugger early; add a formatter/linter like Ruff.

Practice the examples

Change an input, predict the result, then compare it with the output. Explain why the result changes.

Try A script you can run and debug in any IDE in Webnest Codelab

Use your local project environment for these examples. Codelab currently runs Python and HTML/CSS/JavaScript; framework examples may need project dependencies.