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Test Python Setup

A Python notebook used to verify that a local Python environment is correctly installed and ready for development.

Β·2 min read

By Davina Leong

πŸ§ͺ Introduction: Making Sure Python Works

Before writing complex programs or running advanced notebooks, one important question needs answering:

Is my Python setup working correctly?

This notebook serves as a simple sanity check β€” a place to confirm that Python is installed, notebooks run correctly, and basic code executes as expected.

Sometimes the most important step is verifying the basics.


🎯 Purpose: Verifying the Development Environment

The goal of this notebook is to help learners:

  • Confirm that Python is installed properly
  • Verify that Jupyter Notebook runs without errors
  • Test basic Python syntax and output
  • Catch environment issues early

This avoids confusion later when things don’t work.


🧠 How It Works: Simple Checks, Clear Signals

At a high level, the notebook performs a few straightforward actions:

  1. Run basic Python statements
  2. Print output to confirm execution
  3. Test simple calculations or variables
  4. Ensure cells run without errors

If these steps work, the environment is ready for learning.


🧩 The Technical Part: Minimal but Intentional Code

A simple example from a setup test looks like this:

print("Python is working!")

Or a quick calculation:

2 + 2

πŸ” What This Confirms

  • 🐍 Python interpreter is installed
  • πŸ““ Jupyter Notebook is functioning
  • ▢️ Code cells execute correctly
  • 🧠 Output appears as expected

These checks may look trivial β€” but they save time and frustration.


πŸ’‘ Key Takeaways: Don’t Skip Setup

This notebook reinforces an important habit:

  • 🧱 Strong setups prevent downstream issues
  • πŸ” Test early, not after something breaks
  • πŸ›  Environment issues are common β€” and normal
  • 🧠 Confidence grows when tools behave predictably

Professional developers do this instinctively.


🏁 Conclusion: A Small but Essential Step

The Test Python Setup notebook may be simple, but it plays a critical role:

Before building anything, make sure the tools work.

With a confirmed setup, learners can move forward confidently into:

  • Python basics
  • Data processing
  • OOP
  • Tooling and automation

Every successful project starts with a working environment.


πŸ”— Link to Notebook

Notebook link: Coming Soon

PythonJupyter NotebookEnvironment SetupPython BasicsDeveloper WorkflowGetting Started
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