jupyter notebook vs python script

Jupyter Notebook and Python scripts are both powerful tools used in the world of programming and data science. Each has its own strengths and use cases. In this tutorial, we will explore the differences between Jupyter Notebooks and Python scripts, and when to use each.
Jupyter Notebook is an interactive computing environment that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. It supports multiple programming languages, but we'll focus on its use with Python.
Interactive Execution: Jupyter Notebooks allow you to run code in a step-by-step manner, making it easy to test and debug small pieces of code.
Data Visualization: It's great for exploring and visualizing data using inline charts and graphs.
Mixed Content: You can include formatted text, equations, and code in the same document, making it an excellent tool for data analysis and reporting.
Let's create a simple Jupyter Notebook with a code cell that calculates the sum of two numbers:
To run the code, simply select the cell and press Shift + Enter.
A Python script is a text file containing a sequence of Python statements. It is a standalone program that can be executed from the command line or within an integrated development environment (IDE).
Reusability: Python scripts are excellent for reusable code. Functions and classes can be defined and imported into other scripts.
Automation: Ideal for tasks that need to be automated or run without user interaction, making them suitable for batch processing.
Version Control: Easier to manage with version control systems like Git.
Now, let's create a simple Python script that performs the same sum calculation:
In summary, Jupyter Notebooks are excellent for interactive data analysis and visualization, while Python scripts are better suited for reusable and automated tasks. Choose the tool that best fits your specific needs, and don't hesitate to use them in combination for a more comprehensive workflow.
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