Skip to content

How to Run Your Python Scripts: A Comprehensive Guide

Python is a versatile and powerful programming language, widely used for various applications. Running Python scripts is essential for any Python developer. This comprehensive guide will teach you how to run Python scripts in different ways, depending on your environment and skills. You'll learn how to use the command-line, IDEs, and file managers to run your scripts efficiently and effectively.

Want to quickly create Data Visualization from Python Pandas Dataframe with No code?

PyGWalker is a Python library for Exploratory Data Analysis with Visualization. PyGWalker (opens in a new tab) can simplify your Jupyter Notebook data analysis and data visualization workflow, by turning your pandas dataframe (and polars dataframe) into a Tableau-style User Interface for visual exploration.

PyGWalker for Data visualization (opens in a new tab)

What is the Difference Between a Script and a Module in Python?

Before diving into running Python scripts, it's essential to understand the difference between a script and a module. In Python, a script is a sequence of instructions written in a text file, which can be executed. A module, on the other hand, is a Python file containing functions, classes, or variables that can be imported and used by other scripts or modules.

What is the Python Interpreter and Why Do I Need It?

The Python interpreter is a program that reads and executes Python code. It converts the human-readable code into machine instructions, allowing the computer to understand and execute the script. To run Python scripts, you need the Python interpreter installed on your machine. You can check your Python version to see if it's already installed.

How Can I Run Python Code Interactively?

Running Python code interactively is a great way to learn and experiment with the language. You can use Python's built-in interactive interpreter by launching the Python shell from your command-line interface (CLI).

  1. Open the command prompt (Windows) or terminal (macOS/Linux).
  2. Type python and press Enter.
  3. You can now type Python commands and see the output immediately.

What are the Different Ways to Run Python Scripts?

Running Python Scripts from the Command-Line Interface

The most straightforward way to run a Python script is through the command-line interface. Navigate to the directory containing your script, and then run the following command:

python script_name.py

Replace script_name.py with the name of your Python script.

Running Python Scripts on Windows

On Windows, you can also run Python scripts by double-clicking the script file in the file explorer. Make sure the file extension is associated with the Python interpreter. If not, right-click the file, select "Open with," and choose "Python."

Running Python Scripts on Linux

On Linux, you can run Python scripts using the terminal. Ensure the script file has executable permissions by running the following command:

chmod +x script_name.py

Then, run the script with:

./script_name.py

Running Python Scripts with Arguments

You can run Python scripts with arguments from the command-line. To do so, pass the arguments after the script name:

python script_name.py arg1 arg2 arg3

Replace arg1, arg2, and arg3 with the arguments you want to pass.

How Do I Run Python Scripts from an IDE or a Text Editor?

An Integrated Development Environment (IDE) or a text editor with Python support can make running Python scripts more accessible and efficient. Some popular Python IDEs include PyCharm (opens in a new tab), Visual Studio Code, and Jupyter Notebook.

To run Python scripts from an IDE or text editor, open the script file in the IDE or text editor, and then use the built-in "Run" or "Execute" command, often available through a toolbar icon or keyboard shortcut.

Best Python IDEs for Beginners

For beginners, some of the best Python IDEs include:

  1. PyCharm (opens in a new tab): A powerful and feature-rich IDE, PyCharm is perfect for Python development. It offers robust debugging capabilities, code completion, and version control integration. PyCharm also has a free community edition.
  2. Visual Studio Code: A lightweight and versatile code editor with Python support through extensions. Visual Studio Code provides syntax highlighting, code completion, and built-in Git support.
  3. Jupyter Notebook: An interactive web-based environment for running Python code. Jupyter Notebook is excellent for data analysis, visualization, and learning Python interactively.

How to Debug Python Code

Debugging is a critical skill for any Python developer. Learning how to debug Python code in PyCharm or other IDEs can save you time and frustration. Some common debugging techniques include:

  1. Using breakpoints to pause the execution of your code at specific lines.
  2. Stepping through your code line-by-line to inspect variables and program flow.
  3. Evaluating expressions and modifying variables during runtime.
  4. Utilizing logging or print statements to trace code execution.

Python Development Cycle and Best Practices

A typical Python development cycle involves writing, running, and debugging your code. To improve your productivity, consider the following Python best practices:

  1. Write clean and readable code: Follow the PEP 8 style guide for Python code.
  2. Use version control: Track changes to your code and collaborate with others using a version control system like Git.
  3. Write tests: Write unit tests to ensure your code works as expected and catch bugs early.
  4. Use virtual environments: Create isolated environments for your projects with Python virtual environments, keeping dependencies separate and organized.
  5. Use packages: Leverage the vast ecosystem of Python packages to simplify development.

Conclusion

Running Python scripts is an essential skill for any Python developer. This guide has covered various methods for executing Python scripts, from the command-line to IDEs and text editors. By understanding the basics of Python programming and leveraging available tools, you can improve your productivity and write better, more efficient code.