How to execute Python script in interactive shell

Introduction

Python interactive shell provides developers with a powerful and flexible environment for executing and testing Python scripts. This tutorial explores various methods to run Python code directly in the command-line interface, offering insights into interactive coding techniques that can streamline your development process and improve programming efficiency.

Skills Graph

Python Shell Basics

What is Python Shell?

Python Shell is an interactive command-line interface that allows developers to execute Python commands and scripts in real-time. It provides an immediate environment for testing code, exploring language features, and performing quick computations.

Types of Python Shells

Starting Python Shell

To launch the Python shell in Ubuntu 22.04, you can use multiple methods:

## Method 1: Standard Python Shell
python3

## Method 2: IPython (if installed)
ipython3

Basic Shell Operations

## Arithmetic operations
>>> 2 + 3
5

## Variable assignment
>>> x = 10
>>> print(x)
10

## Function definition
>>> def greet(name):
...     return f"Hello, {name}!"
>>> greet("LabEx")
'Hello, LabEx!'

Shell Navigation and Shortcuts

Exiting the Shell

## Method 1: exit() function
>>> exit()

## Method 2: Keyboard shortcut
Ctrl + D

Best Practices

• Use shell for quick tests and experiments
• Save complex code in script files
• Leverage auto-completion and history features
• Explore different shell environments like IPython

By understanding Python Shell basics, developers can enhance their coding efficiency and interactive programming skills.

Script Execution Methods

Direct Script Execution

Running Python Scripts from Command Line

## Basic script execution
python3 script.py

## Example: hello.py
$ cat hello.py
print("Hello, LabEx!")
$ python3 hello.py
Hello, LabEx!

Execution Methods Overview

Interactive Shell Execution

Running Scripts within Python Shell

## Method 1: Using exec()
>>> exec(open('script.py').read())

## Method 2: Using run command
>>> %run script.py

Module-based Execution

## Executing as module
python3 -m module_name

## Example
python3 -m http.server 8000

Executable Scripts

Making Scripts Directly Executable

## Add shebang line
#!/usr/bin/env python3

## Make script executable
chmod +x script.py
./script.py

Execution Method Comparison

Advanced Execution Techniques

## Conditional script execution
if __name__ == '__main__':
    ## Code to run only when script is primary
    main()

Best Practices

• Choose appropriate execution method
• Use shebang for system-wide compatibility
• Understand script context
• Leverage LabEx environments for testing

Interactive Coding Tips

Shell Productivity Techniques

Command History Navigation

Code Completion and Exploration

Using Tab Completion

## Auto-completion example
>>> import ma[TAB]
## Suggests: math, matplotlib, etc.

>>> math.[TAB]
## Shows available math module methods

Interactive Debugging Techniques

Quick Debugging Strategies

## Inline debugging
>>> def calculate(x):
...     import pdb; pdb.set_trace()
...     result = x * 2
...     return result

Shell Environment Enhancements

IPython Advanced Features

Error Handling and Inspection

Detailed Error Information

## Traceback exploration
>>> try:
...     1 / 0
... except ZeroDivisionError as e:
...     print(f"Error details: {e}")

Performance Measurement

Timing Code Execution

## Measuring execution time
>>> %timeit [x**2 for x in range(1000)]

Interactive Environment Tools

Best Practices

• Use tab completion extensively
• Leverage magic commands
• Practice inline debugging
• Explore different interactive environments
• Utilize LabEx for consistent coding experience

Keyboard Shortcuts

Recommended Tools

1. IPython
2. Jupyter Notebook
3. Python REPL
4. LabEx Interactive Environments

Summary

By mastering Python interactive shell execution methods, programmers can enhance their coding workflow, quickly test scripts, and gain deeper insights into Python's dynamic programming capabilities. Understanding these techniques enables more efficient script development and debugging across different programming scenarios.