Skip to main content

Creating command line utility in python



Learning Sections          show

Creating Command Line Utility in Python

Introduction

Creating a command line utility in Python can simplify tasks and automate workflows. Python provides several libraries to help create command line interfaces (CLI) easily, such as argparse, click, and typer.

Using argparse

The argparse module is part of the Python standard library and helps create simple to complex command line interfaces.

Example with argparse

import argparse

# Create the parser
parser = argparse.ArgumentParser("CLI Example")

# Add arguments
parser.add_argument("--name", type=str, required=True, help="Name of the user")
parser.add_argument("--age", type=int, help="Age of the user")

# Parse the arguments
args = parser.parse_args()

# Use the arguments
print(f"Name: {args.name}")
print(f"Age: {args.age}")

Using click

The click library is a package for creating command line interfaces in a composable way with as little code as necessary.

Example with click

import click

@click.command()
@click.option("--name", prompt="Your name", help="Name of the user")
@click.option("--age", default=0, help="Age of the user")
def cli(name, age):
    click.echo(f"Name: {name}")
    click.echo(f"Age: {age}")

if __name__ == "__main__":
    cli()

Using typer

The typer library is a newer library for creating command line interfaces. It's designed to be easy to use and leverages Python's type hints.

Example with typer

import typer

app = typer.Typer()

@app.command()
def cli(name: str, age: int = 0):
    typer.echo(f"Name: {name}")
    typer.echo(f"Age: {age}")

if __name__ == "__main__":
    app.run()
Labels:

Popular posts from this blog

Generators in Python

  Learning Sections          show Generators in Python Generators are a special type of iterator in Python that allow you to iterate over a sequence of items without storing them all in memory at once. They are useful for generating large sequences of data on-the-fly, or for processing data in a memory-efficient manner. Creating Generators In Python, generators are created using generator functions or generator expressions: # Generator function def my_generator ( n ): for i in range ( n ): yield i # Generator expression my_generator = ( i for i in range ( 10 )) A generator function uses the yield keyword to yield values one at a time, while a generator expression creates an anonymous generator. Iterating Over Generators You can iterate over the values produced by a generator using a for loop: for value in my_generator ( 5 ): print ( value ) This w...
Read more

Walrus Operator in Python

  Learning Sections          show Walrus Operator in Python The walrus operator ( := ) is a new assignment operator introduced in Python 3.8. It allows you to assign values to variables as part of an expression, making certain constructs more concise. Basic Usage The basic syntax for the walrus operator is: variable_name := expression Here, variable_name is assigned the value of expression , and the result of the expression is also returned. Example: Simplifying Code Consider the following example where we find and print the length of a list if it's greater than 3: # Without walrus operator my_list = [ 1 , 2 , 3 , 4 ] if len ( my_list ) > 3 : length = len ( my_list ) print ( length ) # With walrus operator my_list = [ 1 , 2 , 3 , 4 ] if ( length := len ( my_list )) > 3 : print ( length ) In the second example, the walrus operator assigns the result of len(my...
Read more

Lambda Functions in Python

  Learning Sections          show Lambda Functions in Python Lambda functions, also known as anonymous functions, are small, unnamed functions defined with the lambda keyword. They can have any number of arguments but only one expression. Lambda functions are often used for short, throwaway functions that are not needed elsewhere in the code. 1. Basic Syntax The syntax for a lambda function is: lambda arguments : expression Example: add = lambda x , y : x + y print ( add ( 2 , 3 )) # Output: 5 2. Using Lambda with Built-in Functions Lambda functions are commonly used with built-in functions like map() , filter() , and sorted() . Example with map() : numbers = [ 1 , 2 , 3 , 4 , 5 ] squared = map ( lambda x : x ** 2 , numbers ) print ( list ( squared )) # Output: [1, 4, 9, 16, 25] Example with filter() : numbers = [ 1 , 2 , 3 , 4 , 5 ] even = filter ( lambd...
Read more