Skip to main content

Shutil Module in Python

 


Learning Sections          show

Shutil Module in Python

The shutil module in Python provides a collection of functions for high-level file operations, such as copying and removing files. It is especially useful for tasks that require dealing with file and directory manipulation.


Copying Files and Directories

The shutil module provides several methods for copying files and directories:


# Copy a file
import shutil
shutil.copy('source.txt', 'destination.txt')

# Copy a directory
shutil.copytree('source_folder', 'destination_folder')
    

The copy method copies a single file, while the copytree method copies an entire directory along with its contents.


Moving Files and Directories

You can move files and directories using the move function:


# Move a file
shutil.move('source.txt', 'new_location/source.txt')

# Move a directory
shutil.move('source_folder', 'new_location/source_folder')
    

The move function moves a file or directory to a new location, similar to the Unix mv command.


Removing Files and Directories

The shutil module also provides functions to remove files and directories:


# Remove a file
os.remove('file_to_remove.txt')

# Remove a directory
shutil.rmtree('directory_to_remove')
    

Use the remove function to delete a file and the rmtree function to delete a directory and its contents.


Archiving Files

The shutil module can create archives (e.g., zip, tar) from directories:


# Create a zip archive
shutil.make_archive('archive_name', 'zip', 'directory_to_archive')

# Create a tar archive
shutil.make_archive('archive_name', 'tar', 'directory_to_archive')
    

The make_archive function creates an archive file from a directory.


Disk Usage

You can check the disk usage of a given path using the disk_usage function:


# Check disk usage
usage = shutil.disk_usage('/')
print(usage)
    

The disk_usage function returns a named tuple with the total, used, and free disk space in bytes.


Popular posts from this blog

Introduction to OOPs in Python

  Learning Sections          show Introduction to Object-Oriented Programming (OOP) Object-Oriented Programming (OOP) is a programming paradigm that organizes software design around objects rather than actions and data rather than logic. It revolves around the concept of "objects", which are instances of classes. These objects encapsulate data, in the form of attributes or properties, and behaviors, in the form of methods or functions. OOP promotes modularity, reusability, and extensibility in software development. Key Concepts of OOP: Class: A class is a blueprint or template for creating objects. It defines the attributes (data) and methods (functions) that will characterize any object instantiated from that class. Object: An object is an instance of a class. It is a concrete realization of the class blueprint, containing actual values instead of placeholders for attributes. Encapsulation: Encapsulation is ...

Classes and Objects in Python

  Learning Sections          show Classes and Objects in Python In Python, a class is a blueprint for creating objects. An object is an instance of a class. Classes allow you to logically group data and functions in a way that is easy to manage and reuse. 1. Defining a Class To define a class in Python, you use the class keyword followed by the class name and a colon. Inside the class, you can define attributes and methods. Example: # Define a class class Person : # Class attribute species = 'Human' # Class method def greet ( self ): return 'Hello, I am a person.' # Create an object of the class person1 = Person () # Access class attribute print ( person1 . species ) # Output: Human # Call class method print ( person1 . greet ()) # Output: Hello, I am a person. 2. Creating Objects To create an object of a class, you simply call the class name followed by paren...

Exception Handling in Python

  Learning sections          show Exception Handling in Python Exception handling in Python is done through the use of try , except , else , and finally blocks. This allows you to catch and handle errors gracefully. Below are some examples and explanations: 1. Basic Try-Except The try block lets you test a block of code for errors. The except block lets you handle the error. # Example of basic try-except try : result = 10 / 0 except ZeroDivisionError : print ( "Cannot divide by zero!" ) # Output: # Cannot divide by zero! 2. Handling Multiple Exceptions You can catch multiple exceptions by specifying multiple except blocks. # Example of handling multiple exceptions try : result = 10 / 0 except ZeroDivisionError : print ( "Cannot divide by zero!" ) except TypeError : print ( "Invalid operation!" ) # Output: # Cannot divide by zero! 3. Using Else The e...