The Python pathlib module provides an object-oriented, cross-platform framework for handling filesystem paths, replacing older string-based modules like os.path. Instead of manipulating raw strings, you work directly with Path objects that automatically handle variations between operating systems (like / vs. )

Creating and Joining Paths

  • You can create a Path object by passing a string, using environment-based methods, or combining them with the / operator 
from pathlib import Path # Create a path from a string path1 = Path("documents") / "reports" / "data.csv" # Get important system directories cwd = Path.cwd() # Current working directory home = Path.home() # User's home directory # Convert relative path to absolute absolute_path = path1.resolve()

Extracting Path Components

  • If you have a path like /home/user/documents/report.tar.gz, pathlib makes it incredibly easy to extract individual components using properties

File and Directory Operations

  • You no longer need to import separate modules to create, delete, or check files. 
path = Path("data/records.txt") # Check status and types print(path.exists()) # True if path exists print(path.is_file()) # True if it's a file print(path.is_dir()) # True if it's a directory # Creating items path.parent.mkdir(parents=True, exist_ok=True) # Safely make directories path.touch() # Create empty file # Deleting items path.unlink() # Delete a file path.parent.rmdir() # Delete an EMPTY directory

Searching & Directory Iteration

You can easily navigate through folders or search for specific file patterns using glob and rglob (recursive glob)

dir_path = Path("my_project") # Iterate over immediate contents for item in dir_path.iterdir(): print(item.name) # Find all .py files in this folder py_files = dir_path.glob("*.py") # Find all .csv files here AND in all subfolders recursively all_csv_files = dir_path.rglob("*.csv")