Monitor Your File System With Python’s Watchdog


Monitor Your File System With Python’s Watchdog
Picture by Writer | DALLE-3 & Canva

 

Python’s watchdog library makes it straightforward to observe your file system and reply to those adjustments robotically. Watchdog is a cross-platform API that lets you run instructions in response to any adjustments within the file system being monitored. We will set triggers on a number of occasions resembling file creation, modification, deletion, and motion, after which reply to those adjustments with our customized scripts.

 

Setup for Watchdog

 

You will want two modules to start:

  • Watchdog: Run this command beneath within the terminal to put in the watchdog.

     

  • Logging: It’s a built-in Python module, so there is no such thing as a must externally set up it.

 

Fundamental Utilization

 

Let’s create a easy script ‘essential.py’ that screens a listing and prints a message every time a file is created, modified, or deleted.

 

Step 1: Import Required Modules

First, import the required modules from the watchdog library:

import time
from watchdog.observers import Observer
from watchdog.occasions import FileSystemEventHandler

 

Step 2: Outline Occasion Handler Class

We outline a category MyHandler that inherits from FileSystemEventHandler. This class overrides strategies like on_modified, on_created, and on_deleted to specify what to do when these occasions happen. The occasion handler object can be notified when any adjustments occur within the file system.

class MyHandler(FileSystemEventHandler):
    def on_modified(self, occasion):
        print(f'File {occasion.src_path} has been modified')

    def on_created(self, occasion):
        print(f'File {occasion.src_path} has been created')

    def on_deleted(self, occasion):
        print(f'File {occasion.src_path} has been deleted')

 

Some helpful strategies of FileSystemEventHandler are defined beneath.

  • on_any_event: Executed for any occasion.
  • on_created: Executed upon creation of a brand new file or listing.
  • on_modified: Executed upon modification of a file or when a listing is renamed.
  • on_deleted: Triggered upon the deletion of a file or listing.
  • on_moved: Triggered when a file or listing is relocated.

 

Step 3: Initialize and Run the Observer

The Observer class is accountable for monitoring the file system for any adjustments and subsequently notifying the occasion handler. It repeatedly tracks file system actions to detect any updates.

if __name__ == "__main__":
    event_handler = MyHandler()
    observer = Observer()
    observer.schedule(event_handler, path=".", recursive=True)
    observer.begin()

    attempt:
        whereas True:
            time.sleep(1)
    besides KeyboardInterrupt:
        observer.cease()
    observer.be part of()

 

We begin the observer and use a loop to maintain it working. Whenever you need to cease it, you’ll be able to interrupt with a keyboard sign (Ctrl+C).

 

Step 4: Run the Script

Lastly, run the script with the next command.

 

Output:

File .File1.txt has been modified
File .New Textual content Doc (2).txt has been created
File .New Textual content Doc (2).txt has been deleted
File .New Textual content Doc.txt has been deleted

 

The above code will log all of the adjustments within the listing to the terminal if any file/folder is created, modified, or deleted.

 

Superior Utilization

 

Within the following instance, we are going to discover tips on how to arrange a system that detects any change in Python information and run exams for it robotically. We have to set up pytest with the next command.

 

Step 1: Create a Easy Python Undertaking With Exams

First, arrange the fundamental construction of your undertaking:

my_project/
│
├── src/
│   ├── __init__.py
│   └── instance.py
│
├── exams/
│   ├── __init__.py
│   └── test_example.py
│
└── watchdog_test_runner.py

 

Step 2: Write Code in Instance Python File

Create a easy Python module in src/instance.py:

def add(a, b):
    return a + b

def subtract(a, b):
    return a - b

 

Step 3: Write the Take a look at Instances

Subsequent, write the take a look at circumstances for features in exams/test_example.py:

import pytest
from src.instance import add, subtract

def test_add():
    assert add(1, 2) == 3
    assert add(-1, 1) == 0
    assert add(-1, -1) == -2

def test_subtract():
    assert subtract(2, 1) == 1
    assert subtract(1, 1) == 0
    assert subtract(1, -1) == 2

 

Step 4: Write the Watchdog Script

Now, create the watchdog_test_runner.py script to observe adjustments in Python information and robotically run exams:

import time
import subprocess
from watchdog.observers import Observer
from watchdog.occasions import FileSystemEventHandler

class TestRunnerHandler(FileSystemEventHandler):
    def on_modified(self, occasion):
        if occasion.src_path.endswith('.py'):
            self.run_tests()

    def run_tests(self):
        attempt:
            end result = subprocess.run(['pytest'], verify=False, capture_output=True, textual content=True)
            print(end result.stdout)
            print(end result.stderr)
            if end result.returncode == 0:
                print("Exams handed efficiently.")
            else:
                print("Some exams failed.")
        besides subprocess.CalledProcessError as e:
            print(f"Error working exams: {e}")

if __name__ == "__main__":
    path = "."  # Listing to observe
    event_handler = TestRunnerHandler()
    observer = Observer()
    observer.schedule(event_handler, path, recursive=True)
    
    observer.begin()
    print(f"Anticipating adjustments in {path}...")

    attempt:
        whereas True:
            time.sleep(1)
    besides KeyboardInterrupt:
        observer.cease()
    
    observer.be part of()

 

Step 5: Run the Watchdog Script

Ultimately, open a terminal, navigate to your undertaking listing (my_project), and run the watchdog script:

python watchdog_test_runner.py

 

Output:

Anticipating adjustments in ....
========================= take a look at session begins =============================
platform win32 -- Python 3.9.13, pytest-8.2.1, pluggy-1.5.0
rootdir: F:Net Devwatchdog
plugins: anyio-3.7.1
collected 2 objects

teststest_example.py ..                                                 [100%]

========================== 2 handed in 0.04s ==============================

Exams handed efficiently.

 

This output reveals that every one the take a look at circumstances are handed after adjustments had been made to instance.py file.

 

Summing Up

 

Python’s watchdog library is a strong software for monitoring your file system. Whether or not you are automating duties, syncing information, or constructing extra responsive purposes, watchdog makes it straightforward to react to file system adjustments in actual time. With only a few strains of code, you can begin monitoring directories and dealing with occasions to streamline your workflow.

 
 

Kanwal Mehreen Kanwal is a machine studying engineer and a technical author with a profound ardour for knowledge science and the intersection of AI with drugs. She co-authored the book “Maximizing Productiveness with ChatGPT”. As a Google Era Scholar 2022 for APAC, she champions variety and tutorial excellence. She’s additionally acknowledged as a Teradata Variety in Tech Scholar, Mitacs Globalink Analysis Scholar, and Harvard WeCode Scholar. Kanwal is an ardent advocate for change, having based FEMCodes to empower girls in STEM fields.

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