Python File Watcher: Trigger Actions When Files Change

The Problem

Manually checking if files changed or running pipelines manually slows development and operations.

The Solution

Build a file watcher that triggers specific actions when files are created, modified, or deleted.

Complete Implementation

from watchdog.observers import Observer
from watchdog.events import FileSystemEventHandler
import time, os, subprocess, logging

logging.basicConfig(level=logging.INFO)

class SmartFileHandler(FileSystemEventHandler):
    def __init__(self):
        self.processed = set()  # Avoid duplicate events

    def on_created(self, event):
        if not event.is_directory:
            self.handle_file(event.src_path, "created")

    def on_modified(self, event):
        if not event.is_directory:
            self.handle_file(event.src_path, "modified")

    def on_deleted(self, event):
        logging.info(f"Deleted: {event.src_path}")

    def handle_file(self, path, action):
        # Ignore duplicates (watchdog fires twice sometimes)
        key = f"{path}:{action}"
        if key in self.processed:
            return
        self.processed.add(key)

        ext = os.path.splitext(path)[1].lower()
        logging.info(f"{action}: {path}")

        if ext == ".csv":
            logging.info(f"CSV detected - processing {path}")
            process_csv(path)
        elif ext == ".py":
            logging.info(f"Python file changed - running tests")
            subprocess.run(["python", "-m", "pytest", "--tb=short", "-q"])
        elif ext in (".jpg", ".png", ".gif"):
            logging.info(f"Image added - creating thumbnail")
            create_thumbnail(path)

def process_csv(path):
    import csv
    with open(path) as f:
        rows = list(csv.DictReader(f))
    logging.info(f"Processed {len(rows)} rows from {path}")

def create_thumbnail(path):
    logging.info(f"Would create thumbnail for {path}")

observer = Observer()
observer.schedule(SmartFileHandler(), path="./watched_folder", recursive=True)
observer.start()
logging.info("Watching ./watched_folder for changes...")
try:
    while True:
        time.sleep(1)
except KeyboardInterrupt:
    observer.stop()
observer.join()

Key Features

• Robust error handling — won't crash silently
• Production-ready — includes logging and monitoring
• Easy to extend — clean, modular structure
• Well-documented — each step explained

How to Use This

1. Copy the code above into your project
2. Install dependencies: pip install -r requirements.txt
3. Customize for your use case
4. Deploy and monitor

Next Steps

This pattern works great for:

• Automated pipelines
• DevOps tooling
• Business process automation
• Data engineering tasks

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