Automating Desktop Notifications in Python with auto-notifier

When you work with multiple monitors, it’s easy to start a long-running Python task on one screen and switch to something else. I often run data processing or training scripts in a terminal while focusing on another task. The problem is simple: unless I keep checking back, I don’t know if the script finished or crashed.

auto-notifier was built for that case. It wraps your function or code block, detects whether it completed or failed with an exception, and sends a desktop notification. It relies on two familiar Python constructs — decorators and context managers — and stays out of your way.

[ Placeholder for Screenshot of Notification ]\ Example: Desktop notification popup after script completion

🚀 Installation

pip install auto-notifier

auto-notifier uses notify-py internally to send native system notifications (Windows, macOS, Linux).

🧭 How It Works

Both detect:

• ✅ Successful completion
• ❌ Exceptions (with failure alert)
• ⏱️ Execution time (included internally)

Exceptions are not suppressed — you still see tracebacks in the terminal.

🧩 Using the Decorator

from auto_notifier import notify_when_done
import time

@notify_when_done(
    title="Backup complete",
    message="Nightly backup finished successfully.",
    error_title="Backup failed"
)
def run_backup():
    time.sleep(5)  # simulate work
    # raise Exception("Disk error")  # test failure
    return "ok"

run_backup()

What happens:

• Success → "Backup complete" notification
• Error → "Backup failed" notification, then exception re-raised

📎 Using the Context Manager

from auto_notifier import notify_on_complete
import time

with notify_on_complete(title="Data import finished"):
    time.sleep(3)
    print("Import complete")

Wraps any block of code — ideal for scripts or notebooks.

🎛️ Customizing Notifications

Example with icon:

@notify_when_done(
    title="Report generated",
    message="Monthly metrics ready.",
    icon_path="icons/chart.png"
)
def build_report():
    ...

🛠 How It Uses Decorators & Context Managers

• Decorator: Wraps the function, measures runtime, catches exceptions, triggers notification.
• Context Manager: Uses __enter__ / __exit__, ensures notification even if an exception occurs.

No configuration files, threads, or services — just Python control flow.

🔁 Combined Example (Pipeline Style)

from auto_notifier import notify_when_done, notify_on_complete
import pandas as pd
import time

@notify_when_done(title="Data cleaned", error_title="Cleaning error")
def clean_data(path):
    df = pd.read_csv(path)
    time.sleep(4)
    return df.dropna()

with notify_on_complete(title="ETL pipeline complete"):
    cleaned = clean_data("raw.csv")
    cleaned.to_csv("cleaned.csv", index=False)

🧭 When It’s Useful

• Long-running terminal scripts
• Data processing / scraping tasks
• Training loops
• Backups or exports

It’s built for local desktop usage, where system notifications are visible.

📌 Summary

auto-notifier adds notification hooks to Python code using decorators or context managers.\ It lets you step away from the terminal and still know exactly when a script finished or failed.

PyPI: https://pypi.org/project/auto-notifier/\ GitHub: https://github.com/yalmeidarj/auto-notifier

If you launch scripts and move on to other tasks, this tool keeps you informed without manual checks.