Build a Python Error Monitoring App with Automated Gmail Alerts

This project includes full source code, video walk-through, and step-by-step instructions.

This week we’re sharing a new Python project, including source code, a video walk-through, and a step-by-step tutorial. We’re also going to cover how to create desktop apps with Python, not to mention how to join Pandas dataframes, and Docker commands that everyone seems to get wrong.

This Week’s Resources

New Python Project: Build an Error Notification App

We're psyched to share this new Python project with you. This is all about building a real-time log monitoring system with automated Gmail alerts. It’s the perfect blend of automation, file monitoring, and email notifications, all wrapped up in a practical and real-world project.

This is a fantastic way to level up your Python skills while solving real-world problems. Whether you're a developer, sysadmin, or just love automation, this project will show you how to detect errors in logs and get notified instantly—no more manual log checking!

You can follow along as we build this, and we’ll be sharing all the code so you can customize and improve it however you want!

How to Create Desktop Apps with Python

Want to build your own Python desktop application? This step-by-step video tutorial (less than 30 minutes) walks you through creating GUI-based apps with Tkinter, Python’s built-in GUI library.

Specifically, the video covers:

  • The fundamentals of Tkinter for GUI development

  • How to create a main window with labels, buttons, and text fields

  • How to implement event-driven programming in Python

  • How to structure a Tkinter app using OOP for scalability

  • How to display message boxes and handle user input

And make sure to check out the upcoming walkthroughs. We’ve got a fun project that automates log error notifications coming up soon. It detects errors and sends instant email notifications.

We will have the full walkthrough, including the full source code for the project, on Hackr.io.

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How To Join Pandas DataFrames

Want to merge Pandas DataFrames effortlessly? We just released a quick guide to the Pandas join() method, showing the best ways to combine DataFrames based on their indexes.

Specifically, this guide covers:

  • How to use join() for efficient DataFrame merging

  • The differences between left, right, inner, and outer joins

  • Handling mismatched indexes when joining DataFrames

  • How join() compares to merge() in Pandas

  • A practice challenge to apply what you’ve learned

df1 = pd.DataFrame({
    "A": [1, 2, 3],
    "B": ["x", "y", "z"]
}, index=["one", "two", "four"])  

df2 = pd.DataFrame({
    "C": [4, 5, 6],
    "D": ["p", "q", "r"]
}, index=["one", "three", "four"])  

df_merged = df1.join(df2)
print(df_merged)

Pandas join() is a powerful tool for merging indexed data in Python. Read the full guide to see how it works and level up your data analysis skills.

Are You Getting These Docker Commands Wrong?

Not every Docker command works the way you think — some can cause unexpected issues, wasted time, or even data loss. While Docker is an essential tool for containerized development, there are a few common command mistakes that might leave you wondering, Why did that just happen?

Here’s a breakdown of four critical Docker mistakes that can trip up anyone, plus the quick fixes to keep your workflow smooth and efficient.

The Code Editor

Did you know about the free Python, HTML, and JavaScript code editor? Just log into your free account at Hackr.io to use them.

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