Tutorials

Monitoring what happens on your computer can be incredibly useful, whether you’re trying to track your productivity, analyze how you spend your time, or even ensure that certain applications are being used efficiently. Python makes this task approachable and powerful by allowing you to interact directly with the Windows operating system. Let’s dive into the concepts and build a monitoring tool from scratch, step by step, using the interactive Python terminal.

Step 1: Getting the Active Window Title

The first thing we want to do is identify the active window—that is, the window currently in focus on your screen. We’ll use the pywin32 library, which provides a direct interface with Windows APIs. Start by installing the necessary package:

When tasked to automate anything within Linux, you might find that Shell is the easiest tool to get the job done fast. Most of the time these shell scripts are built for a specific purpose and don’t have any need for configuration in different usage scenarios. However, it is possible to build a fully fleshed Command Line Interface (CLI) using a shell script, which I will outline for you the steps on how to do this.

Not all of us have the privilege of having access to the internet at all times of the day. Imagine someone who travels to another city to attend a coding bootcamp, where they learn code with the help of freecodecamp.org, but when they go home, they can’t continue to learn on their own because they don’t have access to the internet at their home. Imagine also another person who struggles to learn to code on their own during the 4 hours every day when the internet happens to be working. This is the reality for many who aspire to learn how to code.

In this guide, I will show you how to run freecodecamp.org offline, so you can complete coding certifications completely without internet access.

The world of web development can be insanely complex and overwhelming, however building a simple website doesn’t have to be difficult. Many people’s needs can be fulfilled simply by taking 30 minutes to set up a website on Github pages completely for free.

I am not endorsed in any way by Plaid to share this info, just helping others get a head start on using Plaid with Django.

Plaid is a plaform-as-a-service API which you can use to build your own financial apps. It has features such as easily linking to existing bank accounts, and also auto-categorization of transactions. Plaid’s API brings all the data from different financial sources into one place and one format so you can build apps with a holistic view of a user’s finances.

Ok. Now all praise of Plaid aside, I’m sure you are here because you want to build a Django app that uses Plaid to obtain users’ financial data. In all of Plaid’s tutorials shown in their quickstart github page, they have a tutorial for Python, but it’s using Flask for the backend rather than Django.

I’ve taken the time to translate their tutorial from Flask to Django. The main difference was Django’s requirement of having CSRF protection.