Let’s face it – the technical aspect of writing R and Python packages from scratch isn’t complicated. However, the challenging part lies in proper testing. The goals with package tests are to ensure the package works properly and without any bugs on the client’s hardware and that the ...

Most of the real-world data is stored in databases, so knowing how to access different database systems from Shiny is a mandatory skill. With the rise of Shiny for Python, databases and their access got a whole new meaning, as Shiny developers are no longer limited to R. That being ...

Deep learning might seem like a challenging field to newcomers, but it’s gotten easier over the years due to amazing libraries and community. PyTorch library for Python is no exception, and it allows you to train deep learning models from scratch on any dataset. Sometimes it’s easier to ...

Want to include only the libraries you use in requirements.txt? Try pipreqs, a Python module for creating leaner requirements files.

There's more than one way to Python square roots. Learn 5 approaches to square roots in Python + some bonus advanced tricks.

Want to check if a sentence is grammatically correct with Python? Try Gingerit - a free Python grammar checker. Here are code examples and errors you might run into.

If you truly want to wrap your head around a deep learning model, visualizing it might be a good idea. These networks typically have dozens of layers, and figuring out what’s going on from the summary alone won’t get you far. That’s why today we’ll show ...

There's more than one way to square a number in Python. Learn 4 approaches to Python squaring + some bonus tricks for lists.

Want to automate Whatsapp messages? Try PyWhatKit - A Python Whatsapp automation library.

If you haven’t been living under a rock for the past couple of weeks, you’ve likely noticed some groundbreaking news in the Shiny department. Yes, it’s finally available for Python! But how is the current Shiny for Python version? How does R Shiny compare vs Shiny for ...