Like a lot of people, I'm guilty of using print() to debug my code. While it's a good idea to use a proper debugger, it can also be good to …

Python has supported optional type annotations since Python 3.6, like: # Specify argument and return types def add(x: int, y: int) -> int: return x + y All currently supported Python …

Design Patterns (Part 1): What? Why? What is a Design Pattern In software engineering, a software design pattern is a general, reusable solution to a commonly occurring problem within a …

cuda-vs-cpu-example CUDA is faster than CPU for deep learning, but how fast are we talking about? Let's find out! Introduction At the core of most of the popular whizbang deep …

You can use tools like black to automatically style your Python code in a consistent way. However, if you're just running it manually, you have to remember to run it …

Getting the dataset Flight data downloaded from https://raw.githubusercontent.com/apache-superset/examples-data/master/tutorial_flights.csv: R library(dplyr) library(readr) data <- read_csv("https://raw.githubusercontent.com/apache-superset/examples-data/master …

The Problem Python lets you have multiple virtual environments and that's cool for running scripts but when you need to install Jupyter and run a notebook in Jupyter Lab (the …

If your conda environment is taking a long time to solve (or failing to solve altogether), you might want to try mamba, which reimplements conda in C++ with an improved …

Issues with memory use can be hard to pin down, as your program may only show issues after carrying out multiple memory intensive steps. Using the memory_profiler package in Jupyter …

Autocompletion of variable names in Jupyter Lab (or Notebook) can be frustratingly inconsistent. For a smoother development experience, the jupyterlab-lsp extension provides better completions using the same language servers as …