and why WasmEdge is on the critical path of AGI adoption of Rust! Why not Python? Today’s LLM applications, including inference apps and agents, are mostly written in Python. But this is about to change. Python is simply too slow, too bloated, and paradoxically too unwieldy for the new wave of developers. In…

The ‘eff’ in f-strings may as well stand for… (not that! What a twisted mind you have) for ‘freaking awesome’! — If you clicked on this article, you've probably already used f-strings in Python. You know that you can throw almost any expression between braces to sprinkle dynamic values into strings. But, from time to time, you see a guy using something like print(f"{f'${number:.3f}':>10s}") (probably to show off) and you undoubtedly…

Time to go out of the shadows — While the big guys, Pandas, Scikit-learn, NumPy, Matplotlib, TensorFlow, etc., hog all your attention, it is easy to miss some down-to-earth and yet, incredible libraries. They may not be GitHub rock stars, or taught in expensive Coursera specializations, but thousands of open-source developers pour their blood and sweat into writing…

HandleException is the solution to cumbersome try-catch blocks in Python. Say goodbye to messy error handling code and hello to clean and efficient exception handling with HandleException. With its simple and intuitive interface, you’ll never want to go back to traditional error handling methods. …

Originally posted September 2021 on the Split Blog When writing APIs, REST (short for representational state transfer) is considered the standard. And yet, REST itself isn’t actually a standard. This makes designing intuitive REST APIs tricky to get right. It is a way of thinking or an art form more…

Hands-on tutorial for starting your Parquet learning — If you like to experience Medium yourself, consider supporting me and thousands of other writers by signing up for a membership. It only costs $5 per month, it supports us, writers, greatly, and you get to access all the amazing stories on Medium. Parquet file is a file storage system…

With Panda Examples — Written by: Amal Hasni & Dhia Hmila As you may know, python is an interpreted language. This means that python code is not directly compiled to machine code but is interpreted in real-time by another program called an interpreter ( cpython in most cases ). This is one of the…

Recently I was tasked with creating subnets across all our 9 environments. Each environment is deployed to 3 availability zone, with about 14 standard subnets in total to manage our different services. Some environments tend to have a few more subnets added to the standard subnets. To be able to…

6 Python mistakes you need to fix to become a better programmer — It is undeniable that Python might be one of the easiest languages to learn and use. It is a high-level, multi-purpose programming language. This has contributed to it being extremely popular and has seen a lot of growth in the recent years, especially with the advent of data science. However…

Was it worth it, and how to prepare — Having been through the process of preparing for, and passing, the TensorFlow Developer Certificate exam, I thought it might be useful to give other people an overview of what to expect, the best resources to use to prepare, what to watch out for in the exam, and advice on whether…

A step towards data analysis run-time optimization — The motivation to design and build real-world applicable machine learning models has always intrigued Data Scientists to leverage optimized, efficient, and accurate methods at scale. Optimization plays a foundational role in sustainably delivering real-world and user-facing software solutions. While I understand that not everyone is building solutions at scale, awareness…

It’s time to say goodbye to pd.to_csv() and pd.read_csv() — Building an end-to-end data-driven pipeline is challenging and demanding. Having been there myself, the process is extremely tedious, and one may inevitably end up with numerous intermediate files. …

Discussing another major caveat of Pandas — Input-output operations with Pandas to a CSV are serialized, making them incredibly inefficient and time-consuming. It's frustrating when I see ample scope for parallelization here, but unfortunately, Pandas does not provide this functionality (yet). Although I am never in favor of creating CSVs in the first place with Pandas (read…