Training

There’s a long history of scientists who built new tools to enable their discoveries. Tycho Brahe built a quadrant that allowed him to observe the path and distance of a comet as it crossed the solar system, helping to prove the heliocentric model of the way the stars and planets move. Galileo Galilei built his…

Scientists gain superpowers when they learn to program. Programming makes answering whole classes of questions easy and new classes of questions become possible to answer. If you have some programming experience, large language models (LLMs) can raise the ceiling of your performance and productivity. Using LLMs to write code turns a challenging recall task (What’s…

You know it. We know it. NumPy is cool. Pandas is cool. We can bend them to our will, but sometimes they’re not the right tools for the job. Enter Xarray and Awkward Array. Read on for the four reasons why you need to learn these Python packages.   Reason 1:  You need labeled arrays of…

Like most people, I mostly interact with Python using the default REPL or with IPython. Yet, I often reach for one of the Python tools that come with the standard library. All these tools are implemented as “mains” in the various scripts and modules. Here are 7 I use on a semi-regular basis. 1. &…

Recently, I’ve been working on a new course offering in Enthought Academy titled Software Engineering for Scientists and Engineers course. I’ve focused on distilling the software engineering best practices that we use at Enthought with our clients, with the twist of “what parts are most useful for a scientist who writes software for R&D?” After…

if __name__ == “__main__”: When I was new to Python, I ran into a mysterious block of code that looked something like: def main():     # do some stuff if __name__ == “__main__”:     main() Looking at the code, I could see that it ran the main() function after checking the status of…