I’m heading toward grad school in physics and haven’t had much programming practice. Python seems useful, especially for simulations and data analysis, but I’m not sure how to build solid foundations or what tools to start with.
How should I get started with programming for physics grad school?
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Ollie
Answers
Start with Python basics before jumping into a big simulation. Get comfortable with variables, conditionals, loops, functions, lists and dictionaries, and reading simple errors. Then write small programs that use ideas you already know from physics, like plotting a function or stepping a basic system forward in time.
Try to write the code yourself rather than only following along. When something breaks, inspect the values and narrow down where the result stops making sense. Those habits matter more than memorizing syntax.
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For physics work, Python is a sensible first choice. NumPy, SciPy, and Matplotlib give you tools for arrays, numerical methods, and plots without making you build everything from scratch. Learn enough plain Python to understand what those libraries are doing, then use them on small problems.
Don’t worry about choosing a faster language before you have a concrete reason. If a particular task becomes too slow, you can investigate optimization or another language then. The best language can also depend on your research group and the tools used in your field.
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Make the practice project small enough that you can finish it. For example, calculate a simple trajectory, compare a numerical result with an analytical one, and plot how the error changes as you adjust the time step. That teaches loops, functions, plotting, and checking results without turning into a huge project.
Once the basics feel comfortable, build toward the physics topics you care about. A simulation is much easier to debug when you can separate the physics question from the programming problem.
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Keep Linux as a separate learning track. Start with the terminal basics you actually need, such as moving between folders, managing files, and running a Python script. You don’t have to understand the whole operating system before doing useful scientific programming.
And don’t assume you need to become a software engineer to benefit. It’s still worth picking up practical habits like clear variable names, small functions, and saving working versions of your code.
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Ollie:
Would you recommend starting in a notebook, or writing regular Python files?
goodcall:
Notebooks are handy for experimenting with equations, plots, and notes. For code you want to reuse or run as a program, move the useful parts into regular Python files and organize them into functions.