Introduction to Programming

What is a program?

A program is a set of instructions that tells a computer what to do. Each instruction is called a statement. The computer carries out the statements in order and does exactly what they say: it never guesses what you meant, and it never skips a step because it seems obvious.

A useful comparison is a written laboratory procedure. A good procedure lists every step in order, with precise quantities, so that anyone following it gets the same result. A program is the same idea, except the reader is a computer and the steps are written in a language it understands.

That precision is both the strength and the challenge of programming. Once a program is correct, it will repeat the same work perfectly, millions of times if needed. But a small mistake, such as a missing bracket or a misspelled name, stops the program or gives a wrong answer, because the computer follows your instructions literally.

Programming languages and Python

Computers ultimately work with very low-level instructions that are hard for people to read. A programming language lets us write instructions in a form that is much closer to human language and mathematics. The text you write is called source code.

Python is an interpreted language. A program called the Python interpreter reads your source code from top to bottom and carries out each statement as it reaches it. If it finds a statement it cannot understand, it stops and shows an error message explaining what went wrong and on which line.

Why scientists write programs

Research increasingly depends on computation. Programming lets you do things that are slow, error-prone or impossible by hand:

• Automate repetitive work: apply the same calculation to thousands of samples, files or simulation results.
• Handle large datasets: instruments such as diffractometers, spectrometers and microscopes produce far more data than a spreadsheet can comfortably manage.
• Model and simulate: predict how a material, molecule or system behaves before running an experiment.
• Visualise results: turn columns of numbers into clear, publication-quality plots.
• Make work reproducible: a script records exactly what was done to the data, so you and others can check or repeat it later.

Why Python?

• Readable: Python's syntax is short and uses plain English words, so programs are easier to write and to understand later.
• Widely used in research: it is a standard tool in materials science, chemistry, physics, biology and data science.
• Rich scientific libraries: packages such as NumPy (numerical arrays), Matplotlib (plotting), SciPy (scientific algorithms) and pandas (tables) are built on Python. Materials scientists also use packages such as ASE and pymatgen.
• Free and open source: anyone can install and use it, on any operating system.

Your first look at Python

The statement below uses print() to display a message. print is a function: a named piece of code that performs a task. You call a function by writing its name followed by brackets, and you put the information it needs inside the brackets.

print("Hello, science!")

The text inside the quotation marks is called a string. The quotes tell Python where the text starts and ends; they are not printed.

Press Try it hands-on under the example to open an editor. Change the message, press Run, and see your new output. You can't break anything: the Reset button restores the original code.

Text versus calculations

Quotation marks make a big difference. Inside quotes, Python treats characters as text and prints them exactly. Without quotes, Python treats 2 + 3 as a calculation, works out the result and prints that.

print("2 + 3")print(2 + 3)

print(1085 + 273.15)

How you will learn in this course

1. Each lesson explains one idea with short examples. Run them, change them and see what happens.
2. A knowledge check at the end of the lesson tests your understanding.
3. From Module 2 onwards, a hands-on exercise follows each lesson. You write a small program yourself, with hints and a model solution if you need them.
4. A lab at the end of each later module applies everything to a realistic scientific problem.

Examples use materials science by default. If you work in another field, choose it with the Examples in this lesson selector, or set a default for the whole course in the header.