Module 1 · Introduction to Python · Lesson 5 of 6

Why not Python?

No language is perfect, and pretending otherwise does you no favours. Python's biggest cost is the flip side of how it runs: because it's interpreted line by line rather than compiled ahead of time, it's slower at raw, repetitive number-crunching.

Same task, raw speed

C (compiled)

⚡🏁

Python

🐍🏁

Slower for heavy number-crunchingNot made for mobile appsUses more memorySome errors only show at runtime

For most programs that gap never matters — the computer is waiting on you, the network or the disk, not on Python. And when speed truly counts, Python often hands the hot path to fast C libraries under the hood, which is exactly how the data-science world gets away with it.

The other catches: it's not the natural choice for mobile apps, it uses more memory than lower-level languages, and because types are checked while the program runs, some mistakes only surface at runtime rather than ahead of time. Worth knowing — rarely a dealbreaker for learning.