What Python Is Really Good At (And Where It Falls Short)
A clear, honest breakdown of Python’s real strengths, limits, and tradeoffs so you know when Python is the right choice and when another tool makes more sense.
Python has a bit of an image problem. People often talk about it like it can do everything. From web apps, data science, and automation. All the way to Machine learning, games, desktop apps, APIs and DevOps. The list goes on and one.
This is why people just talk about it as “the everything language”.
On the surface, that sounds amazing. In real life, it usually just creates confusion.
When beginners hear that Python can do everything, they expect it to be the right tool for every job. When experienced devs hear the same thing, they sometimes push Python into places where it does not really belong.
That is when you start seeing slow systems, rubbish designs, and a lot mistakes. Most of the time, those mistakes are not Python’s fault.
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Python is a great language. But it does have a point of view, even if it is not loud about it. It cares more about code being easy to read than being clever.
This article is about setting boundaries. Not to box Python in, but to respect what it is built for. When you know what Python is truly good at, your projects feel simpler and cleaner. When you know what it is not good at, your system designs get smarter.
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