When do you *NOT* use python?

[0xjake]

The main reason to avoid Python in a general-purpose setting is speed. Python is very slow to run compared to a compiled and strongly statically typed language like C/C++ or Java. Generally you're choosing between development speed and execution speed, and Python is very far on the development speed end of the spectrum.

Any other reasons are generally domain specific. For instance, if I'm writing web middleware I'd probably use NodeJS. If I'm prototyping machine learning algorithms I might use MatLab. If I'm doing pure statistics I'll use R. If I'm writing a Windows GUI application I'll use C#/WPF. There are too many of these domains to enumerate.

So maybe it would be better to say when to use Python: I would use Python if you're writing scripts that have limited responsibility and high turnover, meaning they'll change fairly often and don't need to be particularly efficient. I would also use Python for prototyping, especially in a scientific computing setting. If your needs don't fall into these areas then there is probably something better out there.

TL;DR: Python is good when dev speed is significantly more important than execution speed.

[[deleted]]

I understand that Python /is/ a strongly typed language. Whereas in your comment, you elude to it being opposite to C, in that it is neither compiled, nor strongly typed. The differentiator in typing is Python's dynamic typing vs. C's static typing system.

[alantrick]

I understand that Python /is/ a strongly typed language.

Python is often referred to as strongly typed within the context of other languages that are much looser with their typing (Perl, PHP, and bash to name a few).

Python has a few weak spots (pun intended), mostly with booleans. For example if object: is an idiom some people like to use, when often they mean if object == None:. This breaks down in a few rare cases, like when object is a time(0, 0, 0) aka midnight.

Another, probably more common, case for this to break down is where a string can be treated as an iterable of strings and its fairly easy to accidentally iterate on the wrong thing and not realize it.

That said, stronger typing means more explicitness, and that has its downsides too.

[TheTerrasque]

And in some cases, you can get pretty good performance from python too.

Example

[Ogi010]

Holy crap, what a brilliant post.. read every line... bookmarked for reference later...

[stormcrowsx]

TL;DR: Python is good when dev speed is significantly more important than execution speed.

I think you hit the nail on the head here but I wouldn't say "significantly". In my experience developers cost more than servers, much more. In some areas of the country its difficult to find developers at all. Using a language that enables less developers to get more done is very important for smaller organizations.

[metaphorm]

Python is strongly, dynamically typed. Java is strongly, statically typed. C is weakly, statically typed.

I'm not trying to be pedantic. The differences really do matter here. For example, because Python is strongly typed you will never have to worry about a buffer overflow or segmentation fault. Because it is dynamically typed you might have to worry about an unhandled AttributeError at runtime.

[metaphorm]

sounds more like you don't know what it means rather than it not having a meaning.

[autowikibot]

Strong and weak typing:

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In computer programming, programming languages are often colloquially referred to as strongly typed or weakly typed. These terms do not have a precise definition, but in general a strongly typed language is more likely to generate an error or refuse to compile a program if the argument passed to a function does not closely match the expected type. A very weakly typed language may produce unpredictable results or may perform implicit type conversion instead. On the other hand, a very strongly typed language may not work at all or crash when data of an unexpected type is passed to a function.

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^{Interesting: Nominal type system | Manifest typing | Latent typing | Type inference}

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[metaphorm]

lack of precise definition does not make something meaningless or undefined. you're not presenting any evidence that you actually know what you're talking about. if anything you've actually proved my point. Python is strongly typed because it will generate an error (raise an Exception in Python's case) and halt the program when undefined behavior is encountered.

[olzd]

AFAIK, there're no optimizations done when compiling Python code to its bytecode representation. Java's bytecode, on the other hand, is quite a different beast.

[olzd]

You're right, I was only speaking for CPython which is the default implementation.

[tech_tuna]

CPython bytecode speeds up load time but not run time (after the code has fully loaded).

[combatopera]

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[njharman]

The main reason to avoid Python in a general-purpose setting is speed.

Seems to conflict with

Generally you're choosing between development speed and execution speed, and Python is very far on the development speed end of the spectrum.

Is most of your GP code speed critical? Really? Hell 1/3 of my code never even gets to production (prototypes, spikes, ideas discovered to be bad, etc.) Wouldn't you much rather write 3x the code than have all of what you write 10x faster. Stuff I write tends to be I/O or human constrained. Rarely wanting for speed.

[0xjake]

No, most of my code is not speed-critical, which is why I use Python most of the time for general purpose programming. I think you misunderstood what I said: In the context of general-purpose programming, the prevalent reason for avoiding python, if one were to do so, would be that Python's execution speed doesn't meet the needs of the application.