3 ms·

It's unique to Python in that most other languages used for more than just scripting have true concurrency via OS preemptive threads with no GIL. Python is rea

It's unique to Python in that most other languages used for more than just scripting have true concurrency via OS preemptive threads with no GIL. Python is really decades behind in this area and no async hack is going to improve matters. I think it's safe to say that this is an obvious example of how Python is not really a general purpose language (disregarding the fact that it started out as a christmas hack and really has no design behind it). It should be used for scripting and quick prototyping but architecting anything substantial on it is not advisable.

Daishiman 11y ago
I think this a very unfair comparison. Everyone who works with Python who understands its limitations has usually found reasonable workarounds for the things you would expect the language to bend to, much like other, similar languages that occupy that niche. By the same token, we can claim that C++'s horrendous and undecidable syntax and footguns make it a language inadequate for "general purpose" programming; and for many cases you would be right! But there is no such thing as a language that can do everything well. The other big contender for "general purpose" is the JVM languages, which also suffer from innumerable issues such as slow VM startup time, long VM warmup, enormous RAM usage, lack of very reasonable primitives such as unsigned integers, etc. etc. Those are the reasons why very large systems either use a hybrid of languages and runtimes for different tasks, or use a monolythic solution and make the adequate compromises. No one will disagree that the multithreading story would be easier in Python if it chucked the GIL out of the way, but then again, if you're doing that you might as well start a project in Elixir, Julia, Rust, or any number of modern languages that don't suffer from the cruft, but easily will need a decade to catch up in terms of library support and tooling.
agentultra 11y ago
> architecting anything substantial on it is not advisable. If you're in Toronto, Canada in November you should come to my talk at Pycon CA. Openstack is a rather large Python codebase that powers some rather large public and private clouds from Rackspace to HP and even CERN. I'll be discussing the various technologies and processes that allow us to do that in Python. It's also one of the more popular platforms for scientific computing and data analysis. There are huge code-bases designed in Python that work quite well and continue to grow in adoption and usefulness. I don't see why anyone would advise against writing a substantial system in Python.

Daishiman 11y ago

I think this a very unfair comparison. Everyone who works with Python who understands its limitations has usually found reasonable workarounds for the things you would expect the language to bend to, much like other, similar languages that occupy that niche. By the same token, we can claim that C++'s horrendous and undecidable syntax and footguns make it a language inadequate for "general purpose" programming; and for many cases you would be right! But there is no such thing as a language that can do everything well. The other big contender for "general purpose" is the JVM languages, which also suffer from innumerable issues such as slow VM startup time, long VM warmup, enormous RAM usage, lack of very reasonable primitives such as unsigned integers, etc. etc. Those are the reasons why very large systems either use a hybrid of languages and runtimes for different tasks, or use a monolythic solution and make the adequate compromises. No one will disagree that the multithreading story would be easier in Python if it chucked the GIL out of the way, but then again, if you're doing that you might as well start a project in Elixir, Julia, Rust, or any number of modern languages that don't suffer from the cruft, but easily will need a decade to catch up in terms of library support and tooling.

agentultra 11y ago

> architecting anything substantial on it is not advisable. If you're in Toronto, Canada in November you should come to my talk at Pycon CA. Openstack is a rather large Python codebase that powers some rather large public and private clouds from Rackspace to HP and even CERN. I'll be discussing the various technologies and processes that allow us to do that in Python. It's also one of the more popular platforms for scientific computing and data analysis. There are huge code-bases designed in Python that work quite well and continue to grow in adoption and usefulness. I don't see why anyone would advise against writing a substantial system in Python.