I think the only way MS knows how to make money is lock someone into an ecosystem. I think their next attempt should be a closed source lean checker that has will have proprietary code for NL -> lean formalization checker.
This should be called Python Type Server Protocol, no? Seems weird to mine the generic protocol namespace for a protocol that only supports Python. Especially coming from the company behind LSP, which actually is generic.
This is the company that named its web framework "MVC". At least this time they're not eternally polluting search results for an industry standard term.
It’s really good that folks over at Astral decided to implement it. It was difficult for me to understand what does this protocol provide that couldn’t be implemented with a new LSP capability, the linked document doesn’t really explain that, but what did become clear to me is that seemingly Microsoft are trying to invent new features for their proprietary LSP server that only works in VS Code so people will have harder times switching to other editors. This way, no matter what Microsoft comes up with, will be matched with very high quality open source tools.
As someone with minimal knowledge of LSP specifics, I'm a bit confused about why this exists. Is it the case that LSP alone does not provide adequate functionality for Python type queries?
> The "type server protocol" is a desperate attempt from microsoft to prevent pylance from becoming obsolete by outsourcing its type checking to other language servers like basedpyright, ty or pyrefly -- while continuing to keep certain language server features exclusive to pylance.
> This protocol benefits nobody except microsoft. It adds needless complexity to any language server that chooses to support it. Basedpyright does not support it and strongly advises other language servers to avoid supporting it as well.
It seems to be a more structured representation of the type. Normally in LSP you'd have a plain string or markdown that you render in the IDE, but nothing that you can analyse structurally.
It's a shame it's not just an LSP extension though, or a feature in a newer LSP version. LSP is maintained by Microsoft engineers.
So basically adding machine readable type-at-point queries as an lsp extension so Pylance and Pywright can be separated?
The 'result types'format is super python specific, like not having a for all binder. I don't think this specific schema will be used for any non-python languages.
Language server protocol is the interface of a software piece that sits between an IDE and a language toolchain so you don't need to change code in the IDE to add support of new languages (you add support on the LSP server). Then server provides things such as completions/intelli-sense, navigation to definitions and some correction checking. From the anouncement TSP extends LSP for better python type awarness.
I just use the Pyrefly extension in VSCode/Zed, run Pyrefly in the CI, and everything works well. The fragmentation around pyright/pylance/basedpyright/cursor-pyright etc. makes it pretty much unusable, you can't get consistent results across IDEs.
When I wrote the initial version of the neovim LSP client, I got intimately familiar with LSP, and how much I hate it. Microsoft protocols have a habit of being extremely specialized to their application despite being recommended for broader use. I will never, ever, ever adapt another microsoft language protocol.
It's such a shame python got such mindshare. It's a disaster of a language and ecosystem that people keep bolting and hacking things that much better thought out languages have had for decades.
At this point, Python is less of a programming language by itself but more of an interop protocol between various C/C++/Fortran/Rust binaries. But again, it's just part of the cycle, Python was a breath of fresh air 10 years ago when academia is still dominated by Matlab, but now it is mostly a mess of a language that's good for throwaway scripts but not very convenient for large software projects compared to statically typed languages.
I remember falling in love with Python when I first learned it at version 1.5, liked it even more with 2.0, but when 3.0 came around, that's when I noticed the ecosystem falling apart. Not for the obvious incompatibility schism: I do think most of 3.0's changes were good ones, and it finally is the standard default version now, but in many other ways it feels like the ecosystem has still never really recovered. Virtualenv is still the same grotesque hack, where rather than doing what other languages like Perl and Ruby do and making some wrapper around setting PYTHONPATH, it relies on python's behavior of locating the library path relative to the install, thus hardlinking a whole python installation in and making you "activate" it first. That nothing has managed to replace it in 20 years speaks volumes.
I'm hoping one day people look at Python the same way they look at Perl and PHP.
There has been so much programming language innovation in the past decade that I'm surprised someone hasn't built a better Python. I'd like to see something like Rhai or Roto take off which has a natural upgrade path to Rust.
Maybe it's because interpreted languages just aren't in vogue anymore and probably won't be for a long time if humans aren't even coding anymore.
Roughly the time when Guido stopped fighting the hordes. The hordes won, wrested the language away from its creator and now they own the pieces. 2 to 3 was the worst possible way a language has ever been upgraded bar none. Hilariously, even today Python 2 persists in many places because of this.
Pretty much every other mainstream language bar JS. I'd say also Ruby because I also do not like a lot of its choices, but there's at least a kind of heady elegance to it in a REPL, though I would never want to work on a production system written in Ruby.
Frankly, I just really prefer statically and strongly typed compiled languages.
I did my last company's first Demo and MVP in Python after running through the Koans at my co-founder's behest and ultimately we decided that the production system would not be done in Python. There are some cool things about it - specifically I do like that annotations are real AOP seams, but the numerous footguns and lack of types and a compiler just make it a very annoying ecosystem to work in for me.
And the thing that maddens me the most is that it has a critical mass where it’s basically the default starting language and most people never really move from there. And so we’re stuck with this grotesque abomination that somehow keeps on rolling. The amount of money that was poured into python to make it barely bearable is probably the GDP of a small nation.
20 years working on Python. Two things have driven its success.
First, it's easy to learn and reasonably powerful. You can make a lot of useful things really quickly, which was true even 15 years ago. It's only gotten easier since, and the ecosystem has continued to grow.
Second, ML latched onto it. That gave Python a lot of credibility for people coming through CS programs and into industry, especially as AI use cases were picking up momentum. Think Tensorflow starting 10-ish years ago, then Pytorch, and so on.
[opinion time] Unfortunately, ML has contributed to disaster. The quality of software engineering in ML applications lags badly behind that in other segments, and there's where most Python development is happening now. The feedback loop of training Bad Python into LLMs is only making it worse. The skill floor was dropping, and now it's practically zero.
It also wasn't helped much by language design decisions. Gradual typing was a huge mistake. It would have been much better to go the Typescript route and define a superset of the language that compiles to native Python. The grafted-in typing features that rely on runtime behavior and never got an actual spec for a type system haven't helped.
It's incredibly easy for new engineers to pick up. On the spectrum between "features easy for beginners but nightmarish for experienced engineers" and "features complex for beginners but great for experienced engineers" it always makes the tradeoff for the former.
I'm not the OP, but it seemed to me that major teaching institutions settled on Python as a pedagogic language after previously having rallied around Java for same, and various other languages before that.
They provide binaries for almost every open source library for every popular platform. If you need something, whatever it is, python was and is probably the easiest way to install and use it.
It was the first language that actually felt ready-to-use, available for free-as-in-speech. Batteries included, robust online development community, sensible featureset, main libs that were designed bottom-up instead of top-down. I remember learning Java 1.2 or 1.4 after learning Python and it felt like a huge regression. Swing was a joke compared to TkInter (which was weak compared to proper GUI editors like VB but at least made nice scalable native-feeling GUIs and had a sensible API) and the standard collections were miserable without generics.
But Python peaked like 20 years ago. The later features were too ugly, and it was too slow to fill the obvious gaps in the language.
Marketing in academia, decent C-API that led to use in scientific Python.
The language is a disaster since it deviated from its original purpose. The community is ruled by insane, mediocre narcissists who drove away all reasonable people.
I've been thinking recently, there's hardly any reason not to use a native language like Rust anymore. The classic reasoning for languages like Python is that it prioritizes developer time and resources over compute resources, but now developer time is rapidly trending to zero and everything is compute dominated.
Not having to build still saves wall clock time. Also Python is a concise language (fewer tokens in context) with a monster ecosystem that avoids a lot of code having to written by agents (fewer tokens for the current task and fewer for future tasks by keeping the code base smaller).
I work in python. It's only real and big issue is the slow interpreter. Everything else is resolvable one way or another. The only other big issue it has is the envy of people who imagine that if not for python, their beloved language would be as used as python is now. Most of their beloved languages are older than python or when they were created, they had much bigger ticket backing than python and those languages are still not where python is. The reason? Python is made to solve the issue one has now, not the issue one might have in the future. Local optimum at its best and worst. And honestly, most people have the current issue to solve and rarely reach the imaginary issue to be. If python didn't exist, it would have been invented.
The issue is that it just becomes a “bad at everything” tarpit.
- performance is awful.
- gradual typing is sort of ok, but relies too much on runtime behaviour.
- async support is a bit all over the place.
- uv has made the packaging experience sort of liveable, but collectively it’s still very limited: feature support, conditional dependencies, rudimentary tree shaking, cargo-style workspaces, etc.
In an era where your options of tech stack are freer than ever, unless you explicitly need PyTorch, I’m not really sure why you’d choose Python over literally everything else.
Venvs, activate, deactivate, shitty scripts hacking on $PATH. How did this ever ship? Then there was poetry, `uv`, and maybe something in else in $CURRENT_YEAR.
Try to set it up on a new macOS, go on. Install a package from pip, and there's a bunch of garbage that won't let you do it.
It's horrible. Python packaging engineer is now an FTE, maybe that's what they wanted.
As a Ruby dev I'm kind of primed to hate on Python a little bit, but I have to agree. I've written some Python over the years, I've tried to like it, but it just doesn't feel good to me. There are things that are really great about Rust, Elixir, C#, Swift, Java, Common Lisp... Sometimes it's the standard library, sometimes the package manager, sometimes a feature (borrow checker, pattern matching), sometimes a principle (everything is an object, the code is just data). In Python, everything is kind of meh. Like they came up with the list comprehension syntax and that was it for cool things.
List comprehensions? Really? I remember when they were pretty and I was learning them alongside other languages with higher order functions and Python's approach seemed to be the ugliest of its cohort. They were neither as logical as simple Lispy "take a function as a parameter" things like Ruby, nor were they the kind of clean and legible stuff we expect from Python.
Python had no corporate backing, no marketing, it became popular because people actually like to use it. Sorry you've only been using "better thought out languages" instead.
The syntax and meaningful spaces are annoying. The dynamic typing is abused to hell in everything including the standard library. It has wacky paradigms like "exceptions instead of conditionals" or having "else" clause for loops.
It lacks decent packaging and by design cannot handle multiple versions of dependencies or perform metadata-only/declarative resolution. To resolve the dependencies of a Python package you need to install it. Many Python packages resolve their dependencies imperatively depending on the current system state. When you need binary dependencies like numpy it gets even worse since libpython doesn't have a stable ABI.
It is one of the most underdesigned languages but it holds a dear place due to being easier to translate from pseudocode to actual implementation. This resulted many academics to pick it up and write advanced math libraries in it.
i primarily work in python and from a language-design standpoint, sure, there are generally better options out there. but all the people convincing themselves that a language with this much of a user base and this large of an ecosystem will fade away because of ai or some other reason are deluding themselves. i'm sure the death of python will be imminent for the next several decades, just as it has been for java
Trisodium phosphate was at one time extensively used in formulations for a variety of consumer-grade soaps and detergents, and the most common use for trisodium phosphate has been in cleaning agents.
languages with dynamic types will be obsolete thanks to AI, you heard it here first. It is just introduces more errors, with AI you want formal checking, sure static types are not that, but it is a small piece of it. If 10 percent of errors are types, with a typed language keeping everything the same you have 10 percent less errors, simple as that.
100%. This is a solution to a problem you wouldn't have if you were just using a statically typed language. AI will naturally drive us to more rigid languages.
DetachHead (maintainer of basedpyright) has criticized the TSP before:
- https://docs.basedpyright.com/v1.40.2/type-server/
- https://github.com/microsoft/pylance-release/discussions/718...
Ty (the type checker maintained by astral) however will apparently support the TSP: https://github.com/astral-sh/ruff/discussions/23432
I think the only way MS knows how to make money is lock someone into an ecosystem. I think their next attempt should be a closed source lean checker that has will have proprietary code for NL -> lean formalization checker.
Applies to all big tech contributing to FOSS, they don't do it out of charity.
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This should be called Python Type Server Protocol, no? Seems weird to mine the generic protocol namespace for a protocol that only supports Python. Especially coming from the company behind LSP, which actually is generic.
Type Server Subsystem for Python
Copilot+ Type Server Subsystem for Python Series S
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Language Server Protocol Server Subsystem for Type Server Protocol Servers for Python
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Python Server Subsytem Typing - PSST
It is namespaced under the pylance project. I also don't see any announcement here, just a markdown file.
Perhaps the post title could use a tweak
This was the announcement https://devblogs.microsoft.com/python/announcing-tsp/
This is the company that named its web framework "MVC". At least this time they're not eternally polluting search results for an industry standard term.
I've usually heard it called "ASP.NET MVC" except when the former part was clear from context.
100% - it would make more sense if they also supported elixir or other dynamic languages
I do wonder if it generalizes outside of python similar to how LSPs do.
So now I need a TSP AND an LSP eating loads of memory?
这个协议真正有价值的地方不在于又多了一个 JSON-RPC 接口，而在于类型信息从字符串变成结构化数据。LSP 的悬停信息本质上是给人看的 Markdown，客户端或代理想程序化地使用类型时只能脆弱地解析文本；如果类型查询返回的是结构化的类型节点，编辑器、重构工具和代理就能直接消费，而不必猜测格式。关键的取舍在于范围与成本：如果每次查询都要计算完整类型图，延迟会很难接受，所以按需、增量的查询和明确的能力协商比协议本身更重要。另外，当前的结果类型明显偏向 Python，未来要推广到其他语言，需要把语言无关的类型骨架和语言特有的类型构造分开，否则很容易变成第二个只服务于单一生态的协议。
It’s really good that folks over at Astral decided to implement it. It was difficult for me to understand what does this protocol provide that couldn’t be implemented with a new LSP capability, the linked document doesn’t really explain that, but what did become clear to me is that seemingly Microsoft are trying to invent new features for their proprietary LSP server that only works in VS Code so people will have harder times switching to other editors. This way, no matter what Microsoft comes up with, will be matched with very high quality open source tools.
As someone with minimal knowledge of LSP specifics, I'm a bit confused about why this exists. Is it the case that LSP alone does not provide adequate functionality for Python type queries?
> why this exists
https://docs.basedpyright.com/v1.40.2/type-server/
> The "type server protocol" is a desperate attempt from microsoft to prevent pylance from becoming obsolete by outsourcing its type checking to other language servers like basedpyright, ty or pyrefly -- while continuing to keep certain language server features exclusive to pylance.
> This protocol benefits nobody except microsoft. It adds needless complexity to any language server that chooses to support it. Basedpyright does not support it and strongly advises other language servers to avoid supporting it as well.
> For more info see here https://github.com/microsoft/pylance-release/discussions/718... and here https://github.com/astral-sh/ty/issues/1190#issuecomment-337...
It seems to be a more structured representation of the type. Normally in LSP you'd have a plain string or markdown that you render in the IDE, but nothing that you can analyse structurally.
It's a shame it's not just an LSP extension though, or a feature in a newer LSP version. LSP is maintained by Microsoft engineers.
workspace/symbol will do it (and the output may need some massaging), but it's optional.
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So basically adding machine readable type-at-point queries as an lsp extension so Pylance and Pywright can be separated?
The 'result types'format is super python specific, like not having a for all binder. I don't think this specific schema will be used for any non-python languages.
Can someone explain what this is to someone like me that doesn't know python very well, but programs a lot in c#?
Language server protocol is the interface of a software piece that sits between an IDE and a language toolchain so you don't need to change code in the IDE to add support of new languages (you add support on the LSP server). Then server provides things such as completions/intelli-sense, navigation to definitions and some correction checking. From the anouncement TSP extends LSP for better python type awarness.
It kept with UTF-16. New protocol is a chance to correct that poor decision.
It's just an .md file and a few hundred lines of json schema defining some extension messages, not a bottom-up protocol revision.
What's wrong with UTF-16 for transport?
I just use the Pyrefly extension in VSCode/Zed, run Pyrefly in the CI, and everything works well. The fragmentation around pyright/pylance/basedpyright/cursor-pyright etc. makes it pretty much unusable, you can't get consistent results across IDEs.
[flagged]
Reading the main README, I'm not sure why I'd reach for this over ant other typed JSON RPC, tRPC or similar. What are the benefits I'm missing here?
When I wrote the initial version of the neovim LSP client, I got intimately familiar with LSP, and how much I hate it. Microsoft protocols have a habit of being extremely specialized to their application despite being recommended for broader use. I will never, ever, ever adapt another microsoft language protocol.
Is there any application for that, except python?
Right now it's specific to Python but I think there are other languages w/o an official type checker that might benefit.
PHP, Erlang, Ruby, etc.
The primary reason i guess is standardizing the type checking, so you can bring your own (3rd party).
It's such a shame python got such mindshare. It's a disaster of a language and ecosystem that people keep bolting and hacking things that much better thought out languages have had for decades.
At this point, Python is less of a programming language by itself but more of an interop protocol between various C/C++/Fortran/Rust binaries. But again, it's just part of the cycle, Python was a breath of fresh air 10 years ago when academia is still dominated by Matlab, but now it is mostly a mess of a language that's good for throwaway scripts but not very convenient for large software projects compared to statically typed languages.
thank you for putting this this way. it helped me crack a big unrelated problem
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I remember falling in love with Python when I first learned it at version 1.5, liked it even more with 2.0, but when 3.0 came around, that's when I noticed the ecosystem falling apart. Not for the obvious incompatibility schism: I do think most of 3.0's changes were good ones, and it finally is the standard default version now, but in many other ways it feels like the ecosystem has still never really recovered. Virtualenv is still the same grotesque hack, where rather than doing what other languages like Perl and Ruby do and making some wrapper around setting PYTHONPATH, it relies on python's behavior of locating the library path relative to the install, thus hardlinking a whole python installation in and making you "activate" it first. That nothing has managed to replace it in 20 years speaks volumes.
I'm hoping one day people look at Python the same way they look at Perl and PHP.
There has been so much programming language innovation in the past decade that I'm surprised someone hasn't built a better Python. I'd like to see something like Rhai or Roto take off which has a natural upgrade path to Rust.
Maybe it's because interpreted languages just aren't in vogue anymore and probably won't be for a long time if humans aren't even coding anymore.
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Roughly the time when Guido stopped fighting the hordes. The hordes won, wrested the language away from its creator and now they own the pieces. 2 to 3 was the worst possible way a language has ever been upgraded bar none. Hilariously, even today Python 2 persists in many places because of this.
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> thus hardlinking a whole python installation in and making you "activate" it first
You don't have to activate a venv to use it; `$VENV_PATH/bin/python3` just works.
(It also softlinks/symlinks the binaries.)
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I work in python daily, it's not necessarily my favourite language, but I'd say it's mostly fine.
What languages are you thinking of specifically when you mention better thought out ones?
Pretty much every other mainstream language bar JS. I'd say also Ruby because I also do not like a lot of its choices, but there's at least a kind of heady elegance to it in a REPL, though I would never want to work on a production system written in Ruby.
Frankly, I just really prefer statically and strongly typed compiled languages.
I did my last company's first Demo and MVP in Python after running through the Koans at my co-founder's behest and ultimately we decided that the production system would not be done in Python. There are some cool things about it - specifically I do like that annotations are real AOP seams, but the numerous footguns and lack of types and a compiler just make it a very annoying ecosystem to work in for me.
They are a heavy C# user. Coke/Pepsi situation.
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And the thing that maddens me the most is that it has a critical mass where it’s basically the default starting language and most people never really move from there. And so we’re stuck with this grotesque abomination that somehow keeps on rolling. The amount of money that was poured into python to make it barely bearable is probably the GDP of a small nation.
I’m not a fan either, but it doesn’t bother me at all. Who cares? Let the python people do their thing.
Fascinating take.
What do you attribute Python's success to, in spite of being a disaster of a language and ecosystem?
20 years working on Python. Two things have driven its success.
First, it's easy to learn and reasonably powerful. You can make a lot of useful things really quickly, which was true even 15 years ago. It's only gotten easier since, and the ecosystem has continued to grow.
Second, ML latched onto it. That gave Python a lot of credibility for people coming through CS programs and into industry, especially as AI use cases were picking up momentum. Think Tensorflow starting 10-ish years ago, then Pytorch, and so on.
[opinion time] Unfortunately, ML has contributed to disaster. The quality of software engineering in ML applications lags badly behind that in other segments, and there's where most Python development is happening now. The feedback loop of training Bad Python into LLMs is only making it worse. The skill floor was dropping, and now it's practically zero.
It also wasn't helped much by language design decisions. Gradual typing was a huge mistake. It would have been much better to go the Typescript route and define a superset of the language that compiles to native Python. The grafted-in typing features that rely on runtime behavior and never got an actual spec for a type system haven't helped.
It's incredibly easy for new engineers to pick up. On the spectrum between "features easy for beginners but nightmarish for experienced engineers" and "features complex for beginners but great for experienced engineers" it always makes the tradeoff for the former.
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I'm not the OP, but it seemed to me that major teaching institutions settled on Python as a pedagogic language after previously having rallied around Java for same, and various other languages before that.
Probably the batteries included Standard Library.
Cross platform interpreter.
NumPy and SciPy really set the stage.
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BASIC rebooted. Right at the right time too, BASIC was never going to thrive in the days of the internet.
I'll give Python one thing though, it is by far the most elegant way to glue together a large number of otherwise incompatible C libraries.
They provide binaries for almost every open source library for every popular platform. If you need something, whatever it is, python was and is probably the easiest way to install and use it.
well, for one, my boss can use it and kinda understand it, so it must be dead simple
Definitely ease of use...
It was the first language that actually felt ready-to-use, available for free-as-in-speech. Batteries included, robust online development community, sensible featureset, main libs that were designed bottom-up instead of top-down. I remember learning Java 1.2 or 1.4 after learning Python and it felt like a huge regression. Swing was a joke compared to TkInter (which was weak compared to proper GUI editors like VB but at least made nice scalable native-feeling GUIs and had a sensible API) and the standard collections were miserable without generics.
But Python peaked like 20 years ago. The later features were too ugly, and it was too slow to fill the obvious gaps in the language.
Marketing in academia, decent C-API that led to use in scientific Python.
The language is a disaster since it deviated from its original purpose. The community is ruled by insane, mediocre narcissists who drove away all reasonable people.
- Math + visualization libraries (which ironically have to break out of Python to do their job)
- Reasonable ergonomics for describing data flows, as long as you never run the code, which you often don't care about if you're a mathematician
- Adoption by people who optimize pumping citations, not reproducible results -- non-working code is a feature when you're trying to BS
No other language came even close to a combination of easiness and expressivity of Python.
I've been thinking recently, there's hardly any reason not to use a native language like Rust anymore. The classic reasoning for languages like Python is that it prioritizes developer time and resources over compute resources, but now developer time is rapidly trending to zero and everything is compute dominated.
Not having to build still saves wall clock time. Also Python is a concise language (fewer tokens in context) with a monster ecosystem that avoids a lot of code having to written by agents (fewer tokens for the current task and fewer for future tasks by keeping the code base smaller).
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Rust has Rhai and Roto too if you need better than Python level of developer considerations.
Unpopular take, but:
I work in python. It's only real and big issue is the slow interpreter. Everything else is resolvable one way or another. The only other big issue it has is the envy of people who imagine that if not for python, their beloved language would be as used as python is now. Most of their beloved languages are older than python or when they were created, they had much bigger ticket backing than python and those languages are still not where python is. The reason? Python is made to solve the issue one has now, not the issue one might have in the future. Local optimum at its best and worst. And honestly, most people have the current issue to solve and rarely reach the imaginary issue to be. If python didn't exist, it would have been invented.
The issue is that it just becomes a “bad at everything” tarpit.
- performance is awful.
- gradual typing is sort of ok, but relies too much on runtime behaviour.
- async support is a bit all over the place.
- uv has made the packaging experience sort of liveable, but collectively it’s still very limited: feature support, conditional dependencies, rudimentary tree shaking, cargo-style workspaces, etc.
In an era where your options of tech stack are freer than ever, unless you explicitly need PyTorch, I’m not really sure why you’d choose Python over literally everything else.
I will take Python over typescript every second of every day. TypeScript is just so unreadable compared to Python.
OTOH I don't want to live in a universe where Haskell wins
The packaging is a nightmare thats for sure.
Venvs, activate, deactivate, shitty scripts hacking on $PATH. How did this ever ship? Then there was poetry, `uv`, and maybe something in else in $CURRENT_YEAR.
Try to set it up on a new macOS, go on. Install a package from pip, and there's a bunch of garbage that won't let you do it.
It's horrible. Python packaging engineer is now an FTE, maybe that's what they wanted.
The fact that they didn't solve Venv when they did the breaking change in Python 3 is absolutely bonkers.
As a Ruby dev I'm kind of primed to hate on Python a little bit, but I have to agree. I've written some Python over the years, I've tried to like it, but it just doesn't feel good to me. There are things that are really great about Rust, Elixir, C#, Swift, Java, Common Lisp... Sometimes it's the standard library, sometimes the package manager, sometimes a feature (borrow checker, pattern matching), sometimes a principle (everything is an object, the code is just data). In Python, everything is kind of meh. Like they came up with the list comprehension syntax and that was it for cool things.
List comprehensions? Really? I remember when they were pretty and I was learning them alongside other languages with higher order functions and Python's approach seemed to be the ugliest of its cohort. They were neither as logical as simple Lispy "take a function as a parameter" things like Ruby, nor were they the kind of clean and legible stuff we expect from Python.
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Python had no corporate backing, no marketing, it became popular because people actually like to use it. Sorry you've only been using "better thought out languages" instead.
Python should have done runtime type checking instead of compile-time only String and List annotations and so on
Worse is better. Avoid using it yourself and tell others; that's the best you can do.
Python is pretty decent. What are you talking about?
The syntax and meaningful spaces are annoying. The dynamic typing is abused to hell in everything including the standard library. It has wacky paradigms like "exceptions instead of conditionals" or having "else" clause for loops.
It lacks decent packaging and by design cannot handle multiple versions of dependencies or perform metadata-only/declarative resolution. To resolve the dependencies of a Python package you need to install it. Many Python packages resolve their dependencies imperatively depending on the current system state. When you need binary dependencies like numpy it gets even worse since libpython doesn't have a stable ABI.
It is one of the most underdesigned languages but it holds a dear place due to being easier to translate from pseudocode to actual implementation. This resulted many academics to pick it up and write advanced math libraries in it.
I blame Perl 6
it could be worse like …PHP
> It's a disaster of a language and ecosystem
"unhinged" take
i primarily work in python and from a language-design standpoint, sure, there are generally better options out there. but all the people convincing themselves that a language with this much of a user base and this large of an ecosystem will fade away because of ai or some other reason are deluding themselves. i'm sure the death of python will be imminent for the next several decades, just as it has been for java
Is it Python specific only?
Interesting, LSP, DAP, MCP, and TSP now...
TSP : TriSodium Phosphate. Very good for cleaning up a mess.
From Wiki:
Trisodium phosphate was at one time extensively used in formulations for a variety of consumer-grade soaps and detergents, and the most common use for trisodium phosphate has been in cleaning agents.
Ref: https://en.wikipedia.org/wiki/Trisodium_phosphate
Blog posts:
Pylance + Pyrefly: bring your preferred type checker to Visual Studio Code
https://devblogs.microsoft.com/python/announcing-tsp/
Pyrefly + Pylance Integration in VS Code
https://pyrefly.org/blog/pyrefly-pylance/
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Type-shed, type-server. When can this Python madness stop? How about using CORBA to make it even more enterprisey?
Why don't you spend your resources on F# instead of this nonsense?
> Why don't you spend your resources on F# instead of this nonsense?
Absolutely!
F# is criminally under-invested in.
Exactly what i came to write as well. I'd expect Microsoft to invest in F# so that python can slowly fade away the way php did.
The cottage industry around fixing gaps in Python is sometimes awe-inspiring and most times just downright awful.
Maybe just make a Python 4 with better types built in at this point...
languages with dynamic types will be obsolete thanks to AI, you heard it here first. It is just introduces more errors, with AI you want formal checking, sure static types are not that, but it is a small piece of it. If 10 percent of errors are types, with a typed language keeping everything the same you have 10 percent less errors, simple as that.
100%. This is a solution to a problem you wouldn't have if you were just using a statically typed language. AI will naturally drive us to more rigid languages.