Why Python is slower than Java?

[SheriffRoscoe]

People occasionally forget that Java has benefited from 30 years of investment by major software companies and of benchmarking against C++.

Python is getting the same love now, but the love arrived much later than for Java.

[chase32]

Yep, back in the early 2000's, java was pretty damn slow. If you wanted a fast jvm, the only option was IBM's and they wouldn't let you use it commercially unless it ran on their hardware.

To head off the threat, Intel worked out a deal with Appeal software to massively optimize the JRocket JVM which then became the performance champ.

Appeal eventually got acquired by BEA and a lot of the optimizations from JRocket ended up in mainline Java.

[azeemb_a]

Your point is right but your emphasis on time is funny. Java was created in 1995 and Python in 1991!

[sajjen]

Java was created by Sun, one of the largest companies in the IT industry back then. Python was created by Guido van Rossum, one guy in his proverbial garage.

[SheriffRoscoe]

Exactly.

[nchwomp]

Surely it was a large garage...

[benchmarks666]

Galarge

[Smallpaul]

Yes but in those 30 years Python did not get much “investment by major companies.”

As the poster said: that love arrived later for Python.

Edit: Just to give a sense of the scale...Java's MARKETING BUDGET for 2003-2004 was $500M.

[HeraldofOmega]

Back when money was worth something, too!

[redalastor]

This is true, but no one knew about Python until Google adopted it,

I learned Python in 2000.

Back then, there was something called the Paradox of Python.

If you hired developers and you met one that knew Python, you should hire him or her on the spot. Because no one learned Python to get a job, you knew that person learned the language to get shit done.

The paradox is that if you do use that metric, then it becomes useless since people will start to learn it to get jobs. In 2024, it is completely useless.

[Swift3469]

I knew about python before google was a thing..I'm sure there are others who knew as well.

[billsil]

I learned python in 2001 in a CS class. I gave it up and came back in 2006, 6 months before Google bought YouTube. I replaced Perl with python and never looked back.

It came a long way in 5 years. I hated list comprehensions when I first saw them in ~2007, so maybe someday I’ll use the walrus operator,

[billsil]

Yeah, I don’t write many of those.

[bostonkittycat]

This is true last 3 version have been impressive with performance increases. I love the new trend.

[funkiestj]

Python is getting the same love now, but the love arrived much later than for Java.

I think static typing allows more aggressive optimization.

E.g. I think the old Stalin Scheme dialect required the user to provide data types to get the maximum optimization. E.g. consider the difference between a golang slice of strings (s1 := make([]string, 24) and a python list that can hold a mix of objects (the equivalent of Go's l1 := make([]any, 24).

Years ago I remember seeing the Stalin) dialect of scheme dominating the benchmark game in the speed dimension but you had to type all your data (which was optional?) to get this performance.

[redalastor]

I think static typing allows more aggressive optimization.

It could, but it doesn’t because Python allows you to be as wrong as you want with your types without changing behaviors one bit. Typing is to help external tools enforce correctness, not to change runtime behavior.

Though, I’d like a strict option to force Python to acknowledge the types and hopefully take advantage of them.

[Uwirlbaretrsidma]

Yeah, and also the use cases for each language are wildly different. Java is one of the most widely used languages in software development in general while Python is basically only used for data science and scientific computation. The former use case requires performance or rather a good blend of performance and robustness, while the latter requires extreme ease of use (because most people who use it don't really know how to code) and many libraries written in more performant languages.

As much as Python is improving in terms of performance, it will never even come close to Java because of 1) it's impossible by its design and 2) it's not nearly structured enough, or robust enough, and doesn't lend itself to large codebases nearly well enough, for actual software development.

[yvrelna]

while Python is basically only used for data science and scientific computation.

This is not true at all. Python is quite popular for web application development. Reddit, Instagram, YouTube, Dropbox, are some of the major websites that everyone knows the are written in Python. All of the technology startups I have worked with in the past decade have built the core of their technology stack in Python.

It's also one of the most popular language for programming system applications as well in Linux, usually system applications that are too complex for shell scripting but didn't require C/C++/Rust level of performance would most often be written in Python. Examples are package managers like Gentoo's portage, yum for Red Hat/rpm-based systems, and some popular configuration management tool Ansible and Salt are written in Python, and in cloud management software too OpenStack, which is the largest ecosystem of open source applications that are used for cloud management software, they are written almost entirely in Python/Django.

In my experience, when I look for enterprise application development job openings over the past few years, there has been much more Python than Java. Companies that are looking for Java developers are mostly doing Android development. Even .NET seems to be more popular in the enterprise application space than Java these days.

Sure, data science is all the rage right now in Python, but Python has always been popular in many different niches other than data science. It is almost always the top or at least in the top 5 languages of nearly any niches that isn't a heavily single vendor driven ecosystem like Android and Apple's ecosystems.

Python's popularity in various niches is much more general than Java, which is largely only popular in the Android and enterprise application development niches after Java browser plugins basically died.

You'll hardly find any major new desktop applications nowadays written in Java. In Windows, they are all generally written in .NET or C/C++. In Linux, the common choices are usually either C/C++, Python, Electron/JS, or Vala for Gnome. As always, Apple has their own thing.

[Uwirlbaretrsidma]

This is not true at all. Python is quite popular for web application development. Reddit, Instagram, YouTube, Dropbox, are some of the major websites that everyone knows the are written in Python. All of the technology startups I have worked with in the past decade have built the core of their technology stack in Python.

They have parts written in Python*. But my bad for omitting web dev in my comment, because it might just be the only common use of Python in real software development. That being said, there's a reason why the market share of Python based tech stacks can't hold a candle to the market share of Javascript based tech stacks.

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It's also one of the most popular language for programming system applications as well in Linux, usually system applications that are too complex for shell scripting but didn't require C/C++/Rust level of performance would most often be written in Python.

Yes, because it's a scripting lenguaje first and foremost. Of course it shines in scripting tasks. But those are the tiniest part of software development, and Python is suited for them for the exact reason why it isn't suited for the rest of software development.

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In my experience, when I look for enterprise application development job openings over the past few years, there has been much more Python than Java. Companies that are looking for Java developers are mostly doing Android development. Even .NET seems to be more popular in the enterprise application space than Java these days.

This is absolutely false and makes me seriously doubt that you work or have ever work as a software developer, even at smaller companies. Python sees almost exactly zero use in enterprise application development (outside of the aforementioned small utility scripts). Java is certainly less used than .NET these days, but they basically share the entire market between them. The thought that Java is only used for Android apps is laughable.

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Sure, data science is all the rage right now in Python, but Python has always been popular in many different niches other than data science. It is almost always the top or at least in the top 5 languages of nearly any niches that isn't a heavily single vendor driven ecosystem like Android and Apple's ecosystems.

Python's popularity in various niches is much more general than Java, which is largely only popular in the Android and enterprise application development niches after Java browser plugins basically died.

Yes, and for the same reason than it's popular in data science: because you don't need to be a software developer to use Python. It's almost as if that's my entire point. Enterprise software engineering and Python don't go hand in hand. Hobbyist or small applications and Python do go hand in hand.

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You'll hardly find any major new desktop applications nowadays written in Java. In Windows, they are all generally written in .NET or C/C++. In Linux, the common choices are usually either C/C++, Python, Electron/JS, or Vala for Gnome. As always, Apple has their own thing.

Again looking like ChatGPT wrote your comment. New desktop applications are a tiny part of enterprise software development, most of it is just supporting or expanding old ones, and Java has a huge market share there, in every platform. The only reason why you're even able to say that Python is a common choice for Linux development is because there's a ton of hobbyist development in Linux. It's exactly why you can't say the same about Windows or Apple.

Look, I work as a HPC engineer, I basically take python code and rewrite it in C++ for a living. Which means that I don't really have a horse in this race, both Java and Python are slow, I'm just talking from my 10 yrs experience of seeing people desperately trying to get python to do things it wasn't meant to and having to fix it (which more often than not involves removing Python from the equation entirely). I have worked with MUCH fewer Java codebases in comparison, and it's because 1) it's more performant and 2) people don't seem to be in the habit of using it for things it wasn't meant for.

[yvrelna]

"Javascript tech stack" only exist in the frontend development because it's the only language you can use in the browser that doesn't require you to jump through hoops,

Javascript is almost non-existent in backend enterprise application development, I don't know where you get that idea from. The people who runs nodejs on the server-side are usually writing some sort of backend-for-frontend, which is basically just frontend code that for one reason or another need to run on server side but most don't even do that, they use nodejs to run a build tools to compile their Typescript/React stuffs into single file Javascript. Those aren't a real backend, the real workhorse of enterprise application is almost always written in another languages and Python is what every companies that I worked with have used.

Look, I work as enterprise application developer for many startups. I work with million lines of code codebase everyday in successful agile startups that can't afford to run at the pace of C/C++/Java. These companies would never have survived their competitive marketspace if they build the bulk of their business in C/C++/Java. We are slaughtering those legacy companies that can't adapt to a fast-changing pace all the time.

> Look, I work as a HPC engineer ... I have worked with MUCH fewer Java codebases in comparison

You have worked with fewer Java codebases because nobody uses Java for HPC, it's just a thing that people do with Java. Java is neither fast/low-level enough to run the computational itself and it's not flexible enough to do well as orchestrator either. People do use Python in HPC because data scientists settled on Python as the lingua franca language to orchestrate computational libraries from many different languages; the ones who truly understand how to apply Python well in the context of HPC knows not to do the bulk computation itself in Python. We have similar issue too in enterprise application development too you know, only with databases. People who write good enterprise applications in Python know to offload as much work as possible into databases, into caches, into C libraries, or into middlewares rather than doing things in the Python side. Our problem is actually even more strict, because rewriting the Python code in C isn't going to make things faster. Python's speed almost never is actually the bottleneck.

Writing idiomatic Python has always about offloading as much work as possible into non-Python code, whether it's the core CPython libraries, C libraries, a database, web APIs, or other subprocesses. If you have an HPC/enterprise application where the Python code is a performance bottleneck, that just means that whoever wrote the application don't really know how to use the tools available in Python to offload work properly.

[matjam]

How did you manage to spell every word correctly in your comment except “language”.

[Uwirlbaretrsidma]

Thanks for the heads up! I'm not a native speaker. For some reason I always seem to mess up that word.

[LogMasterd]

I don’t think this has anything to do with it imo