Since its inception, Microsoft Excel has changed how people organize, analyze, and visualize their data, providing a basis for decision-making for the..
Since its inception, Microsoft Excel has changed how people organize, analyze, and visualize their data, providing a basis for decision-making for the flying billionaires heads up in the clouds who don't give a fuck for life offtheline
I mean, whatever speed java has or doesn't have, what the other person said was emulate, you'll have your os then on top of that the JVM then on top of that your python implementation, then finally the python code. If that's faster than os->python imp..
Just like Python doesn't run from the source code through the interpreter all the time (instead, if I'm not mistaken, the interpreter pass converts the code to a binary runtime form, so interpretation of the source is done only once), so does "modern" Java (I put modern between quotes because it's been like that for almost 20 years) convert the code in VM format to binary assembly code in the local system (the technology is called JIT, for Just-In-Time compiler).
Eh...Java source code compiles into bytecode which runs in a virtual machine. Compare this to a language like C which compiles to native machine code. Java still gets interpreted.
That's not how it works. If that really was how it worked there'd be no point even having bytecode; you'd just straight up get the native code. Unless you're talking about JIT, but your wording seems to be implying that all the bytecode turns into native code at once.
Yeah, in my personal experience (with numerical compute-heavy code), normal python code, ran in the normal python interpreter, is much slower than the equivalent normal Java code with the normal Java VM (like 50x). Then C/Fortran is ~2x faster than Java (with gcc + optimization flags).
I think Java is a good middle-ground between coding speed and execution speed. Sadly, it seems to be dying. And JavaFX is shit for trying emulate full-stack web-dev. The fucking ancient Swing is even better.
Scala and Kotlin are OK, but I think they are making the mistake of feature-creep that causes large projects with many people to contain multiple programming paradigms that only some of the team can grok well, instead of a restricted OOP Java codebase that encourages Gang of Four style code. Though, I guess GoF-style code resulted in that crazy complicated "enterprise" Java shit.
Last I checked Java was alive and well in the server-side for things like middleware and backend, especially because the whole development ecosystem is incredibly mature and significantly more stable and well integrated with corporate-category systems than pretty much anything else (good luck managing a single reliable transaction across, say, 2 different databases in 2 different sites and 1 MQ system with Python).
Absolutelly, it's been mostly limping in a half-dead state on the UI ever since day 1 and even Google using it with Android didn't exactly help (because Google's architectural design of the entire Android framework is, well, shit, and has become worse over time).
It also lost it's proeminence in dynamic web page generation at around the early 00s to actual templating languages (such as PHP) with a much lower learning curve and later to Python.
The ecosystem for Java is rock-solid and in widespread use in corporate multi-tier architectures that require reliable operation (were, for example, it's native multi-threading synchronisation support and core libraries make a huge difference) and integration with professional backend systems, but for the rest, not so much (I did both that stuff and Android, and the latter is like the amateur-hour of Java ecosystems in comparison with the former).
The problem in Android has always been that the framework design is pretty bad in design and technical architecture terms and its evolution over time has made its glaring flaws more obvious and actually made it even messier, rather than the language (Java is fine as languages go and UI stuff only has to run in user-time, so response times of 100ms are fine and bleeding edge performance is not required).
Further, splitting the user base into two languages, by introducing a new language that is not used anywhere else (hence you're not going to find Kotlin programmers from outside Android development whilst you will find plenty of Java programmers) is one of the stupidest technical architecture decisions I've seen, and I've been in the industry for over 2 decades.
Last but not least, the gains from the small programming-time efficiency advantages of Kotlin over Java are a drop in the ocean next to the losses due to the Android Framework itself being badly designed (something as simple as not having functions in different core classes that do the same thing named the same).
Even for programmers going for Kotlin is a less than wise career move: as an Android-only language those who specialize in it are locking themselves into programming for Android only and have fewer career options - hands up anybody who expects to still be programming Android in 10 years time! The great thing of generic languages is that there are a lot of lateral career moves you can make without the high likelihood of failure that comes from hiring managers naturaly prefering people with several years of experience in the programming language used in their projects over people who say "I've mainly done Kotlin but I can learn that easilly".
What many years of experience in the industry tells me is that you don't want your career to hang on the ficklness of a vendor, any vendor, especially the likes of Google who will drop massivelly hyped systems with tons of 3rd party investment whenever they feel like: just ask everybody who invested in developing for Stadia.
I used to make high performance distributed computing server-systems for Investment banks.
Since the advent of Just In Time compiling, Java isn't slow if properly used.
It can however be stupidly slow if you don't know what you're doing (so can something like Assembly: if you're using a simple algorithm with a O(n) = n^2 execution time instead of something with O(n) = n*log(n) time, it's going to be slow for anything but a quantum computer, which is why, for example, most libraries with sorting algorithms use something more complex than the silly simple method of examining every value against every other value).