You missed that Julia can use all the Python libraries just like there were native Julia libraries, but it goes further and can also use R, C++, Fortran, and Java libraries too as easily as Python in the case of C++ and almost as easily for the other languages. So, one of your big selling points for Python is not actually a selling point versus Julia.

it's interesting how Julia on board looks so modern and python's defense was "it has a huge community and lot of packages". Check Julia 1.9 first the plot is fixed :D

Julia is like a Python 4.0. Many libraries in Python are needed to fix the lacks of Python. Julia doesn't need libraries like Numpy, Numba, Cython, Cpython. Matrix multiplication? Already built in. And there are a lot of things I like in Julia, but you'll never get in Python. I like that every block is terminated by an end. In Python I get often confused by nested blocks. I like Julia's support of Unicode and Latex. Formulas are more like they look in math. Python is easy to learn, but if performance is needed, you have to do some extra mile. Julia, which is as easy to learn, write and read, doesn't need this effort. Therefore there are just 2 advantages of Python over Julia: much bigger community and much more written code. I hope these advantages will decrease in the future.

As a pure science background (biology), I like programming language with high level performance in any OS and also have strong types system. That's why I choose Julia. Julia combine both concept of Java (JIT) and C/Rust (LLVM Compiler). I think Julia has a bright future for scientist. Great video. Thank you🙏

Julia is (can be) as fast as C and as easy as Python...it's an incredible achievement.

*The real problem of Julia is that Julia did not find a big tech company to spend money on it, just like how Google spent money on Python.*

I’ve heard of Julia but this really has opened my eyes. Thanks, I’m going to learn it.

Nice video. But I think you have the point about extensibility backwards. Python’s lack of extensibility has forced, for example, multiple projects to write their own custom NumPy implementations from scratch (e.g. jax.numpy). The basic problem is that in Python there is no way to extend a given function onto a type that you don’t own. This extensibility is one of the prime selling points of Julia. In fact, the most recent criticism of Julia that sparked a lot of discussion was that Julia is _too_ extensible and that the culture of extensibility has led to correctness bugs in popular third party libraries. I think the point you were making wasn’t necessarily about extensibility but how “batteries included” each language is. On the continuum of “all functionality needs to be imported” (Python lives around here) to “all functionality is in the base language” (MATLAB lives around here), Julia is pretty decidedly on the Python side. The one notable difference is that Julia’s arrays have a concept of dimensionality baked in, so matrices and higher-dimension arrays are part of the core language. Personally, I’m a fan, because NumPy is hamstrung into some pretty clunky syntax around matrices. And it’s nice to not have to care about the difference between a list and a numpy.array. But I think those are more personal preferences. People seem to like NumPy, so I won’t tell them they’re wrong. I’ll note one last difference in that community in Python and Julia mean different things. In Python, community is generally a one-way street. You can search a question and almost always find an answer someone gave at some point in time. In Julia, you won’t always find a lot of answers by searching, but you can hop on the Discourse, Slack, Zulip, etc. and very quickly get an answer, as the community is very active. There are advantages and disadvantages to both approaches. Julia’s approach certainly isn’t going to scale well as the user base grows, but for now it feels kinda nice. The people who most often answer your questions tend to be working on similar problems as you, so industry-specific connections kinda happen naturally.

Maybe I was not paying attention but I don't remember any reference to the main difference between Python and Julia: namely that Python is interpreted and Julia is compiled just-in-time.

Great video! Thank you for mentioning multiple dispatch, a real game changer. I think your comparison is fair to both languages. Looking forward to upcoming videos.

More videos on Julia would be really interesting.

It not really true if you say that Julia is “dynamically typed language” because Julia in contrast to Python can be use as “dynamically and statically typed language”. It depends on the user which approach he will choice. Special for the large scale Application it is the key difference.

I just want to point out that Julia has a lot libraries. I learned Julia before python. Python's syntax can be confusing. Also, Julia does not depend on white spaces so you can see the formatting. I have used Julia for signal processing for my acoustics work. Julia does not have a fragmented packaging system like python and can be ran only basically any desktop operating system.

You make it sound like Julia cannot use 3rd party libraries for various tasks. I don't believe this is true, but someone naive to coding would think that was the case from what you said.

Scalability in terms of networking is the biggest issue in Python. Serializing / deserializing data and passing it to individual processes / nodes, across a distributed environment such a pain.

If you're going to become an actual scientist, study both. If you need to go to work and can't get an advanced degree, start with Python and get to Julia later. Guido was not an expert in computer languages. Python had major flaws as a purely frame-based language from the beginning. There are packages that you can run from Python that are highly-performant. Jax is my favorite. However, Python's implementation of the features needed to support a JIT compiler show that it is now nothing more than bad macro language for these packages. Python 4 is Julia.

Python is "do anything" because it has, for some strange reason, accumulated enormous number of additional libraries. In most cases Python programs are little more than glue code for those libraries (usually written in C/C++ or more and more Rust.) Julia also has many good libraries available for it. Also, perhaps with a bit of glue code ("wrappers") one can call virtually anything from anything else, although having to rely on different virtual machines and/or runtimes will complicate things.

Thankful for such awesome recommendation! Sticking around for more of such content!❤

Also, I would add, that numpy is not as intuitive as the in-built matrix operators in Julia. Plotting in Julia is so much easier than with matplotlib. JAX which is the new package for ML by DeepMind in python is almost a clone of the paradigm of FluxML in Julia. They even have their own version of JAX numpy which is made to resemble the matrix operations in Matlab and Julia. Some quirky things in the Python syntax do not exist and in general that 'pseudo code abbreviations' in python are not always obvious, like in python it is 'len' but Julia it is simply 'length' spelling it out completely

I realized something while watching this. Chat GPT is trying to mimic answers like these. Not sure if it will ever be as fun as people can make the experience. Thanks to IBM for all the efforts you make in educating the general public of new technology people like myself may never get a chance to experience or even hear about, much less the inner workings. Just had to add my sincere appreciation and couldn’t imagine a more trustworthy source of truth than the Experts at IBM. Thank you for believing in your audience. Shows I’m not alone in believing this with the numbers of views.

I’m going to make a bet in Julia for ML / DS and Rust for system programing. Lets see if they’ll have a kind of QT…

What a great way to present by writing mirrored against the screen of the viewer! 💡😃

It was an excellent explanation on the application of Python vs Julia! Since, Julia is used for applications such as Artificial Intelligence and Machine Learning. Is it possible to make an video on how it is applied in these areas? I will be waiting for the Video!

Mmmm Julia is dynamically typed by default but unlike Python real static typing is an option. Also, Python libraries are usable in Julia by default, that's not an advantage of Python

The argument of extensibility listed under Python is very much also a Julia advantage. The ecosystem is not yet as large, but you may need only a small part of the ecosystem. For me it's been quick to start with CSV, NCDatasets, Dates, Makie, Images packages. There is a good deal of plotting options, but it was a bit hard to decide which one to learn first. The syntax and layout of Julia look a lot cleaner to me than Python. I have been using Scilab (a free Matlab alternative) for years, and IDL/PVWAVE before that. I am finding the transition to Julia very smooth. I actually don't mind the type annotations, especially for the speed gained. It is pretty much mandatory if you wish to input data into certain functions. In Julia you need to be careful about assigning variables to other variables, if you don't want to change those as well - this can lead to unexpected bugs you can lose hours with :)

Great video. Please make a video like that java vs csharp

The real problem with Julia is the lack of a good debugger. I was using it a couple years ago and had to add print statements all over the place to trace down issues. It's like I was living in the 80's. Not good.

Would be nice to see actual benchmarks

Thank you, I am goin' for Julia, as I do like the beauty of Matlab

Great video. Love the content you guys put out.

Your videos are always insightful. Thanks!

A small question: Will Julia replace Python in performing some data science tasks in the near future? If yes, then what are those tasks?

Thank you, I love you ❤

What about cython? By adding types performance can be enhanced 20x.

but you can call Python from Julia. Does that help with extensibility? or not really?

Python does support single and multiple dispatch. Singe dispatch is part of the Python distribution and has to be imported from functools; multiple dispatch has to be installed from the repositories.

Great video! Learning about the differences between Python and Julia is a great way to expand your knowledge and become a more well-rounded programmer.

Could someone make a python variant having non-significant whitespace?

Python: "Do anything" (slowly)

the biggest plus for me in julia: static typing support, and broadcast operator

Is Julia ready for use in a production environment? Have used it years ago (v0.4/0.5), and contemplating on using it for analysis. How well are packages maintained and how often will implementations break?

Really strange when a very simple program runs differently from Jupyter and the command line -- both Julia 1.10.3. x = 10 # x in the global scope for i = 1:5 x = i # x in the soft scope (inside the for loop) end println(x) # prints: 5 for Jupyter and 10 for command line

Python is a lot of fun for hobbies and experimenting with new technologies because of the huge user community. But if there is any serious number crunching, it is so slow that it will make you commit suicide. It sounds like Julia is better for that. (But every language is faster than Python)

MY MIND IS BLOWNWNWNNW..... HOMEBREWER MARTIN KEEN IS AN IBM MASTER INVENTOR..... I SHOULDVE KNOWN

...I don't know much but, I'm just going to throw this out there: NumPy is a wrapper around Fortran code ...your not going to get faster than that, are you? what kind of performance hit do you take from the 'wrapper?' Nice video, thanks!

It's weird he didn't drink a beer at the end

If you like Julia or Python but you prefer static typing then you may like the Nim programming language, a little known gem!

Thanks for the video!

Let's learn Julia

I no have idea about a program called Julia. It's interesting video, I'm a beginner in that new world about programing.

Is he left handed and writing mirrored or is the video mirored?

Once Julia is used in University textbooks, this will stsrt to grow. So, need to write a very good programming, web application and data science books with lots of excercise for students, then Julia will get popular

Hi I just curious what do you write the borad, with writing from left to right and display also left to right?

how do u write backwards

Weird not hearing about a grain bill in this video

That is easy, modern c++ ;)

0:29 this thing writing on our screen could give heart stroke xD

I tried studying Python and my vision started to blur when the Walrus operator was introduced. I doubt I could debug my own Python program after a year. I really hate the forced indentation means of packaging as much as I hate C's curly braces. Sounds like what was said for these languages was also touted for Java. I guess I'll stick to REXX or Forth. I used REXX to rename files and the performance was dismal with each "address DOS ... " statement. So nowadays, my REXX programs write BATCH programs which are executed as fast as CMD can clear them. Not greased lightning like the big guys but I get the job done under my terms and control. I mainly use these to organize JPGs from digital cameras into a single folder/subdirectory. My programs rename each file with a 4 hex fingerprint prefix and an optional time-date-stamp infix into the filename. Another program traverses the directory tree and moves the files to the parent folder/directory. Someday they will write the HEX file directly which can be burnt into an EEPROM of a microcontroller. Good for implanting a secret copyright notice bypassing the IDE.

Why it's so quiet?

Why this audio is so low?

How the heck do you write backwards!

Julia all the way

The review is flawed, as Julia is capable of utilizing all Python libraries. For instance, if you run a Python-based LLM (AI) locally on an i7 8-core processor, it may take around 13 seconds to generate a response. In contrast, the same LLM implemented in Julia could potentially provide an answer in just 1.6 seconds. This performance advantage is one reason why organizations like the DOD and NASA are adopting Julia for various applications. Additionally, projects like the Next Generation Air Dominance System (NGADS) and future fighter aircraft featuring integrated AI piloting systems are also being considered towards a transitioning towards Julia or another in-house language built from Julia. Rewriting the James Web Telescope from C++ to Julia could yield significant benefits, particularly due to Julia's ability to leverage unlimited core and device access unavailable in other programming languages. Given 100% flex control on every moving piece through the actual manipulate of power flow cut off as fractional and part cycles. With that, Python has no advantage over Julia, which was original built around having its future adopters coming from the Python programming community.

Julia vs Rust, which one do you prefer?

With sustainability in mind it's nice to see an alternative for Python with high performance. The "It's slow, yet fast enough" sratement I often hear from Python developers starts to annoy me a bit. This 'slow-yet-fast-enough'-mindset is killing our planet. Though responsive enough, in a lot of 'sluggish' languages (like also Perl, Ruby and many, many more) too many processor cycles are used and this costs an unnecessary amount of energy and time, and therefore physical hardware.

All I have to say, julia is hella faster than python for solving differential equations.

Its funny how Amazon and their AWS company debunked that Julia was fast. As Python was tested against Julia in AWS and AWS said Python was much faster and even more economical when doing extensive tests with them. Julia takes up most electricity than python when tested in the AWS, which means AWS seen that Julia cost more to operate than Python. AWS and Amazon even created a 5 page website extensively going through each and every language and how fast and feasible they were to run within AWS Amazon services. Python won and beat every language including Java and C#

cool video)

Is OpenBlas worth using? never heard of it before.

You forgot to mention Julia's array is 1-based but Python like most other languages, its array is 0-based.

Did the dude just write stuff on screen in reverse?

👍👍👍

Seems weird not to include R in this conversation.

I can tell you first hand, if you are doing computationally heavy things, e.g., simulating agent-based models, Julia just simply wins against python. It takes far less effort to crank out very heavy scientific computing. Python is what's used when you want to make science to a proof of concept (POC), but isn't even the best for real-world production code. It just ends up taking more effort to just get it to be as performant as other languages. Great for that POC area of work, but falls short everywhere else. Even MOJO sucks in my experience, with even their previous benchmarks proving a lie once you decompile them. Once the ML/AI hype hits, it's gonna be really rough for those who pigeonholed themselves as python monkeys, rather than people are doing serious work with C++, SQL, etc.

Wow he is really good at writing words backward.

Dude: Julia is way more extensible than Python.

It's never important to me that my algorithm gets there quickly, I love slowness. I think it's great that IBM had this video, but it was more of a round about way to say yeah Julia is fast but python can do more.

NICE!

You're very good at writing backwards.

Can you also consider comparing Polar in your future video?

I just hope they stop inventing more new languages. There are so many different syntax to remember. Just stick on the language and keep improving will be much easier.

The way I see it is that, I have been using computers since the days of Atari, and commodore, I have programmed them and fix them too, and all I’ve experienced is pain, and more pain, beginning and ending with, limitations, it is like living in a communist country, with communist programmers, I remember how painful was programming with basic, qbasic and Visual Basic, and with the ridiculous and stupid, and illogical, no purpose limitations Microsoft set with the 64k limit memory access crap. Every single programming language that I have used, is full of limitations, ridiculous error messages, etc, etc, so maybe now with AI will have AI design programming languages on the fly, we also need a new hardware design, a flexible hardware, more like software, programming languages are like religious denominations, and we need to move on with a true programming language. My prediction is this, engineers and programmers days are numbered, THATS just the way it is, AI is moving so fast, there is no escape, my advice to software engineers and programmers is this, find a new skill, cause you/we cannot beat computers at their own game. Why the hell would anyone, knowing what is going in, want to learn another programming language, when programmers will be out of jobs in less that’s, I would say, 2 years. That’s my take. Thanks for the video.

What about with elixir?

The comments are way more enlightening than this video.

Solskjær changed a lot after Man Utd

I literally hate python. I find refuge in julia. But julia made me upset in some ways. One always pays price at initial run, since it it can not be precompiled even though there are several efforts for precompilation.

julia is all about performance unless you're doing something really esoteric such as making a plot

Why make a video of 2 programming languages while showing no code

👍🏻

wow the guy really writes backwards

IBM Technology should work on sound-audio technology. your youtube videos sound are terrible 😁

A “problem” that prevents Julia to grow is the lack of support for…newbies! Python is taught for kids, teens. It’s everywhere. It’s used for practical things like office automation, web scraping, solve problems for regular people and daily needs. Julia’s developers seems to focus only on big tasks, math, engineering…but dont evangelize young people, they don’t advertise Julia as a fantastic general purpose tool. If they want to make Julia get users, get traction, they should invest more in the “grassroots”, not only the math/engineering/computing elites.

Truth about julia is that it's a nice tool but it's not worth it. Python needs something way better go get dethroned

How he is writing in reverse is making me dizzy 🥴

It's a very very easy choice! Python is in everywhere! Julia, well... is not!

Python must be the king in this versus. Women head stakes, they would run away

What?! Come on, Python over all things.

The other day I asked Julia to execute a code , she rejected my request. She said she's busy learning coding in Python! What can I say interns will be interns ;)

ptyhon = wc ipa, julia = neipa, java = crappy commercial lager, c++ = brew like a monk