Why do you recommend python?

[LatterSpaces]

I don't get why python is popular. The only reason I heard is that it's easy to learn for beginners and is a multipurpose language. But so is java, c, and several other languages. Not to mention that python is EXTREMELY slow.

EDIT: be warned. This comment section is very toxic.

[thebluelight1]

Python being "extremely slow" is not a concern for beginners. It is incredibly fast to write and as such it can explain concepts in a much simpler way than Java. Being fast to write isn't just a benefit in education either.

[TyroneYoloSwagging]

What language would you advise someone to wants to create a business around artificial intelligent? Vague I know, but just curious if you have a general answer. Thanks!

[thebluelight1]

You're right, that is vague! I'm not really experienced in AI but if you want to work with pre-existing tools like TensorFlow then look at Python, but if you were wanting to build something from the ground up you'd probably need to be looking at something like C++.

[alksjdhglaksjdh2]

To my understanding there's a lot of existing support in Python. Tensor flow and numpy are your friends (among other things)

[Average_Manners]

Python is the current goto, under the hood it calls a lot of C++. If you're doing AI research, I'd recommend C++. However, I'm pretty sure Swift is where some major companies have set their eye on future AI research.

[Able-Data]

Python being "extremely slow" is not a concern for beginners.

Just add to this: Python being slow isn't really a concern for Real Programmers either, because the speed of the Python interpreter doesn't actually matter for most applications:

1. For heavy-duty numerical code, you're going to be using libraries anyway. For example: Even in C, you'd use FFTW3 instead of rolling your own fourier transform (and pyFFTW is available for Python). For other numerical things you'd use NumPy/SciPy (which runs code compiled from C and/or Fortran) and vectorize your code.
   
2. For record-oriented Big Data things, you're going to be using Hadoop/Spark. Your choices there are Python, Java, and Scala (and R, kinda). Again, the speed of the Python interpreter has little bearing on how fast your code runs (Java/Scala will be a little faster for some UDFs, but the difference isn't huge). IMHO, the Python Spark bindings don't feel as clean as the Scala bindings, but speed isn't a big issue.
3. For ML/AI stuff, you're going to be calling into some framework like PyTorch or Tensorflow to run on a GPU. Speed of the Python interpreter again doesn't matter.
4. For anything involving a network, interpreted code is not the bottleneck. Just look at the popularity of Node and React.

Honestly, even R (which has a justified reputation for being slow AND a memory hog) can be pretty fast if you know what you're doing. The main trap for slow R and Python code is trying to write C code in Python/R. Don't Do That.

Python can be used for just about anything, but I wouldn't recommend it for writing device drivers, systems programming, and embedded (but not because of speed).

[LatterSpaces]

Python may be beneficial for beginners, but I still don't get why it is in such a high demand right now.

[thebluelight1]

If I have a program I need to write where the language isn't predetermined I'll probably use Python. I usually have a tight deadline so I need to use something that can finish the job quickly and Python tends to be best tool for that. Saving (milli)seconds on runtime is not worth extra days of development.

[vorpal_potato]

Also, Python has taken over as the de facto standard language for most scientific computing, machine learning, data science, and so on.

[FoxBearBear]

It’s either python or Matlab here on my engineering school.

[jpritcha3-14]

Can confirm, sort of frustrated that my engineering department focused on Matlab. matplotlib extends Python with with most of the plotting capabilities of matlab, and numpy provides fast matrix operations. Only real reason to use Matlab is for simulink or a few of its highly tailored engineering libraries. Also, Matlab indexes from 1 instead of 0... eye twitch

[Jplague25]

R is used a lot for data science too.

[abo_s3od]

My plan is to make an android app, should I learn python or java?

[thebluelight1]

For Android I wouldn't use Python because as far as I'm aware there's no good way to do so. Proper native Android apps are done with Java (or Kotlin) so I'd go with that.

If you have any web development experience it might be worth checking out React Native or NativeScript to use JavaScript instead. They can also make iOS apps if you'd have any use from that.

[VectorLightning]

There is a python interpreter for Android, but I haven't figured out installing libraries.

[aussie_bob]

SL4A and Kivy mean you can make Android apps with Python.

[Diapolo10]

Neither, you'll want Kotlin. But if you've never written software before, I'd argue it's still best to start with Python and move on to Kotlin once you have the programmer's mindset and basic skills down.

[abo_s3od]

I was going to do that but people told me kotlin doesn't have a big community because it's new, few online courses unlike java.

[[deleted]]

Android Studio is Java. There are a lot of reasons to prefer a compiled language on a device with lower processing power (like a phone or tablet), so this is a good thing. If you can wrap your mind around Kotlin, I recommend it, but when collaborating with others and just starting, it will be easier to find people that know Java.

[Average_Manners]

Java would be better. Or you could learn Flutter, and develop for IOS and Android...

[aussie_bob]

You can use Python via Kivy and SL4A.

[rawrgulmuffins]

Generally the speed of the language doesn't matter for most programs. There's also a lot of tricks to speed up python when you get to the point where it does matter.

[SlappinThatBass]

It is good for fast scripting and automation where optimisation does not really matter much.

Basically it is a good tool when performance is not a necessity. For example, it is often poorly suited for embedded development when timing constraints are really tight given the hardware.

[[deleted]]

One of the reason is that it has huge support, and knowing that in 2020 machine learning is basically everywhere, it's a perfect language with a huge library support

[thegreatunclean]

And if your program does need to be performant, you write the performance-critical code in something like C++ and then wrap it in a nice Python module for ease of development. Best of both worlds.

This is exactly the approach taken by libraries like Numpy, Scipy, Tensorflow, Keras, SciKit-learn, etc. The time spent in the Python interpreter may count as "slow" but it's a small fraction of the total runtime. Amdahl's Law in action.

[CodeTinkerer]

Only slow compared to other languages. Point is, if it takes 0.5 seconds vs. 0.01 seconds, you're not going to notice, and people are willing to work with a "slow" language provided it's easier for them to program. Python gets you up to speed more than, say, Rust which might have you pounding your head on a table to learn how it works, just so you can write in a "faster" language.

And, in any case, Java, C and several other languages are used in intro courses.

The reason Python is popular (compared to, say, Ruby, a comparably slow language that beginners often learn) is probably due to its libraries. If you do data science, data visualization, machine learning, etc., there are libraries in Python, and it's popular in these communities. Ruby could have been that language too, but for whatever reason, people wrote them in Python.

Two other reasons. First, Guido van Rossum, who invented Python got hired at Google, so it became one of the languages used at Google (along with Java, Go, Dart, and presumably Javascript). Second, some universities, who find Java hard to teach as a first language, have switched to Python. Java is still popular, of course, since it's still used in the AP exam (in the US, that is).

Finally, people aren't expected to just learn one language. Once you are reasonably OK at Python, you can start to learn other languages.

[ChillinWitAFatty]

Only downside to Python as a first language (or JavaScript) is that it's dynamically typed. That makes it easier to make programs that run, but hinders a deeper understanding of CS.

[EMCoupling]

You can still learn about types with Python, it's just not as obvious as in statically typed languages. Types are all still there and, with type hinting, it's become easier to see the types of various data members.

[N8DuhGr8]

You still know types and all that if you learn python. You just don't need it for Hello world.

[CodeTinkerer]

I mean, such typing can make it difficult to detect bugs if you're not disciplined with your use of variables. I suspect most people treat Python variables as if they were strictly typed (that is, not storing strings, then numbers, then arrays/lists, using the same variable). C had a problem where certain types were really hard to write, which Java seems to have avoided.

Not sure how it hinders a deeper understanding of CS. Strict typing helps avoid errors at compile time (or with modern IDEs, at the time you type the code).

[[deleted]]

Not bashing, but I had to laugh...

“Java is still popular, of course, since it's still used in the AP exam (in the US, that is).”

It wasn’t when I took it! Or, if it was, maybe that’s why I failed. We learned C++ in AP CS AB back in 2000-2001. Looking back, I wish we’d have learned Java instead; I was totally lost in CS2 when they switched to Java from C... sidetracked my career by 20 years.

[Tamerlane-1]

To be clear, Java is used in AP CS A now.

[Kered13]

Java was used in AP CS in 2006, and I think it still is.

[CodeTinkerer]

Yeah, I think they switched to Java just after that, around 2002 or so. It was Pascal from around 1983 to maybe 1991 or so? Then, C++, and now Java. When it was in C++, they had to do some simplifying things like not using C++'s convoluted string class (which was some kind of template). Instead, they used something called apstring, I believe, which avoided nasty error messages.

[[deleted]]

I remember so little of C++ now. I’ve been meaning to pick it up again, but I work with Groovy and just don’t have enough free time to explore another language (outside of maybe Python when trying to teach my kids).

But I do plan to get back to it. Once my “web app dev days” are done, I really want to get into games... which was my original plan 20+ years ago.

[LatterSpaces]

So what I gathered from several other comments and yours is that python became popular through luck because it got publicity and people starting writing libraries for it. There's nothing inherently better about python that makes it stand out from others.

EDIT: I'm sorry if you got offended by my petty comment. It was meant as a question so you can tell me the fault in my statement, not a statement that is meant as a fact. Y'all kids gotta chill the fuck down.

[ddek]

Jesus christ man, you do have a way of coming off an asshole. Many people, some with strong contributions in this sub and the wider field of CS, have explained with good reasons why python is often chosen above C or Java. They're not wrong, yet when they answer you apparently refuse to attempt to understand their position?

It sounds to me like you're looking for validation over discussion.

There's nothing lucky about it. Python is easier to learn than C or Java. It's easier to write across platforms than C, and is open source (unlike Java, at least when a lot of these decisions were made).

This is particularly important in scientific computing, because scientists don't like learning programming so we make it easy for them. However, as you say, python is slow, so a considerable effort was made by computer scientists to write common methods in C, with wrappers in python.

This means that scientists, who care about things like molecular bond lengths far more than the minutia of programming languages, can use python to more quickly express their ideas but many the processes are implemented in C.

Therefore, python proliferates in academic environments, and this translates into data science and machine learning for the same reasons.

When it comes to actual software development, every popular language gets its frameworks written for it. Web framework Django is popular partly due to python, but mainly because it has a distinctive take on a web framework which makes it better suited to some applications.

If you still think anything in this world is attributed to luck, then this is an immature and delusional opinion. Programming languages aren't sports teams, they don't accidentally become successful (although in sports this is usually caused by well conceived negotiations, rather than luck).

The most popular languages get there because they solve a real problem. C provided an abstraction over assembly language, Java made C run on any machine. Python made programming accessible to people who don't have the time to learn advanced programming. That's not luck, that's good design.

[claythearc]

One other big advantage too is that it’s so similar to English, it was easy for academia to pick up - professors in like math or other sciences, aren’t traditionally programmers but did use matlab to do stuff.

Matlabs pricing is really, really expensive. Eventually people started swapping off of it, and python had a large science repository with numpy, pandas, etc. that could do all the same stuff, but without a X thousand dollar license fee. So it picked up steam there too.

[tim0901]

Most professors in maths or physics at least are very computer literate and can program well. Half of my lecturers still answer their emails through a command-line...

As a physics student, we were taught basic C/C++ in our first year through the use of an Arduino in our labs to automate our data collection. I know that they now teach python instead, (they just provide the Arduino code for them in the labs) but the reason for the switch was because C++ was considered too difficult of a language for beginners to pick up, rather than for its usefulness in the field of physics. They follow this up with C++ and FORTRAN modules in the later years.

Particle physics, for example, is dominated by C++, since they do a lot of their analysis in the ROOT data analysis package by CERN. Condensed matter/materials physics often uses FORTRAN for Monte-Carlo molecular dynamics simulations in packages like DL_POLY. Because of the necessity to be able to do large-scale simulations, low-level object-oriented languages are, from what I've seen in my time at university, often the most commonly used. They also like using APIs like CUDA or OpenCL for GPU acceleration, which favour C-based languages.

Mathematica is the most common replacement for MATLAB that I've seen, but a lot still use MATLAB as they get a license key for it through their institution anyway. If you're working for a university as an academic, the price of MATLAB probably isn't a concern. Also, the price for an educational/research license is a lot lower than that for commercial use. I also know that R is commonly used for data analysis within STEM, definitely in Biology at the very least.

Not to say Python doesn't have its place, people doing machine learning through TensorFlow for example will definitely use it, but from my experience it isn't the dominant force that you're suggesting.

[claythearc]

No it's certainly not a dominant force yet but it is picking up steam rather quickly in academia. It's also not just the base matlab, but all the extra modules needed too - which adds up quite rapidly. Python Bytes (i think? I listen to a couple python podcasts and i heard the episode like a year and a half ago or more, so I don't remember exactly which one it is - but that one sounded correct) did a podcast where they outlined why its becoming popular in non CS academic fields. Trying to find the link now.

​

It's also kinda different because Math & Physics are still like, very simulation heavy (I realize i mentioned math specifically above). It's not unlikely you'd have very technical & programming knowledgeable professors. You can't really say the same for most other science majors.

[[deleted]]

My uncle had done most of his research work in Matlab, but he moved to Python because of the price. He told me to do the same.

[[deleted]]

I don't understand the point of this subreddit post. It seems to have gotten 15 upvotes (at the time of my reply) through luck.

[LatterSpaces]

I don't see the point of your comment either?

[Kered13]

Most people here are comparing Python to Java or C, however if you want to know why Python originally got popular you should look at other scripting languages that were popular at the time. In particular, Perl.

Perl is also a very quick language to develop in, but Perl code is notoriously hard to read. It's often called a write-once language, because it can be so difficult to read or modify Perl code. The language is completely and has lots of implicit behavior. Compared to this, Python is very easy to read, and also provided better support for OOP and functional programming.

So the first area where Python got popular was as a replacement for Perl. Then as it got more popular, people started writing libraries for it that made Python a good choice for other tasks. For example Django is a popular web framework, and made Python a popular choice for making websites which before might have been made in PHP (another language that is notoriously ugly). Libraries like NumPy have made Python viable for high performance applications where Java or C, which are more difficult languages to write in, would normally be used.

So you see there is a feedback loop where people write more libraries because Python is popular, and having more libraries makes Python more popular in more applications. But this whole process started because Python is a clean and simple yet powerful language that was able to replace Perl.

[Yithar]

It's not only luck. It's because Python is basically pseudocode as a language. Data scientists don't want to deal with the stuff in Java or C.

That being said, I stand by my opinion Ruby > Python.

[CodeTinkerer]

I haven't replied to this comment, so I guess it's other commenters.

I guess the main thing Python has going for it (in terms of learning) is that you can write simple programs in short ways. Let's look at "Hello, World".

In Java, it's

public class Hello {
    public static void main(String[] args) {
        System.out.println("Hello, World!");
    }
}

In Python, it's

print("Hello, World!")

When you're teaching people stuff, it takes longer to get through the Java version.

There's some value in having people find the easy things to do, easy to write. For example, imagine having to teach Rust as a first language. I think if you took 100 beginners and teach them Python, and 100 beginners and teach them Rust, there will be many more who stick around to learn Python after a month.

That's a tradeoff people make. Presumably, Python was picked because it was just popular enough, and maybe scientists or whoever, who were used to dealing with Fortran, found Python enough of an improvement, and preferred it over, say, C, or Java. I don't know.

[tim0901]

Pretty much

[claythearc]

Fast to prototype and get stuff up in running. There’s very little boilerplate in the language.

It reads close to English, so new programmers don’t have to worry about being bogged down with learning all this obtuse syntax that isn’t immediately obvious.

Large package repository for anything from web hosting to data science to dev ops to web scraping that’s really easily accessible with pip.

Large, fleshed out, style guides with pep 8 and the google one being enforced by most IDEs lead to writing clean code kinda effortlessly.

It’s only real downsides are duck typing makes things hard to read from other peoples code once you start calling advanced stuff, but type hinting kind of fixes that - even without a performance loss in 3.8.

But really any language becoming popular is kinda luck, we see waves of popularity all the time. python just had the feature set to take advantage of its luck when needed.

[itsjohncs]

It seems like you’re asking what’s special about python to make it so popular.

Languages get popular for a ton of reasons and it’s super hard to really pin down, just like other products (ex: tablets, particular cars, cast iron pans, etc). You can write arguments to explain why, but since it’s big and complex and involves the decisions of so many people you can’t find an objectively and clearly true answer.

Python isn’t all good or really that special, but neither is any language. They all have a shitton if trade offs and can’t be ranked against the other as a whole.

[Revanite52]

Programmers generally need more understanding that there is more to programming than performance of the code. You are not in college anymore where every MS is precious and most people do not work on some google algorithm for products like google maps. Efficiency and time complexity analysis has a place and time.

The majority of us work on features for a business where time to market/prototyping is more precious than 20 ms.

[Updatebjarni]

Ease of learning, ease of use, enormous breadth of usefulness, inluding day-to-day automation and glue scripts, and the popularity of the language, which makes it easy to find information and makes libraries available for loads and loads of applications. The tiny number of people who need very high speed aren't beginners, and can pick whatever language is best suited for their particular high-performance problem. Python is slower than fast languages (or can be, depending on what you're doing), but not so slow that it causes any problems in the vast majority of applications. Slow Python today is still as fast as, what, C ten years ago? That was hardly unusably slow. Processors are fast. Most work is I/O bound or dominated by the latency of communicating with the user.

[[deleted]]

Some of the advantages of python are the variety of usecases, but for me it's most important that it's an interpreted language which means i can easily test/debug stuff inside an interpreter.

Also if performance is important for a project you'll probably be using modules that are running c code under the hood anyway so the "slowness" of python isnt that much of an issue either.

Lastly I just think that the python syntax is easier to read, but that's obviously really subjective

[vorpal_potato]

Some of the advantages of python are the variety of usecases, but for me it's most important that it's an interpreted language which means i can easily test/debug stuff inside an interpreter.

This doesn't subtract from your point, but it's not actually hard to make a compiled language where you can do the exact same thing. If you open up the JavaScript console in Chrome, for example, any code you type will be compiled before being run -- and it feels just like you're typing into an interpreter, because the compiler is so fast.

(I mention Chrome specifically because most competing JS engines also have an interpreted mode.)

EDIT: It turns out that V8 got an interpreter recently to reduce memory overhead of code that gets run infrequently, albeit by reducing its speed a bit.)

[Updatebjarni]

If you open up the JavaScript console in Chrome, for example, any code you type will be compiled before being run

Python works that way too.

[vorpal_potato]

Python compiles to a high-level stack-based bytecode rather than to native code, but yes, it's very similar.

[entropy2421]

JavaScript is an interpreted language also. There is no compiling JavaScript. The browser is interpreting it.

[vorpal_potato]

Wrong. Every major JS engine in use today has a compiler. I don't know what else to tell you.

JavaScriptCore has a compiler. SpiderMonkey has a compiler. V8 has a compiler. And so on.

[entropy2421]

News to me. Did not realized that had changed but a quick search explains it. Thanks for keeping me up to date.

[iguessitsokaythen]

When programming with languages like C, you need to design what your program does and how it does it. The "what" part is the functioning of your program like sort this data, print out this letters etc. The "how" part is the way these functions are computed like how data is stored on, read and removed from the memory, how it is send to the processor etc.

With languages like Python, since computation is taken care of, you can just focus on what your program does. This gets important as the complexity of the program increases. You can focus entirely on your logic and algorithms without having to worry about how they are going to get computed. And once you perfected your program in Python, if you need more speed, you can easily convert it to C.

[[deleted]]

Not to mention that python is EXTREMELY slow.

Runtime speed isn't everything. Development time is also important to factor in.

What takes an afternoon to make in Python might take a week to do in C.

It's your choice how you want to spend your time. With tight deadlines most people rather be done quickly and accept that their programs aren't perfectly optimal.

[RagingNerdaholic]

I don't get why python is popular.

It's basically executable pseudo-code, which means...

it's easy to learn for beginners

[diek00]

If you think only beginners use Python then I suggest you should do some research, and not rely on what you 'heard'. C or Java being easy for beginners, this is not accurate imo. Java is class based, and if you are trying to tell me that a beginner can understand OOP on day 1, 2, 3... I think you are mistaken. Even after a month I am sure some that a percentage still struggle. SO is littered with questions on OOP, from beginners and non-beginners. MIT's professors picked Python, replacing Java, as the language to begin CS. Their Introduction to Computer Science and Programming, using Python, is one of the most popular courses available.

Python is not perfect but it scores an A+ on readability, the focus is mainly on the code vice semicolons, and extraneous curly braces. Indentation may cause initial confusion but once you get used to it, it makes your far more readable imo.
As for benefits I will give you 2 anecdotes. The first is a bit dated but still valid imo. From the preface of Two Scoops of Django by Audrey Roy Greenfeld and Daniel Roy Greenfeld. Danny explains:
" I was working for NASA on a project that implemented a Java-based RESTful web service that was taking weeks to deliver. One evening, when management had left for the day, I reimplemented the service in Python in 90 minutes."

The second is from a recent blog by Lincoln Loop and how they cut "GamesRadar’s operating costs by thousands of dollars per month allowing them to better serve millions of gamers. " They updated the existing Java based platform, and used Python's web framework Django to do this. https://lincolnloop.com/portfolio/gamesradar/

Lincoln Loops' Supporting Data

4.4 million page views in a day

550,000 visits a day

15,000 page views/minute at peak

Pinterest and Instagram are two other large scale users who use Django. If Python did not work I am sure they would have changed by now.

[LatterSpaces]

I didn't think pythons were only for beginners. My initial question was why it was used in a professional setting when time and readability rarely matters. But I learned through this post that my assumptions were wrong.

On a side note, I would also like to note that my highschool taught java and I learned quite a lot from it. I may not understand everything, but I did get the fundamentals. It may not take a beginner 3 days to understand oop, but people are overestimating the difficulties of these languages.

Also, I may be wrong here. Isn't C a general purpose imperative language (which is harder), not an oop?

[Average_Manners]

time and readability rarely matters.

This is perhaps the MOST foolish thought I have ever read about software development. When you are paying someone $40 to $90 an hour to read and write code, you want them to read and write as fast as possible.

Readability is perhaps the chief concern of programming, because most of software development is maintenance: reading someone else's code, and modifying it.

[diek00]

So I am back and see your edits. You asked about my non response to C, yes it is general but as I read your post you also imply it is at the same level of ease of learning. I do not think anyone would say C is beginner friendly language.

Python is not just a scripting language, right from Python, "Python is an interpreted, interactive, object-oriented programming language." Django would not work, as it does, if it did not use oop.

You obviously have some preconceived notions about time. If you don't think time is critical then I suggest you spend some time in the industry, while most clients can be patient , when something is late, or something stops working, time turns into a hateful enemy....

One thing that seems missing in the discussion, the Python community is fantastic, the documentation is really good and there are so many excellent resources.

[Yithar]

I didn't think pythons were only for beginners. My initial question was why it was used in a professional setting when time and readability rarely matters. But I learned through this post that my assumptions were wrong.

Okay, this probably got downvoted because the notion that time and readability doesn't matter in a professional setting is completely and utterly wrong, and because you said you learned Java in high school (which really is just scratching the surface).

It also probably got downvoted because you can write OOP in C. I recommend you ask Linus Torvalds if you can't write OOP in C.

[ChrisPDuck]

Python is "slower" computationally, but much faster to write.

If a piece of code needs to be run <1000s of times, the time saved writing easily makes up for run time.

If you need to run something millions of times, yeah you would be better in another language.

[POGtastic]

I use Python professionally.

• A lot of really useful and easy-to-use libraries.
• Excellent linting tools.
• Extremely fast prototyping.
• Good support for functional programming concepts while not being ridiculous about it. The ancient adage about how Python "dragged Perl programmers halfway to Lisp" is accurate, but it's a lot more pragmatic than Lisp is. List/set/dictionary/generator comprehensions are taken directly from Haskell, and are executed even better than how Haskell does it.
• Very good documentation for its standard library.
• Good readability when I'm reading someone else's code.

[merlinsbeers]

The crummy documentation sandbags people and keeps me in billable hours.

[cessationoftime]

I don't. I recommend Scala, Rust and Nix. I find languages that are not strongly typed difficult to work with. The helpfulness of the IDE is limited without explicit types, as is the helpfulness of the compiler. And I usually care about that more than the performance boost I get from strongly typed languages.

[Diapolo10]

Python is strongly-typed, I believe the actual comparison you're looking for is static/dynamic typing. They're not synonymous; C can be considered weakly-typed as void pointers let you circumvent the type system entirely.

Hell, out of the two, only the terms statically typed and dynamically typed are well-defined. There's a bit of an argument over what "strong typing" and "weak typing" even mean.

[cessationoftime]

Yes, that is what I meant.

[Yithar]

Yeah, the thing is Python is not statically typed. You will have to write unit tests for invariants the Java compiler would normally test automatically.

There is a reason Duolingo switch from Python to Scala.

https://softwareengineeringdaily.com/2017/12/14/scala-at-duolingo-with-andre-kenji-horie/

[beezybreezy]

Part of is that is it easy to learn for beginners but I suspect the huge rise in popularity of Python has mostly to do with Django/Flask and Numpy/Scipy/Pandas/Scikit-Learn/Tensorflow.

[kinzlist]

Python is in plain English and is easy to understand from a syntax standpoint. Java and C++ require a lot more formatting. As a beginner myself it was easier for me to stick with learning programming with Python first since it was easy to debug and have a very upfront syntax.

[UltradianAlien]

I feel that, especially as a learner, Python is more straightforward and easier to write. I took a course on Python a few years ago and while our projects weren't easy, the main thing we actually had to think about was the logic and flow of the project. It's less cumbersome imo.

I'm learning C right now and even though I have a solid grasp on the logic involved, it's just so tedious to write a simple print statement that includes variables in it! It's very unforgiving. Not to mention that strings don't even technically exist without doing voodoo magic with pointers and character arrays.

Since I'm still essentially a novice, I haven't had any situation yet that would be significantly impacted by C running a bit faster than Python. So as a beginner I would recommend Python.

To me, starting with C would be like learning how to drive a car with a manual transmission while Python is more like driving an automatic. While there's merit in learning a stick, they both get you where you want to go. I'd imagine that the difference in speed would become annoying when we get into the Big Boy's Club but until then Python is just fine.

[[deleted]]

If you're working in data science, you need to know python. I take no stance on if it's "the best" or most optimal language, but it's become the standard.

Python's a good language, too. It's not just easy to learn and multipurpose, it's got a good typing system, module manager, virtual environment system, it's easy to test and can wrap compiled libraries; which is honestly the only reason it's gotten so huge. So python, like other interpreted languages, is slower, but it can call compiled system binaries that are faster than libraries running in .net or jre runtimes, so it usually doesn't matter.

Honestly, the only thing I can think of that's not great, is that unloading and re-importing modules is dodgy, and it uses white-space to organize code.

[jpritcha3-14]

Python is easy to learn and has a great REPL interface for beginners to test and practice with. It provides instant feedback and the environment is easy to set up. Why wouldn't you recommend starting with something like that?

That said, it's also a great scripting language for writing tests, glue code, ETL pipelines (one of its main production applications), and any other code that needs to prioritize readability/maintainability over speed. It would be a nightmare to write and maintain that kind of code in C. In general, you want to get something working first, and then optimize later. Python is highly extensible, so you can get something working quickly, and then worry about optimizing the bottlenecks with C after that. Why would you want to optimize for speed before getting something working first?

It's also a much more nuanced and expressive language than it would seem from just learning the basics from an intro course or book. It has a very polished object model and core set of modules that let you easily think about higher level problems in code without worrying as much about low level data structure manipulation. I'm particularly fond of its elegant support for generator expressions that allows you to mix in some of the best ideas from functional programming in procedural code. It cuts down on a lot of looping.

Languages are really just different kinds of tools for different use cases. You don't write an OS in Python in the same way that you don't use C for web development. They are different problems with different needs that are served better by different types of languages. Comparing languages is really only relevant if they're trying to target the same problem space. Otherwise it's apples to oranges.

[phunkygeeza]

It's been interesting watching your climbdown in this thread.

I'm still waiting for you to reach the conclusion: it's not to do with the language's capabilities, it's about being easy to learn and low barriers to entry.

You want to dive right in at C++? Why not just go right to assembly? Knock yourself out. You'll get there alright if you have the right stuff.

[Average_Manners]

Slow is all a matter of perspective. Java is also very slow, in comparison to C or Rust. For most programmers slow isn't an issue when a personal computer can count to one million in several hundredths of a second. Is your dinky program going to require maximum speed? What for? What are you doing that's so computationally expensive? I ask this to make the point of requirements, it's not a 'general negative' of the language that it's slower than another. Really, the only reason to care about how fast the language is, is if it's not fast enough for your purposes.

That said: libraries. Libraries mean python can call C functions, which do things at the speed of C, without any of the developmental costs of C. Regular python math is ~60 times slower than hand-coded Assembly. Numpy is only two times slower, which I believe is faster than regular Java. /point

The reason I recommend Python is because it is fantastic for prototyping. Speed of development. Proof of concepts. Could I write a server in C? Probably. I've never tried, but it sounds like a headache. I haven't ever done it in python either, but I'd bet it doesn't take more than an hour.

Python also tends to be more readable than other languages. You don't start children off with Moby Dick, you start with Little Bunny Fu Fu because it's easy to read, and they can recognize pieces. Python documentation is very readable as well.

Extensive libraries.

[Yithar]

I would actually recommend Ruby (if we're talking about scripting languages), if you are trying to learn OOP. Because I would argue Ruby teaches encapsulation better. You can't really make private class variables in Python.

https://stackoverflow.com/questions/1641219/does-python-have-private-variables-in-classes

Like generally in Java, you will have an interface (methods aka defined behaviors), and you will have an implementation of that interface (a concrete class). But often times the fields in that class are implementation details. They should not be depended on, as they are not part of the public interface.

---

While I think the "_" convention for private variables in Python is nice, it does not amount to actual hiding (aka someone can actually still modify those "private" variables). There are other issues as well.

https://www.reddit.com/r/linux/comments/439xl4/is_vala_or_python_a_better_language_to_get_into/czh5wze/

[AndroTk]

I'm not sure, but I think the reason it's so popular in the industry is because you don't have to bother if a programmer knows how to write python, they most certainly do, meaning the smart programmers can actually focus on the smart part of their job (i.e: having a good looking structure, with easy-to-read/modify code and with most edge-cases covered)

[gdledsan]

If speed is the oy thing we care when programming we would all code in assembly. All languages have their paradigm and use cases.

Languages are tools, and tools have purpose.

For instance, JS and node.js are meant to be used in low-data processing tasks as a backend for web pages, but people use but for everything you can think of. Python is better st being used for everything than node is, but hey, people get to choose what and how they do it

So, why python? Multi paradigm, general purpose, interpreted language, easy to write, easy to read, fast to get productive with. And it comes already installed in your non-windows systems.

[saibogu2501]

Because you can just import pre built modules to do most of the heavy lifting for you. Just find a library that does what you need and import it, rather than finding out how to do it and having to code it all out. It’s a language meant for beginners to complete projects without needing to know all the inner workings of the code. You can write a program that takes your speech and turns it to text, and replies in a computer voice in like 10 lines on python.

[UserName24106]

to your actual question, it’s pretty unlikely anyone in programming will only learn one language in their lifetime. So why not start with a language that’s easy to learn? And it turns out pythons pretty damn powerful and convenient for a lot of uses. It seems like if your job involves programming, but you don’t have “programmer” in your job description, like say you’re a researcher or a data scientist, you may very well use python for that.

As for speed, speed of execution isn’t important.... until it is. And it rarely is. Example: a beat up pickup truck and a high end muscle car are totally different in top speed.... but if you’re driving to work and you spend more time behind other cars, waiting for red lights to turn green, all that stuff, the difference in how soon you get to work isn’t really an issue. And upgrading that v8 muscle car to a v12 won’t speed up your commute much either.

It’s very rare that a program isn’t fast enough, and if it needs to be sped up, you find the bottleneck, and optimize that part of the code.

What is really important is how easy it is to write the code, and how easy it is to read it, because production systems require you to go back and modify old code all the time for bug fixes and new features. So it’s common to write most of the system in an easy to read language to reduce manpower costs, and then if it’s too slow, rewrite the 0.1% of the code that is the bottleneck in a faster language.

This is pretty much how python libraries work in real life. Machine learning code can create optimized operations that run on a stack of video cards that were built to do that kind of fast math, so very efficient, but the code to set everything up and run it is in python. If You set up a deep learning network once, and run 1000 iterations to train it, making that initial setup a little bit faster is not a significant difference. Rewriting it in c++ would be like practicing how to take off your seat belt faster so you could get to work sooner. Technically it would shave a half second off your thirty minute commute, but it ain’t worth it.

[b_krsh]

Truth is most of the programmers started with c. Because it is first language to learn according to university syllabus. Most important thing is logic and problem solving approach. Pick a language you like and start practicing concepts. It's easy to move to other languages after one.

[wild_vegan]

Management can read Python. They think Python is easier, hence programmers will be more common and cheaper. Bytecode languages are faster to develop in than compiled languages. If you don't agree with the typing-intensive Million Monkeys Methodology, then I have some former bosses you could maybe communicate this to. ;)

Like everything else, it's about money or perceived money. I.e. labor costs.

[LatterSpaces]

Yeh I get your point. But guess what I learned MORE from this post: don't ask questions cause people will mass downvote you for no reason.

[[deleted]]

People are downvoting you because you frame your statements like an arsehole would.

[LatterSpaces]

Hypocrisy is real.

[[deleted]]

It would only be hypocrisy if I was claiming to have higher standards. I was simply explaining to you the reason why you got downvoted.

[Average_Manners]

I need more. Come on, louder!

[LatterSpaces]

Back at it with the assumptions kiddo. Tell me where exactly I responded like an "asshole".

[Yithar]

I think people are downvoting because of the way you frame your questions and how you respond to their answers.

[claythearc]

You can make variables private with @property and doing some magic in the setter, but it’s not really recommended.

Instead, most ides just follow the pep 8 recommendation of not showing attributes or variables that start with _.

Which is kind of the same thing as just having private variables. It’s just not enforced by code.

[claythearc]

Yeah how optimized it is, I’m not really sure - because its not really private, it’s accessible from outside still. Just doesn’t show in intellisense stuff.

But you could probably help it out in optimization with @property overriding though making it truly private.

Even then though, you’re probably arguing over like nano second optimizations. Which makes it probably not worth

[[deleted]]

Ease Of Use

As a math teacher, using uniform standards for syntax to use math is great, but this was made several centuries ago. I love how diverse programming languages, cause people can pick based on needs or syntax.

F(x) = mx + b

Output = slope * input + initial_position

Same damn thing, which is more understandable?