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I had assumed that there would be an easy to find list of programming languages sorted by the number of libraries that they have. I have been able to find no such thing. Is there any way to find or make such a list? Specifically, what would be the top 5? I understand that this would require defining what is and isn't a library, but I was shocked to see that I couldn't find even as much as an attempt at such a list.
Check the Website http://www.modulecounts.com/
The top three are:
JavaScript
Java
Python
Please Note - Having more libraries Does not mean it's better.
It strongly depends on the use.
I rank programming languages by their efficiency to solve problems in either a general case (otherwise unspecified) or in a specific domain such as:
Robotics
Mobile computers
Mathematics and Science
Web development
Embedded systems
Systems programming
Network and infrastructure programming
Database programming
Consider the following. According to IEEE, the popularity of a programming language is measured by quantifying these indicators:
Google Search, number of hits for the programming language
Google Trends, past year to date trend for programming language
Chatter on Twitter about the programming language
New and active repos' on Github for a particular language
SO
Hacker News
Demand on career builder and IEEE job board
The result is this
R and javascript/typescript are in the same list. However, they are primarily used in different domains. This does NOT mean that R cannot be used to write a solution that would typically be written in javascript, it simply means that it is the wrong tool for the job.
A little more detail on this.
General Purpose:
Python ~ Easy to use, easy to learn, known for data science.
JAVA ~ Popular for enterprises and client/server topos' since the intro of the concept of JVM (run code on any architecture).
C++ ~ Fast. I mean REALLY FAST! game engines are built with it.
Embedded Systems and Programs:
C ~ low memory usage, small file size. Every microcontroller in every car built after 2011 probably has a C program running on it
Assembly ~ but not so much since one needs low-level microprocessor knowledge
Rust ~ very promising because of memory leak handling.
Web:
Javascript ~ every dynamic website has js in it
HTML ~ I don't understand how this was missed
IaaS:
Golang ~ nothing even comes close to Go
It is important to understand, that the problems within the domain, are what necessitate the development of a new programming language library if one does not exist already. And not the other way around.
One can also argue, that continual improvement of technological standards, leads to new, and improved libraries at a faster pace.
This is a bit difficult question as it depends on what do you count as a publicly available library. One way is to check most used languages on GitHub. Checking out The 2020 State of the OCTOVERSE, the top three are:
JavaScript
Python
Java
I'm not sure there is any plausible, comprehensive and credible statistical data on which languages have the most publicly available libraries, that covers, at least, substantial number of programming languages (not even talking about all languages).
Therefore, your question will, most likely, lead to opinion based answers, and you should avoid asking such questions on Stack Overflow.
The only reliable resources that come to my mind, and that will give you the data about popularity of the programming languages (not publicly available APIs) are Tiobe and Redmonk.
I'm a web developer mostly working in Ruby and C#..
I wanna learn a low level language so i dont look like an ass infront of my (computer science expert) boss.
Ive heard a lot of purist buzz about how assembly language is the only way to learn how computers actually work, but on the other hand C would probably be more useful as a language rather than just for theory.
So my question is..
Would Learning C teach me enough computer science theory / low level programming to not look like a common dandy (complete tool)?
Thanks!
Daniel
Thanks guys!
Some really great answers,
I think i'll learn C just to get a grasp of memory management, but i think your right and i'll be better off studying more of the languages i use!
First learn the actual theory. Learning C's syntax means nothing if you can't do anything meaningful with it. After you have a solid grasp of how algorithms and data structures work, this knowledge will be appliable in most languages you'll probably use.
If you're planning to work in C# and Ruby, I don't see the point in learning assembler just for the sake of doing so.
You'll be fine learning just C since it's C.
You can do "real programming" in any language, as long as you do it right.
Would Learning C teach me enough
computer science theory / low level
programming to not look like a common
dandy (complete tool)?
You're using C# which can perform unmanaged pointer manipulation, not too far off what you can achieve in C++ land. For instance, games can be successfully programmed in C#, although most games will be C++.
Assembler is basically moving bits of memory around and sometimes doing a bad job of it too if you don't know what you're doing. C++/C compilers create quite good assembly code underneath, so why would you do it yourself unless you had to write low-level driver software. The only bit of assembler in our 2,000,000 lines of mixed C++/C# code is to detect VMWare.
I don't think in this modern age and given your description of your job there is much call for you to know about how many registers you can use on your processor. By all means learn C++, but as mentioned before, learning syntax is not the same as learning how to apply it.
At a minimum learn and understand patterns (Gang of four), OO design, understand the implications and benefits of different testing methodologies and the impact of all this on business costs.
Learning C will get you all the information you need and be able to accomplish things in a reasonable time.
I suggest you do a few meaningful projects in C, then one or two in an Assembler dialect, maybe for a Microcontroller or specializing in SSE/MMX.
In the end it all comes down to opcodes, registers, and addressing modes, of which C teaches you absolutely nothing. However, assemblers are tightly coupled to their platforms; learning how to write assembler on x86 won't help you much when you work on a Sparc or PA-RISC box.
C really isn't going to teach you much that other languages won't in terms of theory. The thing about C is that it doesn't provide many tools or abstractions beyond naked pointers and byte streams. You have to roll all your own containers (lists, stacks, queues, etc.), and if you want them to be generic, you have to figure out how to separate the code that needs to be type aware (assignments and comparisons) from the general algorithm. You have to manage your own memory. Text processing is a pain in the ass (C doesn't even provide a dedicated string type).
Is that something that would be useful to know for your day-to-day work, or to impress your boss? Maybe. I'm not sure how you would apply that knowledge in your C# or Ruby code, which operates in a virtual machine (as opposed to native binaries generated from C).
You want to impress your boss with Computer Science knowledge, read up on Turing machines and Markov algorithms.
I don't think knowledge of Assembler would make you a better Ruby / C# programmer.
You can go as low level as writing to a disk using a magnetized needle, but if your programs aren't working or are insecure, you wouldn't have gained anything by it.
Learning the syntax of a "new" language won't assist you in gaining more knowledge of the depth of programming.
Real programming is not about a particular low level programming languge. To understand how a computer works it would be not bad to know some CPU instructions and how the hardware processes them.
To become a good programmer it is absolutely not necessary to know how the hardware works, except you want to program hardware.
I wouldn't worry about looking like a fool in front of that boss if that's the criteria your boss has for not being a fool.
C and Assembler isn't the best languages if you want to learn computer science. As you know Ruby and C# I guess you know some object orientation.
"Real programming" works the same in every language and that's what you should really worry about. That being said, working up something in C is a very useful exercise/
Learning C won't necessarily teach you too much about how computers work, but it is a good access door to that, considering that it is still the language of choice for system programming.
Learning ASM is of course useful as well, but it's probably uncalled for if you want to apply it to your job. It might teach you a few useful concepts though, or at least help you get a better understanding of how CLR works (or in general, how bytecode compilation and bytecode-compiled code do their stuff). Maybe you could try learning ASM for an older/simpler platform; there's still a heavy Atari 2600 scene around, and due to the platform's inherent limitations, some of the hacks they do to squeeze some extra functions in a game are quite awesome. The modern x86_64 architecture is pretty complex and somewhat hairy, although that's more of a personal opinion than an actual fact. Learning to use a microcontroller might also get the job done, but be warned that many (most?) use a Harvard architecture (i.e. separate program and data memory) which is different from that of a typical general-purpose CPU.
ask your boss first, than do exactly what he tells you, finally ask again for feedback and review of the exercises you will do. act accordingly. repeat until he says "you now know more than me".
this is the more efficient way of exploiting the expertise of a real expert you have the luck to have, and will leave extremely positive impression forever.
it will be as difficult as learning C or assembler alone in your spare time.
I wanna learn a low level language so i dont look like an ass infront of my (computer science expert) boss.
This is like so true in many aspects, I learned c++, and haskell for similar reasons, I have no regrets since they taught me many things, but I do understand the peer pressure.
This is a 6 years old question, and it is interesting to see that no one mentioned a good textbook on programming that covers the fundamentals of computer science.
If you want to learn "real programming", just try to tackle
"Structure and Interpretation of Computer Programs"
by MIT Press in your free time. It should cover most if not all of your curiosity with respect to programming whatever your level is.
There is also "The Art of Computer Programming" by Donald Knuth. Knuth is especially well versed in machine languages and other low level stuff.
Beware though both of these works are very dense.
Here is my two cents on how to approach them. First of all, they are not "tutorials" that sugar coat your way towards a skill, they introduce a scientific discipline in an appropriate manner, so the mind set of "what am I going to do with this? How can I use this ?" should be replaced by "how does this work ? What does this do ? Why does it do it this way ?".
Try to do the exercises included in the books, but don't push yourself too hard. If you can't do it, it is okay, pass to the next one.
However if you are not doing any of the exercises given in a section, you should take your time with the chapter, and revise it so that you can at least do couple of the exercises included for the section.
Just keep this up, and you would caught up with your boss/peer in no time. Some chapters/exercises might even be a subject of conversation if you feel like it. He might even like the fact that you are acquiring new skills, or not, don't take my word for it, I do programming not to deal with people.
Well, "Real Programming" doesn't refer to a specific language, or low level languages. In my mind, "real Programming" is the process of analyzing a task, deciding the best way to solve it, and putting that method into a set of simple steps, and then revising and editing as necessary until you have achieved your goal. From that, the language doesn't really matter, it's all in the thought process. Furthermore, there is nothing wrong with high level languages, I use python all the time and love it. However, learning low level languages can really help develop your understanding programs and computers in general. would suggest c, because it is where c# and c++ stem from, and would provide a bases for understanding both those languages.
After five years of professional Java (and to a lesser extent, Python) programming and slowly feeling my computer science education slip away, I decided I wanted to broaden my horizons / general usefulness to the world and do something that feels more (to me) like I really have an influence over the machine. I chose to learn C and Unix programming since I feel like that is where many of the most interesting problems are.
My end goal is to be able to do this professionally, if for no other reason than the fact that I have to spend 40-50 hours per week on work that pays the bills, so it may as well also be the type of coding I want to get better at. Of course, you don't get hired to do things you haven't done before, so for now I am ramping up on my own.
To this end, I started with K&R, which was a great resource in part due to the exercises spread throughout each chapter. After that I moved on to Computer Systems: A Programmer's Perspective, followed by ten chapters of Advanced Programming in the Unix Environment. When I am done with this book, I will read Unix Network Programming.
What I'm missing in the Stevens books is the lack of programming problems; they mainly document functionality and provide examples, with a few end-of-chapter questions following. I feel that I would benefit much more from being challenged to use the knowledge in each chapter a la K&R. I could write some test program for each function, but this is a less desirable method as (1) I would probably be less motivated than if I were rising to some external challenge, and (2) I will naturally only think to use the function in the ways that have already occurred to me.
So, I'd like to get some recommendations on how to practice. Obviously, my first choice would be to find some resource that has Unix programming challenges. I have also considered finding and attempting to contribute to some open source C project, but this is a bit daunting as there would be some overhead in learning to use the software, then learning the codebase. The only open-source C project I can think of that I use regularly is Python, and I'm not sure how easy that would be to get started on.
That said, I'm open to all kinds of suggestions as there are likely things I haven't even thought of.
Reinvent a lot of the core Unix utilities. Most of these were (and still are) written in C, so they are a good way to start off learning. Depending on your skill, pick harder or easier utilities to copy.
Try writing your own malloc. You'll learn a lot about Unix and a lot of C programming as well.
Google for computer science operating system courses and do the projects there. Many schools have these projects on public websites so you could get everything you need. Here is a link to Purdue's site. Give the shell project a shot; it was difficult, but really educational.
Here are a few stackoverflow postings discussing C/Unix programming books. Their main claim to fame is extensive fan-out to other resources.
Practice some of the idioms (understand the ins and outs of pointers etc) and pick projects that help with that. The third item in the list has an answer (disclaimer, I wrote it) with a bunch of high-level C idioms where an idiomatic C program would differ from Java.
Learning XLib or Win32 GUI programming with C is probably less useful as almost anything is better than C for GUI programming and wrapping a core C engine with another language is generally much easier - unless you're really concerned with speed. As a starting point, concentrate on 'systems' programming applications, which is where you are most likely to get real mileage from C. Learn how the C interface of one of the scripting languages like Tcl or Python works.
Writing some bit-twiddly and pointer heavy code (e.g. picking apart network packets or interpreting a protocol), or server-side items using sockets will take you right into C's core competencies. If you've got some of the WRS books, try making pthreads work (IIRC UNP2 has a big section about pThreads). For a contrast, write something that uses non-blocking I/O. This stuff is C's home turf and you'll get a good working knowledge of C by doing this. Troll through the RFCs for some ideas of network protocols to implement.
What are good Linux/Unix books for an advancing user?
What are some good resources for learning C beyond K&R
Resources for learning C program design
What’s a good way to start learning about Data Structures & Algorithms?
Algorithms in C
Are you open to book suggestions? Although it is a bit dated (where "a bit" perhaps is a huge understatement), Maurice Bach's "The Design of the Unix Operating System" is a great book. It belongs next to K&R on your bookshelf.
You might try working your way through all the examples in the book Software Tools (Amazon). Much of it is pretty pedestrian (right-justify text, de-tabify, etc.), but it's a great introduction to the Unix philosophy and basic C programming.
This is pretty interesting. As we know that Unix is designed by using the C language, it may not difficult to learn. If you are using the Windows OS, you can use a "Windows services for Unix" application to practice your programs. If you are using Unix, then we can use editors like vi.
I would recommend one thing highly.
Try and re-write all usual Linux command lines tools like ls, mkdir, cd etc.
You'll gain a lot of knowlege about programming and Linux both at the same time.
Pick the commands from the easiest, say "time" and work all the way up to the more complicated ones.
The best way to consolidate your learnings it to practise. So just choose a kind of application that interest you and start developing it (for example, a network client/server simple application).
Try to test most of the Unix APIs (files, sockets, etc.) to see how they work. You could for example get an Unix programming book, follow its chapters and test on your application everything you read, by creating your own functions. On that way, you can start to develop your own function library to be used in further projects.
Write a webserver.
Make it multi-threaded.
Have it support a new scripting language you develop (a la PHP, etc.)
Allow uploads from authenticated users.
Write a plugin for your favorite tool (i.e. integrate with SVN to give a webview).
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I'm starting a job search, ideally ending up at a C shop. So far, I'm coming up empty in my local ads, and am starting to think I need to broaden my search, targeting specific types of businesses.
So, what type of places typically use this language?
C is typically used for fairly low-level development. You'll see it used in embedded systems, frequently, which is often listed as a computer engineering position (rather than computer science, or software engineering.) C is also used frequently for device drivers and 'generic' low-level code like math utility code for larger projects.
Generally the sorts of jobs that -need- C are taken by developers who've been using it forever, and have likely been in that position a long time.
Just keep looking! C is a rarity in terms of seeing a job just listed as "C Developer" as you've seen - so obviously they'll just be hard to find.
But I'd just wonder why you're exclusively looking for a C job as opposed to a language like C++ or Objective C :)
Edit:
Just a little note also, not to mislead you with the answer; C is still used for a lot of different stuff. Browsers, instant messengers, server daemons, the network code for even some code written on other languages even. The problem is this is just inefficient in terms the amount of time spent doing the work when you easily write it in Python, on .NET, or any number of other technologies. As such, it just isn't common, but the work can exist.
I work primarily as a C (and Perl) developer, because the application is mature, with a fairly long history (i.e. originally developed in the early 90s). The application suite originally was developed for Unix based graphical workstations. My previous job was a similar situation, a mature distributed application that was developed on multiple Unix platforms, originally in the early 1990s, and due to the source code size and maturity, it would be difficult to justify simply throwing that code base away to move to a new development language or even migrating to C++.
I would imagine there are still a number of larger in-house (used for internal purposes, not sold as a product) applications written in C that are still being maintained. Not entirely unlike the massive COBOL applications that large companies (insurance, finance, banking) that are also still being maintained.
For new development in C, others have already mentioned the embedded systems market, where the development is often for software put into ROM or EEPROM / flash memory where it is referred to as firmware, for microcontrollers (Microchip PIC, Atmel AVR, 80C51, 68HC11, etc.), where object code size, RAM usage, and performance matters so the usage of a programming language with fewer high-level or generic abstractions or assumptions is desirable.
One critical thing about good to great C programmers, is that they are expected if not required to know more about data structures and algorithms. Priority Queues, Binary Trees, MergeSort, QuickSort, Knuth-Morris-Pratt, and Karp-Rabin should be at least vaguely familiar. This is because the C language lacks the STL, Boost, CPAN, and other standard libraries available in other languages. This is at least partly because most implementations are type-specific (due to lack of templates or dynamic typing or similar mechanism) to have generic enough routines to be useful in practise.
Knowing more than one programming language is not a bad thing, even if you don't feel comfortable enough to claim to be comptent enough to program in the additional langages professional. A "modern" scripting or "trendy" web development language might be a good match. Perl, Python, and Ruby are good potential candidates.
For programming experience, functional languages like LISP, Scheme, Prolog*, ML, Objective Caml, Haskell, and Scala are good candidates for making you "think different." Admittedly Prolog is actually a declarative logic programming language, but it is still programming experience expanding.
To add on to Anthony's excellent answer, C is still used extensively in the development of operating systems and firmware, so you may want to try looking in that direction as well.
Good luck in your search for a job.
Things that must run close to the metal, and be fast.
So in addition to what Anthony wrote -- networking protocols, storage device drivers, file systems, the core of operating systems, are still big on C.
Because the focus of interest has commonly moved to applied and web development where you can't do much with C.
Either extend your search geography to other cities/countries or follow the industry trend and learn something new.
Most C programming jobs are in "embedded systems" ... things like televisions, cars, phones, alarms, clocks, toys. Such applications are often memory-constrained by cost reasons, so higher-level languages (eg, Python) are not an option there.
At a time when C and C++ were the predominant coding environments, it was said that 90% of the C programming jobs were for embedded work. Stuff that isn't advertised as software, and for which there are rarely any famous names or faces associated. This is even more the case today.
Linux is completely in C. So any company that contributes to Linux is likely to employ C coders. I worked for an industrial automation company that developed in C. Though most automation shops run PLCs and ladder logic.
iPhone development shops online. Try craigslist as well.
Objective-C is a slim superset of C, so your C skills translate nicely.
Good luck!
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I'm a business major, two-thirds of the way through my degree program, with a little PHP experience, having taken one introductory C++ class, and now regretting my choice of business over programming/computer science.
I am interested in learning more advanced programming; specifically C, and eventually progressing to using the CUDA architecture for artificial neural network data analysis (not for AI, vision, or speech processing, but for finding correlations between data-points in large data sets and general data/statistical analysis).
Any advice about how I should start learning C? As well as ANN/Bayesian technology for analyzing data? There are so many books out there, I don't know what to choose.
Since CUDA is fairly new, there doesn't seem to be much learner-friendly (i.e. dumbed-down) material for it. Are there learning resources for CUDA beyond the NVIDIA documentation?
Further, what resources would you recommend to me that talk about GPGPU computing and massively parallel programming that would help me along?
I don't recommend trying to learn CUDA first since it's a new technology and you don't have much background in programming.
Since you don't have much experience in C (or C++), CUDA will be a pain to learn since it lacks maturity, libs, nice error messages, etc.
CUDA is meant for people who are familiar with C (C++ experience helps too) and have a problem which needs performance improvement by recoding or rethinking the solution of a well known problem.
If you're trying to solve "ANN/Bayesian" problems I would recommend creating your solution in C++ or C, your choice. Don't bother about creating threads or multithreading. Then, after evaluation the response times of your serial solution try to make it parallel by using OpenMP, Boost threads, w/e. After this, if you still need more performance, then I would recommend learning CUDA.
I think these are valid points because CUDA has some pretty cryptic errors, hard to debug, totally different architecture, etc.
If you're still interested, these are some links to learn CUDA:
Online courses:
GPGP
CIS 665
Richard Edgar's GPU Computing Pages
Forum (the best source of information):
NVIDIA CUDA Forum
Tools:
CUDPP
Problems solved in CUDA:
gpuDG
Histogram Computation
You've expressed 3 different goals:
Learning to program in C
Learning to write code for the CUDA platform
Learning to use Bayes' Nets and/or Neural nets for data analysis
Firstly: these things are not easy for people who already have several degrees in the field. If you only do one, make sure to learn about Bayesian inference. It's by far the most powerful framework available for reasoning about data, and you need to know it. Check out MacKay's book (mentioned at the bottom). You certainly have set yourself a challenging task - I wish you all the best!
Your goals are all fairly different kettles of fish. Learning to program in C is not too difficult. I would if at all possible to take the "Intro to Algorithms & Data Structures" (usually the first course for CS majors) at your university (it's probably taught in Java). This will be extremely useful for you, and basic coding in C will then simply be a matter of learning syntax.
Learning to write code for the CUDA platform is substantially more challenging. As recommended above, please check out OpenMPI first. In general, you will be well-served to read something about computer architecture (Patterson & Hennessy is nice), as well as a book on parallel algorithms. If you've never seen concurrency (i.e. if you haven't heard of a semaphore), it would be useful to look it up (lectures notes from an operating systems course will probably cover it - see MIT Open Courseware). Finally, as mentioned, there are few good references available for GPU programming since it's a new field. So your best bet will be to read example source code to learn how it's done.
Finally, Bayesian nets and Neural nets. First, please be aware that these are quite different. Bayesian networks are a graphical (nodes & edges) way of representing a joint probability distribution over a (usually large) number of variables. The term "neural network" is somewhat vaguer, but generally refers to using simple processing elements to learn a nonlinear function for classifying data points. A book that gives a really nice introduction to both Bayes' nets and Neural nets is David J.C. MacKay's Information Theory, Inference and Learning algorithms. The book is available for free online at http://www.inference.phy.cam.ac.uk/mackay/itila/. This book is by far my favorite on the topic. The exposition is extremely clear, and the exercises are illuminating (most have solutions).
If you're looking for a friendly introduction to parallel programming, instead consider Open MPI or Posix Threading on a CPU cluster. All you need to get started on this is a single multi-core processor.
The general consensus is that multi-programming on these new architectures (gpu, cell, etc) have a way to go in terms of the maturity of their programming models and api's. Conversely, Open MPI and PThreads have been around for quite a while and there are lots of resources around for learning them. Once you have gotten comfortable with these, then consider trying out the newer technologies.
While there's certainly programming interfaces for many other languages, C is probably the most common modern language (Fortran and Pascal are still kicking around in this area) in use in high performance computing. C++ is also fairly popular though, several Bioinformatics packages use this. In any case, C is certainly a good starting place, and you can bump up to C++ if you want more language features or libraries (will probably be at the cost of performance though).
If you are interested in data mining, you might also want to look at the open source system called Orange. It is implemented in C++ but it also supports end-user programming in Python or in a visual link-and-node language.
I don't know if it supports NNs but I do know people use it for learning datamining techniques. It supports stuff like clustering and association rules.
(Also, in case you didn't know about it, you might want to track down somebody in your B-school who does operations management. If you're interested in CS and datamining, you might find likeminded people there.)
Link: gpgpu.org Has some interesting discussion
The latest CUDA releases (3.1, 3.2) have a full featured set of functions called CuBLAS that will handle multi-coring matrix operations for you on single card setups. Paralleling the backproagation will be a bit more of a challenge, but I'm working on it.
I was able to find some great video courses free from Stanford on iTunesU
Programming Methodology (CS106A)
Programming Abstractions (CS106B)
Programming Paradigms (CS107)
Machine Learning (CS229)
Programming Massively Parallel Processors with CUDA
Each one of these courses has around 20 or so lectures so it's a investment to watch them all but well worth it.