If you're asking whether there's a programming language that is suitable to all tasks and environments, the answer is no. This question would be analagous to asking if there's a hand tool that is capable of replacing hammers, screwdrivers, drills, planers, saws, pliers, diagonal cutters, wrenches, etc., etc.

If you're asking whether there's a programming language that is so good at the things it's used for that there is no way to imagine it being better, the answer is again no, but for a different reason. Software languages are implemented in software and all software is improvable in one way or another.

There are languages that are dearly loved by their communities. Perl comes to mind - the folks who use perl for quick text extraction and manipulation scripts seem to really love it. Python also comes to mind. C is particularly well-suited to the things it's still heavily used for, and is very elegant if you aren't trying to make it do things that are unnatural for it.

According to your definition of “amazing”ness.

• If you mean “amazing” as in “this is amazingly simple” then Python.
• If you mean “amazing” as in “it is amazing how popular this language is” then Java.
• If you mean “amazing” as in “holy shit! This language is so f****d up it's amazing that you can write anything in it!” then JavaScript.
• If you mean “amazing” as in “look at this freak! Amazing creature!” then C++.
• If you mean “amazing” as in “it is amazing that you can do almost everything in this language” then C.
• And above all, machine code itself. It is really amazing how a bunch of 0/1s or “current”/”no current” can let you order a piece of hardware to do whatever you like.

The most elegant is Haskell.

Why?

Everything works like a fine Swiss watch. Everything is designed exactly as needed, no strange superfluousness.

I don’t mean clarity or readability only, as Applescript has that too, but it’s not elegant:

It’s very clear what’s happening, it’s easy to read, and not just because a factorial is something almost everybody knows.

Elegance is in maximum simplicity, but this is paradoxical. As simplicity reaches max, it becomes something else, something different from what we normally know as ‘simple’.

Elegance is doing (or being able to do) the same thing in a way that makes the process enjoyable, the end result sublime. And all the while remaining clear and simple enough to know exactly what’s going on.

Look at this Arturo example. It is the exact translation of our earlier Applescript:

factorial: $[n][ 
	if? n>0 [n * factorial n-1] 
	else [1] 
] 

It’s shorter, but it’s not clear and elegant.

But Arturo has ‘fold’, which makes the process somewhat enjoyable:

factorial: $[n][ 
    fold.seed:1 1..n [a,b][a*b] 
] 

Yet, the end result is not sublime. It’s only marginally better than the explicitly recursive version.

Now, let’s see the same in Haskell. It ought to satisfy these criteria:

• Simple
• Easy
• Clear
• Enjoyable to write
• Sublime to behold

Here you go:

facto k = foldr (*) 1 [1..k] 

Let’s dissect it: [1..3] gives us: [1, 2, 3]. Then foldr applies * to 1 (called the accumulator) and then multiplies it to each element of the generated list, starting from right (hence, first 3 is multed to the 1 outside the list, then the result is multed to 2, then its result to the 1 inside the list):

facto 3 
foldr (*) 1 [1, 2, 3] 
3 * 1    * 2 * 1  
3        * 2 * 1 
6            * 1 
-- 
6 

Nearly all modern mainstream languages have stolen the design choice of foldr from Haskell*, but even then, their versions are not sublime:

Python:

from functools import reduce 
def facto(n): 
    return reduce(lambda x, y: x * y, range(1, n + 1), 1) 

Scala:

def facto(n: Int): Int = (1 to n).foldRight(1)(_ * _) 

JavaScript (ES6):

function facto(n) { 
    return Array.from({length: n}, (_, i) => i + 1).reduceRight((a, b) => a * b, 1); 
} 

Rust:

fn facto(n: usize) -> usize { 
    (1..=n).fold(1, |acc, x| acc * x) 
} 

F#:

let facto n = [1..n] |> List.foldBack (*) 1 

F# comes closest to Haskell, but the design is not as intuitive.

Please note that I’m not talking only about syntax. If it came to syntactical elegance, no language would beat APL. APL’s syntax is from Mars.

In the criteria I mentioned earlier, you saw ‘enjoyable to write’. This is not based on syntax alone—although syntax plays a role. Programming language elegance is beyond syntax: it involves working with a different mindset and thinking in terms of ideas, not mere syntax.

This simple ‘foldr’ example merely scratches the surface of what’s possible in Haskell. As programs become bigger, Haskell behaves very differently, and shows maximum elegance in a world mired with mediocre languages that have been catapulted to popularity due to mere randomness**.

• * Note, I mean the specific design choice for foldr. The concepts (on which foldr is based: that is, recursion and pattern-matching) originally were crystallized in IPL, an old language that predates Lisp (so it wasn’t Lisp that introduced them first.). In my answer, I make no claim that foldr appeared in Haskell first. The languages that I listed imitate stylistic choices peculiar to Haskell, and that’s my point.
• ** Language-camp answers tend to appear rather abrasive, since some people who have spent years writing programs in languages that are not as elegant as Haskell will probably find my answer a sort of ‘dis’. I assure the readers that I have meant no disrespect (except to imbeciles who can’t read or those who comment before they think. See comment below.), and only point out facts. It is very likely that such programmers, with the help of my answer, might actually begin to explore Haskell to see what the fuss is all about. Or at least find enough motivation to see for themselves whether I’m right.

—

PS: The flurry of comments that are wrong, irrelevant, or otherwise show the commenter lacks reading comprehension ability prompts me to disable comments.

Elixir (and Erlang).

What would you do if all your problems were fixed, and not just fixed but fixed decades ago with systems already running proving it.

Elixir is built on top of Erlang virtual machine. This is an absolute joy to work on. Absolutely every problem you have with every other language has been solved. Scaling? Not a problem.

In one book I own, there is a list of normal services you need to make a modern scalable application, it lists a few services like queues, Redis, databases and out of a list of 10 or so items, only 1 is the language you are using, be it C# or Python.

If you pick Elixir, you can easily do everything in Elixir. You see, as I said, all the problems you have been having are already solved. They were solved in the end of the 1990’s, by Ericsson.

But Ericsson, an enormous company absolutely mismanaged their golden egg but through sheer luck it became public. It was a system for phone operators, to handle phone calls.

Lets say this. The phone system is on version 1.0 and you and your wife are on the phone with one another, your parents are also talking to one another on the phone. This is two services running. The phone company needs to upgrade the system. What can you do?

Well, with Elixir you just update the system. All the calls that are going on will continue to run on 1.0 until they hang up. When they want to make another call they will do so on 1.1.

The system is functional, and all variables are static, so they can not be changed except to read them all again. This gives you the guarantee that you can always run the system and move data to and from workers.

It has so called green threads which means you can create 100,000 workers and never think about it again, they just finish.

Need to build services? No problem, it is built in, just follow a little format and you have a server.

It is almost impossible to explain this. It took me a few days just to comprehend what I was doing.

A lot of online gaming engines are written in Erlang and Elixir. Whatsapp had million users on a single machine, single server, and everyone chatted away.

It is absolutely something everyone should look into.

Let's start with Rust. No, not the reddish-brown metal that your grandpa's old car is probably rusting away into oblivion. I'm talking about the programming language that offers memory safety, data race freedom, and high-performance. Rust is known for its strong safety features that prevent common programming mistakes.

And then there's Haskell. Don't let its name fool you, it's not a character from a Harry Potter book. Haskell is a functional programming language that's designed to make writing code easy, maintainable, and error-free. In other words, it's like a personal assistant for your coding needs, without the coffee runs or awkward small talk.

The choice of programming language depends on what you want to achieve and what you feel comfortable with.

In the end, the most impressive programming language is the one that helps you get the job done and doesn't make you want to throw your computer out the window.

This is pretty relevant.

Different programming languages are designed with different things in mind.

Some languages are made to be as simple as possible. Others are made to be as expressive as possible. Etc.

C has an enormous amount of control over memory. Java has relatively little control. Either one can be a plus depending on the situation. Unfortunately one size fits all is hard, if not impossible.

It depends on your criteria.

What is your definition of robust? What kind of ecosystem do you want? What maturity level do you need?

I consider a robust language to be one that is difficult for the programmer to make mistakes. In this regard, nothing beats a pure functional language with strong, static types.

Purity prevents surprises due to unindented side-effects. Strong, static types allow the compiler to formally verify a large class of program correctness.

Haskell is one such language. It is quite mature, but the ecosystem is nowhere close to the level Java enjoys. That said, it is production-ready and you are find jobs that require it as a skill.

Idris goes even further by featuring dependent types. By allowing types that can depend on values, it can further close the gap because programs and proofs. Idris is said to be Pacman-complete, which means you can write the pacman game in it, I guess. Don’t rewrite all your micro-services in Idris just yet…

Because programming languages are tools, and tools have each a specific purpose. You can't do the same things with a screwdriver, a hammer, paste, a saw and a drill. Some can be used to do similar things in different ways (you can assemble wooden pieces with screws or with nails and paste), but one is probably better than the other for a given task. It's the same with programming languages; you don't do the same things with, say Javascript, Python, C, Java and Lisp. (Even if it is technically possible, it would be a bad idea to write a compiler in Javascript or a full user interface in pure C : the result would be ugly and unpractical).

Besides, tools evolve with technology. Portable electric drills were not around one century ago, and similarly, most high-level languages only appeared in the late 80s or 90s. Before that, we just didn't have the science, technology and know-how for them.

What do you think a perfect programming language would look like?

To me, the perfect programming language would be no programming language at all. You would explain what you want, and the computer would understand what that means and just do it.

It would know that you want a particular screen of a program to come up in the same place it came up last time. Unless there's something there already, in which case it should come up somewhere else. But if the thing that's there already isn't important, the screen can still come up there. If you've unplugged one of your monitors since last time the program ran, it should just come up in an appropriate place.

But let's say you think about that, and realize that it's too hard. It's a generalized AI problem. So we're stuck with a programming language, even if that's not ideal. So what would a nearly-perfect programming language look like?

What pieces are important to you? How closely what you say corresponds to natural language? Terseness? Speed? Predictability? Ease of use?

Some of the things you want will conflict with other things. Being close to natural language conflicts with terseness. Speed means, among other things, using multiple threads. Using multiple threads is one way to almost certainly reduce predictability, as things on different threads may get performed in a different order each time the code runs. If you have mutable data and don't use locks, you're going to have problems with different threads reading and writing data unpredictably. If you do use locks and aren't careful, you can create deadlocks. If you are careful, you've sacrificed ease of use.

Different languages make different trade offs. People who are used to C/C++ often hate garbage collection, because they don't know when that will happen and it may introduce lag at a critical time. People who are used to garbage collection will often complain about the need to explicitly manage their own resources.

Saying what you want done in higher-level terms means that you're trusting the compiler/interpreter to do what you want at a lower level. Saying what you want done in lower-level terms mean you get to specify exactly how you want stuff done, but you lose out somewhat on expressability.

I made a scoreboard from a couple Hammer Principle pages.

The results came out:

1. Smalltalk - 7 points
2. Scheme - 6 points
3. Haskell - 5 points
4. Standard ML, Clojure, Prolog, Forth - 4 points
5. F#, Python, Eiffel, Lua, Io, APL, J, Factor - 3 points

…and a whole bunch of others with only 2 or 1 points.

Sources: There is a lot of accidental complexity when writing code in this language (took bottom), Code written in this language is very readable, This language has well-organized libraries with consistent, carefully thought-out interfaces, This language has a very coherent design, This language is minimal, This language is built on a small core of orthogonal features, This language has many features which feel "tacked on" (took bottom), This language has an annoying syntax (took bottom).

That would be Haskell, for me. I might like Idris even more if I learned it, but I haven’t.

Haskell is a great language for control freaks because no functions can ever do anything you don’t know about. Functions just take arguments and evaluate values and that’s basically it. There can be side effects (because a program is useless without them), but side effects have their own types, and are executed later in a special context where you know exactly what’s happening.

While Haskell is famous for its functional programming features (like those mentioned above), it is equally sophisticated when it comes to type theory. Haskell is very different from a classical OO languages, but it provides mechanisms for all the best parts of OO design. Structs give you composition and encapsulation while polymorphism is provided not by classes, but by typeclasses (which are more like interfaces in Go, if you’re familiar with that—doesn’t matter what a type is, but what interfaces it provides), generics everywhere, algebraic data types, higher-kinded types (a.k.a. type constructors), and Hindley-Milner type inference as the cherry on top. Haskell is among the most polymorphic statically typed languages in the world.

Because Haskell gives you so many assurances about how your program works, there’s a pretty good chance your program will work correctly if it compiles.

Haskell is the closest language to perfection I know. There’s just one problem: While it is possible to do anything with Haskell, some things that are simple in other languages are kind of difficult in Haskell because all those safety features mean you have to do everything in a way that the compiler can prove. For this reason, it doesn’t have super high industry adoption except in applications where there is zero room for bugs.

“Non-complete” usually means not Turing complete — which means in common terms that there are things that cannot be done with the language, whereas Turing complete means in common terms that the language has enough constructs to formulate any type of program.

This does not mean much in the modern scheme of things — but let us do some thought experiments with this.

Say a language has no concept of “files” or access to hardware devices like mice. It would then be impossible to write a program in the language that loads and writes files or uses the mouse. Is that “incomplete”? No, not like that is what they would say. The language is not for that.

Many languages don’t have sound built in. The language does not have the ability to make noise. Nobody calls that “incomplete”.

Just because you can’t make a video game with the language does not make it incomplete.

Completeness in modern times for a language usually means that

• You can interface with the operating system
• There are C library modules that provide system access and functions to facilitate binary processing, access to files, access to devices. They may not be visible to source code, they may have to be built-in to an interpreter.
• programs can be written to files in source form, bytecode, or compiled.
• Programs have commands, variables, memory to store things.
• Programs have symbolic interpretation — things can be stored in named entities
• variables, constants, numbers
• procedures, operations
• directives

There are very few languages out there that do not have all of that. Most have things much more powerful and complicated like:

• advanced types such as reference types, generic types, hierarchical sub-typing
• string functions, strings as a basic language feature
• recursion, function stacks, scoping
• advanced math functions, integers, floating point, decimals, roman numerals, fractions, exponents
• objects, structures, records, formats
• deferred procedures (waiting to call functions until a signal or state happens)
• continuations (storing procedures mid-calculation, and picking them up again later)
• lambda functions (unnamed procedures) do some task on data inline without
  the overhead of a full function. Often used to “pass a function into a function”.
• functors (function objects) objects with their own state that are used
  as a function, called like a function, but can “remember” values, configurations and calculations between calls.
• error procedures, exceptions, signals
• slots and signals (pluggable architectures)
• foreign function interface (ability to interact/load modules written in other languages)
• debugging facilities

Languages that lack most of the above are probably the ones you might call “incomplete.”
Completeness is not essential if the language is good enough to get its jobs done in its domain.
The language in a calculator is good enough for what it does.

Some “incomplete” languages:

• HTML (a subset of sgml) only is for other programs to render, you cannot really write “programs” in it. It provides a minimal layout language around the text and image data in the text file.
• CSS (cascades style sheets) is a layout language to modify how the browser creates the web page display from the html.
• JSON (Java Script Object Notation) is a description language for a JavaScript (JS) interpreter to create data from. It usually does not contain JS code but describes how data should be formatted for use in the JS program. It is often called a “configuration” language because it is mostly used for setting up a JS configuration.
• Scripts for interpreters such as shells (bash, telnet, etc.) These are sets of commands that trigger
  the underlying interpreter to call commands. Python, Perl, TCL, are complete languages and run scripts that are full programs, but shells only accept a limited number of commands, most of the work they do is calling other programs and job control, managing input and output streams and user interactions.
• Query Languages for databases (SQL, dbIV, QXL ), are usually just commands and data, and limited in many ways.
• Regular Expressions are a string matching/sifting language that only is for selecting and modifying strings out of other strings. It is powerful for working with data, but does not “do” anything else by itself.
• Template systems are a sub-language within a language that generate specific code from a generic boilerplate set of code, where certain variables are place-holders that get filled-in when the program is run or compiled. Such sub-languages are really limited to small uses, but come in handy for tasks that are repeated very often with only the values changed for each use.

The simplest language is Forth. Its syntax is read left-to-right. There are no precedence rules. It has a trivial execution model and can easily construct complex systems. Unlike most languages, it does nothing whatsoever to keep you from shooting your foot off. The language’s attitude is “If you said it, you must have meant it.” Forth is mostly used in embedded systems. It is especially useful in situations where you need a lot of functionality in very little space. Forth is an ideal first language, but it is usually a stretch for those who have already learned another language.

Lisp is another language that has almost no syntax. It has a very small semantic bootstrap, but a somewhat larger runtime package, which usually has features far beyond the minimal bootstrap. It has a simple execution model and can easily construct complex systems. For all its simplicity, it has immense abstractive power. Lisp is probably the most powerful language that has ever been built. It is used for a wide variety of applications, from the trivial to the mind-boggling. Lisp is a very good first language, but it is usually a stretch for those who have already learned another language.

Smalltalk is not as simple as Forth or Lisp, but examples of its entire syntax can still be written on a corner of one sheet of paper. Its execution model is usually explained in terms of sending messages between discrete objects. There are lots of kinds of objects in the standard library, and it is easy to create more, where each kind of object defines its own messages. There are two operators, five reserved words, and three kinds of messages. The development tools are excellent, and any other language’s tools are measured in comparison to these. Like Lisp, Smalltalk is used for a wide variety of applications. It is not as powerful as Lisp, but it comes close, and it is probably the easiest of these three languages to learn if you have already learned another language.

No. There will not be a single programming language that replaces all others.

The reason all the others exist is because they are good at doing different things. Often at direct odds with other languages.

For example C is very good for working directly with the hardware. Fast. Efficient. You can see every single clock cycle reflected in the source code. Good for boot loaders, device drivers, operating system kernels, utilities and some applications.

At the opposite end are very high level languages specialized for certain things. CAS (Computer Algebra System) languages. Term rewriting languages. Logic languages like Prolog. Abstract languages such as various dialects of Lisp. Special purpose languages like SQL. As a rule these higher order languages abstract you far away from the low level machine. You don’t know (or care) what the width of a machine word is. An integer has no limits on its size. Need a ten thousand digit integer? No problem. And where and how such a large integer (or other structure) gets allocated or deallocated is a mere detail you don’t want to even waste your time thinking about. The language should take care of that so you can think of much higher order concepts. Thunks. Lambda Functions. Generators. Pattern matching.

Being at direct odds, it seems unlikely there could ever be a language that spans the very low level and the very high level without being bad at both.

Such a language would probably be named after some curse word.

The best programming language with a good future depends on your goals and the field you’re working in. Here’s a breakdown of some of the most promising languages, followed by a strong contender for those working in data analytics and processing:

Python continues to dominate due to its versatility, simplicity, and massive ecosystem. It’s widely used in data science, AI, and web development, and its community support ensures it will remain relevant for years.

SQL has been and will always be a critical skill for database management and querying. With the explosion of data, its role in extracting and processing structured data is vital.

If you’re diving deep into statistical computing or academic research, R remains indispensable due to its focus on data visualization and statistical analysis.

For full-stack and web development, JavaScript (and its ecosystem) is indispensable. Technologies like Node.js ensure its utility beyond the browser.

For those in data analytics or who work extensively with structured data, I recommend looking into esProc SPL. While it’s not as mainstream as Python or SQL, it offers a specialized toolset for data analysis, ETL, and complex data calculations.

Unlike general-purpose languages, SPL is built specifically for data manipulation, making it more intuitive and efficient for such tasks.

With simplified syntax, SPL provides simpler solutions for handling complex problems that might require verbose Python or SQL code.

As for performance, it is designed for efficiency and often outperforms Python in tasks involving large datasets or intensive calculations.

SPL can work as an Excel add-in, making it a perfect bridge for analysts who want to go beyond Excel’s built-in functions.

For example, tasks like multi-field deduplication, grouped sorting, or ranking often take several lines in Python or SQL but can be handled in a single SPL expression.

If you’re working in data processing or business intelligence and need a tool that’s efficient, future-proof, and tailored for data, SPL is worth exploring. It might not replace Python or SQL entirely, but it can complement them—or even outperform them—in certain scenarios.

In conclusion, Python and SQL remain dominant choices for their versatility, but for data-related tasks, esProc SPL offers a specialized, forward-looking solution.

Hi Friend,

You can easily learn and create the application using any coding language. There are three best coding languages in current.

You can use the free online tutorial for learning a coding language. for example, the tutorial point anyone can use for learning and create applications.

Python

Python is one of the most commonly used programming languages today and it easy to write the code.

It is a free, open-source programming language with extensive support modules and community development, easy integration with web services, user-friendly data structures, and GUI-based desktop applications.

It is a popular programming language for machine learning and deep learning applications.

Python is used to develop 2D imaging and 3D animation packages like Blender, Inkscape, and Autodesk.

It has also been used to create popular video games, including Civilization IV, Vegas Trike, and Toontown.

Python is used for scientific and computational applications like FreeCAD and Abacus and also by popular websites like YouTube, Quora, Pinterest, and Instagram.

Python developers earn an average annual salary of about $72,500.

Java

Java is one of the most common, computer programming languages it has several methods and classes to solve the solution.

Owned by Oracle Corporation, this general-purpose programming language with its object-oriented structure has become a standard for applications that can be used regardless of platform (e.g., Mac, Windows, Android, iOS, etc.) because of its Write Once, Run Anywhere (WORA) capabilities.

As a result, Java is recognized for its portability across platforms, from mainframe data centers to smartphones. Today there are more than 3 billion devices running applications built with Java.

Java is widely used in web and application development as well as big data. Java is also used on the backend of several popular websites, including Google, Amazon, Twitter, and YouTube.

It is also extensively used in hundreds of applications. New Java frameworks like Spring, Struts, and Hibernate are also very popular.

With millions of Java developers worldwide, there are hundreds of ways to learn Java. Also, Java programmers have an extensive online community and support each other to solve problems.

Java is a more complex language to learn, but experienced developers with Java coding skills are in high demand.

The average Java developer earns around $79,000 each year.

Kotlin

Kotlin is a general-purpose programming language originally developed and unveiled as Project Kotlin by JetBrains in 2011.

The first version was officially released in 2016. It is interoperable with Java and supports functional programming languages.

Kotlin is used extensively for Android apps, web applications, desktop applications, and server-side application development. Kotlin was built to be better than Java, and people who use this language are convinced.

Most of the Google applications are based on Kotlin. Some companies using Kotlin as the programming language include Coursera, Pinterest, PostMates among many others.

Kotlin developers earn an average of $136,000 a year, with the potential to earn up to $171,500.

There is no one programming language that is ideal or best for all possible programming tasks. Each has strengths and weaknesses. Each contains tradeoffs. Each is better for some programming tasks, and less-well-suited to other programming tasks. There is no one language to rule them all. There never has been, and there probably won’t ever be. Attempts to create such languages have resulted in languages with lots of tradeoffs, rendering the language not well-suited to all possible programming tasks.

Rather than trying to chase the “best” language, just choose a language that is appropriate for the type of programming task at hand. And don’t think that you’re stuck with one language forever. Professional software developers are fully expected to learn and properly use programming languages, programming paradigms, and many other things as needed along the way. The first language you learn and use will not be your last.

Think of programming languages as tools, nothing more. You learn and use the right tool for the right task. Some projects require multiple tools, for different parts of the project.

Programming languages are just tools. If you think of programming languages as tools, and consider the wide variety of tools that exist in the world for different tasks, having different programming languages for different types of programming tasks makes sense.

Consider the real world of carpentry. All saws “essentially do the same thing” — they saw things. But consider what a “universal” saw would look like. To effectively replace all the various types of saws, it would have to strive to be equally good at all sawing tasks…just as good as a hacksaw, band saw, jig saw, back saw, coping saw, fret saw, rip cut saw, pruning saw, crosscut saw, bow saw, wire/cable saw, bone saw, keyhole saw, compass saw, razor saw, Japanese saw, veneer saw, carcass saw, wallboard saw, table saw, miter saw, circular saw, reciprocating saw, scroll saw, rotary saw, chainsaw, pole saw, chop saw, flooring saw, track saw, masonry saw, radial arm saw, tile saw, oscillating saw, panel saw, and concrete saw. It is neither feasible nor more practical to have a “universal” saw to replace all the various types of saws we have today. Each type of saw was designed to make some types of cutting easier. There is no way to design a single “universal” saw that can do all of these things equally well.

Now, cutting stuff is a pretty simple, basic concept. And yet, we need many different types of saws for different types of cutting tasks. Programming languages are much more complex than saws. They enable a developer to express the performance of an infinite variety of tasks, from very simple to extremely complex. Programming languages have a lot of different capabilities, not just one.

Each programming language has strengths and weaknesses, and some are better suited to some types of programming tasks than others. Attempts to design and implement new languages which have all the strengths, none of the weaknesses, and are universally appropriate for all programming tasks invariably result in languages which still have strengths, weaknesses, might be applied to most (but not all) programming tasks, and typically make some things easier for developers and some things much harder for developers. Attempts to compromise between strengths and weaknesses typically result in mediocrity for some types of programming tasks, and that in itself is a weakness. And if you improve something in the language over here, it can be at the expense of something over there.

Engineering efforts, including programming language design, always involve tradeoffs.

Let’s take one obvious programming language area: dynamic memory management.

You decide that your universal language should be garbage-collected, to make life easier for developers. Unfortunately, your universal language can’t be used in projects with real-time requirements (e.g., many embedded systems). Alarms go off, because your language isn’t universal.

So, you change your mind and say that the developer is responsible for all dynamic memory management, with no garbage collection. Suddenly, you have masses of developers crying out with one anguished voice, because they grew up on garbage-collected languages, and have no idea how to avoid dangling pointers, double deallocations, memory leaks, etc. Many opt to never deallocate anything, causing their applications, operating systems, device drivers, etc. to gobble up memory and bring systems to a grinding, thrashing, painful demise. Of course, you can attempt to train them in the ways of memory management, but that won’t work for everyone, and many those who are able to adapt will continue to complain that they have to deal with these issues themselves.

As a result, you change your mind once again and decide that the developer gets to make the decision, for each and every object, whether it will be garbage-collected or managed by the developer. This seems like a nice, “universal” approach. But then developers must make an extra non-trivial decision every time they deal with object creation. A decision like this requires a solid understanding of the implications of the decision on behavior of the software, performance characteristics, etc. Developers then have to remember which objects they are managing, and which objects they’re not managing, so they don’t get into trouble. In the end, solid knowledge and experience are required to make this decision on every allocated object. This raises the barrier to entry and barrier to success with the language, and that doesn’t bode well for the language, long term.

Ask a systems programmer for their language feature priorities, and ask an application programmer for their language feature priorities. You’re going to get two different lists, with sometimes conflicting priorities. If you try to merge the two, there will be things about the language that neither programmer likes.

Could there ever be a 'perfect' programming language?

No.

Each programming language is a mathematical notation designed for a particular problem domain.

There are no general programming language that will fit all problem domains.

Fortran is VERY good for scientific research. C++ can do the same task, just not as well as that isn’t what it was designed for.

C is VERY good at CPU and device control… but it is not as good as C++ for complex applications.

And is really horrible as a Fortran replacement.

Each language is a notation for the problem domain that is designed to make it easier to use within that domain.

No language is good at everything.

In the natural language, English is pretty good… But don’t expect it to actually be used for legal contracts. Those use legalese with specific definitions of words that don’t necessarily line up with common English.

This question comes to most of the beginner programmers mind. When I start programming, I also had the same question in my head.

Here I give you ONLY the basic idea:

Computers can only understand electrical signals. For example, If light ON, it means 1. If light OFF, it means 0. In Mathematics, Binary is a concept where we can only represent 0’s and 1’s.

Computer scientists used Binary to represent keywords on to the computer screen.

Take a look at this picture:

This is how binary represent numbers. The same concept goes to represent alphabets and symbols.

A very long time ago where we don’t have any programming languages, Computer Scientists used Binary Language/Machine Language to ‘progam’ since they find it very difficult to understand binary language and make programs with it, so they made programming language(human-readable) using Binary Language(Machine-readable). (Let’s say they made Assembly language using Binary)

We made another programming language using the assembly language and it goes on.

Nowdays, we have C, C++, Java, Python and so on. You know. C is a successor of B language. C++ made in C language.

Now you have an IDEA on how programming languages are made. High Five!

P.S|Kindly give editing suggestions to improve this answer.

It's hard to predict the future but here it goes:

Kotlin: The language that started as JVM only and now it can target multiplatform development (ios, android, jvm, js, ios, windows, linux). I think it strickes a pragmatic balance of legibility, productivity and performance like no other and that will continue to grow and become a powerhouse in the industry, in part because of the excellent tooling Jetbrain creates (IntelliJ IDEA and Fleet)

I am sure JS will stick around but have a poor reputation as a messy language prone to bugs. A new performance oriented language will take over its niche but it is unclear which one (maybe rust).

There is an article comparing languages in respect to safety.

How Safe is Your Programming Language

This article was probably posted in 2008. It took specific classes of errors (Ex. Null Pointers, Array Index Out Of Bounds, Type Errors etc) and checked how and when a language catches them.

According to this article Haskell is the safest language. I would like to mention Haskell is a functional programming language and purely functional code is guaranteed to have no side effects and will never throw exceptions.

Now the problem with purely functional code with no side effect is that it is not that productive. Querying database or even calling date function introduce side effect to the code. This is why you have to use monads for these sort of functionality. But that will be a whole new discussion.

Sticking with your question, There is a programming language called Rust which is a systems programming language that claims to runs blazingly fast, prevents segfaults, and guarantees thread safety. They are associating the safe word with this programming language very frequently. Now the problem is when working on system level, you need a lot of flexibility and for that reason enforced safety does not seem to always work. So, to unleash the full potential, even rust introduced unsafe code. In the following article Meet Safe and Unsafe, they mention -

Well, unlike C, Rust is a safe programming language.

But, like C, Rust is an unsafe programming language.

…

Unsafe Rust is exactly like Safe Rust with all the same rules and semantics. It just lets you do some extra things that are Definitely Not Safe

This reminds me of C. Lets talk about C++ a little bit. There is a book called Safe C++: How to avoid common mistakes by Vladimir Kushnir. This books talk about the best practices that will make C++ code safe. My point being, You can make almost any programming language safe by following best practice for making it safe.

Summery

There is a trade-off between safety and capability. For example, Assembly language is not safe. If you want to make it safe then it will not be able to tell the machine a lot of things which you might want it to do. So you have to set your priorities straight.

Being said that, Safest language is Haskell. Second safe language is safe rust. And finally, if you following best practice for making it safe then almost any language is safe including C.