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This article introduces the knowledge of "what are the slow dynamic programming languages". Many people will encounter this dilemma in the operation of actual cases, so let the editor lead you to learn how to deal with these situations. I hope you can read it carefully and be able to achieve something!

Programming languages have been around for many years, and each language is built to meet specific needs.

As of today, there are about 700 programming languages in the world. There are only 250 languages left to survive, and the rest have been largely abandoned by the programming community.

Performance has always been a must for programmers. In the past, the running time of a program could be measured by days, but now, thanks to advances in science and technology, it can be run in just a few seconds.

The speed of computer evolution follows Moore's Law:

Moore's law

In electronics, speed and performance are translated into the number of transistors that a particular chip can have. According to Moore's Law, this number doubles every two years. That's why your phone is much faster than a room-sized supercomputer in the 1990s.

Back to computer science, there is a difference between fast code and fast computers. There is also a difference between a slow program and a slow computer. Although many of us can't affect the speed of computer hardware, we can control the speed of the code.

When developing, we often have to consider one factor, and that is language expectation. Each language is implemented in a different way, so each language has its own advantages, and few people will incorporate the running speed of the program into the programming advantages of the language.

If you are working on game projects or demanding tasks such as heavy mathematical calculations, it is best not to use a programming language that is too slow.

In general, there are two types of programming languages:

Static type programming language

Dynamic type programming language

Statically typed languages are usually compiled, meaning that the compiler's program parses and converts the entire English-like code into assembly language and generates a new file that can be run manually by the user.

A dynamically typed language is a language that does data type checking only at run time, that is, when programming in a dynamically typed language, you never have to assign a data type to any variable, and the language records the data type internally when you assign a value to a variable for the first time.

Most people like dynamically typed languages. Languages such as Python that are error-prone and easy to interpret manually. But this comes at a price, that is, at the expense of speed.

In this article, we will list four common dynamically typed programming languages that are relatively slow.

1. Perl

If you have used UNIX before, you must have seen the Perl script. Because most UNIX files are in Perl format.

Perl is a Unix scripting language. It was created to ease the difficulty that programmers have to endure coding lengthy Shell programs, and Perl crammed a lot of Shell commands into a file.

More importantly, Perl can also be used to accomplish tasks that are difficult to accomplish in C and other Unix languages.

Perl is a real headache in terms of speed.

In addition, trying to find a good Perl programmer now is like trying to find a needle in a haystack. This is because, unlike Python, Perl is very implementation-sensitive, and each operator must be in the right place to have a relatively efficient program.

Even with the most efficient implementation, Perl still lags behind other high-level programming languages. However, after the release of a version of Perl 6 called Raku in 2019, the speed problem of Perl is being solved one after another.

2.PHP

PHP is a scripting Web development programming language that usually complements HTML, CSS, and MySQL in Web site deployments.

Many people think that PHP is out of date, but this is not the case.

Some studies show that:

Of all the websites we know of server-side programming languages, 79.0% use PHP.

In addition, the 2020 StackOverflow survey on programming, scripting, and markup languages shows that PHP is still a very active language, ranking above C++ and Typescript:

However, because PHP's learning curve is gradual and the hosting cost is low, there will be a lack of performance.

PHP is very slow because of the lack of just-in-time compilation (JIT compiler) and because it is a dynamically typed language. Fortunately, on November 26, 2020, PHP 8 introduced a performance optimization feature: the built-in JIT compiler.

The built-in JIT compiler helps PHP approach other similar programming languages in terms of speed and performance.

3.Ruby

Yukihiro Matsumoto, the official author of Ruby, once said:

Ruby is designed to satisfy programmers.

Ruby is an object-oriented programming language, everything can be interpreted as objects. This makes it an easy-to-use tool. Just move your fingers and the task can be done.

However, in terms of performance, Ruby is a typical interpretive language. Because interpreting languages run code statements one by one, they tend to be slower than languages that use compilers.

The speed of Ruby is again cut in the global interpreter lock (GIL) because the language allows only one thread at a time to use GIL.

Finally, the speed of Ruby is also affected by high memory consumption and slow garbage collection.

4.Python

Python ranks first in the ranking of many programming languages and has become a very popular programming language. It is widely used in data science, Web development, artificial intelligence and so on.

This is not an exaggeration of Python, because its advantages outweigh its disadvantages. But as things stand, the speed of Python is still a problem.

Python and Ruby are programming languages with the same attributes. Both are slow because of GIL and the use of interpreters. The main difference between them is that the former focuses on data science, while the latter prefers Web development.

However, Python has many powerful libraries and features to support. Some of these libraries and features, such as the Numpy module and the Filter () built-in functions, can be implemented in C++, resulting in significant performance improvements. That's why Python is now rapidly surpassing other programming languages.

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