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Tech

[Discussion] Julia Programming Language : A True Python Alternative

2018-08-26 02:44:16
296 5

Hey, Mi fans!

Big data has grown to become one of the most lucrative fields. In fact, data scientists are some of the most sought people. They are usually hired to analyze, control and parse large chunks of data. Implementing these actions using traditional techniques is not a walk in the park. This is why most data scientists prefer using programming languages such as R and Python. However, there is one more programming language that can do the job. That is Julia programming language.

What Is Julia Language?
Julia is a programming language that came into the limelight in 2012. It is a high-level, high-performance dynamic programming language for technical computing. It has a syntax which is familiar to users of other technical computing languages. It provides a great compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.


Julia was meant to be an alternative to Python, R and other programming languages that were mainly used for manipulating data. This is because it has numerous features that can minimize the complexities of numerical computations. It is a flexible dynamic language with performance comparable to traditional statically-typed languages.

Who Is Julia Language For?
Julia is the most preferred programming language for data scientists and mathematicians. This is because its core features are similar to the ones that are used on most data software. Also, the language is ideal for these two subjects because its syntax is similar to the standard mathematical formulas.


Another reason why Julia is preferred by data scientists is that it supports cloud computing and parallelism. Most big data projects rely on these technologies. If you are a data scientist or you intend to become one, consider learning Julia.

Features Of Julia Language:-
  • Simple Syntax: Just like the Python programming language, Julia has a simple and direct syntax that you can easily understand.
  • Parallelism: Although you can run Python and R codes in parallel, the process is a bit complex. Julia programming language makes things simpler. Its parallelism feature allows functions to run independently hence utilizing the full function of the CPU.
  • Dynamic Typing: Julia will allow you to type your strings of codes dynamically while at the same time gives you the full advantages that come with static typing. Dynamic typing allows you to declare a variable without stating its type.
  • Allows Metaprogramming: It is possible to generate other Julia programs from one Julia program. You can also call Python functions & C functions directly without any wrappers or special APIs.
  • High-Performance JIT Compiler: In computing, just-in-time compilation, also known as dynamic translation, is compilation done during execution of a program or at runtime rather than before execution. Julia has an LLVM (Low-Level Virtual Machine) therefore, it is only compiled and not interpreted. This is the main reason why it is faster. JIT (Just-in-time) compilation makes Julia have the same speeds as C programming language.
  • Open Source: It's open source and free with MIT license. It provides efficient support for Unicode, including but not limited to UTF-8.


Comparing Julia To Python And R Programming Languages:-
  • Speed: Julia is faster than both Python and R. This is a very critical aspect that is given special attention in the big data programming. The high speed of Julia is because of JIT compilers.
  • Syntax: Julia has a math-friendly syntax. It is similar to the mathematical formulas hence can be used to perform mathematical and scientific computations. This syntax makes it easier to learn than Python.
  • Parallelism: Although both Python and R use parallelism, Julia uses a top-level parallelism. Julia allows the processor to perform to the optimum level than what Python and R can achieve.
  • Versatility: Julia programming language is more versatile than Python and R. It allows a programmer to move from different codes and functions with ease.


Conclusion:-
Julia is a new programming language, it has a small community as compared to others which have been around for years. In overall Julia programming language is a better alternative that you can use to handle Big data projects. Despite having a small community, it is one of those programming languages that you can easily learn.


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Julia is still new but it has already gained popularity.
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2018-08-26 02:44:16
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Grandmaster Bunny

Solver13 | from Redmi Note 4

#1

Well explained in detail! Thanks for sharing:-)
2018-08-26 04:56:20
Well Explained!!
2018-08-26 08:05:39
Thanks for share detail information

2018-08-28 20:06:17
Invalid floor, the posts have been deleted #4
Julia has been around for two or three years now and keeps on pulling in new clients. cheap assignment writing service Julia Language utilizes ideas from entrenched programming dialects keeping in mind the end goal to make a simple to-utilize elite programming.

2018-08-29 03:15:41
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