Have you ever watched Godfather? When Don Vito Corleone was taking care of the reigns of the gangster era, he was unique in his own way with the way he operated and handled all the daily activities. When his son Michele Corleone replaced him, he was characterized by his speed and performance as the new don by executing his plans perfectly, by offering everyone of his opponents an offer they cannot refuse. This situation can be compared to Julia development replacing the iron-fist of Python development. Python was a fair programming language offeri
ng unimaginable solutions a decade ago to its users. While many experts felt that Python development lacked the lustre performance level, Julia development came as a surprise to all of them with its ever-growing capability. It has a huge scope in the upcoming days with vast features. There is a statistic revealed by HackerRank 2019 Developer report that 11.5% of developers have shown interest in learning Julia in 2020. Such is the growing prominence of Julia development.
In the coming days, Julia development is going to be of utmost importance. It has a lot to do with the credibility of your app and software. Julia has the ability to offer multiple features for all its users. The features would include multiple dispatches, built-in package manager, thorough support for all your parallel and distributed Julia computing. One of the major reasons for its popularity is how it blends C, Ruby, Python, R and MATLAB. Owing to all those features, it has become one of the most sought after for various business models including the best brands in the world such as Intel, NASA, Disney, Tencent and Alibaba. Viral Shah, one of the most renowned Julia experts says that Machine learning and Artificial Intelligence developers have been using Julia in recent days for its high-end performance, ease of use and syntax. This goes on well with the parallel and distributed computing that includes the usage of TPUs and GPUs. With numerous exciting projects in machine learning and artificial intelligence available in Julia, you can also include cataloguing each and every visible object in your universe. This can go on to identify life-saving medicines as well as introducing them to various markets. This year 2020 may mark the visibility of new Julia projects which are in development since 2020.
Julia comes across with a number of developer-friendly features which we cannot ignore. It has the ability to scale higher in comparison to any other programming languages in the world. Let’s discover some of the features which marks Julia vs Python:
Julia is known to be a compiled language. This is one among the major reasons why it is performing faster compared to any other interpreted languages. Unlike any other traditional compiled languages, we should know that Julia is no more strictly statically typed. The usage of JIT (Just In Time) compilation for inferring all the individual variables in code makes it special. The end result is an absolutely splendid dynamically-typed language with an ability to run any command-line similar to Python. You can go on to achieve any high level of speeds for any compiled languages such as C and Go.
You can run your code in parallel while using Python. If you want to get the maximum out of every CPU core belonging to your system, Julia is the best language as well. You can import various modules using parallelism along with an extremely capable syntax to declare if a function runs concurrently.
Python is quite older in comparison to Julia with a far and wide community in picture. While compared to any other language, Python consists of a huge library with well-maintained packages and libraries. Even though Julia is a new language with a relatively smaller user base, it only has less number of packages available. You can run all your Python libraries using Julia, with the help of the PyCall package. With more number of C/Fortran libraries being called as well as run directly from your Julia code, you can easily allow any number of Julia users to go on to access a large number of external libraries. Python still consists of more advantage in this case with its versatile native packages along with a vibrant community.
Python is also a dynamically-typed language. This means that you have the freedom to declare any variable with no need to specify any of its types. You should note that the Python interpreter can allow you to determine what type of value is being provided. You can also see that the number of Variables in Julia can easily be declared using this pertaining way. You can also specify the types, or go on to specify a range of types that are meant for your variable. You should note that expected type specification for any function would help your compiler to optimize the system meant for better performance. You can also go on to prevent any kinds of errors that result from various unexpected or incorrect types of input.
Multiple dispatch is a term that refers to the way of declaring any different version belonging to the same function. You can use it to better handle any kind of input belonging to different types. If at all you are of the preference to write any two contrasting reverse functions, it is possible for you to accept any array as a possible argument as well as the one that goes on to accept any string. You should make note that the Julia interpreter can go about checking the argument types when you call the reverse, You can also easily dispatch it to the version that matches with the type.
This is known among the masses to be the most significant difference available between Julia as well as Python. You should note that Julia is 1-indexed. This means that you can access the first element belonging to an array with this_array instead of using this_array. You can ensure that this choice is made with a purpose to make the Julia programming language intuitive for any kinds of users in the field of Mathematics as well as any other technical Julia computing tools. This would not lead to any errors that zero-indexed languages are subjected to.
Julia comes with a number of advantages for a common developer. Here are a few of them:
Are you aware of the endless advantages that Julia vs Python can pose upon you? You should know if Julia is really the best choice for Machine learning. Are you being sceptical if it has any scope in the near future? Do not worry about that. Julia programming has gone on to win the hearts of developers with its speed and competent nature. We need not worry much about the advantages and features since it already offers multitude of them for all its audience. Developers have started using it in recent days for many applications. These are the applications that Julia development possesses for developers:
You should be aware that Julia has gone on to receive accolades from a number of developers. The well-aware growth track would act as a sufficient proof to it. As time goes on, we would see a lot of applications related to Julia development. Want to know more about the Julia latest version? You should rely upon expert support for these reasons.
Pattem Digital has a number of advantages to offer while you rely upon us for Julia development services. We have been the industry experts who can take care of all your requirements without forgoing the quality factors. From documentation to maintenance, we are there to support you. Contact us if you need any support.
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