Python received a lot of attention back in 2022 when it was named Programming Language of the Year by the Tiobe index. It is very popular among machine learning professionals and is widely used in the field of artificial intelligence.

Python’s popularity has undoubtedly grown in recent years, but Julia, a relatively newer language, has recently enjoyed a lot of attention and demand. Recently, it has been increasingly argued that Julia as a programming language can compete with Python and even take its top spot. According to a new study, Python has been named the best language that developers would choose if Julia did not exist.

Python vs. Julia: Which is Faster and More Preferred?

Julia is not interpreted, therefore it is a fast programming language. It is compiled at runtime using the LLVM framework. Julia provides high speed without optimization or special profiling routines and is thus the solution to all your performance problems.

Both Julia and Python programming languages can execute tasks in parallel. On the other hand, Python’s techniques need data serialization and deserialization to parallelize between threads, while Julia’s parallelization is much more precise. Julia also has a less heavy parallelization syntax than Python, which lowers the barrier to using it.

Every programming language should have a large and active community behind it. A programming language must have a strong following in the community. Julia has a vibrant and energetic community, but because it is a new language, the size of the community is limited.

On the other hand, Python has been around for a long time and therefore has a large community working in its favor. Julia’s developer community is still in its infancy. Python’s large community is a great advantage for developers as it provides many resources to deal with difficulties and uncertainty.

Dynamically typed
Julia and Python are dynamically typed programming languages, which means that developers don’t have to declare variables. But with Julia, you can combine and take advantage of both static and dynamic types.

Working with Shell
Julia has a really good relationship with Shell. For example, the Shell commands to check the contents of a file. Julia variables are exported to the shell as environment variables. Once opened, users can modify the file. Working with Shell commands is much easier in Julia than in Python. In this aspect, Julia is well ahead of Python.

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