Can Julia Replace Python

Can Julia Replace Python?

With time, Julia will be able to replace Python in some areas where speed is most critical, Python is mature and widely used, it has many success stories and has powered many applications, it has a large community of developers and many helpful resources, this makes Python reliable and very hard to replace.

Julia was designed by Jeff Bezanson, Stefan Karpinski, Viral B. Shah, and Alan Edelman in 2012, it is a high-level language that is very fast. It has since grown in popularity and usage to become the 5th most loved programming language, behind Rust, Elixir, Closure, and Typescript.

According to a Stack overflow survey of 2022, Julia is loved by 72.51% of professional developers versus 27.49% of professional developers who dreaded it. Its popularity and usage in Data visualization & plotting, Data Science, Machine Learning, Parallel & Heterogeneous Computing, continue to grow rapidly.

On the other hand, Python is the third most popular programming language used by many companies and individual developers, it is the 6th most loved programming, the same Stack Overflow survey reported that Python is loved by 67.34% of professional developers versus 32.66% of professional developers who dreaded it.

Python is widely used in Web development, Machine Learning & Artificial Intelligence, Automation, System Administration, GUI development, Software Testing, Data Science, Scientific & Numeric computation, and Software development. It is beginner-friendly and very easy to use.

Python is highly extensible through modules, it can call extension modules written in other programming languages like C to run time-critical functions. It also has a huge number of standard libraries that makes it useful in Automation, Databases, Mobile apps, web frameworks, Machine Learning, Data Analytics, image processing, networking, multimedia, web scraping, etc.

Python is used by a lot of big companies for a variety of projects, these companies include Google, Microsoft, Facebook, Amazon, Yahoo, NASA, Instagram, Spotify, CERN, Reddit, and many others too numerous to mention.

Julia is glowing and becoming widely adopted, but it is still far from being used at the scale and range of Python. For comparison, Python is 4th on the most commonly used programming language with a 43.51% usage while Julia is 35th with a 1.04% usage. (Stack Overflow Survey 2022).

This is an enormous difference and it shows that Julia has a long way to go before it beats Python in usage and eventually replaces Python. It is worth noting that Julia is rapidly growing and already replacing programming languages like MATLAB in some areas.

For example, the Federal Reserve Bank of New York has used Julia to make models of the United States economy (including estimating COVID-19 shocks in 2021), noting that the language made model estimation “about 10 times faster” than its previous MATLAB implementation.

This shows that the Federal Reserve Bank of New York has replaced some of its MATLAB implementations with Julia. In time to come, Julia may be to replace Python in some areas as shown above as it did for MATLAB.

Julia is also getting a wide adoption from a lot of big companies, some of the corporations using Julia include Aviva, NASA, Brazilian INPE, Moderna, BlackRock, Climate Modelling Alliance, Google, Microsoft, and many others.

There are some areas of Python’s weaknesses that Julia will be able to replace, but there are some features of Python that make it superior to Julia. In other cases, Julia and Python will work side by side using extension modules, and foreign function interfaces to provide the best of both worlds.


Julia is a very fast and high-performance language compared to Python. Julia is one of the few high-level programming languages in which petaFLOPS computations have been achieved, the others being C, C++, and Fortran.

Julia is easy to work with, its syntax is concise and straightforward, and Julia has foreign function interfaces that make it work well with other programming languages such as Python, R, C, C++, Java, and many others. Python and R packages such as PyJulia and JuliaCall can be used to call Julia packages.

Julia is also useful for low-level systems programming, web development, and High-level Synthesis (HLS) tool for hardware like FPGAs. Some of these features can be achieved with Python but others will be very difficult to achieve.

Julia is relatively new and has a lot of features that are very useful for modern needs. The developers of Julia had time to study, and identify the weakness and limitations of other available languages like Python.

They were able to improve on some features and add new ones to come up with a programming language that is more powerful, fast, and efficient in solving current problems.

Although Julia provides a lot of advantages over Python, there are many features that make Python superior to Julia.


Python is mature, well established, and reliable. It was developed in 1991 and has had a lot of time to evolve and become better. It has gone through many changes, and it has been tried, tested, and earned its trust over the years. Julia on other hand is relatively new.

Python has a huge community of developers with many resources to choose from. Whenever you get stuck, there is always help from thousands of developers in different online communities.

Python is highly extensible with a lot of standard libraries that allow it to be used in many different fields. From Web development to Mobile apps, web scraping, Game development, Scientific computations, and more.

Popular platforms and libraries such as Django, NumPy, Tensorflow, Keras, Pygame, Abaqus, Raspberry PI, Blender, Cinema 4D, SciPy, Flask, GIMP, Paint Shop Pro, Capella, LibreOffice, and many others use Python.

Because there are a lot of companies using Python than Julia, there are more Python jobs available than Julia. You will have more opportunities if you know Python only than knowing Julia only.


Julia will be able to replace Python in some areas where speed, and performance are extremely critical, Julia is also a good choice for numerical analysis, and computational science. But Python is still popular, and widely used.

It will take a very long time for Julia to be used at a range and scale of Python, much more to replace Python.