How much faster is Fortran than Python?

Published on Sep 14, 2025

5 min read

How much faster is Fortran than Python? image

Fortran is a programming language that was first developed in the 1950s for scientific and engineering applications. It is known for its high performance and is still widely used in many fields such as numerical simulations, data analysis, and high-performance computing. Fortran is also one of the oldest programming languages that are still in use today.

Python is a high-level, general-purpose programming language that is widely used for web development, scientific computing, data analysis, artificial intelligence, and other applications. It is known for its simple and easy-to-read syntax, which makes it a popular choice for beginners and experienced programmers alike. Python also has a large and active community, which provides a wide range of libraries and frameworks for various tasks. It is also cross-platform which means it can run on multiple operating systems like Windows, macOS, and Linux.

What Fortran is used for?

Fortran is primarily used for scientific and engineering applications, such as:

Numerical simulations: Fortran is well-suited for performing complex mathematical calculations and simulations, such as weather forecasting, fluid dynamics, and structural analysis.
High-performance computing: Fortran is often used to write code that runs on supercomputers and other high-performance computing systems, where performance is a critical factor.
Data analysis: Fortran is used to process large data sets and perform statistical analysis, such as in financial modeling and bioinformatics.
Engineering applications: Fortran is commonly used to write programs for engineering applications such as aircraft design, bridge design, and other civil engineering projects.
Legacy systems: Fortran is also used to maintain and update legacy systems and codes, written in the past. It's still used in some scientific institutions and research centers due to their existing large code base and compatibility with some specific systems.

What Python is used for?

Python is a versatile programming language that can be used for a wide range of tasks, including:

Web development: Python can be used to build server-side web applications using frameworks such as Django and Flask.
Scientific computing and data analysis: Python is commonly used for scientific computing and data analysis tasks, such as data visualization, numerical simulations, and machine learning.
Artificial intelligence and machine learning: Python has a wide range of libraries and frameworks, such as TensorFlow and sci-kit-learn, which are used for AI and ML tasks.
Scripting: Python can be used for writing scripts to automate tasks, such as web scraping and data processing.
Game development: Python can be used to create games using libraries such as Pygame.
Internet of Things (IoT): Python is a popular language for IoT applications because of its ease of use and large community, which provides a wide range of libraries and frameworks.
Desktop applications: Python can be used to create desktop applications using libraries such as Tkinter and PyQt
System Administration: Python is also popular in system administration for its powerful libraries for system management and automation.

How much faster is Fortran than Python?

Fortran is generally considered to be faster than Python for numerical computations, particularly when it comes to performance-critical tasks such as simulations and data analysis. This is because Fortran is a compiled language, which means that the code is translated into machine code before it is executed, while Python is an interpreted language, which means that the code is executed line by line by an interpreter. The compilation step in Fortran allows for more optimized and efficient code execution, which can result in significant performance gains.

However, the difference in performance between Fortran and Python can vary depending on the specific task and the libraries and frameworks used. For example, if you're using a Python library that is written in C or Fortran and is optimized for performance, it may be faster than a similar Fortran program. Additionally, the performance of a Python program can be improved by using JIT compilers like Numba, Cython, etc.

In general, for performance-critical tasks, it's recommended to profile and optimize the code, rather than to compare the language performance in general.

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