Data Science

Difference Between C and Python

Published: 9th May, 2023

Gurneet Kaur

Data Science Consultant at almaBetter

Do you want to know how Python and C differ from one another? Discover what makes these popular programming languages unique and what each excels at. Read Now!

Programming languages are crucial tools for the creation of software. The two most well-liked programming languages are C and Python.

However, what is the difference between C and Python? To assist you in choosing which language to utilize for your next Data Science project, we will examine the Python vs C and the disparities between the two languages in this blog, along with some examples.

Introduction to C

C language, created in the early 1970s by Dennis Ritchie, is a cornerstone in programming. Renowned for its efficiency and versatility, C has been a driving force behind modern software development. Its concise syntax, and powerful capabilities have enabled the creation of everything from operating systems to embedded systems.

With a focus on control structures and memory manipulation, C remains a fundamental educational language and an essential tool for professionals, shaping the digital landscape and influencing subsequent languages. Its enduring legacy underscores its significance in the ever-evolving world of programming.

Introduction to Python

Python, a dynamic and high-level programming language, has swiftly emerged as a favorite for developers and beginners since its inception in the late 1980s by Guido van Rossum. Known for its readability and elegant syntax, Python emphasizes code clarity and ease of use, fostering rapid development across various applications.

Python's vast libraries and community support simplify complex tasks, from web development to data analysis and AI. Its versatility and gentle learning curve have made Python an essential tool for innovation, propelling it to the forefront of modern programming languages.

Now let’s take a look at the difference between Python and C:

Difference Between C and Python

Comparison FactorCPython
SyntaxComplex, requires explicit declarations and syntax rules.Clear and concise, focuses on readability and simplicity.
UsageGeneral-purpose, suitable for system programming and performance-critical tasks.Versatile, excels in web development, data analysis, scripting, and automation.
Memory ManagementManual memory management using pointers, leads reduces to potential memory leaks and segmentation faults.Automatic memory management with built-in garbage collection, reducing the risk of memory-related errors.
TypingStatically typed, requires explicit type declarations.Dynamically typed, variables can change type during runtime.
Development SpeedUsually requires more lines of code for equivalent tasks, resulting in longer development times.Requires fewer lines of code due to high-level abstractions, enabling faster development.
PerformanceOffers low-level control, making it potentially faster but requiring careful optimization.Generally slower than C due to its interpreted nature, but performance-critical sections can be optimized using C extensions.
Learning CurveSteeper learning curve due to complex syntax and memory management.Gentle learning curve with easy-to-understand syntax, suitable for beginners.
Community & LibrariesRich set of libraries, especially for system-level programming.Extensive libraries and frameworks for various applications, including web development, data analysis, and machine learning.
PortabilityCode may need modification for different platforms due to system-dependent features.High portability, code can be executed on different platforms without significant changes.
DebuggingDebugging can be more challenging due to manual memory management and low-level details.Easier debugging thanks to higher-level abstractions and built-in tools.
Use CasesIdeal for performance-critical tasks, embedded systems, and low-level programming.Well-suited for rapid development, scripting, data manipulation, and building applications across various domains.

Let’s have a detailed analysis of difference between c and python with examples:

C vs Python: Syntax

Python and C have quite distinct syntaxes. However, some essential things to consider:

Unlike Python, which utilizes indentation to identify code blocks, C code is written with curly brackets () to indicate code blocks.

While Python does not require semicolons ( ; ) after each statement, C does.

Because C is a statically typed language, you must define the data type of each variable. Conversely, Python is dynamically typed; therefore, you do not need to choose the data type. Here’s an example: an integer variable would be declared as follows in C: int x = 10; in Python, you would write: x = 10.

You can choose which programming language to use by knowing the syntax difference between C and Python.

C vs Python: Data Types

Programmers can choose from a variety of data types in both C and Python.

While Python offers more high-level data types like lists, tuples, and dictionaries, C has more basic data types like char, int, and float.

Python is dynamically typed compared to C, where a variable’s type is determined at runtime. C is a statically typed language, meaning a variable’s type must be stated before it is used.

While Python offers automatic memory management and garbage collection, C supports direct memory manipulation.

For instance, in Python, “c = ‘a’” would be used to declare a character variable instead of the C equivalent of “char c = ‘a’;”. The complexity and readability of code in each language can be impacted by these variations in data types.

C vs Python: Memory Management

Different approaches to memory management are used in C and Python.

Using functions like malloc() and free(), manual memory allocation and deallocation are required in C. However, it can also result in issues like memory leaks or segmentation faults. This allows developers more direct control over memory utilization.

Python uses a garbage collector for autonomous memory management. In other words, the language automatically releases memory when it is no longer required, which facilitates safer and easier coding but may also affect performance.

Python also offers reference counting capabilities for shared memory management. This makes it simpler to work with large data sets and prevents memory leaks.

C vs Python: Object Oriented Programming

C and Python have different approaches to object oriented programming. Here are some of the key differences between C and Python with example.

The object-oriented features of classes and objects are not entirely supported by the object-oriented language C. The usage of structures and function pointers allows for the creation of object-oriented code.

Python is a fully object-oriented language with support for classes, objects, and inheritance. It makes it simpler to build object-oriented programming because it comes with built-in support for creating and using objects.

In Python, for instance, you may define a class’s methods and attributes as follows:

class Person: def init(self, name, age): = name self.age = age

def introduce(self):
    print("Hi, my name is",, "and I am", self.age, "years old.")

In C, you can create a struct and define functions to operate on it, like this:

typedef struct { char name[50]; int age; } Person;

void introduce(Person *p) { printf(“Hi, my name is %s and I am %d years old.”, p->name, p->age); }

C vs Python: Libraries

Developers can choose from multiple libraries for Python and C.

Although there are many libraries for C, most are low-level and focused on tasks like file I/O, networking, or cryptography. The Standard Library, OpenSSL, and libcurl are well-known C libraries.

There are several libraries for Python, many of which are specialized in fields like Data Science, Web Development, or Machine Learning. Many people are familiar with the Python libraries NumPy, Pandas, Flask, and Tensorflow.

C vs Python: Performance

In terms of design and implementation, C and Python perform differently from one another.

Because C is a compiled language, a compiler transforms it into machine code before the code is run. Because of this, C programs run incredibly quickly and efficiently.

The Python interpreter runs the code directly because Python is an interpreted language. This can sometimes result in Python software running more slowly than C programs.

C vs Python: Use Cases

Python and C each have unique advantages and disadvantages that make them appropriate for particular use situations. Here are a few instances:

Use C if you need to create high-performance software, such as operating systems, game engines, or simulations for scientific purposes.

Use Python when you need to create scripts, web applications, or data analysis software that can take advantage of Python’s rich library system.


In the conclusion of the difference between Python and C language, C and Python each have advantages and disadvantages. You should choose the appropriate language depending on your unique use case and requirements.

Do you want to learn more about C and Python? Join AlmaBetter’s Web Development course and Data Science course to understand such concepts better and upgrade your knowledge and skills.

Frequently asked Questions

Q1: What is the difference between C and Python?

Ans: Python is interpreted programming language and is object-oriented whereas C is a compiled programming language that binds the bridges between machine-level and high-level languages.

Q2: Which is easier Python or C?

Ans: The syntax of Python programs is easy to learn, write and read, but the syntax of a C program is harder than Python.

Q3: Is C much faster than Python?

Ans: Yes, C is faster than Python as Python is an Interpreted Language.

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