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Why does C code run faster than Python's?
In this article, we will learn why the C language code runs faster than Python.
Guido Van Rossum developed Python, one of the most well-known programming languages. Python is popular among developers because of its clear syntax and simple code, even for newcomers. Learning Python can be highly advantageous for those who have just begun their career in programming. They can use Python Programming Training, blogs, videos, modules, and thousands of other resources to get into every aspect of this popular language. Once completed, you will be able to do modern development activities such as GUI development, web design, system administration, complex financial transactions or calculations, data science, visualization, and the list goes on.
Python is Slower than C since it is an Interpreted Language.
Python is slower than C since it is an interpreted language.
As a result, more real CPU instructions are needed to execute a given statement.
You may verify if a variable's value in Python code by adding the number 1 to it or by comparing it to a given value to see if it is less than, greater than, or precisely equal to that value.
The difference is that rather than being immediately performed by the CPU, the Python code will be interpreted.
In terms of performance, this makes all the difference in the world.
Almost Always, a Virtual Machine is used to run Python Code
Another name for a virtual computer is a "bytecode interpreter."
Interpreted code is always slower than actual machine code since it requires many more instructions to implement an instruction than it does to carry out an actual machine instruction.
Consider the expression x += 1. In an Intel CPU, a register increment is a single op with a latency of 1 and a reciprocal throughput of one-third(1/3).
In other terms, it refers to the quickest CPU instruction that an Intel processor can provide.
In Python, how is this x += 1 accomplished?
To understand this, you must first understand how Python works internally.
Python's internal components include a tokenizer, a lexical analyzer, a bytecode generator, and a bytecode interpreter −
Tokenizer − It creates a token stream from the ASCII text files (Python code) that are given.
Lexical Analyzer − This area of Python is concerned with appropriate indentation and spacing. Syntax checking happens at this point.
Bytecode Generator − If any optimizations are made, they are made by the Python component; however, because Python is not a compiled language, the range of available optimizations is constrained in contrast to what you could get from a C compiler.
The Python module known as the "bytecode interpreter" manages the bytecode stream and powers the Python virtual machine (maintains its state).
Once generated, bytecode is often cached in memory.
Because you don't have to repeat the tokenization, lexical analysis, and bytecode generation processes for code that Python has already seen, this enhances speed.
So, instead of going through the tokenization, lexical analysis, and bytecode creation processes each time we loop our while loop, we can just keep passing the bytecode to the bytecode interpreter.
Isn't this faster? No, it is not actually.
Although using cached bytecode is quicker, it does not execute or operate as rapidly as machine code.
The real CPU that runs the code is not a virtual computer.
Compiled UCSD Pascal, unlike other compiled languages at the time, was not compiled to assembly language. It was instead compiled into p-Code.
So p-Code comes to mind when you think of a "compiled Pascal programme." Use "bytecode" if you like Java or Python and want to pretend you came up with something new.
In addition, Python includes the concept of "compiled Python," which refers to Python code that has been processed by the tokenizer, lexical analyzer, and bytecode generator to create cached bytecode that is ready to be given to the bytecode interpreter (AKA the Python Virtual Machine).
It is an ASCII text file containing Python source code when you see a file with the extension.py.
PYthon, Compiled is what a file with the “.pyc” extension stands for.
Still, a virtual computer executes the created code.
Once a program has been built, it hasn't fully been converted to native code until it has been converted to the native binary CPU instructions for the platform it is designed for.
Instead of using bytecode, this frequently involves writing assembly code, passing it to an assembler, and having the assembler create platform-specific object files.
Until the program is connected to a platform runtime, it is not yet ready to be used. A runtime can offer runtime services like dynamic object loading and build the environment in which the code will execute. In compiled C, a runtime exists. C++ that has been compiled has a runtime.
Why Python is Slower than C?
Python performs numerous sanity checks - integers can never overflow, invalid memory can never be accessed, types can never be (silently) incorrect, and arrays can never be written or read past their ends. In Python, it's very difficult to have a "non-local bug," yet in C, it's fairly common to have a bug that isn't actually where the mistake is reported.
Python's compiler doesn't do very advanced optimizations (if any) - for one thing, speed isn't as important as it is in C, and there isn't as much information to go on - for example, in Common Lisp, another dynamic language like Python, you can provide type annotations to get the same speed as C - if you opt out of the safety checks and promise that certain variables will have certain types, you get exactly the same machine code instructions (and exactly the same weird behavior if you have a bug in your program).
In this article we have learned about different reasons as to why C language code execution is faster than Python in this article.
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