How to Make Python Code Run Incredibly Fast - KDnuggets (2024)

How to Make Python Code Run Incredibly Fast - KDnuggets (1)
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Python is one of the most popular programming languages among developers. It is used everywhere, whether it’s web development or machine learning.

There are many reasons for its popularity, such as its community support, its amazing libraries, its wide usage in Machine Learning and Big Data, and its easy syntax.

Despite having these many qualities, python has one drawback, which is it's slow speed. Being an interpreted language, python is slower than other programming languages. Still, we can overcome this problem using some tips.

In this article, I will share some python tricks using which we can make our python code run faster than usual. Let’s get started!

Each data structure has a significant effect on runtime. There are many built-in data structures such as list, tuple, set, and dictionary in python. Most people use a list data structure in all cases.

In python, sets and dictionaries have O(1) lookup performance as they use hash tables for that. You can use sets and dictionaries instead of lists in the following cases:

  • You do not have duplicate items in the collection.
  • You need to search items repeatedly in the collection.
  • The collection contains a large number of items.

You can see the time complexity of different data structures in python here:

Time Complexity via Python Wiki
This page documents the time-complexity (aka "Big O" or "Big Oh") of various operations in current CPython...


Python’s built-in functions are one of the best ways to speed up your code. You must use built-in python functions whenever needed. These built-in functions are well tested and optimized.

The reason these built-in functions are fast is that python’s built-in functions, such as min, max, all, map, etc., are implemented in the C language.

You should use these built-in functions instead of writing manual functions that will help you execute your code faster.

Example:

newlist = []for word in wordlist: newlist.append(word.upper())

A better way to write this code is:

newlist = map(str.upper, wordlist)

Here we are using the built-in map function, which is written in C. Therefore, it is much faster than using a loop.


If you want to assign the values of multiple variables, then do not assign them line by line. Python has an elegant and better way to assign multiple variables.

Example:

firstName = "John"lastName = "Henry"city = "Manchester"

A better way to assign these variables is:

firstName, lastName, city = "John", "Henry", "Manchester"

This assignment of variables is much cleaner and elegant than the above one.


List comprehension is an elegant and better way to create a new list based on the elements of an existing list in just a single line of code.

List comprehension is considered a more Pythonic way to create a new list than defining an empty list and adding elements to that empty list.

Another advantage of list comprehension is that it is faster than using the append method to add elements to a python list.

Example:

Using list append method:

newlist = []for i in range(1, 100): if i % 2 == 0: newlist.append(i**2)

A better way using list comprehension:

newlist = [i**2 for i in range(1, 100) if i%2==0]

Code looks cleaner when using list comprehensions.


You should avoid importing unnecessary modules and libraries until and unless you need them. You can specify the module name instead of importing the complete library.

Importing the unnecessary libraries will result in slowing down your code performance.

Example:

Suppose you need to find out the square root of a number. Instead of this:

import mathvalue = math.sqrt(50)

Use this:

from math import sqrtvalue = sqrt(50)


In python, we concatenate strings using the ‘+’ operator. But another way to concatenate the strings in python is using the join method.

Join method is a more pythonic way to concatenate strings, and it is also faster than concatenating strings with the ‘+’ operator.

The reason why the join() method is faster is that the ‘+’ operator creates a new string and then copies the old string at each step, whereas the join() method does not work that way.

Example:

output = "Programming" + "is" + "fun

Using join method:

output = " ".join(["Programming" , "is", "fun"])

The output of both methods will be the same. The only difference is that the join() method is faster than the ‘+’ operator.


That’s all from this article. In this article, we have discussed some tricks that can be used to make your code run faster. These tips can be used especially with competitive programming where the time limit is everything.

I hope you liked this article. Thanks for reading!



Pralabh Saxena is a software developer with 1 year of experience. Pralabh writes articles on topics such as Python, Machine Learning, Data Science, and SQL.


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How to Make Python Code Run Incredibly Fast - KDnuggets (2024)

FAQs

How to Make Python Code Run Incredibly Fast - KDnuggets? ›

Using Built-in Functions and Libraries

How to make your Python code run faster? ›

25 Ways to Speed Up Python Code
  1. Embrace Django. ...
  2. Use PyPy Instead of CPython. ...
  3. Use NumPy Arrays Instead of Lists. ...
  4. Use the Built-in “timeit” Module. ...
  5. Apply Generator Expressions Instead of List Comprehensions. ...
  6. Use Multiprocessing in Python Coding. ...
  7. Apply Python Profiling. ...
  8. Optimize Loops with Code Maps.
Aug 17, 2023

How do you increase the efficiency of Python code? ›

9 tips to improve Python performance
  1. Select correct data types.
  2. Know standard functions, methods and libraries.
  3. Find performance-focused libraries.
  4. Understand the different comprehensions.
  5. Use generator functions, patterns and expressions.
  6. Consider how to process large data.
  7. Run profiles to identify problematic code.
Oct 4, 2023

How to optimize a code in Python? ›

Techniques for Optimizing Python Code
  1. Profiling and Identifying Bottlenecks.
  2. Utilizing Data Structures and Algorithms.
  3. Implementing Efficient Loops and Iterations.
  4. Minimizing Function Calls and Variable Lookups.
  5. Using Built-in Functions and Libraries for Speed.
  6. List and Dictionary Comprehension.
Jan 3, 2024

How do I speed up Python interpreter? ›

10 ways to make Python programs run faster
  1. Measure, measure, measure.
  2. Memoize (cache) repeatedly used data.
  3. Move math to NumPy.
  4. Move math to Numba.
  5. Use a C library.
  6. Convert to Cython.
  7. Go parallel with multiprocessing.
  8. Know what your libraries are doing.
Feb 28, 2024

Will Python be faster than C++? ›

Key Differences Between C++ and Python

It has a simple and easy-to-learn syntax. Moreover, its features are easy to use, which allows you to write short and readable code. C++ is faster than Python because it is statically typed, which leads to a faster compilation of code.

How much faster is C++ than Python? ›

Now, let's take a look at the same algorithm in C++. After compiling, if you run the code, it takes about 2.42 seconds to generate all 67 million 13-mers. It means Python takes 25 times more time to run the same algorithm compared to C++.

Is Python 3.12 faster? ›

Speaking of the 3.12 version, it is ~10% slower than 3.11, and the results are stably reproducible. Though both 3.12 and 3.11 are significantly faster than 3.9 that comes as standard on macOS.

How fast is a Python snake? ›

Pythons can't move very fast though—only about 1 mile per hour (1.6 kilometers per hour) on open ground. But since they don't have to chase their food, they don't really need to move quickly. Pythons have predators.

Is Python faster than Java? ›

Java vs Python - Speed

In terms of speed, Java is faster than Python as it is a compiled language. It takes less time to execute a code. Python is an interpreted language and it determines the type of data at run time which makes it slower comparatively.

How do I optimize my code to run faster? ›

What are the best ways to optimize your code for performance, security, and scalability?
  1. Choose the right language and framework.
  2. Write clean and modular code.
  3. Use data structures and algorithms wisely.
  4. Implement caching and memory management.
  5. Apply security best practices. ...
  6. Test and monitor your code.
Aug 3, 2023

What is the fastest loop in Python? ›

(spoiler alert!) The answer is… the for loop! You can test it easily using the timeit function like this: Code that tests the difference in performance between the while loop and the for loop in Python (CPython to be more precise).

What is JIT Python? ›

JIT, or “Just in Time” is a compilation design that implies that compilation happens on demand when the code is run the first time. It's a very broad term that could mean many things. I guess, technically the Python compiler is already a JIT because it compiles from Python code into Bytecode.

Why is Python interpreter so slow? ›

Python deals with memory management for you, but that means it doesn't always make the optimal decisions. Python has a global interpreter lock (GIL) which largely makes multithreading ineffective in native python. Many other features like this all amount to python being extremely slow compared to C.

Why is Mojo faster than Python? ›

Difference #3: Speed

Mojo is designed for high-performance tasks through innovative compiler technologies like embedded caching, multithreading, and cloud distribution. It is compiled and generally faster than Python, which is an interpreted language.

Which code will run faster using an interpreter? ›

Interpreting code is slower than running the compiled code because the interpreter must analyze each statement in the program each time it is executed and then perform the desired action, whereas the compiled code just performs the action within a fixed context determined by the compilation.

Why is my Python code so slow? ›

GLOBAL INTERPRETER LOCK (GIL)

Unlike other popular programming languages including C# or JAVA, Python is dynamically typed and an interpreted language. It is slow primarily due to its dynamic nature and versatility.

Why is Python running so slow? ›

Python is a high-level programming language: The code of Python looks very similar to how humans think. For that reason, it must Separate the details of the computer from you: memory management, pointers,… Hence, it is slower than “lower-level language” like C.

How do I run Python code every 15 minutes? ›

Specify the schedule properties. For example, if you wanted to execute a python script every 15 minutes, set the Settings to Daily, then specify a Start date and time. Under the Advanced settings, check Repeat task every and set this to a value. Then set the for a duration of setting.

How to reduce the time complexity of a code in Python? ›

The easiest way to reduce the time complexity is to avoid a for loop whenever possible. Ideally, you may want to check the time complexity of time Python functions you use, and refactor your code by selecting the less complex functions.

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