10 Top Python Cheat Sheets
- Website Setup
- Programming With Mosh
- Python for Data Science
- Real Python
- Python Crash Course
- Python for Data Science
- Basic and Intermediate Cheat Sheet for Python
Python is the ultimate language for developers thanks to its unique, flexible and simplified syntax and its robust developer community.
Globally known applications such as BitTorrent, DropBox and YouTube all use Python to achieve their functionality, and the number of applications using Python is only increasing.
What Is a Python Cheat Sheet?
While you may understand Python and its concept, it’s impossible to remember everything about the language.
Even the most experienced developers can easily forget how to slice a list, make various character classes for a regex or create a loop.
This is where Python cheat sheets come into play. They help you find solutions without worrying about unnecessary details. They make it straightforward so that you don’t need to remember everything about the language.
These cheat sheets provide a basic reference for beginners and advanced developers. Along with lowering the entry barrier for newcomers, they can also help veterans refresh their old Python tricks.
Top Python Cheat Sheets
Now that we’ve discussed what a Python cheat sheet is and how they’re a critical help for developers, let’s examine some of the top Python cheat sheets used by developers across the globe.
Every cheat sheet comes with its benefits and drawbacks, but the cheat sheets ranked here are some of the most popular and widely used in Python. They can help you up your Python game like nothing else.
Pythoncheatsheet.org is, without a doubt, an all-inclusive Python cheat sheet that has been the first in the ranking for Python cheat sheets for many years.
It covers both Python basics and an extensive support for exception handling and virtual environments.
It’s a complete cheat sheet for both beginner and experienced developers. On top of that, it has a strong community and offers continuous updates to cover all the bugs and include new functions.
2. Website Setup
Website Setup is another excellent Python cheat sheet that closely follows Pythoncheatsheet.org in terms of ranking.
It’s an extensive cheat sheet that covers all primary and secondary concepts for Python and how to create strings and troubleshoot errors.
The primary and intermediate concepts that Website Setup covers in Python include defining functions, lists, data types, loops, dealing with exceptions, math operators, tuples, conditional statements and dictionaries, etc.
3. Programming With Mosh
This cheat sheet is named after Mosh Hamedani, its founder and a software engineer who runs the Programming With Mosh YouTube channel. He also offers a Python 3 cheat sheet that covers various topics regarding Python 3.
In the cheat sheet that Mosh Hamedani offers, we can see that almost all the basics of Python have been covered, just like they are in Pythoncheatsheet.org.
However, there’s a lot more to this sheet compared to the previous cheat sheets.
In this one, we can find topics like arithmetic operations, operators, receiving inputs, packages, standard libraries, if statements, PyPI, inheritance, and a lot more.
It’s essential to know that the topics we have mentioned here are hardly ever covered in other Python cheat sheets.
4. Python for Data Science
That doesn’t mean that it only covers data science. It does include almost all the basics of Python, which is equally helpful for developers. Still, it’s a one-page cheat sheet that aims to provide quick answers to data types and conversions, lists, operations, libraries, NumPy arrays, methods, variables and calculations, strings and functions methods and how to install Python.
5. Real Python
Real Python is another extensive yet straightforward Python cheat sheet that can help developers in their Python-related tasks. It not only covers the basics of Python, but it does so with syntax and practical examples.
Apart from the primary topics that it covers, Real Python deals with strings, Booleans, numbers, functions, control statements and loops.
Since it covers numbers, it’s also a useful resource for data scientists. To make it more friendly for data scientists, Real Python also covers tuples, advanced list comprehensions, numerical lists and almost everything that a data scientist working with Python could ask for.
Unlike some of the other cheat sheets we have covered before, Cheatography is a two-page cheat sheet that can help you find quick solutions for your Python projects.
It primarily covers Python sys topics like Python
sys.argv, file methods, list methods, datetime methods, Python os variables, Python indexes and slices, unique methods and string methods, etc.
Cheatography for Python includes both operating system and built-in system variables, on top of standard methods for working with strings, lists, files and a lot more. You can easily download Cheatography for free in PNG or PDF version, or simply view it online.
Gto76 is a very extensive Python cheat sheet offered by GitHub that should be your go-to cheat sheet when you are working on a Python project. GitHub has ensured that it’s a complete guide for developers and data scientists and that it’s equally helpful for beginners and experts.
Gto76 covers Python topics such as range, enumerates, dictionaries, generator, covers lists, iterator and tuple. It’s also a complete cheat sheet for issues like data types, logging, scraping, NumPy, games, data, image, introspection, metaprogramming, operators, audio and threading, etc.
8. Python Crash Course
Python Crash Course is another practical, multi-paged Python cheat sheet designed to help beginners but also serve professional and expert developers.
It primarily focuses on Python lists, i.e., how to build and modify a list, access elements from a list and loop through the values in a given list.
It also covers numerical lists, advanced list comprehensions, tuples and almost everything else you need to know about lists.
Python Crash Course isn’t just a cheat sheet for lists, however, as it also touches on essential topics like variables, classes, dictionaries and functions, etc. If you’re a beginner in Python, this is the perfect cheat sheet to help you move to the next level.
9. Python For Data Science (Bokeh)
This is a handy cheat sheet for interactive plotting and statistical charts with Bokeh, specially designed for data scientists.
Bokeh has always distinguished itself from many other Python visualization libraries such as Seaborn and Matplotlib in a way that is a very interactive visualization library that is perfectly designed for beginners and advanced data scientists who want to quickly and easily create data interactive plots, dashboards, and other data applications.
Bokeh cheat is designed to make you familiar with how data can be prepared, how you can create a new plot, and how you can add renderers for your data with a variety of custom visualizations, how you want to output your plot and show/save it.
10. Basic and Intermediate Cheat Sheet for Data Science
While the basic part of this cheat sheet deals with all the basic concepts that we have read in other cheat sheets, the intermediate portion of this cheat sheet by
DATAQUEST is designed for expert developers.
Its intermediate part assumes that you have all the basic knowledge of Python. You won’t be able to make the most of it unless you completely understand the basics.
This cheat sheet will help you deal with range, lists, logging, scraping, NumPy, iterator, tuple and data types, etc. However, if you don’t understand these topics at an advanced level, you should consult with the basic part of this cheat sheet. Only then will you be able to use the intermediate cheat sheet.
Advantages of a Python Cheat Sheet
We have covered almost all the necessary cheat sheets that you need to know for beginners and advanced levels. While some developers can remember everything about Python, most have trouble remembering every little thing. This ends up making the process of development very time consuming.
Python cheat sheets are helpful for both types mentioned above of developers and data scientists, as it offers quick Python solutions without worrying about remembering every bit of Python.