While Python is easy to learn and still highly used, sometimes there are many small details in the code snippets which is not possible to remember always. This is where Python Cheat Sheets come into the picture to save your day. So, we curated a list of some of the amazing Python Cheat Sheets that every expert developer should have bookmarked.
What are Python Cheat Sheets?
Python cheat sheets are concise guides you can refer to whenever you need to find some essential information about Python programming language. This can be summaries of syntax, common functions, libraries, and coding conventions.
- Syntax and Structure: Quick reference to Python syntax rules, such as how to define variables, write loops, and handle conditional statements.
- Functions and Methods: Lists of commonly used built-in functions and methods, along with their basic usage.
- Libraries and Modules: Information on standard libraries and modules, including key functions and how to import them.
- Data Structures: Summaries of Python’s data structures, such as lists, tuples, dictionaries, and sets, including common operations.
- String Operations: Tips on string manipulation, including formatting, slicing, and common methods.
- File Handling: Examples of reading from and writing to files.
- Error Handling: Basics of exception handling and common error messages.
- Useful Shortcuts and Commands: Handy shortcuts for common tasks, like list comprehensions, lambda functions, and more.
So, for beginners and even expert developers, they can be very useful. They can act as learning aids for beginners and memory aids for experienced ones. You can increase your productivity because you can quickly access important information about Python,
Following are some of the types of information they can provide:
7 Amazing Python Cheat Sheets
Here are the best Python Cheat Sheets available online that will make you adept with Python basics:
1. Python For Data Science Bokeh
The Python for Data Science Cheat Sheet for Bokeh is a handy reference guide designed to help data scientists quickly and efficiently create interactive visualizations using the Bokeh library.
Bokeh is a powerful, flexible, and interactive visualization library in Python that allows you to create complex, aesthetically pleasing plots that can be embedded into web applications.
As an extremely interactive visualization library, Bokeh has always set itself apart from many other Python visualization libraries, like Seaborn and Matplotlib. It is ideal for both novice and expert data scientists who wish to quickly and simply create data interactive plots, dashboards, and other data applications.
Example Content from the Cheat Sheet:
from bokeh.plotting import figure, output_file, show
from bokeh.io import output_notebook
# Basic Plot Setup
output_notebook() # Render plots in Jupyter notebooks
output_file("plot.html") # Save plot to an HTML file
# Create a new plot
p = figure(title="Basic Bokeh Plot", x_axis_label='x', y_axis_label='y')
# Add a line renderer
p.line([1, 2, 3, 4, 5], [6, 7, 2, 4, 5], legend_label="Temp.", line_width=2)
# Show the plot
show(p)This sheet can familiarize you with the preparation of data, the creation of new plots, the addition of renderers for a range of unique visualizations, and the output and display/save of your plots.
Having the Python for Data Science Cheat Sheet for Bokeh at your disposal can greatly enhance your ability to create and customize interactive visualizations, making it a valuable tool for any data scientist working with Python.
2. gto76
The gto76 Python Cheat Sheet is a comprehensive, user-friendly reference guide designed to cover a wide array of Python topics. It’s particularly appreciated for its thoroughness and the breadth of information it provides, making it a valuable resource for both beginners and experienced Python developers.
Python concepts including range enumerates, dictionaries, generators, covers lists, iterator, and tuple are covered in GTO76. Additionally, it serves as a comprehensive reference for topics such as operators, audio, threading, games, data, images, logging, scraping, NumPy, introspection, and metaprogramming.
Example Content from the Cheat Sheet:
#Tuple's subclass with named elements.
>>> from collections import namedtuple
>>> Point = namedtuple('Point', 'x y')
>>> p = Point(1, y=2)
Point(x=1, y=2)
>>> p[0]
1
>>> p.x
1
>>> getattr(p, 'y')
2
#iterator
<iter> = iter(<collection>) # `iter(<iter>)` returns unmodified iterator.
<iter> = iter(<function>, to_exclusive) # A sequence of return values until 'to_exclusive'.
<el> = next(<iter> [, default]) # Raises StopIteration or returns 'default' on end.
<list> = list(<iter>) # Returns a list of iterator's remaining elements.Overall, The gto76 Python Cheat Sheet is a valuable resource for any Python developer.
3. Pythoncheatsheet.org
The Pythoncheatsheet.org Python Cheat Sheet is a comprehensive and user-friendly reference guide designed to assist Python developers of all levels. It offers a wide array of topics, making it an excellent resource for quickly looking up syntax, functions, and best practices. It has been ranked as the number one Python cheat sheet for several years.
Functions, data structures, lists, JSON, loops, sets, debugging, YAML, data classes, context managers, and much more are covered by Pythoncheatsheet.org. Along with comprehensive support for virtual environments and exception handling, it also covers the fundamentals of Python.
Example Content from the Cheat Sheet:
#This is how we create a new list from an existing collection with a For Loop: >>> names = ['Charles', 'Susan', 'Patrick', 'George', 'Carol'] >>> new_list = [] >>> for n in names: ... new_list.append(n) >>> print(new_list) # ['Charles', 'Susan', 'Patrick', 'George', 'Carol'] #And this is how we do the same with a List Comprehension: >>> names = ['Charles', 'Susan', 'Patrick', 'George', 'Carol'] >>> new_list = [n for n in names] >>> print(new_list) # ['Charles', 'Susan', 'Patrick', 'George', 'Carol']
Furthermore, it has a robust community and gives frequent updates to fix all the flaws and add new features.
4. Zero To Mastery
The Zero To Mastery Python is a detailed and practical guide created by the Zero To Mastery Academy, which offers comprehensive programming courses. This cheat sheet is designed to help Python developers quickly access essential information and best practices, making it a valuable resource for both beginners and experienced programmers.
This cheat sheet not only covers basic topics such as detailed information on strings, numbers, lists, tuples, dictionaries, and sets, and instructions on using for and while loops, including loop control statements like break and continue. But also essential functions and methods for data manipulation and analysis.
Example Content from the Cheat Sheet:
#Strings in python are stored as sequences of letters in memory
type('Hellloooooo') # str
'I\'m thirsty'
"I'm thirsty"
"\n" # new line
"\t" # adds a tab
'Hey you!'[4] # y
name = 'Andrei Neagoie'
name[4] # e
name[:] # Andrei Neagoie
name[1:] # ndrei Neagoie
name[:1] # A
name[-1] # e
name[::1] # Andrei Neagoie
name[::-1] # eiogaeN ierdnA
name[0:10:2]# Ade e
# : is called slicing and has the format [ start : end : step ]
'Hi there ' + 'Timmy' # 'Hi there Timmy' --> This is called string concatenation
'*'*10 # **********
#True or False. Used in a lot of comparison and logical operations in Python
bool(True)
bool(False)
# all of the below evaluate to False. Everything else will evaluate to True in Python.
print(bool(None))
print(bool(False))
print(bool(0))
print(bool(0.0))
print(bool([]))
print(bool({}))
print(bool(()))
print(bool(''))
print(bool(range(0)))
print(bool(set()))
# See Logical Operators and Comparison Operators section for more on booleans.You can find this cheat sheet on the Zero To Mastery Academy’s website, often available as a downloadable PDF, and it is regularly updated to include the latest Python features and best practices.
5. Code With Harry
One of my favourite cheat sheets for Python. The Code With Harry Python Cheat Sheet is a concise and well-structured reference guide designed to help Python developers quickly access essential information about Python programming.
Code With Harry is a popular platform known for its programming tutorials and educational content, and this cheat sheet reflects the practical and beginner-friendly approach that the platform is known for.
It is designed for ease of use, making it an excellent tool for quick reference and revision. It covers a broad range of Python topics such as Classes, Functions, Networking, Data Handling and much more with succinct examples and is accessible for users at different levels of proficiency.
Example Content from the Cheat Sheet:
#class with a constructor
class CodeWithHarry:
# Default constructor
def __init__(self):
self.name = "CodeWithHarry"
# A method for printing data members
def print_me(self):
print(self.name)
#setter Decorator
@name.setter
def name(self, value):
self.__name=valueEach and every topic is explained properly with proper oriented code snippets.
6. Real Python
The Real Python is a well-organized and comprehensive reference guide created by Real Python, a trusted source of Python tutorials and resources. This cheat sheet is designed to help Python developers quickly find information on Python syntax, standard libraries, and common programming patterns.
Along with covering the fundamentals of Python, it also provides syntax and real-world examples.
Example Content from the Cheat Sheet:
#You can use the type method to check the value of an object. >>> type(3) <type 'int'> >>> type(3.14) <type 'float'> >>> pi = 3.14 >>> type(pi) <type 'float'> #You can also set default values for parameters. >>> def multiply(num1, num2=10): ... return num1 * num2 ... >>> multiply(2) 20
Real Python works with strings, Booleans, numbers, functions, control statements, and loops in addition to the main subjects it covers. It is also a helpful resource for data scientists because it deals with numbers. Real Python also provides tuples, advanced list comprehensions, numerical lists, and much everything a data scientist working with Python could ask for, making it more user-friendly for data scientists.
7. Memento Python 3
The Memento Python 3 is a concise and comprehensive guide designed to help Python developers quickly find the information they need about Python 3 syntax, features, and libraries. This cheat sheet is useful for both beginners and experienced developers, offering a handy reference for writing and understanding Python code.
This cheat sheet contains a variety of topics and sections such as Variable Assignments, Conditional Statements, File Handling, Error Handling and much more. It also contains code snippets on sequential operations such as indexes, lists, dictionaries and sets.
Example Content from the Cheat Sheet:
#Operations on Dictionaries d[key]=value d[key]→ value d.keys() d.values() d.items() d.clear() del d[key] →iterable views on keys/values/associations Examples d.pop(key[,default])→ value d.popitem()→ (key,value) d.get(key[,default])→ value d.setdefault(key[,default])→value #Operations on Strings s.startswith(prefix[,start[,end]]) s.endswith(suffix[,start[,end]]) s.strip([chars]) s.count(sub[,start[,end]]) s.partition(sep)→ (before,sep,after) s.index(sub[,start[,end]]) s.find(sub[,start[,end]]) s.is…() tests on chars categories (ex. s.isalpha()) s.upper() s.lower() s.title() s.swapcase() s.casefold() s.capitalize() s.center([width,fill]) s.ljust([width,fill]) s.rjust([width,fill]) s.zfill([width]) s.encode(encoding) s.split([sep]) s.join(seq)
It is a helpful resource for both beginners and experienced developers to quickly recall Python syntax and operations.
Conclusion
All these Python Cheat Sheets have been useful to me in my journey as a developer with Python. Go refer to these Cheat Sheets today and embark on a new journey with Python! You can also check these Python Libraries where you can also learn to dive deep into programming. And if you need more help with your Python assignment, we are always here for you!
