The Only Python Cheat Sheet You Will Ever Need
In this article, I present the ultimate Python cheat sheet, covering over 95% of all Python 3 commands with examples. Designed for both beginners and experienced developers, it provides quick answers and efficient learning without overwhelming you with details.
Learning and remembering every fact about a new topic can be challenging, if not impossible. Cheat sheets are crafted to help you memorize and recall essential information swiftly, making them an efficient tool for learning and using new technologies.
The cheat sheet provided in this article is an invaluable resource for both beginners and experienced developers. For novices, it lowers the entry barrier, making Python more approachable. For experts, it serves as a quick refresher to sharpen their skills.
Download the Cheat Sheet
This comprehensive cheat sheet is completely free and easily accessible online. It covers over 95% of all Python 3 commands with examples. At the end of this article, you’ll find the detailed list of all topics covered. To make your learning process smoother and faster, do yourself a favor and utilize this cheat sheet. Download the cheat sheet here.
What Are Cheat Sheets?
Cheat sheets are indispensable tools. They come in handy to students in preparation of or during their exams but also to professionals who can use them as concise quick reference guides.
Cheat sheets provide a condensed, easy-to-access reference for key information. They allow beginners and experts to quickly look up important details without having to search through extensive documentation or manuals.
A well designed cheat sheet usually fits on one page and holds all the information related to one topic. Designing a cheat sheet can be challenging as they need to be both readable while being holistic.
Cheat Sheets for Computer Science
Cheat sheets for Computer Science are particularly useful. They contain all the most essential information about a specific subject or domain into a short format, covering syntax, commands, functions, shortcuts, and hotkeys.
Programming and software cheat sheets are extremely popular amongst computer science students and professionals who can quickly access information at one glance such as the syntax, commands, functions, shortcuts, or hotkeys.
Benefits of Programming Cheat Sheets
Cheat sheets are valuable tools for both novice and experienced programmers. Here are some key benefits of Python Cheat sheet:
- Quick Reference: They save time by providing immediate answers to common questions.
- Learning Aid: They help reinforce learning by summarizing key concepts.
- Consistency: They promote adherence to coding standards and best practices.
- Productivity: They improve coding efficiency by offering quick solutions and reminders.
- Advanced Features: They include less frequently used commands or features that might not be memorized.
- Teaching and Collaboration: They are invaluable for teaching and assisting students with new concepts.
- Compact and Portable: They are easy to carry and use in different environments, whether online or offline.
- Improved Code Quality: They help in writing cleaner and more efficient code by providing examples and best practices.
- Self-Reliance: They encourage independent problem-solving and learning.
- Motivation: They can inspire beginners to explore further and experts to keep their skills sharp.
In summary, cheat sheets are versatile tools that enhance learning, improve productivity, ensure consistency, and promote best practices. They serve as an indispensable resource for both students and professionals in the programming community.
Python Cheat Sheet
The spread sheet I give below is completely free and easily accessible online. It contains over 95% of all Python 3 commands with examples. So remember, to make your learning process smoother and faster, utilize this cheat sheet.
To download the Python cheat sheet click here.
Topics Covered in the Cheat Sheet
This cheat sheet covers the following concepts:
Page 1
Data Types
- Text Type: str
- Numeroc Type: int, float, complex
- Boolean Type: bool
- Sequence Types: List (list), Tuple (tuple), Range (range)
- Set Type: Set (set)
- Mapping Type: Dictionary (dic)
Data Type Conversions
- Integer and Float Conversions: float(), int()
- Real to Complex Data Type Conversion: complex()
- Data Type Conversion with Strings: int(), str()
- Type Conversion to Tuples and Lists: tuple(), list()
- Type Conversion to Dictionaries and Sets: set(), dict()
- Convert Binary to Decimal: bin(), int()
- Convert Hexadecimal to Decimal: hex(), int()
- Convert Text to Decimal: ord(), chr()
Booleans
- Booleans as Numbers
- Comparison Operators: ==, !=, <, >, <=, >=
- Membership and Identity Operators: in, not in, is, is not
- Boolean Operators: not, and, or
Operator Precedence
Print Function
- print(), sep, end
User Input
- input()
Decision Structure
- if-then-elif-else statements
Repetition Structures
- While statement
- For statement
Exceptions
- FileNotFoundError, IndexError, KeyError, ModuleNotFoundError, NameError, SyntaxError, TypeError, ValueError, ZeroDivisionError
Modules
- import statement
- from… import statement
Files
- open(), close(), read(), readline(), readlines()
- access modes: read, write, append, create
Strings
- String Delimiters: single quotes, double quotes, triple single quotes, triple double quotes
- Escape Sequences
- String Operations: concatenation, repetition
- String Length: len()
- Unicode Code/Text Conversion: ord(), chr()
- String Membership: in, not in
- String Indexing
- String Slicing
- String Slicing Steps
- String Methods: upper(), lower(), isupper(), islower(), count(), endswith(), find(), index(), isalnum(), isalpha(), isdecimal(), isdigit(), isnumeric(), strip(), rstrip(), lstrip(), split(), replace()
- Iterating over Strings
Page 2
Lists
- List Creation: list()
- List Comprehension
- List Indexing
- List Slicing
- List Length: len()
- List Membership: in, not in
- List Comparison: ==, !=, <, >, <=, >=
- List Manipulation
- List Concatenation and Repetition
- Adding Elements: append(), extend(), insert()
- Removing Elements: remove(), pop()
- Deleting Elements: del
- List Counting, Searching, and Sorting: count(), index(), reverse(), sort()
- String-to-List and Back: split(), join()
- List Built-in Functions: all(), any(), len(), list(), max(), min(), reversed(), sorted(), sum(), tuple(), zip()
- Iterating over Lists
Tuples
- Tuple Creation: tuple()
- Tuple Unpacking
- Tuple Built-in Functions: all(), any(), count(), enumerate(), filter(), index(), len(), list(), map(), max(), min(), next(), reversed(), slice(), sum(), sorted(), tuple(), zip()
- Tuple Operations: indexing, slicing, concatenation, repetition, membership
- Iterating over Tuples
Sets
- Set Creation: set()
- Adding Elements: add(), update()
- Removing Elements: remove(), discard()
- Set Operations: union, intersection, difference, symmetric difference, subset, superset
- Iterating over Sets
Dictionaries
- Dictionary Creation: dict()
- Dictionary Length: len()
- Key Membership: in, not in
Retrieving a Value Given a Key
- get()
Adding a Key/Value Pair
Updating a Key/Value Pair
Deleting a Key/Value Pair
- del()
Dictionary Methods
- get(), items(), keys(), pop(), popitem(), update(), clear()
Iterating over Dictionaries
Similarities & Differences
- Ordered
- Duplicates allowed
- Mutable
- Comparison
- Access elements
- Slicing
- Concatenation,
- Repetition
- Iteration
About the Author
Promethee Spathis is a Professor of Practice in Computer Science at NYU Shanghai. He is also a Senior Associate Professor in the Faculty of Science & Engineering at Sorbonne Université, France. He received both his Masters and PhD degree in Computer Science from Sorbonne Université.
With a primary focus on Computer Science, Professor Spathis has designed and developed a wide array of courses spanning B.Sc, M.Sc, and Ph.D. levels. At NYU Shanghai, he currently teaches courses in computer networking and computer programming, bringing his extensive expertise and innovative teaching methods to the classroom. His commitment to education and research continues to inspire and shape the next generation of computer scientists.
Keywords
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