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Python Cheat Sheet
Syntax/Concept | Example | Explanation |
|---|---|---|
Print statement | print("Hello, world!") | Outputs the given text to the console |
Comments | # This is a comment | Comments are ignored by Python and are used to document code |
Multiline comment | """ | |
This is a multiline comment. | | |
It can span multiple lines without the need for multiple comment symbols. | | |
You can use it to document your code or temporarily disable a block of code. | | |
""” | | |
Variables | x = 5 | Variables are used to store data and can be assigned and reassigned values |
Data types | int, float, string, bool, list, tuple, dict, set | Different types of data that can be stored in variables |
Numeric operations | +, -, *, /, %, ** | Operators used for arithmetic operations |
Comparison operators | ==, !=, >, <, >=, <= | Operators used to compare values |
Logical operators | and, or, not | Operators used to combine and manipulate boolean values |
Conditional statements | if, elif, else | Statements used to conditionally execute code |
Loops | for, while | Statements used to iterate over a sequence of data |
Functions | def my_func():, return | Blocks of code that can be called and returned |
Lambda functions | lambda x: x + 1 | Anonymous functions used for simple operations |
Classes | class MyClass:, def init(self):, self | Used to define custom data types and associated functions |
List methods | append(), extend(), insert(), remove(), pop(), index(), count(), sort(), reverse() | Methods used to manipulate lists |
Tuple methods | count(), index() | Methods used to manipulate tuples |
Dictionary methods | keys(), values(), items(), get(), update(), pop(), popitem(), clear() | Methods used to manipulate dictionaries |
Set methods | add(), remove(), discard(), pop(), clear(), union(), intersection(), difference(), symmetric_difference() | Methods used to manipulate sets |
- Setting up a Python Development Environment
- Requirements: syntax highlighting, beautification, linter, IntelliSense: list members, parameter info, quick info, autocompletion,
- Why? Logically group our data and functions that we can easily reuse or build upon
- Terminology
- Attributes and methods - functions that is associated with class
- A class is a blueprint for creating instances
class Employee:
pass
# instances of a Employee classes
emp_1 = Employee()
emp_2 = Employee()
s
# unique data
#manually variable setting - prone to human error
emp_1.first = 'Corey'
emp_1.last = 'Scafer'
emp_1.email = '[email protected]'
emp_1.pay = '50000'
emp_2.first = 'Test'
emp_2.last = 'User'
emp_2.email = '[email protected]'
emp_21.pay = '60000'
######
class Employee:
def __init__(self,first,last,pay):
#set instance variable
self.first = first
self.last = last
self.pay =pay
self.email = first +'.' + last + '@company.com'
# each method within a class automatically takes the insance as the first argument
# and we always call that self
def fullname(self)
return '{}{}'.format(self.first,self.last)
# better solution: runs init automatically
emp_1 = Employee('Corey','Scafer',50000)
emp_2 = Employee('Test','User',60000)
print(emp_1.email)
print(emp_2.email)
# running actions
#manually
print('{}{}'.format)emp_1.first,emp_1,last))
# better
print(emp_1.fullname()) # notice the parenthesis as it is a method
#notes
#classes are kinda like function
# remember to put self in methods in class
emp_1.fullname() is same as Employee.fullname(emp_1))
Last modified 2mo ago