Python Reference Sheet
Why Use Python
Python is a powerful and user-friendly programming language known for its open-source nature, community-driven development, and cross-platform compatibility. As a high-level language, it abstracts away complex details of computer hardware, allowing programmers to focus on the logic of their code.
One of Python's key strengths is its readability. It utilizes clear syntax, making code easier to understand and maintain, both for beginners and experienced developers alike. Additionally, Python is dynamically typed, meaning variable types are determined at runtime, offering flexibility during development.
Beyond its ease of use, Python boasts a robust standard library, providing a rich set of built-in modules for common tasks like file handling, networking, and data manipulation. This extensive library, coupled with the vast ecosystem of third-party modules available for download, empowers developers to tackle a wide range of challenges.
The versatility of Python extends to its diverse applications. It is a popular choice for web development, system scripting, and scientific computing due to its powerful mathematical libraries. In recent years, Python has become a prominent language in the fields of artificial intelligence and machine learning, with frameworks like TensorFlow and PyTorch leveraging its capabilities.
Note:
Most of the code examples are written using Python REPL (i.e. '>>>'), this makes testing small segments of code easier. REPL is an acronym for Read, Evaluate, Print, and Loop. Developers use REPL Python to communicate with the Python Interpreter. In contrast to running a Python file, you can input commands in the REPL and see the results displayed immediately. Anything after a ":" will require an indent represented by the three dots ('...'). To access the REPL, just type python3 or python.
For example:
>>> for i in range(5, 10):
... print(i)
Table of Contents
Why Use Python
Using Lists in Python (Examples)
Using Dictionaries in Python (Examples)
Defining Custom Functions in Python
Python Loops (For and While) and Switch
Python Interviewing Reference Materials
Important Python Tips
Below are important tips to remember when programming in Python:
Indentation Matters: Consistent indentation is crucial in Python for defining code blocks.
Meaningful Variable Names: Choose descriptive variable names that clearly reflect their purpose, improving code readability.
Print vs. Return: Grasp the distinction between print (outputs data) and return (sends data back from a function).
Zero-Based Indexing: Remember that strings and lists in Python start indexing at 0, not 1.
Quotes for Strings: Always enclose strings within single or double quotes.
return Inside Functions: The return keyword is only valid within function definitions.
Colons for Structure: Use colons (':') to denote conditionals (if statements), function definitions, and loops.
Type Compatibility: You cannot directly add strings and integers without type conversion (casting).
Valid Names: Variable and function names cannot contain spaces.
Python Basics
These are the basic things you need to know to use Python for programming.
Printing a number
>>> print(123)
123
Printing a string
>>> print("test")
test
Adding two numbers (you can also use the following operators: '-', '/', '*', etc.)
>>> print(2+2)
4
Division (result is a floating point number) and Floor Division (result is an integer number)
>>> 5//2
2
>>> 5/2
2.5
Variable assignment (using '=' [equal sign] to put a value into a variable)
>>> number = 123456
Print a variable
>>> print(number)
123456
Function call (to run the code of the function)
>>> x = min(1, 2)
>>> print(x)
1
Comment (single line)
# a comment
Comment (multiple lines)
"""
Multiline comment
"""
Built-in Python Data Types
Data types are used for storing different types of data (i.e. integers, floating, strings, etc.). It is important to note that Pyton is a Dynamically Typed language. So when you assign a value to variable, it will automatically try to figure out what its data types is.
Integer (no decimal point):
42
Floating Point (has a decimal point):
42.5
String (a sequence of letters surrounded by quotes)
"a string"
List (a type of value that holds other values, and can be change [i.e. mutable])
[1, 2, 3, ...] | ['a', 'b', 'c', ...]
Tuple (like a list, but cannot be changed [i.e. immutable])
(1, 2, 3, ...) | ['a', 'b', 'c', ...]
Dictionary (a mapping from keys to values)
{"a":1, "b":2, "c":3, ...}
Boolean (Can only be True or False)
True | False
Built-in Python Functions
This section displays useful built-in functions for performing different types of actions or operations.
Calculate length the size (i.e. the amount of object it contains) of a variable.
>>> len("test")
4
Display the minimum value of the data passed as a parameter (i.e. 1, 2, 3 would be 1, a, b, c would be a)
>>> min(1, 2)
1
Display the maximum value of the data passed as a parameter (i.e. 1, 2, 3 would be 3, a, b, c would be c)
>>> max(1, 2)
2
Cast a value as an integer
>>> int("123")
123
Cast a value as a string
>>> str(123)
'123'
Cast a value as a boolean
>>> bool(1)
True
Display a range of numbers
>>> for i in range(5, 10):
... print(i)
5
6
7
8
9
Other Useful Python Syntax
Below are examples of useful syntax in Python
Returning a value from custom function
>>> def test():
... return "abc"
>>> print(test())
abc
Indexing (extracting one element at a certain position)
>>> "test"[0]
't'
>>> "test"[1]
'e'
Slicing (extracting some elements in a series from a string)
>>> "test"[1:3]
'es'
Continue to next loop iteration (stop processing at the position in the loops and starts at the next number)
continue
Exits a loop at the point where this statement is located.
break
Appending elements to a list
>>> numbers = [123,456,789]
>>> numbers.append(987)
>>> print(numbers)
[123, 456, 789, 987]
Getting a value from a list
>>> numbers = [123,456,789]
>>> value = numbers[0]
>>> print(value)
123
Replacing a value in a list
>>> numbers = [123,456,789]
>>> print(numbers)
[123, 456, 789]
>>> numbers[0] = 321
>>> print(numbers)
[321, 456, 789]
The Walrus Operator is represented by the `:=` syntax and can be used in a variety of contexts including while loops and if statements. (Requires: Python 3.8 or higher)
names = ["Jason", "Fred", "Jacob"]
if (name := input("Enter a name: ")) in names:
print(f"Hello, {name}!")
else:
print(f"Name {name} not found.")
Python Conditionals
Conditionals in Python allow for the controlling of logic when certain conditions are met.
>>> x = 2
>>> if x == 1:
... print("x is one")
... else:
... print("x is not one")
...
x is not one
Python Comparison Operators
The comparison operators in Python are used by conditional logic (i.e. if, while, etc.) for making boolean comparison.
Equals Operator
>>> a = 2
>>> if a == 1:
... print(True)
False
Not Equals Operator
>>> a = 2
>>> if a != 1:
... print(True)
True
Less than Operator
>>> a = 2
>>> if a < 1:
... print(True)
False
Less Than or Equal Operator
>>> a = 2
>>> if a <= 1:
... print(True)
False
Greater than Operator
>>> a = 2
>>> if a > 1:
... print(True)
True
Greater Than or Equal Operator
>>> a = 2
>>> if a >= 1:
... print(True)
True
Using Lists in Python (Examples)
List (a type of value that holds other values, and can be change [i.e. mutable])
>>> numbers = [7, 8, 9]
>>> first_number = numbers[0]
7
>>> numbers[2] = 11
>>> if 11 in numbers:
... print("11 is in the list!")
11 is in the list!
>>> for n in numbers:
... print(n)
[7, 11, 9]
Using Dictionaries in Python (Examples)
The dictionary data type allows the mapping of keys to values.
>>> numbers = {1: "one", 2: "two"}
>>> print(numbers[1])
one
>>> print(numbers[2])
two
Defining Custom Functions in Python
A custom function is a reusable set of code where arguments can be passed, and new value returned
>>> def my_func (a, b):
... result = a + b
... return result
>>> if __name__ == '__main__':
... print(my_func(5, 10))
15
Python Loops (For and While) and Switch
Python supports two different types of loops (i.e. For and While), and recent versions of Python now support switches
For Loop Example
>>> for numbers in [1, 2, 3, 4, 5]:
... print(numbers)
While Loop Example
>>> a = 0
>>> while a < 10:
... print(a)
... a = a + 1
Switch Statement: The switch case feature called “structural pattern matching”. (Requires: Python 3.10 or higher)
>>> fruit = "apple"
>>> match fruit:
... case "apple":
... print("This is an apple!")
... case "banana":
... print("This is a banana!")
... case "orange":
... print("This is an orange!")
... case _: # This is the default case
... print("This is an unknown fruit.")
Useful Python Methods
Below is a list of useful Python methods that you can use in your coding.
String to lowercase
>>> "AA".lower()
'aa'
String to uppercase
>>> "aa".upper()
'AA'
Splits a string using spaces into a list
>>> "a b c".split(" ")
['a', 'b', 'c']
Removes unused whitespace around a string
>>> " this is a test ".strip()
'this is a test'
Combines a list of strings into one string with a space between the different elements
>>> " ".join(["a", "b", "c"])
'a b c'
Checks if a string starts with a substring
>>> "AA".startswith("a")
False
Checks if a string ends with a substring
>>> "AA".endswith("A")
True
Checks for the occurrence of an element in a list
>>> [1, 2, 3, 4, 4, 5].count(4)
2
Remove an element from a list
>>> a = [1, 2, 3, 4, 5]
>>> a.remove(2)
>>> print(a)
[1, 3, 4, 5]
Dictionary keys
>>> {1:2, 3:4, 5:6}.keys()
dict_keys([1, 3, 5])
Dictionary values
>>> {1:2, 3:4, 5:6}.values()
dict_values([2, 4, 6])
Dictionary key/value pairs
>>> {1:2, 3:4, 5:6}.items()
dict_items([(1, 2), (3, 4), (5, 6)])
Bonus Python Information
Below are some bonus tips that can help you.
Zipping two lists (i.e. converting two lists into a dictionary)
>>> numbers = [1, 2]
>>> words = ["one", "two"]
>>> combined = list(zip(numbers, words))
>>> print(combined)
[(1, 'one'), (2, 'two')]
Set intersection (which element is in both sets)
>>> {1, 2} & {2, 3}
{2}
Set union (which elements are unique to both sets)
>>> {1, 2} | {2, 3}
{1, 2, 3}
Finds the index value of an element in a list.
>>> [1, 2, 3].index(2)
1
Sorts the order of a list of elements
>>> a = [3, 2, 1]
>>> a.sort()
>>> print(a)
[1, 2, 3]
Reverses the order of a list of elements
>>> a = [1, 2, 3]
>>> a.reverse()
>>> print(a)
[3, 2, 1]
Sums the value of a list of elements
>>> sum([1, 2, 3])
6
Numbering a list of elements (displays the index and value of different elements)
>>> a = [1, 2, 3]
>>> for i, item in enumerate(a):
... print(i,item)
...
0 1
1 2
2 3
Read a file line by line
with open("sample_file.txt", "r") as file:
# Read all lines of the file and store them in a list
lines = file.readlines()
# Print each line
for line in lines:
print(line, end="") # Print without adding a newline at the end
Reads and writes a file contents
# Simulate a file with some content
fake_file_content = "This is some sample text content."
# Using with clause to open and close the file automatically
with open("sample_file.txt", "w") as file: # Open in write mode for this example
file.write(fake_file_content) # Write the content to the file
# Now, read the contents using another with clause (assuming the file exists)
with open("sample_file.txt", "r") as file:
contents = file.read()
print(contents)
Generate a random number between 1 and 10
>>> import random
>>> x = random.randint(1, 10)
>>> print(x)
6
List comprehensions (a syntax construction to ease the creation of a list based on existing iterable.)
>>> a = [i for i in range(1, 5)]
>>> print(a)
[1, 2, 3, 4]
Checks if ANY condition holds
# Check if any element in a list is greater than 5
numbers = [1, 3, 7, 2, 4]
is_any_greater_than_5 = any(element > 5 for element in numbers)
# Print the result
print(is_any_greater_than_5) # Output: True
Checks if ALL conditions hold
my_list = [True, True, True, True]
all_true = all(my_list)
print(all_true) # Output: True
Lambda function (an anonymous function. This function can have any number of parameters but, can have just one statement. )
>>> a = lambda a, b : a*b
>>> print(a(5, 10))
50
Python Exceptions
A Python exception is an event that occurs during the execution of a program that disrupts the normal flow of the program.
Python exception syntax using try, except, else, and finally statements
try:
# Code...
except:
# optional block
# Handling of exception (if required)
else:
# execute if no exception
finally:
# Code... (always executed)
Exception Groups: Can be handled using a new except* syntax. The * symbol indicates that multiple exceptions can be handled by each except* clause. (Requires: Python 3.11 or higher)
try:
raise ExceptionGroup('Example ExceptionGroup', (
TypeError('Example TypeError'),
ValueError('Example ValueError'),
KeyError('Example KeyError'),
AttributeError('Example AttributeError')
))
except* TypeError:
...
except* ValueError as e:
...
except* (KeyError, AttributeError) as e:
...
Python Terminology
Argument: Input given to a function (like putting something in the machine)
Function: Reusable block of code (takes input, gives output)
Loop: Repeats a block of code (like doing something over and over)
Parameter: Input defined for a function (like a machine slot)
Return Value: Output from a function (like what the machine gives back)
Syntax: The rules for writing code correctly (like grammar for computers)
Value: Stores data (numbers, text, True/False)
Variable: Storage space in the computer's memory for value
Python Interviewing Reference Materials
Coding Exercises
Books