Python Basics Reference

A comprehensive guide to Python fundamentals. Use this as your go-to reference for Python syntax, data structures, and common operations.

Core Operations

Arithmetic & Comparison

• Power:

  3**2

  (not

  3^2

  )
• Division:

  2/3

  returns

  0

  (int division in Python 2), use

  2.0/3.0

  for decimals
• Comparisons:

  >=

  ,

  <=

  ,

  ==

  ,

  !=

• Logic:

  and

  ,

  or

  ,

  not

Type Conversions

float(a)    # Convert to float
int(a)      # Convert to int
str(d)      # Convert to string
ord("A")   # Returns 65 (ASCII)
chr(65)     # Returns 'A'
hex(100)    # Returns '0x64'
hex(100)[2:] # Returns '64' (without 0x prefix)
isinstance(1, int)  # Returns True

String Operations

"a b".split(" ")      # ['a', 'b']
" ".join(['a', 'b'])  # "a b"
"abcdef".startswith("ab")  # True
"abc\n".strip()        # "abc"
"apbc".replace("p", "")  # "abc"
"a".upper()            # "A"
"A".lower()            # "a"
"abc".capitalize()     # "Abc"

String Indexing & Slicing

'abc'[0]      # 'a'
'abc'[-1]     # 'c' (last character)
'abc'[1:3]    # 'bc' (from index 1 to 2)
"qwertyuiop"[:-1]  # 'qwertyuio' (all except last)

String & List Concatenation

3 * 'a'       # 'aaa'
'a' + 'b'     # 'ab'
'a' + str(3)  # 'a3'
[1,2,3] + [4,5]  # [1,2,3,4,5]

Data Structures

Lists

d = []                    # Empty list
a = [1, 2, 3]
b = [4, 5]
a + b                     # [1, 2, 3, 4, 5]
b.append(6)               # [4, 5, 6]
tuple(a)                  # (1, 2, 3) - convert to tuple
sum([1, 2, 3])            # 6
sorted([1, 43, 5, 3, 21, 4])  # [1, 3, 4, 5, 21, 43]

Tuples

t1 = (1, '2', 'three')
t2 = (5, 6)
t3 = t1 + t2              # (1, '2', 'three', 5, 6)
(4,)                      # Singleton tuple (note the comma)
d = ()                    # Empty tuple
d += (4,)                 # Add to tuple
list(t2)                  # [5, 6] - convert to list
# t1[1] = 'New value'     # ERROR: tuples are immutable

Key difference: Tuples have structure (position gives meaning), lists have order.

Dictionaries

d = {}                                    # Empty dict
monthNumbers = {1: 'Jan', 2: 'Feb', 'Feb': 2}
monthNumbers[1]                           # 'Jan'
monthNumbers['Feb']                       # 2
list(monthNumbers)                        # [1, 2, 'Feb'] (keys)
monthNumbers.values()                     # ['Jan', 'Feb', 2]
monthNumbers.keys()                       # dict_keys([1, 2, 'Feb'])
monthNumbers.update({'9': 9})             # Add/update entries
mN = monthNumbers.copy()                  # Independent copy
monthNumbers.get('key', 0)                # Return value or 0 if key doesn't exist

Sets

myset = set(['a', 'b'])                   # {'a', 'b'}
myset.add('c')                            # {'a', 'b', 'c'}
myset.add('a')                            # No change (no duplicates)
myset.update([1, 2, 3])                   # {'a', 'b', 'c', 1, 2, 3}
myset.discard(10)                         # Remove if present, no error if not
myset.remove(10)                          # Remove if present, error if not
myset.union(myset2)                       # Values in myset OR myset2
myset.intersection(myset2)                # Values in myset AND myset2
myset.difference(myset2)                  # Values in myset but not myset2
myset.symmetric_difference(myset2)        # Values in either but not both
myset.pop()                               # Remove and return arbitrary element
myset.intersection_update(myset2)         # myset = intersection
myset.difference_update(myset2)           # myset = difference

Control Flow

Conditionals

if a:
    # something
elif b:
    # something
else:
    # something

Loops

while(a):
    # something

for i in range(0, 100):      # 0 to 99
    # something

for letter in "hola":       # Iterate over string
    # something with letter

Comments

# One line comment
"""
Several lines comment
Another one
"""

Functions & Advanced Concepts

Lambda Functions

# Simple function
(lambda x, y: x + y)(5, 3)  # 8

# Sort with lambda
sorted(range(-5, 6), key=lambda x: x**2)  # [0, -1, 1, -2, 2, ...]

# Filter with lambda
filter(lambda x: x % 3 == 0, [1, 2, 3, 4, 5, 6, 7, 8, 9])  # [3, 6, 9]

# Create function factory
def make_adder(n):
    return lambda x: x + n
plus3 = make_adder(3)
plus3(4)  # 7

# Lambda in class
class Car:
    crash = lambda self: print('Boom!')
my_car = Car()
my_car.crash()  # Boom!

Map, Filter, Zip

# Map: apply function to all elements
m = map(lambda x: x % 3 == 0, [1, 2, 3, 4, 5, 6, 7, 8, 9])
# [False, False, True, False, False, True, False, False, True]

# Zip: combine iterables (stops at shortest)
for f, b in zip(foo, bar):
    print(f, b)

# Filter: keep elements matching condition
m = filter(lambda x: x % 3 == 0, [1, 2, 3, 4, 5, 6, 7, 8, 9])
# [3, 6, 9]

List Comprehensions

# Filter in one line
mult1 = [x for x in [1, 2, 3, 4, 5, 6, 7, 8, 9] if x % 3 == 0]
# [3, 6, 9]

# Map in one line
squared = [x**2 for x in range(10)]
# [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

Classes

Basic Class

class Person:
    def __init__(self, name):
        self.name = name
        self.lastName = name.split(' ')[-1]
        self.birthday = None
    
    def __lt__(self, other):  # For sorting
        if self.lastName == other.lastName:
            return self.name < other.name
        return self.lastName < other.lastName
    
    def setBirthday(self, month, day, year):
        from datetime import date
        self.birthday = date(year, month, day)
    
    def getAge(self):
        from datetime import date
        return (date.today() - self.birthday).days

Inheritance

class MITPerson(Person):
    nextIdNum = 0  # Class attribute
    
    def __init__(self, name):
        Person.__init__(self, name)
        self.idNum = MITPerson.nextIdNum
        MITPerson.nextIdNum += 1
    
    def __lt__(self, other):
        return self.idNum < other.idNum

Error Handling

Try-Except

def divide(x, y):
    try:
        result = x / y
    except ZeroDivisionError as e:
        print("division by zero!" + str(e))
    except TypeError:
        divide(int(x), int(y))
    else:
        print("result is", result)
    finally:
        print("executing finally clause in any case")

Assertions

def avg(grades, weights):
    assert len(grades) != 0, 'no grades data'
    assert len(grades) == len(weights), 'wrong number of grades'
    # ... rest of function

Generators

def myGen(n):
    yield n
    yield n + 1

g = myGen(6)
next(g)  # 6
next(g)  # 7
next(g)  # StopIteration error

Why use generators: They save memory by yielding values one at a time instead of creating a full list.

Regular Expressions

import re

re.search(r"\w", "hola").group()      # "h"
re.findall(r"\w", "hola")             # ['h', 'o', 'l', 'a']
re.findall(r"\w+(la)", "hola caracola")  # ['la', 'la']

Special Characters

.

\w

[a-zA-Z0-9_]

\d

\s

 \n\r\t\f

\S

^

$

+

*

?

Options

re.search(pat, str, re.IGNORECASE)  # Case insensitive
re.search(pat, str, re.DOTALL)      # Dot matches newline
re.search(pat, str, re.MULTILINE)   # ^ and $ match per line

Non-greedy Matching

re.findall(r"<.*>", "<b>foo</b>and<i>so on</i>")
# ['<b>foo</b>and<i>so on</i>'] (greedy - matches everything)

re.findall(r"<.*?>", "<b>foo</b>and<i>so on</i>")
# ['<b>', '</b>', '<i>', '</i>'] (non-greedy - matches minimally)

Itertools

from itertools import product, permutations, combinations, combinations_with_replacement

# Cartesian product
list(product([1, 2, 3], [3, 4]))
# [(1, 3), (1, 4), (2, 3), (2, 4), (3, 3), (3, 4)]

list(product([1, 2, 3], repeat=2))
# [(1, 1), (1, 2), (1, 3), (2, 1), (2, 2), (2, 3), (3, 1), (3, 2), (3, 3)]

# Permutations (order matters)
list(permutations(['1', '2', '3']))
# [('1', '2', '3'), ('1', '3', '2'), ('2', '1', '3'), ...]

list(permutations('123', 2))
# [('1', '2'), ('1', '3'), ('2', '1'), ('2', '3'), ('3', '1'), ('3', '2')]

# Combinations (order doesn't matter, no repeats)
list(combinations('123', 2))
# [('1', '2'), ('1', '3'), ('2', '3')]

# Combinations with replacement
list(combinations_with_replacement('1133', 2))
# [('1', '1'), ('1', '1'), ('1', '3'), ('1', '3'), ('1', '1'), ('1', '3'), ('1', '3'), ('3', '3'), ('3', '3'), ('3', '3')]

Decorators

from functools import wraps
import time

def timeme(func):
    @wraps(func)
    def wrapper(*args, **kwargs):
        print("Let's call our decorated function")
        start = time.time()
        result = func(*args, **kwargs)
        print(f'Execution time: {time.time() - start:.6f} seconds')
        return result
    return wrapper

@timeme
def decorated_func():
    print("Decorated func!")

decorated_func()
# Output:
# Let's call our decorated function
# Decorated func!
# Execution time: 0.000048 seconds

Quick Reference

Python 2 vs 3

• range()

  in Python 3 =

  xrange()

  in Python 2 (generator, not list)

• print

  is a function in Python 3:

  print("hello")

• Division:

  2/3

  =

  0

  in Python 2,

  0.666...

  in Python 3

Getting Help

dir(str)      # List all available methods
help(str)      # Show class definition
help(function_name)  # Show function documentation

Common Patterns

# Check if key exists in dict
if key in my_dict:
    value = my_dict[key]

# Or use get() with default
value = my_dict.get(key, default_value)

# Iterate with index
for i, item in enumerate(items):
    print(i, item)

# Iterate two lists together
for a, b in zip(list1, list2):
    print(a, b)

# One-liner sum
sum([x**2 for x in range(10)])  # 285

When to Use This Skill

Use this skill when:

• Learning Python basics or reviewing syntax
• Need quick reference for data structures
• Writing Python code and need to recall operations
• Debugging Python code
• Teaching Python to others
• Converting between data types
• Working with strings, lists, dicts, sets, or tuples
• Need help with regex patterns
• Understanding generators, decorators, or lambda functions