SRJahirTech

Python Full Tutorial -- Part 2: Variables & Data Types

By Suraj Ahir 2025-12-05 11 min read

Python is dynamically typed -- you do not declare what type a variable holds. Write x = 5 and Python knows x is an integer. Write x = "hello" and Python knows it is a string. This convenience is real, but understanding Python's type system deeply is still essential. Type mismatches cause bugs, and knowing when to use a list versus a set versus a dict is what separates beginner Python from professional Python.

I remember my first week with Python, using a list everywhere because it was the first data structure I learned. Then I had a loop checking if item in my_list on a list of 50,000 items and wondering why the script was slow. Switching that list to a set reduced that particular operation from O(n) to O(1) -- the script went from 45 seconds to under 2 seconds. Understanding data types matters.

Numbers: int, float

age = 25           # int -- whole numbers, no limit in Python
price = 19.99      # float -- decimal numbers
large = 1_000_000  # Underscores improve readability

print(type(age))    # <class 'int'>
print(type(price))  # <class 'float'>
print(isinstance(age, int))  # True

# Arithmetic
print(17 // 5)   # 3 -- floor division (integer result)
print(17 % 5)    # 2 -- modulo (remainder after division)
print(2 ** 10)   # 1024 -- exponentiation

# Floating point precision gotcha
print(0.1 + 0.2)  # 0.30000000000000004 (floating point!)
from decimal import Decimal
print(Decimal('0.1') + Decimal('0.2'))  # 0.3 (exact decimal)

Strings

Strings in Python are immutable sequences of Unicode characters. Python has an extraordinarily rich set of string methods.

name = "Suraj Ahir"

# Common methods
print(name.upper())           # SURAJ AHIR
print(name.lower())           # suraj ahir
print(name.title())           # Suraj Ahir (capitalise each word)
print(name.replace("Suraj", "Raj"))  # Raj Ahir
print(name.split(" "))        # ['Suraj', 'Ahir']
print(len(name))              # 10
print(name.strip())           # remove leading/trailing whitespace
print(name.startswith("Sur")) # True
print("Ahir" in name)         # True

# Indexing and slicing
print(name[0])      # S (first character)
print(name[-1])     # r (last character)
print(name[0:5])    # Suraj (slice)
print(name[::-1])   # rihA jaruS (reversed)

# f-strings (Python 3.6+ -- use these)
score = 98.567
print(f"Name: {name}, Score: {score:.2f}")  # 2 decimal places
print(f"Price: Rs.{1234567.89:,.2f}")        # 1,234,567.89 with commas
print(f"Percentage: {0.856:.1%}")            # 85.6%

Lists -- Ordered, Mutable

skills = ["Python", "Docker", "Kubernetes", "AWS"]

# Modify the list
skills.append("Linux")         # Add to end: O(1)
skills.insert(1, "Git")        # Add at index: O(n)
skills.remove("Docker")        # Remove by value: O(n)
last = skills.pop()            # Remove and return last: O(1)
skills.pop(0)                  # Remove and return first: O(n)

# Useful methods
print(len(skills))
print(skills.count("Python"))  # How many times "Python" appears
print(skills.index("AWS"))     # Index of first occurrence

# Sorting
skills.sort()                  # Sort in-place (modifies original)
skills.sort(reverse=True)      # Descending
sorted_copy = sorted(skills)   # Return new sorted list (original unchanged)

# Slicing
print(skills[1:3])    # Elements at index 1 and 2
print(skills[:2])     # First two elements
print(skills[::2])    # Every other element

# List comprehension -- powerful Pythonic pattern
numbers = list(range(1, 11))
evens   = [n for n in numbers if n % 2 == 0]
squares = [n**2 for n in numbers]
print(evens)     # [2, 4, 6, 8, 10]
print(squares)   # [1, 4, 9, 16, 25, 36, 49, 64, 81, 100]

Dictionaries -- Key-Value Pairs

person = {
    "name": "Suraj",
    "age": 25,
    "skills": ["Python", "Docker"],
    "city": "Mumbai"
}

# Access values
print(person["name"])           # Suraj (KeyError if missing)
print(person.get("age"))        # 25 (None if missing)
print(person.get("salary", 0))  # 0 (default value if missing)

# Modify
person["age"] = 26
person["language"] = "Hindi"    # Add new key

# Iterate
for key, value in person.items():
    print(f"  {key}: {value}")

for key in person.keys():
    print(key)

# Check membership
print("name" in person)   # True

# Dictionary comprehension
squares_dict = {n: n**2 for n in range(1, 6)}
# {1: 1, 2: 4, 3: 9, 4: 16, 5: 25}

Tuples and Sets

# Tuples -- ordered, immutable
coordinates = (28.6139, 77.2090)  # Delhi lat/lng
lat, lng = coordinates             # Tuple unpacking
print(f"Latitude: {lat}")

rgb = (255, 128, 0)   # Orange colour -- should never change
# rgb[0] = 200       # TypeError: tuples do not support assignment

# Multiple return values from functions use tuples
def min_max(numbers):
    return min(numbers), max(numbers)
lo, hi = min_max([3, 1, 4, 1, 5, 9, 2, 6])

# Sets -- unordered, unique values
tags = {"python", "docker", "kubernetes", "python"}
print(len(tags))  # 3 -- 'python' only counted once

# Set operations
required = {"Python", "Docker", "Kubernetes"}
have = {"Python", "Docker", "Linux"}
missing  = required - have    # {'Kubernetes'}
common   = required & have    # {'Python', 'Docker'}
combined = required | have    # All unique skills

# Fast membership testing
valid_users = {"suraj", "raj", "priya"}  # O(1) lookup
if "suraj" in valid_users:
    print("Authorised")

Type Conversion

int("42")           # 42
int(3.9)            # 3 (truncates, does not round)
float("3.14")       # 3.14
str(42)             # "42"
bool(0)             # False
bool(1)             # True
bool("")            # False
bool("anything")    # True
list((1, 2, 3))     # [1, 2, 3]
tuple([1, 2, 3])    # (1, 2, 3)
set([1, 1, 2, 3])   # {1, 2, 3} removes duplicates

# Common pattern: process user input
age_str = input("Enter age: ")
age = int(age_str)
price_str = input("Enter price: ")
price = float(price_str)

Frequently Asked Questions

In Part 3, we cover operators and input/output -- making programs interactive and producing formatted output.

Written by

Suraj Ahir

Cloud & DevOps engineer running four live production services on my own AWS infrastructure. I write everything on this site myself — no ghostwriters, no AI filler.

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