🐍 Python in 12 Days

1. What is Python?

Python is a high-level, interpreted programming language known for its readable syntax. It's used in web development, data science, automation, AI, and pharma-tech tools alike. Unlike C or Java, Python doesn't need you to declare variable types explicitly, and it runs line by line (interpreted), which makes it great for beginners.

2. Your First Program: print()

The print() function displays output on the screen. It's usually the very first thing anyone learns.

print("Hello, World!")
print("Ananya is learning Python")
print(2 + 3)          # prints 5

3. Variables

A variable is a named container that stores a value. You don't need to declare its type — Python figures it out automatically.

name = "Ananya"
age = 20
height = 5.4
is_founder = True

print(name, age, height, is_founder)

4. Data Types

Use type() to check any variable's data type:

print(type(10))        # <class 'int'>
print(type("hi"))       # <class 'str'>

5. Comments

Comments are notes for humans; Python ignores them. Use # for a single line.

# This is a comment — Python will not run this line
print("This line runs")  # you can also comment after code

1. Arithmetic Operators

print(7 + 2)   # 9   addition
print(7 - 2)   # 5   subtraction
print(7 * 2)   # 14  multiplication
print(7 / 2)   # 3.5 division (always returns float)
print(7 // 2)  # 3   floor division (drops decimal)
print(7 % 2)   # 1   modulus (remainder)
print(7 ** 2)  # 49  exponent (power)

2. Comparison & Logical Operators

print(5 > 3)      # True
print(5 == 5)     # True (equality check)
print(5 != 4)     # True (not equal)

a = True
b = False
print(a and b)    # False — both must be True
print(a or b)     # True  — at least one True
print(not a)      # False — flips the value

3. Type Casting

Converting one data type into another using int(), float(), str(), bool().

x = "10"
y = int(x)          # "10" -> 10
print(y + 5)          # 15

z = str(25)          # 25 -> "25"
print("Score: " + z)

4. Taking Input from the User

input() always returns a string, even if the user types a number — you must cast it yourself.

name = input("What is your name? ")
age = int(input("What is your age? "))

print(name + " is " + str(age) + " years old")

1. Strings & Indexing

A string is a sequence of characters. Each character has a position (index), starting at 0.

word = "Python"
print(word[0])     # 'P'
print(word[-1])    # 'n' (last character)
print(word[0:3])   # 'Pyt' (slicing: start to end-1)
print(len(word))   # 6

2. Common String Methods

s = "  Hello Ananya  "
print(s.strip())          # removes leading/trailing spaces
print(s.lower())          # "  hello ananya  "
print(s.upper())          # "  HELLO ANANYA  "
print(s.replace("Hello", "Hey"))
print(s.strip().split(" "))   # ['Hello', 'Ananya']
print("-".join(["a","b","c"]))  # "a-b-c"
print("Python" in "I love Python")   # True

3. String Formatting (f-strings)

The modern, cleanest way to insert variables into text:

name = "Ananya"
project = "Viginyx"
print(f"{name} is building {project}")

score = 91.567
print(f"Score: {score:.2f}")   # Score: 91.57 (2 decimal places)

1. What is a List?

A list is an ordered, changeable (mutable) collection that can hold mixed data types.

fruits = ["apple", "banana", "cherry"]
mixed = [1, "two", 3.0, True]

print(fruits[0])     # apple
print(fruits[-1])    # cherry
print(len(fruits))   # 3

2. Modifying Lists

fruits.append("mango")        # add to end
fruits.insert(1, "kiwi")       # insert at index 1
fruits.remove("banana")        # remove by value
fruits.pop()                   # removes last item
fruits[0] = "strawberry"       # update by index

print(fruits)

3. Looping Through a List

for fruit in fruits:
    print(fruit)

# with index
for i, fruit in enumerate(fruits):
    print(i, fruit)

4. List Slicing & Useful Functions

nums = [5, 2, 9, 1, 7]
print(nums[1:4])     # [2, 9, 1]
print(sorted(nums))   # [1, 2, 5, 7, 9]
print(max(nums), min(nums), sum(nums))
nums.sort()            # sorts in place
nums.reverse()          # reverses in place

5. List Comprehension (Intermediate)

A compact way to build lists in one line:

squares = [x**2 for x in range(1, 6)]
print(squares)   # [1, 4, 9, 16, 25]

evens = [x for x in range(10) if x % 2 == 0]
print(evens)     # [0, 2, 4, 6, 8]

1. Tuples — Ordered & Immutable

A tuple is like a list, but once created, it cannot be changed. Use tuples for fixed data (coordinates, RGB values, constants).

point = (4, 5)
receptor_coords = (127.0, 124.5, 138.0)

print(point[0])       # 4
# point[0] = 10        # ❌ Error! Tuples are immutable

x, y, z = receptor_coords     # unpacking
print(x, y, z)

2. Why Use a Tuple Instead of a List?

• Faster than lists
• Protects data from accidental modification
• Can be used as dictionary keys (lists cannot)

3. Sets — Unordered & Unique

A set automatically removes duplicates and has no fixed order.

letters = {"a", "b", "a", "c"}
print(letters)          # {'a', 'b', 'c'} — duplicate removed

a = {1, 2, 3}
b = {2, 3, 4}
print(a.union(b))        # {1,2,3,4}
print(a.intersection(b))  # {2,3}
print(a.difference(b))    # {1}

a.add(5)
a.discard(1)

4. Quick Comparison

1. What is a Dictionary?

A dictionary stores data as key : value pairs. Instead of accessing by index, you access by key.

student = {
    "name": "Ananya",
    "course": "B.Pharm",
    "year": 3
}

print(student["name"])        # Ananya
print(student.get("year"))     # 3
print(student.get("gpa", "N/A"))  # N/A (default if key missing)

2. Modifying a Dictionary

student["year"] = 4              # update
student["college"] = "SVBCP"       # add new key
del student["course"]              # remove a key
print(student.keys())              # all keys
print(student.values())            # all values
print(student.items())             # key-value pairs

3. Looping Through a Dictionary

for key, value in student.items():
    print(f"{key}: {value}")

4. Nested Dictionaries (Intermediate)

Dictionaries can contain other dictionaries or lists — very useful for real-world structured data.

drug_db = {
    "paracetamol": {"dose_mg": 500, "category": "analgesic"},
    "amoxicillin": {"dose_mg": 250, "category": "antibiotic"}
}

print(drug_db["amoxicillin"]["dose_mg"])   # 250

for drug, info in drug_db.items():
    print(f"{drug} -> {info['category']}")

1. if, elif, else

marks = 78

if marks >= 90:
    print("Grade A")
elif marks >= 75:
    print("Grade B")
elif marks >= 50:
    print("Grade C")
else:
    print("Fail")

2. Nested Conditions

age = 20
has_id = True

if age >= 18:
    if has_id:
        print("Entry allowed")
    else:
        print("ID required")
else:
    print("Underage")

3. Combining Conditions

temp = 30
humidity = 80

if temp > 25 and humidity > 70:
    print("Hot and humid")
elif temp > 25 or humidity > 70:
    print("Hot or humid, not both")
else:
    print("Mild weather")

4. Ternary (One-Line) Conditional

age = 17
status = "Adult" if age >= 18 else "Minor"
print(status)

1. for Loops

for i in range(5):        # 0,1,2,3,4
    print(i)

for i in range(2, 10, 2):  # start, stop, step -> 2,4,6,8
    print(i)

2. while Loops

Runs as long as a condition is True. You must update the condition inside the loop, or it runs forever.

count = 0
while count < 5:
    print(count)
    count += 1     # same as count = count + 1

3. break and continue

for i in range(10):
    if i == 5:
        break        # exits the loop entirely
    print(i)

for i in range(10):
    if i % 2 == 0:
        continue     # skips this iteration, goes to next
    print(i)          # only prints odd numbers

4. Nested Loops

for i in range(3):
    for j in range(3):
        print(f"i={i}, j={j}")

1. Defining and Calling a Function

def greet(name):
    print(f"Hello, {name}!")

greet("Ananya")     # calling the function

2. Return Values

def add(a, b):
    return a + b

result = add(3, 4)
print(result)         # 7

3. Default Parameters

def power(base, exponent=2):
    return base ** exponent

print(power(5))        # 25 (uses default exponent)
print(power(5, 3))      # 125

4. *args and **kwargs (Intermediate)

Used when you don't know how many arguments will be passed.

def total(*numbers):          # collects extra positional args into a tuple
    return sum(numbers)

print(total(1,2,3,4))          # 10

def profile(**info):            # collects extra keyword args into a dict
    for key, value in info.items():
        print(f"{key}: {value}")

profile(name="Ananya", course="B.Pharm")

5. Lambda Functions

A small, anonymous, one-line function — useful for quick operations.

square = lambda x: x ** 2
print(square(5))          # 25

nums = [1, -2, 3, -4]
print(sorted(nums, key=lambda x: abs(x)))   # sort by absolute value

1. Importing Modules

import math
print(math.sqrt(16))     # 4.0
print(math.pi)             # 3.14159...

import random
print(random.randint(1, 10))   # random number between 1-10

from datetime import datetime
print(datetime.now())

2. Writing Your Own Module

Any .py file can be imported into another. If you have helper.py with a function def add(a,b): return a+b, you can use it elsewhere with import helper then helper.add(2,3).

3. Reading & Writing Files

# Writing to a file
with open("notes.txt", "w") as f:
    f.write("Hello from Python\n")
    f.write("Second line")

# Reading a file
with open("notes.txt", "r") as f:
    content = f.read()
    print(content)

# Reading line by line
with open("notes.txt", "r") as f:
    for line in f:
        print(line.strip())

4. File Modes

1. try / except

Prevents your program from crashing when an error occurs, letting you handle it gracefully.

try:
    num = int(input("Enter a number: "))
    print(10 / num)
except ValueError:
    print("That's not a valid number!")
except ZeroDivisionError:
    print("Can't divide by zero!")
finally:
    print("This always runs, error or not.")

2. Raising Your Own Errors

def set_age(age):
    if age < 0:
        raise ValueError("Age cannot be negative")
    return age

try:
    set_age(-5)
except ValueError as e:
    print(f"Error: {e}")

3. Object-Oriented Programming: Classes & Objects

A class is a blueprint; an object is an instance built from that blueprint. OOP helps you model real-world things.

class Student:
    def __init__(self, name, course):     # constructor — runs when object is created
        self.name = name
        self.course = course

    def introduce(self):                    # a method
        print(f"Hi, I'm {self.name}, studying {self.course}")

s1 = Student("Ananya", "B.Pharm")
s1.introduce()          # Hi, I'm Ananya, studying B.Pharm
print(s1.name)            # Ananya

1. Inheritance

A class can inherit attributes and methods from another class — avoiding repeated code.

class Person:
    def __init__(self, name):
        self.name = name

    def greet(self):
        print(f"Hi, I'm {self.name}")

class Student(Person):                 # Student inherits from Person
    def __init__(self, name, course):
        super().__init__(name)          # calls Person's __init__
        self.course = course

    def greet(self):                      # overrides the parent's method
        print(f"Hi, I'm {self.name}, studying {self.course}")

p = Person("Vaibhav")
s = Student("Ananya", "B.Pharm")
p.greet()     # Hi, I'm Vaibhav
s.greet()     # Hi, I'm Ananya, studying B.Pharm

2. Why Inheritance Matters

• Reusability — write shared logic once in a parent class
• Overriding — child classes can customize inherited behavior
• super() — lets a child class call the parent's version of a method

3. Recap: The Full Toolbox

Over 12 days you've covered: variables & types, operators, strings, lists/tuples/sets/dicts, conditionals, loops, functions (incl. *args/lambda), modules & files, exceptions, and classes/inheritance. That's the core of beginner-to-intermediate Python — everything after this is building bigger projects with these same building blocks.