Python Programming Terms Every Beginner Should Understand

# Variables and basic types
name = "Ananya"     # string
age = 27             # integer
height = 5.6         # float
is_student = True    # boolean

print(name)          # "Ananya"
print(age + 1)       # 28

# Python infers the type — no explicit declaration
# You can check it with type()
print(type(age))     # <class 'int'>

# Collections — list, tuple, set, dict
skills = ["Python", "SQL", "Git"]   # list — changeable
coordinates = (12.9, 77.6)          # tuple — unchangeable
unique_ids = {101, 102, 103}        # set — unique only
person = {"name": "Ananya", "age": 27}  # dict — key-value

print(skills[0])         # "Python"
print(skills[0:2])       # ["Python", "SQL"]
print(person["name"])    # "Ananya"
print("Python" in skills)  # True

# if / elif / else
score = 85

if score >= 90:
    print("A grade")
elif score >= 75:
    print("B grade")
else:
    print("Keep practising")

# Logical operators
age = 22
has_id = True

if age >= 18 and has_id:
    print("Entry allowed")
else:
    print("Entry denied")

# for loop — repeat for each item
skills = ["Python", "SQL", "Git"]

for skill in skills:
    print(f"I am learning {skill}")

# while loop — repeat while condition is true
count = 0
while count < 3:
    print("Attempt", count + 1)
    count += 1

# break — exit early
for num in range(10):
    if num == 5:
        break
    print(num)

# continue — skip one iteration
for num in range(5):
    if num == 2:
        continue
    print(num)

# A function with parameters and return value
def greet(name, greeting="Hello"):
    return f"{greeting}, {name}!"

message = greet("Ananya")
print(message)   # "Hello, Ananya!"

# A lambda — short anonymous function
double = lambda x: x * 2
print(double(5))  # 10

# Functions can return multiple values
def min_max(numbers):
    return min(numbers), max(numbers)

low, high = min_max([3, 1, 7, 5])
print(low, high)  # 1 7

# Importing modules
import math
print(math.sqrt(16))  # 4.0

# Import specific names
from datetime import datetime
print(datetime.now().year)

# Alias a module
import numpy as np
# np.array([1, 2, 3])

# Standard library modules you'll use often:
# math, random, datetime, json, os, sys, csv

# Third-party modules are installed with pip
# pip install requests

# Handling an exception
try:
    number = int("not a number")
except ValueError as e:
    print(f"Conversion failed: {e}")

# Handling different exceptions differently
try:
    data = {"name": "Ananya"}
    print(data["age"])
except KeyError:
    print("The 'age' key is missing")

# finally runs no matter what
try:
    f = open("file.txt")
    # do something
finally:
    f.close()

# Common Python errors and causes:

# TypeError — mixing incompatible types
# "5" + 5  → TypeError

# ValueError — correct type, wrong value
# int("abc")  → ValueError

# KeyError — missing dictionary key
# {"a": 1}["b"]  → KeyError

# IndexError — index out of range
# [1, 2, 3][5]  → IndexError

# NameError — variable not defined
# print(unknown_var)  → NameError

# ZeroDivisionError — dividing by zero
# 10 / 0  → ZeroDivisionError

# Learning to read error messages is one of the most
# valuable beginner skills.