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Python

Python Complete Tutorial: Beginner to Advanced (95 Topics with Code)

Complete Python tutorial covering syntax, OOP, Flask, Django, databases, APIs, data tools, testing, and a final web application project — with practical code examples.

August 21, 2026 By malekimtiyajmca@gmail.com 22 min read

Python Complete Tutorial: Beginner to Advanced (95 Topics with Code) — a practical guide to Python complete tutorial with clear examples you can reuse in real projects.

This complete Python tutorial covers 95 topics — from installation and core syntax to OOP, Flask/Django, databases, APIs, data tools, and a final web application project. Beginner-friendly explanations with practical code.

Course roadmap

1. Introduction to Python

Python is a beginner-friendly language used for web development, automation, data science, and APIs. This series covers core syntax, OOP, Flask/Django, databases, and a final web project.

  1. Install Python and set up an editor.
  2. Practice core syntax and data structures.
  3. Build Flask/Django apps and a final project.

Learning path

Basics → data structures → functions/OOP
Files/JSON/regex → databases
Flask/Django → APIs/JWT
Data tools → final web app project

2. What is Python?

Python runs on many platforms and emphasizes readability. You write less boilerplate and can ship scripts, APIs, and apps quickly.

Hello mental model

print('Python is an interpreted language')
# Write code → Python runs it line by line

3. Features of Python

Key strengths include dynamic typing, automatic memory management, batteries-included standard library, and packages via pip for almost every domain.

Feature highlights

- Easy to read syntax
- Large standard library
- Cross-platform
- OOP + functional style
- Huge package ecosystem (pip)
- Great for scripting and backends

4. Python Installation

Download Python from python.org (or use your OS package manager). On Windows, enable “Add Python to PATH”.

  1. Download Python 3.x LTS/stable.
  2. Enable PATH on Windows if prompted.
  3. Verify with `python –version`.

Verify install

python --version
# or
python3 --version
pip --version

5. Setting Up VS Code / PyCharm

Pick an editor, select the Python interpreter, and install helpful extensions (Python, Pylance for VS Code).

VS Code tip

1. Install Python extension
2. Ctrl+Shift+P → Python: Select Interpreter
3. Create/open a .py file and run it

6. First Python Program

Create a `.py` file, add a print statement, and run it from the terminal or your IDE.

hello.py

name = 'Imtiyaj'
print(f'Hello, {name}! Welcome to Python')

# Run: python hello.py

7. Python Syntax

Python uses indentation (spaces) instead of braces. Consistent indentation is required for blocks.

Indentation example

# This is a comment
if True:
    print('Indented block')
print('Outside block')

8. Variables and Constants in Python

Python variables are created by assignment. Constants are a convention (UPPER_SNAKE_CASE), not enforced by the language.

Variables

age = 25
price = 99.5
is_active = True
PI = 3.14159  # constant by convention
print(age, price, is_active, PI)

9. Data Types in Python

Use `type()` to inspect values. Python is dynamically typed — the same variable can hold different types over time.

Common types

print(type(10))          # int
print(type(3.14))        # float
print(type('hi'))        # str
print(type(True))        # bool
print(type([1, 2]))      # list
print(type({'a': 1}))    # dict

10. Type Casting in Python

Casting is useful when reading input (always a string) or preparing values for math/APIs.

Casting examples

x = int('42')
y = float('3.5')
z = str(100)
nums = list((1, 2, 3))
print(x, y, z, nums)

11. Input and Output in Python

`input()` returns a string. Convert it before doing math. Prefer f-strings for readable output.

I/O example

name = input('Your name: ')
age = int(input('Your age: '))
print(f'Hello {name}, next year you will be {age + 1}')

12. Operators in Python

Operators combine values and control decisions. Know precedence basics and use parentheses for clarity.

Operator samples

print(10 + 3, 10 // 3, 10 % 3, 2 ** 3)
print(5 > 2 and 5 < 10)
x = 5
x += 2
print(x)

13. Conditional Statements in Python

Conditionals let your program make decisions. Start with `if`, then add `elif`/`else` branches.

Basic condition

score = 75
if score >= 50:
    print('Pass')
else:
    print('Fail')

14. if, elif and else in Python

Use `elif` for extra checks. Only one branch runs. Keep conditions mutually clear.

Grade example

marks = 82
if marks >= 90:
    grade = 'A'
elif marks >= 75:
    grade = 'B'
elif marks >= 50:
    grade = 'C'
else:
    grade = 'F'
print(grade)

15. Loops in Python

Loops process collections and keep running while a condition stays true. Combine with `break`/`continue` when needed.

Loop idea

for i in range(3):
    print('tick', i)

16. for Loop in Python

`for item in iterable` is the most common Python loop style. Use `range()` for numeric sequences.

for examples

for n in range(1, 4):
    print(n)

for ch in 'hi':
    print(ch)

for name in ['Asha', 'Ravi']:
    print(name)

17. while Loop in Python

While loops need a changing condition to avoid infinite loops. Great for menus and retries.

while example

count = 3
while count > 0:
    print(count)
    count -= 1
print('Go!')

18. break, continue and pass in Python

`break` exits a loop early. `continue` jumps to the next iteration. `pass` does nothing (useful as a stub).

Flow controls

for i in range(5):
    if i == 1:
        continue
    if i == 4:
        break
    print(i)

def todo():
    pass  # implement later

19. Strings in Python

Strings are immutable sequences of characters. Use quotes, f-strings, indexing, and slices.

String basics

s = 'Python'
print(s[0], s[-1], s[0:3])
print(f'Length: {len(s)}')

20. String Methods in Python

String methods return new strings (original stays unchanged). Chain them carefully.

Useful methods

text = '  Hello World  '
print(text.strip().lower())
print(text.replace('World', 'Python'))
parts = 'a,b,c'.split(',')
print('-'.join(parts))

21. Lists in Python

Lists can hold mixed types, grow/shrink, and support indexing, slicing, and methods like append/pop.

List operations

nums = [1, 2, 3]
nums.append(4)
nums.insert(0, 0)
print(nums[1:3])
print(sorted(nums, reverse=True))

22. Tuples in Python

Tuples are like lists but cannot be changed after creation — useful for records and dictionary keys (if hashable).

Tuple example

point = (10, 20)
x, y = point
print(x, y)
print(point[0])

23. Sets in Python

Sets automatically remove duplicates and are fast for membership tests.

Set operations

a = {1, 2, 2, 3}
b = {3, 4}
print(a)              # {1, 2, 3}
print(a | b)          # union
print(a & b)          # intersection
print(2 in a)

24. Dictionaries in Python

Dicts are the go-to structure for JSON-like data. Keys must be hashable (strings/numbers/tuples).

Dict basics

user = {'name': 'Asha', 'age': 28}
user['city'] = 'Pune'
print(user.get('email', 'N/A'))
for key, value in user.items():
    print(key, value)

25. List Comprehension in Python

List comprehensions replace many short for-loops. You can also add conditions.

Comprehension

squares = [n * n for n in range(1, 6)]
evens = [n for n in range(10) if n % 2 == 0]
print(squares, evens)

26. Dictionary Comprehension in Python

Dict comprehensions are great for transforming lists into maps or remapping existing dicts.

Dict comprehension

names = ['a', 'b', 'c']
lengths = {name: len(name) for name in names}
print(lengths)

27. Functions in Python

Functions reduce duplication and make programs modular. Prefer clear names and small responsibilities.

Define a function

def greet(name):
    return f'Hello, {name}'

print(greet('Imtiyaj'))

28. Function Arguments in Python

Defaults make APIs friendlier. Keyword args improve readability at call sites.

Argument styles

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

print(power(3))
print(power(2, 5))
print(power(exp=3, base=2))

29. *args and **kwargs in Python

`*args` collects extra positional values into a tuple. `**kwargs` collects keyword args into a dict.

Flexible signature

def demo(*args, **kwargs):
    print(args)
    print(kwargs)

demo(1, 2, 3, city='Surat', ok=True)

30. Lambda Functions in Python

Lambdas are single-expression functions. Prefer `def` for anything non-trivial.

Lambda examples

add = lambda a, b: a + b
print(add(2, 3))

names = ['zoey', 'amy', 'li']
print(sorted(names, key=lambda s: len(s)))

31. map(), filter() and reduce() in Python

These tools process collections without explicit loops. `reduce` lives in `functools`.

Functional helpers

from functools import reduce

nums = [1, 2, 3, 4, 5]
print(list(map(lambda n: n * 2, nums)))
print(list(filter(lambda n: n % 2 == 0, nums)))
print(reduce(lambda a, b: a + b, nums))

32. Scope of Variables in Python

Names resolve using LEGB. Use `global`/`nonlocal` carefully when you must rebind outer names.

Scope demo

x = 'global'

def outer():
    x = 'enclosing'
    def inner():
        print(x)  # enclosing
    inner()

outer()
print(x)

33. Modules in Python

Each `.py` file can be a module. Import functions/classes to keep projects organized.

math_utils.py + import

# math_utils.py
def add(a, b):
    return a + b

# main.py
from math_utils import add
print(add(2, 3))

34. Packages in Python

A package is a directory of modules. Use clear package names and absolute/relative imports thoughtfully.

Package layout

myapp/
  __init__.py
  utils/
    __init__.py
    helpers.py
  main.py

# from myapp.utils.helpers import clean_text

35. pip and Package Management

pip installs packages from PyPI. Freeze versions for reproducible environments.

pip commands

pip install requests
pip uninstall requests
pip freeze > requirements.txt
pip install -r requirements.txt

36. Virtual Environment in Python

Always create a virtual environment per project. Activate it before installing packages.

  1. Create `.venv` with `python -m venv`.
  2. Activate the environment.
  3. Install packages inside it only.

Create and activate venv

python -m venv .venv
# Windows PowerShell:
.venvScriptsActivate.ps1
# macOS/Linux:
# source .venv/bin/activate
pip install flask

37. Exception Handling in Python

Exceptions interrupt normal flow. Handle expected failures and re-raise or log unexpected ones.

Basic try/except

try:
    value = int('abc')
except ValueError as e:
    print('Invalid number:', e)

38. try, except, else and finally in Python

`else` runs when no exception occurs. `finally` always runs — perfect for closing resources.

Full form

try:
    n = int('10')
except ValueError:
    print('bad')
else:
    print('ok', n)
finally:
    print('cleanup')

39. File Handling in Python

Prefer `with open(…)` so files close automatically even if errors occur.

Open with context manager

with open('notes.txt', 'w', encoding='utf-8') as f:
    f.write('Learning Pythonn')

40. Reading and Writing Files in Python

Choose modes carefully: `r`, `w`, `a`, `rb`, `wb`. Use encoding for text files.

Read and append

with open('notes.txt', 'r', encoding='utf-8') as f:
    print(f.read())

with open('notes.txt', 'a', encoding='utf-8') as f:
    f.write('Another linen')

41. Working with JSON in Python

JSON maps naturally to Python dicts/lists. Use `json.dumps` / `json.loads` and file helpers.

JSON encode/decode

import json

data = {'name': 'Asha', 'skills': ['python', 'sql']}
text = json.dumps(data, indent=2)
print(text)
print(json.loads(text)['name'])

42. Date and Time in Python

Use `datetime` for timestamps, formatting (`strftime`), and parsing (`strptime`).

datetime basics

from datetime import datetime, timedelta

now = datetime.now()
print(now.strftime('%Y-%m-%d %H:%M'))
print(now + timedelta(days=7))

43. Regular Expressions in Python

Regex is powerful for emails, IDs, and cleanup tasks. Start simple and test patterns carefully.

re examples

import re

text = 'Call me at 98765-43210'
print(re.findall(r'd+', text))
if re.fullmatch(r'[w.-]+@example.com', 'user@example.com'):
    print('valid email format')

44. Object-Oriented Programming in Python

OOP helps organize larger programs using encapsulation, inheritance, and polymorphism.

OOP idea

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

    def greet(self):
        return f'Hi {self.name}'

print(User('Ravi').greet())

45. Classes and Objects in Python

A class defines attributes and methods. An object is one concrete instance of that class.

Class + instance

class Product:
    def __init__(self, title, price):
        self.title = title
        self.price = price

p = Product('Book', 499)
print(p.title, p.price)

46. Constructors in Python

`__init__` runs when you create an object. Set required attributes there.

__init__ example

class BankAccount:
    def __init__(self, owner, balance=0):
        self.owner = owner
        self.balance = balance

acc = BankAccount('Asha', 1000)
print(acc.owner, acc.balance)

47. Inheritance in Python

Child classes inherit methods/attributes and can override them. Use `super()` to call parents.

Inheritance

class Animal:
    def speak(self):
        return '...'

class Dog(Animal):
    def speak(self):
        return 'Woof'

print(Dog().speak())

48. Polymorphism in Python

Polymorphism lets you write code that works with many types sharing an interface.

Polymorphism demo

class Cat:
    def speak(self):
        return 'Meow'

class Dog:
    def speak(self):
        return 'Woof'

for animal in (Cat(), Dog()):
    print(animal.speak())

49. Encapsulation in Python

Python uses conventions (`_protected`, `__private`) and `@property` instead of strict access modifiers.

Property example

class Account:
    def __init__(self, balance):
        self._balance = balance

    @property
    def balance(self):
        return self._balance

print(Account(500).balance)

50. Abstraction in Python

Abstraction focuses on what an object does, not how. Use `abc` for formal abstract classes.

Abstract class

from abc import ABC, abstractmethod

class Shape(ABC):
    @abstractmethod
    def area(self):
        ...

class Square(Shape):
    def __init__(self, side):
        self.side = side

    def area(self):
        return self.side * self.side

print(Square(4).area())

51. Magic / Dunder Methods in Python

Dunder methods hook into Python syntax and built-ins so your classes feel native.

__str__ and __len__

class Team:
    def __init__(self, members):
        self.members = members

    def __len__(self):
        return len(self.members)

    def __str__(self):
        return f'Team({len(self)})'

print(len(Team(['a', 'b'])), Team(['a', 'b']))

52. Iterators in Python

Iterators produce values lazily with `next()` until `StopIteration`.

Custom iterator

class Countdown:
    def __init__(self, start):
        self.current = start

    def __iter__(self):
        return self

    def __next__(self):
        if self.current <= 0:
            raise StopIteration
        self.current -= 1
        return self.current + 1

print(list(Countdown(3)))

53. Generators in Python

Generators pause and resume. Ideal for large streams without loading everything into memory.

Generator function

def countdown(n):
    while n > 0:
        yield n
        n -= 1

for value in countdown(3):
    print(value)

54. Decorators in Python

A decorator takes a function and returns a new function. Use `@decorator` syntactic sugar.

Simple decorator

def log(fn):
    def wrapper(*args, **kwargs):
        print('calling', fn.__name__)
        return fn(*args, **kwargs)
    return wrapper

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

print(add(2, 3))

55. Context Managers in Python

Context managers guarantee cleanup. Files, locks, and DB sessions commonly use them.

custom context manager

from contextlib import contextmanager

@contextmanager
def tag(name):
    print(f'<{name}>')
    yield
    print(f'</{name}>')

with tag('div'):
    print('content')

56. Python Type Hints

Type hints do not enforce types at runtime by default, but help editors, mypy, and readers.

Type hints

def area(width: float, height: float) -> float:
    return width * height

names: list[str] = ['Asha', 'Ravi']
print(area(3.0, 4.0), names)

57. Dataclasses in Python

Dataclasses auto-create `__init__`, `__repr__`, and more — perfect for structured records.

dataclass example

from dataclasses import dataclass

@dataclass
class User:
    name: str
    email: str
    active: bool = True

print(User('Asha', 'asha@example.com'))

58. Working with APIs in Python

APIs usually return JSON. You send HTTP requests, parse responses, and handle errors/status codes.

API mindset

Request → HTTP method + URL + headers/body
Response → status code + JSON/text
Handle 2xx success and 4xx/5xx errors

59. HTTP Requests in Python

`requests` simplifies HTTP calls. Always check `response.ok` / status codes.

GET JSON

import requests

r = requests.get('https://jsonplaceholder.typicode.com/posts/1', timeout=10)
r.raise_for_status()
print(r.json()['title'])

60. REST API Integration in Python

REST uses resource URLs and HTTP verbs. Send JSON with correct headers and parse responses.

POST JSON example

import requests

payload = {'title': 'foo', 'body': 'bar', 'userId': 1}
r = requests.post(
    'https://jsonplaceholder.typicode.com/posts',
    json=payload,
    timeout=10,
)
print(r.status_code, r.json())

61. SQLite Database with Python

SQLite is file-based and perfect for learning SQL and small apps. Use parameterized queries.

sqlite3 CRUD sketch

import sqlite3

conn = sqlite3.connect('app.db')
cur = conn.cursor()
cur.execute('CREATE TABLE IF NOT EXISTS users (id INTEGER PRIMARY KEY, name TEXT)')
cur.execute('INSERT INTO users (name) VALUES (?)', ('Asha',))
conn.commit()
print(cur.execute('SELECT * FROM users').fetchall())
conn.close()

62. MySQL with Python

Install a MySQL driver, connect with credentials from environment variables, and use parameterized SQL.

PyMySQL sketch

# pip install PyMySQL
import pymysql

conn = pymysql.connect(host='127.0.0.1', user='root', password='', database='demo')
with conn.cursor() as cur:
    cur.execute('SELECT NOW()')
    print(cur.fetchone())
conn.close()

63. PostgreSQL with Python

PostgreSQL is a robust production database. Keep credentials in env vars and close connections cleanly.

psycopg sketch

# pip install psycopg[binary]
import psycopg

with psycopg.connect('postgresql://user:pass@phpcodeinformation.com/dbname') as conn:
    with conn.cursor() as cur:
        cur.execute('SELECT version()')
        print(cur.fetchone())

64. MongoDB with Python

MongoDB stores JSON-like documents. PyMongo provides insert/find/update/delete APIs.

PyMongo sketch

# pip install pymongo
from pymongo import MongoClient

client = MongoClient('mongodb://localhost:27017')
db = client['demo']
db.users.insert_one({'name': 'Asha'})
print(list(db.users.find({}, {'_id': 0})))

65. Flask Introduction

Flask gives you routing and responses with minimal setup. Extend it with extensions as you grow.

Tiny Flask app

from flask import Flask
app = Flask(__name__)

@app.get('/')
def home():
    return 'Hello Flask'

# flask --app app run

66. Flask Project Setup

Use venv, install Flask, and keep config in environment variables for clean local/prod setups.

Setup commands

python -m venv .venv
.venvScriptsActivate.ps1
pip install flask python-dotenv
# create app.py and run:
flask --app app run --debug

67. Flask Routing

Routes connect HTTP paths/methods to Python functions that return responses.

Routes

from flask import Flask
app = Flask(__name__)

@app.get('/hello/<name>')
def hello(name):
    return f'Hello {name}'

@app.post('/items')
def create_item():
    return {'ok': True}, 201

68. Flask Templates

Templates live in `templates/`. Use `render_template` and `{{ }}` / `{% %}` syntax.

Render template

from flask import render_template

@app.get('/about')
def about():
    return render_template('about.html', title='About')

69. Flask Forms

Read `request.form`, validate fields, then redirect with flash messages on success.

Form POST

from flask import request, redirect, url_for, flash

@app.route('/contact', methods=['GET', 'POST'])
def contact():
    if request.method == 'POST':
        email = request.form.get('email', '').strip()
        if not email:
            flash('Email required')
            return redirect(url_for('contact'))
        flash('Thanks!')
        return redirect(url_for('contact'))
    return render_template('contact.html')

70. Flask CRUD Application

CRUD apps teach routing, templates/JSON, validation, and persistence (SQLite/SQLAlchemy).

In-memory CRUD sketch

items = {}

@app.get('/api/items')
def list_items():
    return list(items.values())

@app.post('/api/items')
def add_item():
    data = request.get_json() or {}
    item_id = str(len(items) + 1)
    items[item_id] = {'id': item_id, 'title': data.get('title')}
    return items[item_id], 201

71. Django Introduction

Django includes ORM, admin, auth, and templates. Great for larger products and rapid development.

Django vs Flask (short)

Flask: minimal, flexible, pick your tools
Django: full stack defaults (ORM, admin, auth)
Choose based on project size and needs

72. Django Project Setup

Install Django in a venv, start a project, and run migrations for built-in apps.

Start project

pip install django
django-admin startproject config .
python manage.py migrate
python manage.py runserver

73. Django Apps

Projects contain apps (blog, accounts, shop). Register apps in `INSTALLED_APPS`.

Create an app

python manage.py startapp blog
# add 'blog' to INSTALLED_APPS in settings.py

74. Django Models

Models describe fields and behavior. Migrate after changes to update the database schema.

Post model

from django.db import models

class Post(models.Model):
    title = models.CharField(max_length=200)
    body = models.TextField()
    created_at = models.DateTimeField(auto_now_add=True)

    def __str__(self):
        return self.title

75. Django Views

Views receive a request and return a response (HTML or JSON). Keep them thin; push logic to models/services.

Function view

from django.http import HttpResponse

def home(request):
    return HttpResponse('Hello Django')

76. Django Templates

Use `{% extends %}` layouts and `{{ variable }}` output. Escape is on by default for safety.

Template render

from django.shortcuts import render

def home(request):
    return render(request, 'home.html', {'title': 'Home'})

77. Django Forms

Forms handle cleaning/validation and can save model instances via ModelForm.

ModelForm sketch

from django import forms
from .models import Post

class PostForm(forms.ModelForm):
    class Meta:
        model = Post
        fields = ['title', 'body']

78. Django Authentication

Django ships with User model, login views, password hashing, and `@login_required`.

Protect a view

from django.contrib.auth.decorators import login_required

@login_required
def dashboard(request):
    return render(request, 'dashboard.html')

79. Django REST Framework

DRF turns Django models into JSON APIs quickly with browsable API and auth support.

Install DRF

pip install djangorestframework
# add 'rest_framework' to INSTALLED_APPS

80. Creating REST APIs with Python

Whether Flask or DRF, keep resources clear: list/create on collections, retrieve/update/delete on items.

Flask JSON endpoint

from flask import jsonify, request

@app.get('/api/posts')
def posts():
    return jsonify([{'id': 1, 'title': 'Hello'}])

81. JWT Authentication in Python

Issue a signed JWT on login and require `Authorization: Bearer <token>` on protected routes.

PyJWT sketch

# pip install PyJWT
import jwt
from datetime import datetime, timedelta, timezone

def create_token(user_id: int, secret: str) -> str:
    payload = {
        'sub': user_id,
        'exp': datetime.now(timezone.utc) + timedelta(hours=24),
    }
    return jwt.encode(payload, secret, algorithm='HS256')

82. File Upload in Python Web Apps

Validate file type/size, sanitize filenames, and store uploads outside executable paths when possible.

Flask upload

from flask import request
from werkzeug.utils import secure_filename

@app.post('/upload')
def upload():
    f = request.files.get('file')
    if not f:
        return {'error': 'No file'}, 400
    f.save(f'uploads/{secure_filename(f.filename)}')
    return {'ok': True}

83. Email Sending in Python

Use SMTP credentials from environment variables. Prefer app passwords / API mail providers in production.

smtplib sketch

import smtplib
from email.message import EmailMessage

msg = EmailMessage()
msg['Subject'] = 'Welcome'
msg['From'] = 'noreply@example.com'
msg['To'] = 'user@example.com'
msg.set_content('Thanks for signing up!')

# with smtplib.SMTP('smtp.example.com', 587) as s:
#     s.starttls()
#     s.login(user, password)
#     s.send_message(msg)

84. Web Scraping with Python

Scrape only when allowed. Prefer official APIs. Parse HTML carefully and throttle requests.

BeautifulSoup sketch

# pip install beautifulsoup4 requests
import requests
from bs4 import BeautifulSoup

html = requests.get('https://example.com', timeout=10).text
soup = BeautifulSoup(html, 'html.parser')
print(soup.title.text)

85. Automation with Python

Python shines at glue code — combining files, APIs, and OS tasks into one script.

Rename files sketch

from pathlib import Path

folder = Path('invoices')
for i, path in enumerate(folder.glob('*.pdf'), start=1):
    path.rename(folder / f'invoice-{i:03d}.pdf')

86. Working with Excel Files in Python

Use pandas for analysis-friendly tables; openpyxl for formatted workbooks.

pandas Excel

# pip install pandas openpyxl
import pandas as pd

df = pd.DataFrame({'name': ['Asha', 'Ravi'], 'score': [90, 88]})
df.to_excel('scores.xlsx', index=False)
print(pd.read_excel('scores.xlsx'))

87. NumPy Basics

NumPy arrays support vectorized math — much faster than Python loops for large numeric data.

NumPy array

# pip install numpy
import numpy as np

a = np.array([1, 2, 3, 4])
print(a * 2)
print(a.mean(), a.max())

88. Pandas Basics

Pandas is the standard tool for CSV/Excel analysis in Python.

DataFrame basics

# pip install pandas
import pandas as pd

df = pd.DataFrame({'city': ['Pune', 'Surat', 'Pune'], 'sales': [10, 15, 7]})
print(df.groupby('city')['sales'].sum())

89. Data Visualization with Matplotlib

Start with line/bar charts. Label axes and titles so charts are understandable.

Simple plot

# pip install matplotlib
import matplotlib.pyplot as plt

plt.plot([1, 2, 3], [3, 5, 4])
plt.title('Demo')
plt.xlabel('x')
plt.ylabel('y')
plt.show()

90. Python Testing with PyTest

Tests catch regressions early. Keep them fast and focused on one behavior each.

test_math.py

# pip install pytest

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

def test_add():
    assert add(2, 3) == 5

# pytest

91. Debugging Python Applications

Reproduce the bug, isolate the failing input, inspect state, fix, then add a test.

pdb breakpoint

def broken(n):
    breakpoint()  # or import pdb; pdb.set_trace()
    return 10 / n

# broken(0)

92. Logging in Python

Use INFO/WARNING/ERROR levels. Configure formatters and handlers for files or stdout.

logging basics

import logging

logging.basicConfig(level=logging.INFO, format='%(levelname)s %(message)s')
logging.info('Server started')
logging.error('Payment failed')

93. Python Security Best Practices

Never hardcode secrets. Validate input, hash passwords, keep dependencies updated, and use HTTPS.

Security checklist

- Store secrets in environment variables
- Hash passwords (bcrypt/argon2)
- Parameterize SQL queries
- Validate/sanitize uploads
- Keep packages updated
- Use HTTPS in production

94. Python Interview Questions

Be ready to explain mutability, GIL/basics of concurrency, decorators, generators, and Flask vs Django.

Sample Q&A

Q: List vs tuple?
A: Lists mutable; tuples immutable.

Q: What is a decorator?
A: A function that wraps another function.

Q: *args vs **kwargs?
A: Extra positional vs keyword arguments.

Q: GIL?
A: CPython lock limiting one bytecode thread at a time.

95. Final Project – Complete Python Web Application

Combine everything: venv, Flask or Django, database models, authentication, forms/API, file upload, and deployment-ready settings.

  1. Choose Flask or Django.
  2. Design models and auth.
  3. Implement web CRUD + API.
  4. Add tests for core flows.
  5. Document and prepare deploy.

Final project scope

1. User registration/login
2. CRUD for a main resource (posts/tasks)
3. Validation + flash/error messages
4. REST JSON endpoints (+ optional JWT)
5. File upload for images/docs
6. Logging + .env config
7. README + requirements.txt

Suggested Flask routes

@app.post('/api/login')
@app.get('/api/items')
@app.post('/api/items')
@app.put('/api/items/<id>')
@app.delete('/api/items/<id>')

Conclusion

You now have a full Python path: language fundamentals, OOP, files/APIs/databases, Flask and Django, data basics, testing, and security. Finish with the complete web application project to lock in the skills.

Keep reading

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