How to Become a Python Full Stack Developer: Complete Career Guide [₹13L Average Salary]

Phase 1: Python Fundamentals and Core Concepts (Month 1-2)

Python Language Fundamentals (3-4 weeks)
Building strong Python foundation is essential for full-stack development:

• Python Syntax and Basics – Variables, data types, operators, control structures, functions
• Data Structures – Lists, tuples, dictionaries, sets, strings, comprehensions
• Object-Oriented Programming – Classes, objects, inheritance, polymorphism, encapsulation
• Error Handling – Exceptions, try-catch blocks, custom exceptions, debugging techniques

Advanced Python Concepts (3-4 weeks)

• File Handling and I/O – File operations, CSV processing, JSON handling, data serialization
• Modules and Packages – Import system, creating modules, package management, virtual environments
• Functional Programming – Lambda functions, map, filter, reduce, decorators, generators
• Testing Fundamentals – Unit testing, pytest, test-driven development, code coverage

Database Concepts and SQL (2-3 weeks)

• Relational Databases – SQL fundamentals, joins, aggregations, subqueries, database design
• PostgreSQL/MySQL – Advanced querying, indexes, transactions, performance optimization
• NoSQL Databases – MongoDB basics, document design, queries, aggregation pipeline
• Database Integration – Python database connectivity, ORMs, connection pooling

Foundation Projects:

1. Personal Finance Tracker – Command-line application with file storage and data analysis
2. Web Scraping Tool – Data extraction from websites with CSV export and scheduling
3. Task Management API – Simple REST API with database integration and user authentication

Phase 2: Django Framework Mastery (Month 2-3)

Django Fundamentals and Architecture (3-4 weeks)

• MVC Architecture – Models, views, controllers, URL routing, template system
• Django Project Structure – Apps, settings, URLs, static files, media handling
• Models and Database – Model definition, migrations, queries, relationships, admin interface
• Views and Templates – Function-based views, class-based views, template inheritance, context

Advanced Django Features (3-4 weeks)

Professional Django Development:

# Advanced Django Application with Modern Features
# File: ecommerce_project/products/models.py

from django.db import models
from django.contrib.auth.models import AbstractUser
from django.core.validators import MinValueValidator, MaxValueValidator
from django.utils.text import slugify
from django.urls import reverse
from django.db import transaction
from django.core.cache import cache
import uuid
from decimal import Decimal

class TimeStampedModel(models.Model):
    “””Abstract base model with timestamp fields.”””
    created_at = models.DateTimeField(auto_now_add=True)
    updated_at = models.DateTimeField(auto_now=True)
   
    class Meta:
        abstract = True

class User(AbstractUser):
    “””Extended user model with additional fields.”””
    email = models.EmailField(unique=True)
    phone = models.CharField(max_length=15, blank=True)
    date_of_birth = models.DateField(null=True, blank=True)
    address = models.TextField(blank=True)
    profile_picture = models.ImageField(upload_to=’profiles/’, blank=True)
    is_verified = models.BooleanField(default=False)
    preferred_language = models.CharField(max_length=10, default=’en’)
   
    USERNAME_FIELD = ’email’
    REQUIRED_FIELDS = [‘username’, ‘first_name’, ‘last_name’]
   
    def get_full_name(self):
        return f”{self.first_name} {self.last_name}”.strip()
   
    def __str__(self):
        return f”{self.get_full_name()} ({self.email})”

class Category(TimeStampedModel):
    “””Product category model with hierarchical structure.”””
    name = models.CharField(max_length=100)
    slug = models.SlugField(unique=True, blank=True)
    description = models.TextField(blank=True)
    parent = models.ForeignKey(‘self’, on_delete=models.CASCADE, null=True, blank=True, related_name=’children’)
    image = models.ImageField(upload_to=’categories/’, blank=True)
    is_active = models.BooleanField(default=True)
    sort_order = models.PositiveIntegerField(default=0)
   
    class Meta:
        verbose_name_plural = ‘Categories’
        ordering = [‘sort_order’, ‘name’]
   
    def save(self, *args, **kwargs):
        if not self.slug:
            self.slug = slugify(self.name)
        super().save(*args, kwargs)
   
    def get_absolute_url(self):
        return reverse(‘products:category’, kwargs={‘slug’: self.slug})
   
    def get_products_count(self):
        “””Get total number of active products in this category and subcategories.”””
        cache_key = f’category_products_count_{self.pk}’
        count = cache.get(cache_key)
       
        if count is None:
            count = Product.objects.filter(
                models.Q(category=self) | models.Q(category__parent=self),
                is_active=True
            ).count()
            cache.set(cache_key, count, 300)  # Cache for 5 minutes
       
        return count
   
    def __str__(self):
        return self.name

class ProductManager(models.Manager):
    “””Custom manager for Product model.”””
   
    def active(self):
        return self.filter(is_active=True, stock__gt=0)
   
    def featured(self):
        return self.active().filter(is_featured=True)
   
    def on_sale(self):
        return self.active().filter(sale_price__isnull=False, sale_price__lt=models.F(‘price’))
   
    def by_category(self, category):
        return self.active().filter(category=category)
   
    def search(self, query):
        return self.active().filter(
            models.Q(name__icontains=query) |
            models.Q(description__icontains=query) |
            models.Q(tags__name__icontains=query)
        ).distinct()

class Product(TimeStampedModel):
    “””Product model with comprehensive e-commerce features.”””
    id = models.UUIDField(primary_key=True, default=uuid.uuid4, editable=False)
    name = models.CharField(max_length=200)
    slug = models.SlugField(unique=True, blank=True)
    description = models.TextField()
    short_description = models.TextField(max_length=500, blank=True)
   
    # Pricing
    price = models.DecimalField(max_digits=10, decimal_places=2, validators=[MinValueValidator(Decimal(‘0.01’))])
    sale_price = models.DecimalField(max_digits=10, decimal_places=2, null=True, blank=True)
    cost_price = models.DecimalField(max_digits=10, decimal_places=2, null=True, blank=True)
   
    # Inventory
    sku = models.CharField(max_length=100, unique=True)
    stock = models.PositiveIntegerField(default=0)
    low_stock_threshold = models.PositiveIntegerField(default=5)
    weight = models.DecimalField(max_digits=8, decimal_places=2, null=True, blank=True, help_text=”Weight in kg”)
   
    # Organization
    category = models.ForeignKey(Category, on_delete=models.CASCADE, related_name=’products’)
    brand = models.ForeignKey(‘Brand’, on_delete=models.SET_NULL, null=True, blank=True)
    tags = models.ManyToManyField(‘Tag’, blank=True)
   
    # Status and features
    is_active = models.BooleanField(default=True)
    is_featured = models.BooleanField(default=False)
    is_digital = models.BooleanField(default=False)
   
    # SEO
    meta_title = models.CharField(max_length=60, blank=True)
    meta_description = models.CharField(max_length=160, blank=True)
   
    # Analytics
    view_count = models.PositiveIntegerField(default=0)
    purchase_count = models.PositiveIntegerField(default=0)
   
    objects = ProductManager()
   
    class Meta:
        ordering = [‘-created_at’]
        indexes = [
            models.Index(fields=[‘category’, ‘is_active’]),
            models.Index(fields=[‘slug’]),
            models.Index(fields=[‘sku’]),
            models.Index(fields=[‘-created_at’]),
        ]
   
    def save(self, *args, kwargs):
        if not self.slug:
            self.slug = slugify(self.name)
       
        # Generate SKU if not provided
        if not self.sku:
            self.sku = f”PRD-{uuid.uuid4().hex[:8].upper()}”
       
        super().save(*args, kwargs)
       
        # Clear related cache
        cache.delete(f’product_detail_{self.slug}’)
        cache.delete(f’category_products_count_{self.category.pk}’)
   
    def get_absolute_url(self):
        return reverse(‘products:detail’, kwargs={‘slug’: self.slug})
   
    def get_current_price(self):
        “””Return sale price if available, otherwise regular price.”””
        if self.sale_price and self.sale_price < self.price:
            return self.sale_price
        return self.price
   
    def get_discount_percentage(self):
        “””Calculate discount percentage if on sale.”””
        if self.sale_price and self.sale_price < self.price:
            return round(((self.price – self.sale_price) / self.price) * 100)
        return 0
   
    def is_in_stock(self):
        “””Check if product is in stock.”””
        return self.stock > 0
   
    def is_low_stock(self):
        “””Check if product is running low on stock.”””
        return self.stock <= self.low_stock_threshold
   
    def get_main_image(self):
        “””Get the main product image.”””
        main_image = self.images.filter(is_main=True).first()
        return main_image.image if main_image else None
   
    def get_average_rating(self):
        “””Calculate average rating from reviews.”””
        cache_key = f’product_rating_{self.pk}’
        rating = cache.get(cache_key)
       
        if rating is None:
            reviews = self.reviews.filter(is_approved=True)
            if reviews.exists():
                rating = reviews.aggregate(avg_rating=models.Avg(‘rating’))[‘avg_rating’]
                rating = round(rating, 1) if rating else 0
            else:
                rating = 0
            cache.set(cache_key, rating, 3600)  # Cache for 1 hour
       
        return rating
   
    def get_reviews_count(self):
        “””Get total number of approved reviews.”””
        return self.reviews.filter(is_approved=True).count()
   
    def increment_view_count(self):
        “””Increment product view count.”””
        Product.objects.filter(pk=self.pk).update(view_count=models.F(‘view_count’) + 1)
   
    def __str__(self):
        return self.name

class ProductImage(TimeStampedModel):
    “””Product image model for multiple images per product.”””
    product = models.ForeignKey(Product, on_delete=models.CASCADE, related_name=’images’)
    image = models.ImageField(upload_to=’products/’)
    alt_text = models.CharField(max_length=200, blank=True)
    is_main = models.BooleanField(default=False)
    sort_order = models.PositiveIntegerField(default=0)
   
    class Meta:
        ordering = [‘sort_order’, ‘created_at’]
   
    def save(self, *args, kwargs):
        if self.is_main:
            # Ensure only one main image per product
            ProductImage.objects.filter(product=self.product, is_main=True).update(is_main=False)
        super().save(*args, kwargs)

class Brand(TimeStampedModel):
    “””Brand model for product manufacturers.”””
    name = models.CharField(max_length=100, unique=True)
    slug = models.SlugField(unique=True, blank=True)
    description = models.TextField(blank=True)
    logo = models.ImageField(upload_to=’brands/’, blank=True)
    website = models.URLField(blank=True)
    is_active = models.BooleanField(default=True)
   
    def save(self, *args, kwargs):
        if not self.slug:
            self.slug = slugify(self.name)
        super().save(*args, kwargs)
   
    def __str__(self):
        return self.name

class Tag(models.Model):
    “””Tag model for product categorization.”””
    name = models.CharField(max_length=50, unique=True)
    slug = models.SlugField(unique=True, blank=True)
   
    def save(self, *args, kwargs):
        if not self.slug:
            self.slug = slugify(self.name)
        super().save(*args, kwargs)
   
    def __str__(self):
        return self.name

class Review(TimeStampedModel):
    “””Product review model with moderation.”””
    product = models.ForeignKey(Product, on_delete=models.CASCADE, related_name=’reviews’)
    user = models.ForeignKey(User, on_delete=models.CASCADE)
    rating = models.PositiveIntegerField(validators=[MinValueValidator(1), MaxValueValidator(5)])
    title = models.CharField(max_length=200)
    comment = models.TextField()
    is_approved = models.BooleanField(default=False)
    helpful_count = models.PositiveIntegerField(default=0)
   
    class Meta:
        unique_together = [‘product’, ‘user’]
        ordering = [‘-created_at’]
   
    def save(self, *args, kwargs):
        super().save(*args, kwargs)
        # Clear product rating cache
        cache.delete(f’product_rating_{self.product.pk}’)
   
    def __str__(self):
        return f”{self.user.get_full_name()} – {self.product.name} ({self.rating}/5)”

# File: ecommerce_project/products/views.py

from django.shortcuts import render, get_object_or_404, redirect
from django.contrib.auth.decorators import login_required
from django.contrib import messages
from django.core.paginator import Paginator
from django.db.models import Q, Avg, Count
from django.http import JsonResponse, Http404
from django.views.generic import ListView, DetailView
from django.views.decorators.http import require_http_methods
from django.views.decorators.cache import cache_page
from django.utils.decorators import method_decorator
from django.core.cache import cache
import json

from .models import Product, Category, Brand, Review
from .forms import ReviewForm, ProductFilterForm
from .serializers import ProductSerializer

class ProductListView(ListView):
    “””Advanced product listing with filtering, sorting, and search.”””
    model = Product
    template_name = ‘products/product_list.html’
    context_object_name = ‘products’
    paginate_by = 12
   
    def get_queryset(self):
        queryset = Product.objects.active().select_related(‘category’, ‘brand’).prefetch_related(‘images’, ‘tags’)
       
        # Search functionality
        search_query = self.request.GET.get(‘search’)
        if search_query:
            queryset = queryset.filter(
                Q(name__icontains=search_query) |
                Q(description__icontains=search_query) |
                Q(tags__name__icontains=search_query)
            ).distinct()
       
        # Category filtering
        category_slug = self.request.GET.get(‘category’)
        if category_slug:
            try:
                category = Category.objects.get(slug=category_slug)
                queryset = queryset.filter(
                    Q(category=category) | Q(category__parent=category)
                )
            except Category.DoesNotExist:
                pass
       
        # Brand filtering
        brand_slug = self.request.GET.get(‘brand’)
        if brand_slug:
            queryset = queryset.filter(brand__slug=brand_slug)
       
        # Price range filtering
        min_price = self.request.GET.get(‘min_price’)
        max_price = self.request.GET.get(‘max_price’)
        if min_price:
            queryset = queryset.filter(price__gte=min_price)
        if max_price:
            queryset = queryset.filter(price__lte=max_price)
       
        # Sorting
        sort_by = self.request.GET.get(‘sort’, ‘name’)
        sort_options = {
            ‘name’: ‘name’,
            ‘price_low’: ‘price’,
            ‘price_high’: ‘-price’,
            ‘newest’: ‘-created_at’,
            ‘popular’: ‘-view_count’,
            ‘rating’: ‘-reviews__rating’
        }
       
        if sort_by in sort_options:
            if sort_by == ‘rating’:
                queryset = queryset.annotate(avg_rating=Avg(‘reviews__rating’)).order_by(‘-avg_rating’)
            else:
                queryset = queryset.order_by(sort_options[sort_by])
       
        return queryset
   
    def get_context_data(self, kwargs):
        context = super().get_context_datakwargs)
       
        # Add filter form
        context[‘filter_form’] = ProductFilterForm(self.request.GET)
       
        # Add categories for sidebar
        context[‘categories’] = Category.objects.filter(is_active=True, parent__isnull=True)
       
        # Add brands for filtering
        context[‘brands’] = Brand.objects.filter(is_active=True).annotate(
            product_count=Count(‘products’)
        ).filter(product_count__gt=0)
       
        # Add current filters for display
        context[‘current_filters’] = {
            ‘search’: self.request.GET.get(‘search’, ”),
            ‘category’: self.request.GET.get(‘category’, ”),
            ‘brand’: self.request.GET.get(‘brand’, ”),
            ‘min_price’: self.request.GET.get(‘min_price’, ”),
            ‘max_price’: self.request.GET.get(‘max_price’, ”),
            ‘sort’: self.request.GET.get(‘sort’, ‘name’)
        }
       
        return context

@method_decorator(cache_page(60 * 15), name=’dispatch’)  # Cache for 15 minutes
class ProductDetailView(DetailView):
    “””Detailed product view with reviews and related products.”””
    model = Product
    template_name = ‘products/product_detail.html’
    context_object_name = ‘product’
    slug_field = ‘slug’
   
    def get_queryset(self):
        return Product.objects.active().select_related(‘category’, ‘brand’).prefetch_related(
            ‘images’, ‘tags’, ‘reviews__user’
        )
   
    def get_object(self, queryset=None):
        obj = super().get_object(queryset)
        # Increment view count
        obj.increment_view_count()
        return obj
   
    def get_context_data(self, **kwargs):
        context = super().get_context_data(**kwargs)
        product = self.object
       
        # Add review form
        context[‘review_form’] = ReviewForm()
       
        # Add approved reviews
        context[‘reviews’] = product.reviews.filter(is_approved=True).select_related(‘user’)
       
        # Add review statistics
        reviews = context[‘reviews’]
        if reviews:
            context[‘review_stats’] = {
                ‘average_rating’: product.get_average_rating(),
                ‘total_reviews’: reviews.count(),
                ‘rating_distribution’: {
                    5: reviews.filter(rating=5).count(),
                    4: reviews.filter(rating=4).count(),
                    3: reviews.filter(rating=3).count(),
                    2: reviews.filter(rating=2).count(),
                    1: reviews.filter(rating=1).count(),
                }
            }
       
        # Add related products
        context[‘related_products’] = Product.objects.active().filter(
            category=product.category
        ).exclude(pk=product.pk)[:4]
       
        # Check if user has already reviewed this product
        if self.request.user.is_authenticated:
            context[‘user_review’] = product.reviews.filter(user=self.request.user).first()
       
        return context

@login_required
@require_http_methods([“POST”])
def add_review(request, product_slug):
    “””Add a product review via AJAX.”””
    product = get_object_or_404(Product, slug=product_slug, is_active=True)
   
    # Check if user has already reviewed this product
    if Review.objects.filter(product=product, user=request.user).exists():
        return JsonResponse({
            ‘success’: False,
            ‘error’: ‘You have already reviewed this product.’
        })
   
    form = ReviewForm(request.POST)
    if form.is_valid():
        review = form.save(commit=False)
        review.product = product
        review.user = request.user
        review.save()
       
        messages.success(request, ‘Your review has been submitted and is pending approval.’)
       
        return JsonResponse({
            ‘success’: True,
            ‘message’: ‘Review submitted successfully!’
        })
    else:
        return JsonResponse({
            ‘success’: False,
            ‘errors’: form.errors
        })

def product_search_api(request):
    “””API endpoint for product search with autocomplete.”””
    query = request.GET.get(‘q’, ”).strip()
   
    if len(query) < 2:
        return JsonResponse({‘products’: []})
   
    products = Product.objects.active().filter(
        Q(name__icontains=query) | Q(description__icontains=query)
    )[:10]
   
    serializer = ProductSerializer(products, many=True)
    return JsonResponse({‘products’: serializer.data})

Django REST Framework and API Development (2-3 weeks)

• API Design Principles – RESTful architecture, HTTP methods, status codes, versioning
• Serializers and ViewSets – Data serialization, validation, nested relationships, permissions
• Authentication and Permissions – Token authentication, JWT, custom permissions, throttling
• API Documentation – Swagger/OpenAPI integration, automated documentation, testing tools

Testing and Quality Assurance (1-2 weeks)

• Unit Testing – Model tests, view tests, form tests, test fixtures
• Integration Testing – API testing, database testing, end-to-end workflows
• Performance Testing – Load testing, database query optimization, profiling
• Code Quality – Flake8, Black, pre-commit hooks, continuous integration

Django Projects:

1. Blog Management System – Complete CMS with user management, comments, categories, SEO optimization
2. E-commerce Platform – Full-featured online store with cart, payments, inventory management
3. Social Media API – RESTful API with posts, likes, follows, real-time notifications

Phase 3: Flask and FastAPI Development (Month 3-4)

Flask Framework Fundamentals (3-4 weeks)

• Flask Architecture – Application factory, blueprints, request context, application context
• Routing and Views – URL routing, HTTP methods, request handling, response generation
• Templates and Forms – Jinja2 templating, form handling, validation, flash messages
• Database Integration – SQLAlchemy ORM, database migrations, relationships, queries

FastAPI Modern Development (3-4 weeks)

High-Performance FastAPI Application:

# Advanced FastAPI Application with Modern Features
# File: fastapi_app/main.py

from fastapi import FastAPI, Depends, HTTPException, status, BackgroundTasks, Request
from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
from fastapi.middleware.cors import CORSMiddleware
from fastapi.middleware.trustedhost import TrustedHostMiddleware
from fastapi.responses import JSONResponse
from sqlalchemy.orm import Session
from contextlib import asynccontextmanager
import asyncio
import logging
from typing import List, Optional
import jwt
from datetime import datetime, timedelta
import redis
import aiofiles
from pydantic import BaseModel, EmailStr, validator
import uvicorn

# Import custom modules
from database import SessionLocal, engine, Base
from models import User, Product, Order
from schemas import UserCreate, UserResponse, ProductCreate, ProductResponse
from auth import create_access_token, verify_token
from tasks import send_email_task, process_order_task

# Setup logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Redis connection for caching
redis_client = redis.Redis(host=’localhost’, port=6379, db=0, decode_responses=True)

@asynccontextmanager
async def lifespan(app: FastAPI):
    “””Async context manager for application lifespan events.”””
    # Startup
    logger.info(“Starting up FastAPI application…”)
    Base.metadata.create_all(bind=engine)
    yield
    # Shutdown
    logger.info(“Shutting down FastAPI application…”)

# FastAPI application with advanced configuration
app = FastAPI(
    title=”Advanced E-commerce API”,
    description=”High-performance e-commerce platform with FastAPI”,
    version=”2.0.0″,
    docs_url=”/api/docs”,
    redoc_url=”/api/redoc”,
    lifespan=lifespan
)

# Security
security = HTTPBearer()

# Middleware configuration
app.add_middleware(
    CORSMiddleware,
    allow_origins=[“http://localhost:3000”, “https://yourdomain.com”],
    allow_credentials=True,
    allow_methods=[“*”],
    allow_headers=[“*”],
)

app.add_middleware(
    TrustedHostMiddleware,
    allowed_hosts=[“localhost”, “127.0.0.1”, “yourdomain.com”]
)

# Request logging middleware
@app.middleware(“http”)
async def log_requests(request: Request, call_next):
    start_time = datetime.utcnow()
    response = await call_next(request)
    process_time = (datetime.utcnow() – start_time).total_seconds()
   
    logger.info(
        f”{request.method} {request.url.path} – “
        f”Status: {response.status_code} – “
        f”Time: {process_time:.4f}s”
    )
    return response

# Database dependency
def get_db():
    db = SessionLocal()
    try:
        yield db
    finally:
        db.close()

# Authentication dependency
async def get_current_user(
    credentials: HTTPAuthorizationCredentials = Depends(security),
    db: Session = Depends(get_db)
):
    try:
        payload = jwt.decode(credentials.credentials, “secret”, algorithms=[“HS256”])
        user_id: int = payload.get(“user_id”)
        if user_id is None:
            raise HTTPException(
                status_code=status.HTTP_401_UNAUTHORIZED,
                detail=”Invalid authentication credentials”
            )
    except jwt.PyJWTError:
        raise HTTPException(
            status_code=status.HTTP_401_UNAUTHORIZED,
            detail=”Invalid authentication credentials”
        )
   
    user = db.query(User).filter(User.id == user_id).first()
    if user is None:
        raise HTTPException(
            status_code=status.HTTP_401_UNAUTHORIZED,
            detail=”User not found”
        )
    return user

# Pydantic models for advanced validation
class UserRegistration(BaseModel):
    email: EmailStr
    password: str
    first_name: str
    last_name: str
    phone: Optional[str] = None
   
    @validator(‘password’)
    def validate_password(cls, v):
        if len(v) < 8:
            raise ValueError(‘Password must be at least 8 characters long’)
        if not any(c.isupper() for c in v):
            raise ValueError(‘Password must contain at least one uppercase letter’)
        if not any(c.islower() for c in v):
            raise ValueError(‘Password must contain at least one lowercase letter’)
        if not any(c.isdigit() for c in v):
            raise ValueError(‘Password must contain at least one digit’)
        return v

class ProductFilter(BaseModel):
    category_id: Optional[int] = None
    min_price: Optional[float] = None
    max_price: Optional[float] = None
    search: Optional[str] = None
    sort_by: Optional[str] = “created_at”
    sort_order: Optional[str] = “desc”
    page: int = 1
    limit: int = 20

# Authentication endpoints
@app.post(“/api/auth/register”, response_model=UserResponse)
async def register_user(
    user_data: UserRegistration,
    background_tasks: BackgroundTasks,
    db: Session = Depends(get_db)
):
    “””Register a new user with email verification.”””
    # Check if user already exists
    existing_user = db.query(User).filter(User.email == user_data.email).first()
    if existing_user:
        raise HTTPException(
            status_code=status.HTTP_400_BAD_REQUEST,
            detail=”Email already registered”
        )
   
    # Create new user
    user = User(**user_data.dict())
    user.hash_password(user_data.password)
    db.add(user)
    db.commit()
    db.refresh(user)
   
    # Send welcome email in background
    background_tasks.add_task(
        send_email_task,
        user.email,
        “Welcome to our platform!”,
        f”Hello {user.first_name}, welcome to our e-commerce platform!”
    )
   
    logger.info(f”New user registered: {user.email}”)
    return UserResponse.from_orm(user)

@app.post(“/api/auth/login”)
async def login_user(email: EmailStr, password: str, db: Session = Depends(get_db)):
    “””Authenticate user and return access token.”””
    user = db.query(User).filter(User.email == email).first()
   
    if not user or not user.verify_password(password):
        raise HTTPException(
            status_code=status.HTTP_401_UNAUTHORIZED,
            detail=”Incorrect email or password”
        )
   
    if not user.is_active:
        raise HTTPException(
            status_code=status.HTTP_401_UNAUTHORIZED,
            detail=”Account is deactivated”
        )
   
    # Update last login
    user.last_login = datetime.utcnow()
    db.commit()
   
    # Create access token
    access_token = create_access_token(data={“user_id”: user.id})
   
    logger.info(f”User logged in: {user.email}”)
    return {
        “access_token”: access_token,
        “token_type”: “bearer”,
        “user”: UserResponse.from_orm(user)
    }

# Product endpoints with caching
@app.get(“/api/products”, response_model=List[ProductResponse])
async def get_products(
    filter_params: ProductFilter = Depends(),
    db: Session = Depends(get_db)
):
    “””Get paginated products with filtering and caching.”””
    # Create cache key
    cache_key = f”products:{filter_params.dict().__hash__()}”
   
    # Try to get from cache
    cached_result = redis_client.get(cache_key)
    if cached_result:
        logger.info(f”Cache hit for products query: {cache_key}”)
        return JSONResponse(content=eval(cached_result))
   
    # Build query
    query = db.query(Product).filter(Product.is_active == True)
   
    # Apply filters
    if filter_params.category_id:
        query = query.filter(Product.category_id == filter_params.category_id)
   
    if filter_params.min_price:
        query = query.filter(Product.price >= filter_params.min_price)
   
    if filter_params.max_price:
        query = query.filter(Product.price <= filter_params.max_price)
   
    if filter_params.search:
        search_term = f”%{filter_params.search}%”
        query = query.filter(
            Product.name.like(search_term) |
            Product.description.like(search_term)
        )
   
    # Apply sorting
    if filter_params.sort_by == “price”:
        if filter_params.sort_order == “desc”:
            query = query.order_by(Product.price.desc())
        else:
            query = query.order_by(Product.price.asc())
    elif filter_params.sort_by == “name”:
        query = query.order_by(Product.name.asc())
    else:  # created_at
        query = query.order_by(Product.created_at.desc())
   
    # Apply pagination
    offset = (filter_params.page – 1) * filter_params.limit
    products = query.offset(offset).limit(filter_params.limit).all()
   
    # Convert to response format
    result = [ProductResponse.from_orm(product) for product in products]
   
    # Cache the result for 5 minutes
    redis_client.setex(cache_key, 300, str([item.dict() for item in result]))
   
    logger.info(f”Retrieved {len(result)} products from database”)
    return result

# Health check endpoint
@app.get(“/api/health”)
async def health_check():
    “””Health check endpoint for monitoring.”””
    return {
        “status”: “healthy”,
        “timestamp”: datetime.utcnow().isoformat(),
        “version”: “2.0.0”
    }

if __name__ == “__main__”:
    uvicorn.run(
        “main:app”,
        host=”0.0.0.0″,
        port=8000,
        reload=True,
        workers=4
    )

API Integration and Microservices (2-3 weeks)

• RESTful API Design – Resource modeling, HTTP status codes, API versioning, rate limiting
• GraphQL Implementation – Schema definition, resolvers, queries, mutations, subscriptions
• Microservices Communication – Service discovery, message queues, event-driven architecture
• API Security – OAuth 2.0, JWT tokens, API keys, secure headers, input validation

Flask and FastAPI Projects:

1. Task Management API – RESTful API with authentication, real-time updates, file uploads
2. Data Analytics Dashboard – FastAPI backend with data visualization and real-time processing
3. Microservices E-commerce – Distributed system with user, product, order, and payment services

Phase 4: Frontend Integration and Full-Stack Development (Month 4-5)

Frontend Technologies and Integration (4-5 weeks)

• React with Python APIs – Frontend-backend integration, state management, API consumption
• Vue.js and Django – Component-based frontend, Vuex state management, authentication integration
• Modern CSS Frameworks – Tailwind CSS, Bootstrap integration, responsive design principles
• Progressive Web Apps – Service workers, offline functionality, push notifications

Database Design and Optimization (3-4 weeks)

• Advanced PostgreSQL – Complex queries, indexing, performance optimization, stored procedures
• MongoDB Integration – Document design, aggregation pipelines, replica sets, sharding
• Database Security – Access control, encryption, audit logging, backup strategies
• ORM Optimization – Query optimization, N+1 problems, caching strategies, performance monitoring

Real-time Features and WebSockets (2-3 weeks)

• Django Channels – WebSocket integration, real-time chat, notifications, live updates
• FastAPI WebSockets – Real-time communication, connection management, broadcasting
• Celery Task Queue – Background job processing, scheduled tasks, distributed task execution
• Redis Integration – Caching, session storage, pub/sub messaging, rate limiting

Full-Stack Projects:

1. Social Media Platform – Complete platform with React frontend, Django backend, real-time features
2. E-learning Management System – Video streaming, progress tracking, interactive content, assessments
3. Real-time Analytics Dashboard – Live data visualization with Vue.js frontend and FastAPI backend

Phase 5: Data Science Integration and Advanced Topics (Month 5-7)

Data Science and Machine Learning Integration (4-5 weeks)

• Pandas and NumPy Integration – Data processing pipelines, statistical analysis, data cleaning
• Machine Learning Models – Scikit-learn integration, model training, prediction APIs, model deployment
• Data Visualization – Matplotlib, Plotly, interactive dashboards, real-time charts
• Big Data Processing – Apache Spark integration, data lakes, ETL pipelines, stream processing

Choose Advanced Specialization:

AI/ML Full-Stack Developer:

• Machine Learning Pipelines – Model training, validation, deployment, monitoring, A/B testing
• Natural Language Processing – Text analysis, sentiment analysis, chatbot integration, language models
• Computer Vision – Image processing, object detection, facial recognition, automated tagging
• Recommendation Systems – Collaborative filtering, content-based filtering, hybrid approaches

Data Engineering Specialist:

• Data Pipeline Architecture – ETL/ELT processes, data warehousing, stream processing, batch processing
• Cloud Data Services – AWS S3, Redshift, Google BigQuery, Azure Data Factory integration
• Data Quality and Governance – Data validation, lineage tracking, privacy compliance, security
• Performance Optimization – Query optimization, data partitioning, caching strategies, monitoring

Enterprise Python Architect:

• System Architecture – Microservices design, distributed systems, scalability patterns, load balancing
• Security and Compliance – Security auditing, GDPR compliance, data encryption, access control
• DevOps Integration – Docker containers, Kubernetes orchestration, CI/CD pipelines, monitoring
• Team Leadership – Code review processes, documentation standards, mentoring, project management

Aditi Patel – From Data Analyst to Python Full Stack Developer

Background: 4 years as data analyst with strong SQL and Excel skills but limited programming experience
Challenge: Wanted to build complete applications beyond just data analysis and reporting
Python Advantage: Leveraged existing data skills while adding web development capabilities
Timeline: 19 months from Python beginner to senior full-stack developer
Current Position: Senior Python Developer at FinTech Startup
Salary Progression: ₹6.8 LPA → ₹11.5 LPA → ₹18.2 LPA → ₹28.5 LPA (over 20 months)

Aditi’s Technical Journey:

• Data Foundation – Used existing analytical thinking to understand application data flow and database design
• Web Development Skills – Mastered Django and React integration for creating data-driven applications
• Machine Learning Integration – Combined web development with predictive modeling and analytics
• Business Understanding – Applied domain knowledge to build applications solving real business problems

Key Success Factors:

• Analytical Mindset – “My data background helped me think systematically about application architecture and user workflows”
• Problem-Solving Focus – “I focused on building applications that solve real problems I encountered in my analytical work”
• Continuous Learning – “Python’s versatility allowed me to gradually expand from data analysis to full-stack development”

Current Impact: Leading development of financial analytics platform processing ₹500+ crores monthly transactions, responsible for ML models predicting market trends with 85% accuracy, managing team of 6 developers.

Vishnu Kumar – From Manual Tester to Python Automation Architect

Background: 5 years in manual testing with good understanding of application workflows but no development experience
Challenge: Wanted to transition from manual testing to development while leveraging testing expertise
Strategic Approach: Combined testing domain knowledge with Python development skills for unique positioning
Timeline: 17 months from Python beginner to automation architect role
Career Evolution: Manual Tester → Python Developer → Test Automation Lead → DevOps Python Specialist
Current Role: Principal Automation Architect at Global Consulting Firm

Automation Excellence and Technical Growth:

• Testing Background – Applied testing mindset to writing robust, error-handled Python applications
• Automation Expertise – Developed comprehensive test automation frameworks using Python and Selenium
• DevOps Integration – Extended Python skills to infrastructure automation, CI/CD pipelines, monitoring
• Team Leadership – Built automation team from 2 to 15 engineers across multiple client projects

Compensation and Career Growth:

• Pre-transition: ₹5.5 LPA (Senior Manual Tester)
• Year 1: ₹9.8 LPA (Python Developer with testing focus)
• Year 2: ₹16.5 LPA (Senior Automation Developer)
• Current: ₹32.8 LPA + bonuses (Principal Automation Architect with client portfolio)

Success Philosophy: “My testing background gave me a unique perspective on Python development. I naturally wrote more reliable code and could automate complex workflows that others found challenging.”

Rajesh Nair – From Mechanical Engineer to AI/ML Full Stack Developer

Background: 6 years as mechanical engineer with strong analytical skills but no software development experience
Challenge: Wanted career change into technology with focus on artificial intelligence and machine learning
Technical Transition: Used engineering problem-solving approach to master Python, ML, and web development
Timeline: 22 months from programming beginner to AI/ML specialist role
Career Evolution: Mechanical Engineer → Python Developer → ML Engineer → AI Full Stack Developer
Current Role: Senior AI Engineer at Healthcare Technology Company

AI/ML Development and Innovation:

• Engineering Mindset – Applied systematic engineering approach to ML model development and deployment
• Full-Stack ML – Built complete ML applications from data pipelines to web interfaces
• Domain Expertise – Specialized in applying AI to engineering and manufacturing problems
• Research Integration – Combined academic ML research with practical application development

Technical Growth and Impact:

• ML Model Development – Created predictive models for equipment maintenance with 92% accuracy
• Web Application Integration – Built Flask/React applications for real-time ML model deployment
• Data Pipeline Architecture – Designed scalable data processing systems handling terabytes of sensor data
• Cross-functional Leadership – Bridged gap between engineering teams and data science initiatives

Compensation Trajectory and Recognition:

• Pre-transition: ₹7.2 LPA (Senior Mechanical Engineer)
• Learning Phase: ₹4.8 LPA (Junior Python Developer – career reset)
• Months 12-18: ₹12.5 LPA (ML Engineer with domain expertise)
• Current: ₹24.8 LPA + equity (Senior AI Engineer with specialized healthcare focus)

Career Transition Insights: “Engineering gave me the methodical approach needed for ML development. When I combined that with Python skills and domain knowledge, I could build AI solutions that actually work in real manufacturing environments.”