Domande per colloqui Django e Python: Le Top 25 nel 2026
Le 25 domande piu comuni nei colloqui su Django e Python. ORM, view, middleware, DRF, signal e ottimizzazione con risposte dettagliate ed esempi di codice.

I colloqui tecnici su Django valutano la competenza con il framework web piu popolare di Python, la comprensione dell'ORM, dell'architettura MVT e la capacita di costruire API REST robuste. Questa guida copre le 25 domande piu frequenti, dai fondamentali di Django ai pattern avanzati del Django REST Framework.
Gli intervistatori apprezzano i candidati che sanno spiegare le scelte architetturali di Django. Comprendere perche il framework adotta determinate convenzioni (convention over configuration) fa una differenza reale durante i colloqui.
Fondamentali di Django
Domanda 1: Descrivere l'architettura MVT di Django
L'architettura Model-View-Template (MVT) e la variante Django del pattern MVC. Il framework gestisce automaticamente la parte del controller, semplificando lo sviluppo.
# models.py
# The Model represents data structure and business logic
from django.db import models
class Article(models.Model):
title = models.CharField(max_length=200)
content = models.TextField()
published_at = models.DateTimeField(auto_now_add=True)
author = models.ForeignKey(
"auth.User",
on_delete=models.CASCADE, # Deletes articles when author is deleted
related_name="articles" # Reverse access: user.articles.all()
)
class Meta:
ordering = ["-published_at"] # Default ordering
def __str__(self):
return self.title# views.py
# The View contains request processing logic
from django.shortcuts import render, get_object_or_404
def article_detail(request, pk):
# get_object_or_404 raises Http404 if the object doesn't exist
article = get_object_or_404(Article, pk=pk)
return render(request, "blog/article_detail.html", {"article": article})In MVT, Django funge da controller instradando gli URL alle view appropriate tramite urls.py. Il Template gestisce la presentazione HTML.
Domanda 2: Qual e la differenza tra un progetto Django e un'app?
Un progetto e la configurazione complessiva (impostazioni, URL root, WSGI/ASGI). Un'app e un modulo riutilizzabile con una singola responsabilita. Un progetto contiene piu app.
# Creating a project and an app
# django-admin startproject myproject
# python manage.py startapp blog
# settings.py
# Registering apps in the project
INSTALLED_APPS = [
"django.contrib.admin", # Admin interface
"django.contrib.auth", # Authentication
"django.contrib.contenttypes",
"django.contrib.sessions",
"django.contrib.messages",
"django.contrib.staticfiles",
# Custom apps
"blog.apps.BlogConfig", # Blog app
"users.apps.UsersConfig", # Users app
]Ogni app segue il principio di responsabilita unica e puo essere riutilizzata in diversi progetti.
Domanda 3: Spiegare il ciclo di vita delle richieste in Django
La richiesta attraversa diversi livelli prima di raggiungere la view. La comprensione di questo ciclo e essenziale per il debug e l'ottimizzazione.
# middleware.py
# Middlewares intercept every request/response
class RequestTimingMiddleware:
"""Middleware that measures processing time."""
def __init__(self, get_response):
self.get_response = get_response # Reference to the next middleware
def __call__(self, request):
import time
start = time.time()
# Request phase: before the view
response = self.get_response(request)
# Response phase: after the view
duration = time.time() - start
response["X-Request-Duration"] = f"{duration:.3f}s"
return responseIl ciclo completo: richiesta HTTP → WSGI/ASGI → middleware (process_request) → URL resolver → view → middleware (process_response) → risposta HTTP.
ORM e Database
Domanda 4: Come funzionano i QuerySet di Django e cos'e il Lazy Loading?
I QuerySet vengono valutati in modo lazy: nessuna query SQL viene eseguita fino a quando i dati non vengono effettivamente utilizzati.
# queryset_lazy.py
# Demonstrating QuerySet lazy loading
# No SQL query executed here
qs = Article.objects.filter(published=True) # No query
qs = qs.exclude(title="Draft") # Still none
qs = qs.order_by("-created_at") # Still none
# The SQL query runs ONLY here
for article in qs: # ONE combined SQL query
print(article.title)
# Other evaluation triggers
list(qs) # Converting to list
qs[0] # Index access
len(qs) # Counting (prefer qs.count())
bool(qs) # Existence check (prefer qs.exists())Questa valutazione lazy consente di concatenare filtri senza overhead, eseguendo una sola query ottimizzata.
Domanda 5: Cos'e il problema N+1 e come risolverlo?
Il problema N+1 si verifica quando una query principale genera N query aggiuntive per caricare le relazioni. E la causa piu comune di lentezza nelle applicazioni Django.
# n_plus_one.py
# N+1 problem and solutions
# ❌ PROBLEM: N+1 queries
# 1 query for articles + 1 query PER article for the author
articles = Article.objects.all()
for article in articles:
print(article.author.username) # SQL query on every iteration!
# ✅ SOLUTION 1: select_related (ForeignKey, OneToOne)
# Joins tables in ONE SQL query (JOIN)
articles = Article.objects.select_related("author").all()
for article in articles:
print(article.author.username) # No additional query
# ✅ SOLUTION 2: prefetch_related (ManyToMany, reverse FK)
# Executes 2 separate queries + Python assembly
articles = Article.objects.prefetch_related("tags").all()
for article in articles:
print(article.tags.all()) # Data already cached
# ✅ SOLUTION 3: Custom Prefetch with filtering
from django.db.models import Prefetch
articles = Article.objects.prefetch_related(
Prefetch(
"comments",
queryset=Comment.objects.filter(approved=True).select_related("user"),
to_attr="approved_comments" # Custom attribute
)
)Si utilizza select_related per le relazioni ForeignKey/OneToOne (SQL JOIN) e prefetch_related per le relazioni ManyToMany o inverse (query separate).
Domanda 6: Come creare un Custom Manager e quando utilizzarlo?
I Custom Manager incapsulano le query frequenti a livello di modello, rendendo il codice piu leggibile e riutilizzabile.
# managers.py
# Custom Managers and QuerySets
class PublishedQuerySet(models.QuerySet):
"""Reusable QuerySet for published articles."""
def published(self):
return self.filter(status="published", published_at__lte=timezone.now())
def by_author(self, user):
return self.filter(author=user)
def popular(self):
return self.annotate(
comment_count=models.Count("comments")
).order_by("-comment_count")
class PublishedManager(models.Manager):
"""Manager that exposes only published articles."""
def get_queryset(self):
return PublishedQuerySet(self.model, using=self._db).published()
class Article(models.Model):
# ...
objects = models.Manager() # Default manager (all articles)
published = PublishedManager() # Custom manager (published only)
# Usage:
# Article.objects.all() → All articles
# Article.published.all() → Published articles only
# Article.published.popular() → Published articles sorted by popularityI Custom Manager seguono il principio DRY e centralizzano la logica delle query.
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View e URL
Domanda 7: Quando utilizzare Class-Based Views rispetto alle Function-Based Views?
Le Function-Based Views (FBV) offrono semplicita e controllo esplicito. Le Class-Based Views (CBV) apportano riutilizzabilita e struttura attraverso l'ereditarieta.
# views_comparison.py
# FBV: Explicit, simple, easy to understand
from django.http import JsonResponse
from django.views.decorators.http import require_http_methods
@require_http_methods(["GET", "POST"])
def article_list(request):
if request.method == "GET":
articles = Article.published.all()
return render(request, "articles/list.html", {"articles": articles})
# POST: article creation
form = ArticleForm(request.POST)
if form.is_valid():
form.save()
return redirect("article-list")
return render(request, "articles/list.html", {"form": form})# views_cbv.py
# CBV: Reusable, extensible via mixins
from django.views.generic import ListView, CreateView
from django.contrib.auth.mixins import LoginRequiredMixin
class ArticleListView(LoginRequiredMixin, ListView):
model = Article
template_name = "articles/list.html"
context_object_name = "articles" # Variable name in the template
paginate_by = 20 # Automatic pagination
def get_queryset(self):
# Override to filter published articles
return Article.published.all()
class ArticleCreateView(LoginRequiredMixin, CreateView):
model = Article
form_class = ArticleForm
success_url = reverse_lazy("article-list")
def form_valid(self, form):
form.instance.author = self.request.user # Assign the author
return super().form_valid(form)Regola pratica: utilizzare le FBV per logica semplice o non standard, le CBV per operazioni CRUD standard.
Domanda 8: Come funzionano i middleware in Django?
I middleware sono hook che elaborano ogni richiesta/risposta. Ogni middleware puo intervenire in diverse fasi del ciclo di elaborazione.
# auth_middleware.py
# Custom authentication middleware
import jwt
from django.conf import settings
from django.http import JsonResponse
class JWTAuthenticationMiddleware:
"""Verifies JWT token on protected endpoints."""
EXEMPT_PATHS = ["/api/auth/login", "/api/auth/register", "/health"]
def __init__(self, get_response):
self.get_response = get_response
def __call__(self, request):
# Skip exempt paths
if any(request.path.startswith(p) for p in self.EXEMPT_PATHS):
return self.get_response(request)
# Extract and verify the token
auth_header = request.headers.get("Authorization", "")
if not auth_header.startswith("Bearer "):
return JsonResponse({"error": "Missing token"}, status=401)
try:
token = auth_header.split(" ")[1]
payload = jwt.decode(token, settings.SECRET_KEY, algorithms=["HS256"])
request.user_id = payload["user_id"] # Attach to request
except jwt.ExpiredSignatureError:
return JsonResponse({"error": "Token expired"}, status=401)
except jwt.InvalidTokenError:
return JsonResponse({"error": "Invalid token"}, status=401)
return self.get_response(request)L'ordine dei middleware in MIDDLEWARE e cruciale: vengono eseguiti dall'alto verso il basso per le richieste e dal basso verso l'alto per le risposte.
Django REST Framework
Domanda 9: Qual e la differenza tra Serializer e ModelSerializer?
Serializer definisce manualmente ogni campo, mentre ModelSerializer genera automaticamente i campi dal modello.
# serializers.py
from rest_framework import serializers
# Manual Serializer: full control over each field
class ArticleSerializer(serializers.Serializer):
id = serializers.IntegerField(read_only=True)
title = serializers.CharField(max_length=200)
content = serializers.CharField()
author_name = serializers.SerializerMethodField()
def get_author_name(self, obj):
return obj.author.get_full_name()
def create(self, validated_data):
return Article.objects.create(**validated_data)
def update(self, instance, validated_data):
instance.title = validated_data.get("title", instance.title)
instance.content = validated_data.get("content", instance.content)
instance.save()
return instance
# ModelSerializer: automatic field generation
class ArticleModelSerializer(serializers.ModelSerializer):
author_name = serializers.SerializerMethodField()
comment_count = serializers.IntegerField(read_only=True)
class Meta:
model = Article
fields = ["id", "title", "content", "author", "author_name",
"comment_count", "published_at"]
read_only_fields = ["published_at"]
def get_author_name(self, obj):
return obj.author.get_full_name()Si preferisce ModelSerializer per i casi standard e Serializer quando la rappresentazione differisce significativamente dal modello.
Domanda 10: Come implementare la paginazione in DRF?
DRF offre diverse strategie di paginazione configurabili globalmente o per singola view.
# settings.py
# Global pagination configuration
REST_FRAMEWORK = {
"DEFAULT_PAGINATION_CLASS": "rest_framework.pagination.PageNumberPagination",
"PAGE_SIZE": 20,
}
# pagination.py
# Custom pagination per view
from rest_framework.pagination import CursorPagination, LimitOffsetPagination
class ArticleCursorPagination(CursorPagination):
"""Cursor pagination: performant for large datasets."""
page_size = 20
ordering = "-published_at" # Indexed field required
cursor_query_param = "cursor"
class ArticleLimitOffsetPagination(LimitOffsetPagination):
"""Offset/limit pagination: flexible but less performant."""
default_limit = 20
max_limit = 100
# views.py
class ArticleViewSet(viewsets.ModelViewSet):
queryset = Article.published.all()
serializer_class = ArticleModelSerializer
pagination_class = ArticleCursorPagination # View-specific paginationLa paginazione basata su cursore e raccomandata per dataset di grandi dimensioni, poiche rimane performante indipendentemente dal numero di pagina, a differenza di OFFSET/LIMIT.
Domanda 11: Come proteggere un'API con i permessi DRF?
DRF fornisce un sistema di permessi modulare che combina autenticazione e autorizzazione granulare.
# permissions.py
from rest_framework.permissions import BasePermission, IsAuthenticated
class IsAuthorOrReadOnly(BasePermission):
"""Only the author can modify, everyone can read."""
def has_object_permission(self, request, view, obj):
# GET, HEAD, OPTIONS are always allowed
if request.method in ("GET", "HEAD", "OPTIONS"):
return True
# Only the author can modify or delete
return obj.author == request.user
class IsAdminOrManager(BasePermission):
"""Access restricted to admins and managers."""
def has_permission(self, request, view):
return (
request.user.is_authenticated
and request.user.role in ("admin", "manager")
)
# views.py
from rest_framework.viewsets import ModelViewSet
from rest_framework.throttling import UserRateThrottle
class ArticleViewSet(ModelViewSet):
permission_classes = [IsAuthenticated, IsAuthorOrReadOnly]
throttle_classes = [UserRateThrottle] # Rate limiting
def get_permissions(self):
# Dynamic permissions based on action
if self.action == "destroy":
return [IsAdminOrManager()]
return super().get_permissions()Si combinano permission_classes a livello di view e has_object_permission per il controllo fine per oggetto.
Signal e task asincroni
Domanda 12: Come funzionano i Django Signal e quando utilizzarli?
I Signal consentono di disaccoppiare i componenti reagendo a eventi del framework o dell'applicazione.
# signals.py
from django.db.models.signals import post_save, pre_delete
from django.dispatch import receiver
from django.core.mail import send_mail
@receiver(post_save, sender=Article)
def notify_on_publish(sender, instance, created, **kwargs):
"""Sends a notification when an article is published."""
if not created and instance.status == "published":
# Triggered only on publication (not creation)
subscribers = instance.author.subscribers.values_list("email", flat=True)
send_mail(
subject=f"New article: {instance.title}",
message=f"Check out the latest article by {instance.author.username}",
from_email="noreply@example.com",
recipient_list=list(subscribers),
)
@receiver(pre_delete, sender=Article)
def cleanup_article_files(sender, instance, **kwargs):
"""Deletes associated files before article deletion."""
if instance.cover_image:
instance.cover_image.delete(save=False) # Deletes the physical fileI Signal sono adatti per effetti collaterali leggeri (logging, invalidazione della cache). Per task pesanti, si preferisce Celery.
Domanda 13: Come integrare Celery con Django per i task asincroni?
Celery consente l'esecuzione di task in background, essenziale per operazioni di lunga durata come l'invio di email o l'elaborazione di file.
# celery_config.py
# Celery configuration in the Django project
import os
from celery import Celery
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "myproject.settings")
app = Celery("myproject")
app.config_from_object("django.conf:settings", namespace="CELERY")
app.autodiscover_tasks() # Discovers tasks.py in each app
# tasks.py
from celery import shared_task
from django.core.mail import send_mass_mail
@shared_task(bind=True, max_retries=3, default_retry_delay=60)
def send_newsletter(self, article_id):
"""Sends newsletter asynchronously."""
try:
article = Article.objects.get(id=article_id)
subscribers = User.objects.filter(newsletter=True)
messages = [
(f"New: {article.title}", article.content[:200],
"noreply@example.com", [sub.email])
for sub in subscribers
]
send_mass_mail(messages, fail_silently=False)
except Article.DoesNotExist:
pass # Article was deleted in the meantime
except Exception as exc:
self.retry(exc=exc) # Automatic retry on error
# Calling from a view
# send_newsletter.delay(article.id) # Async execution
# send_newsletter.apply_async(args=[article.id], countdown=300) # 5-min delayCelery e indispensabile in produzione per qualsiasi operazione che non deve bloccare la risposta HTTP.
Sicurezza e autenticazione
Domanda 14: Come protegge Django dagli attacchi CSRF?
Django include una protezione CSRF integrata tramite un middleware che verifica un token univoco ad ogni richiesta POST.
# CSRF protection in forms
# The {% csrf_token %} template tag generates a hidden field
# For APIs (DRF), CSRF is often disabled in favor of tokens
# settings.py
REST_FRAMEWORK = {
"DEFAULT_AUTHENTICATION_CLASSES": [
"rest_framework.authentication.SessionAuthentication", # Includes CSRF
"rest_framework.authentication.TokenAuthentication", # No CSRF
],
}
# For AJAX views with session auth
# The csrftoken cookie must be sent in the X-CSRFToken header# csrf_exemption.py
# Exempting a specific view (use with caution)
from django.views.decorators.csrf import csrf_exempt, ensure_csrf_cookie
@ensure_csrf_cookie
def get_csrf_token(request):
"""Endpoint that forces sending the CSRF cookie to the client."""
return JsonResponse({"detail": "CSRF cookie set"})
@csrf_exempt # ⚠️ Use only for external webhooks
def stripe_webhook(request):
"""Stripe webhook - authenticated by signature, not CSRF."""
payload = request.body
sig_header = request.headers.get("Stripe-Signature")
# Verified by Stripe signature insteadIl CSRF non deve mai essere disabilitato globalmente. csrf_exempt va utilizzato solo su endpoint autenticati con altri mezzi (webhook, token API).
Domanda 15: Come implementare l'autenticazione personalizzata in Django?
Django consente di sostituire il modello User predefinito e di personalizzare il backend di autenticazione.
# models.py
from django.contrib.auth.models import AbstractBaseUser, BaseUserManager, PermissionsMixin
class CustomUserManager(BaseUserManager):
"""Manager for the custom User model."""
def create_user(self, email, password=None, **extra_fields):
if not email:
raise ValueError("Email is required")
email = self.normalize_email(email) # Normalizes the domain
user = self.model(email=email, **extra_fields)
user.set_password(password) # Hashes the password
user.save(using=self._db)
return user
def create_superuser(self, email, password=None, **extra_fields):
extra_fields.setdefault("is_staff", True)
extra_fields.setdefault("is_superuser", True)
return self.create_user(email, password, **extra_fields)
class CustomUser(AbstractBaseUser, PermissionsMixin):
email = models.EmailField(unique=True) # Login by email
username = models.CharField(max_length=30, blank=True)
is_active = models.BooleanField(default=True)
is_staff = models.BooleanField(default=False)
date_joined = models.DateTimeField(auto_now_add=True)
objects = CustomUserManager()
USERNAME_FIELD = "email" # Field used for login
REQUIRED_FIELDS = [] # Fields required in addition to USERNAME_FIELD
# settings.py
AUTH_USER_MODEL = "users.CustomUser" # Before the first migration!AUTH_USER_MODEL deve essere definito all'inizio del progetto. Modificarlo dopo le prime migrazioni e complesso e rischioso.
Ottimizzazione e performance
Domanda 16: Come ottimizzare le query dell'ORM Django?
L'ottimizzazione delle query e fondamentale per le performance. Diverse tecniche riducono il numero e il costo delle query SQL.
# query_optimization.py
from django.db.models import F, Q, Count, Avg, Prefetch
# 1. Only/Defer: load only needed fields
articles = Article.objects.only("title", "published_at") # SELECT title, published_at
heavy_articles = Article.objects.defer("content") # Everything EXCEPT content
# 2. SQL-level aggregations (not Python)
stats = Article.objects.aggregate(
total=Count("id"),
avg_views=Avg("view_count"),
)
# 3. F() expressions: SQL-level operations
Article.objects.filter(published=True).update(
view_count=F("view_count") + 1 # Atomic SQL increment
)
# 4. Q() objects: complex queries
results = Article.objects.filter(
Q(title__icontains="django") | Q(tags__name="python"),
~Q(status="draft"), # NOT draft
published_at__year=2026
)
# 5. Bulk operations: reduce INSERT/UPDATE queries
articles = [Article(title=f"Article {i}") for i in range(100)]
Article.objects.bulk_create(articles, batch_size=50) # 2 queries instead of 100
Article.objects.filter(status="draft").update(status="archived") # 1 querySi consiglia di utilizzare django-debug-toolbar in sviluppo per identificare query lente e problemi N+1.
Domanda 17: Come implementare il caching in Django?
Django fornisce un framework di caching multilivello: per view, per frammento di template o per dati arbitrari.
# settings.py
CACHES = {
"default": {
"BACKEND": "django.core.cache.backends.redis.RedisCache",
"LOCATION": "redis://127.0.0.1:6379/1",
}
}
# cache_strategies.py
from django.core.cache import cache
from django.views.decorators.cache import cache_page
from django.utils.decorators import method_decorator
# Per-view cache: caches the entire HTTP response
@cache_page(60 * 15) # 15 minutes
def article_list(request):
return render(request, "articles/list.html", {"articles": Article.published.all()})
# Data cache: granular control
def get_popular_articles():
cache_key = "popular_articles_v1"
articles = cache.get(cache_key)
if articles is None:
articles = list(
Article.published.popular()[:10].values("id", "title", "view_count")
)
cache.set(cache_key, articles, timeout=60 * 30) # 30 min
return articles
# Cache invalidation
def invalidate_article_cache(article_id):
cache.delete(f"article_{article_id}")
cache.delete("popular_articles_v1")
cache.delete_pattern("article_list_*") # With django-redisRedis e raccomandato come backend di cache in produzione per la persistenza e le funzionalita avanzate (pattern, TTL).
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Migrazioni e gestione del database
Domanda 18: Come gestire migrazioni complesse in Django?
Le migrazioni Django gestiscono l'evoluzione dello schema del database in modo versionato e riproducibile.
# 0005_migrate_data.py
# Custom data migration
from django.db import migrations
def migrate_user_roles(apps, schema_editor):
"""Converts is_admin booleans to text roles."""
User = apps.get_model("users", "CustomUser")
# Use apps.get_model() to access the historical model
User.objects.filter(is_admin=True).update(role="admin")
User.objects.filter(is_admin=False, is_staff=True).update(role="manager")
User.objects.filter(is_admin=False, is_staff=False).update(role="user")
def reverse_migrate(apps, schema_editor):
"""Reverse migration for rollback."""
User = apps.get_model("users", "CustomUser")
User.objects.filter(role="admin").update(is_admin=True)
class Migration(migrations.Migration):
dependencies = [
("users", "0004_add_role_field"),
]
operations = [
migrations.RunPython(migrate_user_roles, reverse_migrate),
]Una funzione reverse deve sempre essere fornita per consentire il rollback. Le migrazioni vanno testate su una copia del database di produzione prima del deployment.
Domanda 19: Come creare indici personalizzati per l'ottimizzazione?
Gli indici accelerano le query frequenti ma aumentano i costi di scrittura. Una selezione accurata e essenziale.
# models.py
class Article(models.Model):
title = models.CharField(max_length=200)
slug = models.SlugField(unique=True)
status = models.CharField(max_length=20, db_index=True) # Simple index
published_at = models.DateTimeField(null=True)
author = models.ForeignKey("auth.User", on_delete=models.CASCADE)
class Meta:
indexes = [
# Composite index for frequent queries
models.Index(fields=["status", "-published_at"], name="idx_status_date"),
# Partial index: only published articles
models.Index(
fields=["published_at"],
condition=models.Q(status="published"),
name="idx_published_articles"
),
# GIN index for full-text search (PostgreSQL)
GinIndex(fields=["search_vector"], name="idx_search"),
]Gli indici composti seguono l'ordine delle colonne: il campo piu selettivo deve essere posizionato per primo.
Testing e qualita
Domanda 20: Come strutturare i test in un progetto Django?
Django fornisce un framework di test robusto basato su unittest, potenziato da pytest-django per maggiore flessibilita.
# tests/test_views.py
from django.test import TestCase, Client
from django.urls import reverse
from rest_framework.test import APITestCase, APIClient
class ArticleViewTests(TestCase):
"""View tests with Django's test client."""
def setUp(self):
self.client = Client()
self.user = CustomUser.objects.create_user(
email="test@example.com", password="testpass123"
)
self.article = Article.objects.create(
title="Test Article",
content="Content here",
author=self.user,
status="published"
)
def test_article_list_returns_200(self):
response = self.client.get(reverse("article-list"))
self.assertEqual(response.status_code, 200)
self.assertContains(response, "Test Article")
def test_create_article_requires_auth(self):
response = self.client.post(reverse("article-create"), {"title": "New"})
self.assertEqual(response.status_code, 302) # Redirects to login
class ArticleAPITests(APITestCase):
"""REST API tests with DRF."""
def setUp(self):
self.user = CustomUser.objects.create_user(
email="api@example.com", password="testpass123"
)
self.client = APIClient()
self.client.force_authenticate(user=self.user)
def test_create_article_via_api(self):
data = {"title": "API Article", "content": "Created via API"}
response = self.client.post("/api/articles/", data, format="json")
self.assertEqual(response.status_code, 201)
self.assertEqual(Article.objects.count(), 1)I test vanno separati in file per dominio: test_models.py, test_views.py, test_serializers.py, test_services.py.
Domanda 21: Come utilizzare fixture e factory per i test?
Le factory (con factory_boy) sono preferite rispetto alle fixture JSON per flessibilita e manutenibilita dei dati di test.
# factories.py
import factory
from factory.django import DjangoModelFactory
class UserFactory(DjangoModelFactory):
class Meta:
model = CustomUser
email = factory.Sequence(lambda n: f"user{n}@example.com")
username = factory.Faker("user_name")
is_active = True
class ArticleFactory(DjangoModelFactory):
class Meta:
model = Article
title = factory.Faker("sentence", nb_words=5)
content = factory.Faker("paragraphs", nb=3)
author = factory.SubFactory(UserFactory) # Creates a user automatically
status = "published"
class Params:
draft = factory.Trait(status="draft", published_at=None)
# tests.py
def test_published_articles_count(self):
ArticleFactory.create_batch(5) # 5 published articles
ArticleFactory.create_batch(3, draft=True) # 3 drafts
self.assertEqual(Article.published.count(), 5)Le factory garantiscono dati di test consistenti ed evitano dipendenze tra i test.
Pattern avanzati
Domanda 22: Come implementare i WebSocket con Django Channels?
Django Channels estende Django oltre l'HTTP per supportare WebSocket, protocolli in tempo reale e task in background.
# consumers.py
import json
from channels.generic.websocket import AsyncWebsocketConsumer
class ChatConsumer(AsyncWebsocketConsumer):
"""WebSocket consumer for real-time chat."""
async def connect(self):
self.room_name = self.scope["url_route"]["kwargs"]["room_name"]
self.room_group = f"chat_{self.room_name}"
# Join the room group
await self.channel_layer.group_add(self.room_group, self.channel_name)
await self.accept()
async def disconnect(self, close_code):
# Leave the group
await self.channel_layer.group_discard(self.room_group, self.channel_name)
async def receive(self, text_data):
data = json.loads(text_data)
# Broadcast message to the entire group
await self.channel_layer.group_send(
self.room_group,
{"type": "chat.message", "message": data["message"],
"username": self.scope["user"].username}
)
async def chat_message(self, event):
# Send message to the WebSocket client
await self.send(text_data=json.dumps({
"message": event["message"],
"username": event["username"],
}))Django Channels utilizza ASGI (invece di WSGI) e richiede un server compatibile come Daphne o Uvicorn.
Domanda 23: Spiegare il pattern Repository e Service Layer in Django
Il pattern Service Layer separa la logica di business dalle view e dall'ORM, facilitando il testing e la manutenzione.
# services/article_service.py
from django.db import transaction
class ArticleService:
"""Service encapsulating article business logic."""
@staticmethod
def publish_article(article_id: int, user) -> Article:
"""Publishes an article with all validations."""
article = Article.objects.select_for_update().get(id=article_id)
if article.author != user:
raise PermissionError("Only the author can publish this article")
if article.status == "published":
raise ValueError("Article is already published")
article.status = "published"
article.published_at = timezone.now()
article.save(update_fields=["status", "published_at"])
# Side effects: notification, cache, analytics
send_newsletter.delay(article.id)
cache.delete("popular_articles_v1")
return article
@staticmethod
@transaction.atomic
def bulk_archive(article_ids: list[int], user) -> int:
"""Archives multiple articles in a transaction."""
updated = Article.objects.filter(
id__in=article_ids,
author=user,
status="published"
).update(status="archived", archived_at=timezone.now())
return updatedIl Service Layer e il punto di ingresso per tutta la logica di business. Le view e i serializer delegano al service, mai direttamente all'ORM.
Domanda 24: Come gestire le variabili d'ambiente e la configurazione multi-ambiente?
La gestione della configurazione segue i principi della 12-Factor App: separazione rigorosa tra configurazione e codice.
# settings/base.py
# Shared configuration across all environments
import os
from pathlib import Path
from dotenv import load_dotenv
load_dotenv() # Loads the .env file
BASE_DIR = Path(__file__).resolve().parent.parent.parent
SECRET_KEY = os.environ["DJANGO_SECRET_KEY"] # Required, no default value
DEBUG = os.environ.get("DEBUG", "False").lower() == "true"
ALLOWED_HOSTS = os.environ.get("ALLOWED_HOSTS", "").split(",")
DATABASES = {
"default": {
"ENGINE": "django.db.backends.postgresql",
"NAME": os.environ.get("DB_NAME", "myapp"),
"USER": os.environ.get("DB_USER", "postgres"),
"HOST": os.environ.get("DB_HOST", "localhost"),
"PORT": os.environ.get("DB_PORT", "5432"),
}
}
# settings/production.py
from .base import *
DEBUG = False
SECURE_SSL_REDIRECT = True
SESSION_COOKIE_SECURE = True
CSRF_COOKIE_SECURE = True
SECURE_HSTS_SECONDS = 31536000 # 1 yearI segreti non devono mai essere committati nel codice. Vanno utilizzate variabili d'ambiente o un secrets manager (Vault, AWS Secrets Manager).
Domanda 25: Come deployare un'applicazione Django in produzione?
Il deployment in produzione richiede una checklist completa che copre sicurezza, performance e affidabilita.
# Django deployment checklist
# 1. Built-in verification command
# python manage.py check --deploy
# 2. WSGI/ASGI configuration for production
# gunicorn.conf.py
import multiprocessing
bind = "0.0.0.0:8000"
workers = multiprocessing.cpu_count() * 2 + 1 # Recommended formula
worker_class = "gthread" # Threaded workers
threads = 4
max_requests = 1000 # Recycle workers to avoid memory leaks
max_requests_jitter = 50
timeout = 30
accesslog = "-" # Logs to stdout
errorlog = "-"# docker-compose.yml (typical configuration)
# Services: web (gunicorn), db (postgres), redis (cache/celery), worker (celery)
# 3. Static files
# python manage.py collectstatic --noinput
# Serve via nginx or CDN (WhiteNoise for simple cases)
# 4. Nginx configuration
# - Proxy to gunicorn on port 8000
# - Serve /static/ and /media/ directly
# - Enable gzip, HTTP/2, and security headersEseguire python manage.py check --deploy prima di ogni rilascio in produzione. Questo comando verifica le impostazioni di sicurezza essenziali.
Conclusione
Queste 25 domande coprono gli aspetti essenziali dei colloqui su Django e Python, dai fondamentali dell'architettura MVT ai pattern di deployment in produzione.
Checklist di preparazione:
- ✅ Architettura MVT e ciclo di vita delle richieste
- ✅ ORM: QuerySet, N+1, select_related, prefetch_related
- ✅ Django REST Framework: serializer, paginazione, permessi
- ✅ Sicurezza: CSRF, autenticazione, permessi
- ✅ Performance: ottimizzazione ORM, caching, indici
- ✅ Testing: TestCase, APITestCase, factory
- ✅ Pattern avanzati: Channels, Service Layer, deployment
Ogni domanda merita un approfondimento con la documentazione ufficiale di Django. Gli intervistatori apprezzano i candidati che comprendono le sfumature del framework e sanno giustificare le proprie decisioni tecniche.
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