Django: How to handle database transactions properly to avoid data inconsistency?
I'm working on a Django project and encountering an issue with Django admin. Here's my current implementation:
# models.py
# views.py
from django.shortcuts import render
from .models import Article
def article_list(request):
articles = Article.objects.all()
for article in articles:
print(article.author.username) # N+1 problem here
return render(request, 'articles.html', {'articles': articles})
The specific error I'm getting is: "django.db.utils.DataError: value too long for type character varying(100)"
I've already tried the following approaches:
- Checked Django documentation and Stack Overflow
- Verified my database schema and migrations
- Added debugging prints to trace the issue
- Tested with different data inputs
Environment details:
- Django version: 5.0.1
- Python version: 3.11.0
- Database: PostgreSQL 15
- Operating system: Windows 11
Has anyone encountered this before? Any guidance would be greatly appreciated!
2 Answers
Here's a comprehensive approach to implementing JWT authentication in Django REST Framework:
# settings.py
INSTALLED_APPS = [
'rest_framework',
'rest_framework_simplejwt',
]
REST_FRAMEWORK = {
'DEFAULT_AUTHENTICATION_CLASSES': (
'rest_framework_simplejwt.authentication.JWTAuthentication',
),
'DEFAULT_PERMISSION_CLASSES': [
'rest_framework.permissions.IsAuthenticated',
],
}
from datetime import timedelta
SIMPLE_JWT = {
'ACCESS_TOKEN_LIFETIME': timedelta(minutes=60),
'REFRESH_TOKEN_LIFETIME': timedelta(days=7),
'ROTATE_REFRESH_TOKENS': True,
}# urls.py
from rest_framework_simplejwt.views import (
TokenObtainPairView,
TokenRefreshView,
)
urlpatterns = [
path('api/token/', TokenObtainPairView.as_view()),
path('api/token/refresh/', TokenRefreshView.as_view()),
]# Custom serializer for additional user data
from rest_framework_simplejwt.serializers import TokenObtainPairSerializer
class CustomTokenObtainPairSerializer(TokenObtainPairSerializer):
@classmethod
def get_token(cls, user):
token = super().get_token(user)
token['username'] = user.username
token['email'] = user.email
return tokenComments
sarah_tech: Could you provide the requirements.txt for the packages used in this solution? 2 months ago
abdullah: I'm new to Django ORM optimization. Could you explain the database indexing part in simpler terms? 2 months ago
Python decorators with arguments require a three-level nested function. Here's the proper implementation:
import functools
# Decorator with arguments
def retry(max_attempts=3, delay=1):
def decorator(func):
@functools.wraps(func) # Preserves function metadata
def wrapper(*args, **kwargs):
for attempt in range(max_attempts):
try:
return func(*args, **kwargs)
except Exception as e:
if attempt == max_attempts - 1:
raise e
time.sleep(delay)
return wrapper
return decorator
# Usage
@retry(max_attempts=5, delay=2)
def unreliable_function():
# Function that might fail
passClass-based decorator (alternative approach):
class Retry:
def __init__(self, max_attempts=3, delay=1):
self.max_attempts = max_attempts
self.delay = delay
def __call__(self, func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
for attempt in range(self.max_attempts):
try:
return func(*args, **kwargs)
except Exception as e:
if attempt == self.max_attempts - 1:
raise e
time.sleep(self.delay)
return wrapper
# Usage
@Retry(max_attempts=5, delay=2)
def another_function():
passComments
abdullah3: Excellent debugging strategy! The logging configuration is exactly what our team needed. 2 months ago
admin: This Python memory optimization technique reduced my application's RAM usage by 60%. Brilliant! 2 months ago
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