TOP 17 Mistakes when Working with Django ORM

Feb 27, 2024
/
12 min read
TOP 17 Mistakes when Working with Django ORM
Soner Ayberk
Soner Ayberk
Senior Backend Engineer / Team Lead

In the vast and ever-evolving landscape of web development, the journey of overcoming Django’s Object-Relational Mapping mistakes stands as a rite of passage for many developers.

This tale is inspired by the collective experiences of those who tread its path – by chronicling the odyssey of Alex. It’s a developer whose journey through the intricacies of Django ORM is both a testament to the challenges faced by many and a beacon of the wisdom to be found along the way.

Alex’s quest is about overcoming technical hurdles with the guidance of the legendary guild, Django Stars. It’s also a narrative of growth, discovery, and the pursuit of writing clean, efficient, and elegant code. Join me and Alex as we unfold the chapters of adventure, offering insights, solutions, and the camaraderie found in the shared development journey to prevent mistakes when working with Django.

Top 8 Mistakes To Avoid While Working with Django ORM

Gather ’round, dear devs, for a tale of Django ORM issues with woes and wins, a journey through the thickets of Django’s Object-Relational Mapping. It’s an enthralling story that could only be told by those who’ve faced the fiery depths of inefficient queries and emerged victorious, armed with the sacred knowledge of optimization.

The Tale of the Unnecessary Detour: .fk_id vs. .fk.id

Once upon a time, in the land of Database Optimizations, there lived a young developer named Alex. Alex was eager to reference a foreign key, so he would often traverse the dangerous path of model.fk.id, summoning the dragon of database hits each time. This was causing the villagers (or the server) much distress, called Django mistakes.

The Pitfall:

# Alex's original path
dragon_id = Knight.objects.get(id=1).dragon.id
# Awakens the dragon (DB hit) unnecessarily!

The Solution:

A wise sage whispered a secret to Alex, “Use model.fk_id,” like magic, the path cleared, offering a direct route without awakening the beast.

# The enlightened path
dragon_id = Knight.objects.get(id=1).dragon_id
# The dragon remains at peace.

The Quest for Related Objects: select_related and prefetch_related

Alex’s journey led to a fork in the road. One path was laden with separate queries for each related object, while the other was a smooth highway using the mystical powers of select_related and prefetch_related.

The Django ORM errors path:

I wandered, fetching each related object with its query, burdening the land with unnecessary load times.

The Solution:

Armed with select_related for forward relationships and prefetch_related for reverse or many-to-many relationships, Alex summoned related objects in efficient, harmonious queries.

# Using select_related for forward relationships
knight_with_dragon = Knight.objects.select_related('dragon').get(id=1)

# Using prefetch_related for reverse or many-to-many relationships
castle_with_knights = Castle.objects.prefetch_related('knights').get(id=1)

The Scroll of Field Restrictions: defer and only

In a dusty, forgotten library, Alex discovered an ancient scroll, teaching the art of fetching only what’s needed, using defer to postpone and only to summon specific fields, lightening the load on their trusty steed, the database.

# Using only to fetch specific fields
knight = Knight.objects.only('name', 'title').get(id=1)

# Using defer to postpone loading of certain fields
knight = Knight.objects.defer('biography').get(id=1)

The Curse of len(queryset)

Alex then faced the curse of the len(queryset), where counting the inhabitants of a queryset unleashed inefficiency across the land.

The Solution:

A clever enchantress advised, “Use .count() instead, young developer,” and the curse was lifted, bringing peace to the realm.

# Efficiently count queryset without loading it into memory
num_knights = Knight.objects.all().count()

The Illusion of if queryset

Mistaking an empty queryset for the absence of trouble, Alex soon learned that even an empty queryset could cast illusions, appearing as truthy in conditional statements.

The Solution:

“Check with .exists(),” counseled a passing bard, and Alex saw through the illusions, writing conditionals that genuinely reflected the presence of data.

# Check if queryset has any results without loading it
if Knight.objects.filter(title="Sir").exists():
    # Perform action

The Guardians of Performance: Database Indexes

Scaling the cliffs of Database Performance, Alex learned to place guardians known as Indexes on fields frequently traversed in queries, ensuring swift, efficient access and safeguarding the realm against the slow query beasts.

The Power of Bulk Operations

In the market square, Alex conquered first Django ORM mistakes and discovered the power of bulk operations – bulk_create, bulk_update, and friends – allowing them to perform many actions with a single powerful incantation, drastically reducing the time spent in the market.

# Using bulk_create to add multiple records efficiently
Knight.objects.bulk_create([
Knight(name="Sir Lancelot", title="Sir"),
Knight(name="Sir Galahad", title="Sir"),
])

# Using bulk_update to update multiple records efficiently
knights = Knight.objects.filter(title="Sir").all()
for knight in knights:
knight.title = "Lord"
Knight.objects.bulk_update(knights, ['title'])

Alternatively you can use

`update()` method:
Knight.objects.filter(title="Sir").update(title="Lord")

The Wisdom of Using Iterator

Finally, in the dense forest of Large Querysets, Alex learned to use .iterator() to fetch records in chunks, conserving memory and avoiding the exhaustion that plagued many developers before.

The Lesson Learned:

# Using .iterator() to fetch records in chunks, saving memory
for quest in Quest.objects.all().iterator():
# Embark on each quest without burdening the memory steed.

And so, armed with these lessons, Alex became a legend, their tales of optimization and efficiency sung by developers in taverns across the land. Remember, dear devs, wisdom and a dash of humor are your greatest allies in overcoming Django ORM mistakes.
TOP 17 Mistakes when Working with Django ORM 1

How Django Stars Can Help You to Avoid Mistakes

As our fearless protagonist Alex’s journey reaches its zenith, let’s pivot our gaze towards a beacon of wisdom and efficiency to help you avoid mistakes with Django ORM: DjangoStars. Imagine us as a company and a guild of seasoned adventurers, each with our own tales of ORM battles, performance optimizations, and the quest for clean, efficient code. 

Let me, a proud member of this guild, unfold the tapestry of how we at DjangoStars can guide you through the treacherous landscapes of common Django-based project mistakes to the promised land of optimal application performance.

The N+1 Queries Quandary

The notorious N+1 queries are common Django ORM problems and beasts we’ve tamed repeatedly. At Django Stars, I’ve crafted my armory with the finest tools Django offers — select_related and prefetch_related — to slay this beast in its tracks. We don’t just stop at wielding these tools. We imbue our knights with the wisdom to use them judiciously.

Code Sample:

# The Django Stars way
from django.db import models

class Author(models.Model):
name = models.CharField(max_length=100)

class Book(models.Model):
title = models.CharField(max_length=100)
author = models.ForeignKey(Author, on_delete=models.CASCADE)

# Fetching books with their authors in one go
books = Book.objects.select_related('author').all()

The Null in CharFields Dilemma

Defining CharField as nullable is akin to inviting chaos into your database. At Django Stars, I advocate for cleanliness and order, setting defaults or using blank=True instead. This approach keeps our data models pristine and our queries unambiguous so that we can say goodbye to all common Django ORM mistakes.

Writing Instance Methods That Hit the Database

I’ve seen the pitfalls of writing methods that make separate database calls for each object. Instead of descending into this abyss, I’d leverage the power of annotations and aggregations to consolidate these calls into a harmonious symphony of efficiency.

Code Sample:

# Before: An arduous path
class Book(models.Model):
# Imagine there's more to the model
def is_popular(self):
return self.sales_set.count() > 100
# After: The Django Stars' enlightened approach
from django.db.models import Count
books = Book.objects.annotate(sales_count=Count('sales')).filter(sales_count__gt=100)

The Django misunderstanding of distinct

In the vast kingdoms of large tables, using distinct() without precision is like casting a wide net and hoping for the best. At DjangoStars, I precisely target our spells, using distinct on specific columns to avoid the wrath of performance degradation.

Code Sample:

# A common oversight
users = User.objects.distinct()
# The Django Stars' precision
users = User.objects.distinct("id")

The Tale of Selective Harvesting: values() and values_list()

How’s Alex doing? On a bright morning, Alex found himself in the Orchard of Data Retrieval, where the trees were heavy with fruits of information. Eager to gather only the sweetest data, Alex initially filled their basket with whole fruits, peels, and more. This burdened them with unnecessary weight, slowing their journey.

The Solution:

A wandering minstrel shared the secret of selective harvesting with values() and values_list(), allowing Alex to pluck the juicy data needed, leaving the cumbersome peels behind.

# Alex's newfound wisdom
titles = Book.objects.values_list('title', flat=True)

The Echoing Cave of QuerySet Caching

Venturing into the Echoing Cave, Alex found themselves repeating their calls into the darkness, each echoing a duplicate query to the database. This redundancy threatened to trap Alex in an endless loop of inefficiency.

The Revelation:

A sage, hidden in the shadows, taught Alex the magic of caching querysets, a spell to capture the echoes in a magical flask, preventing the need to shout the same queries again.

# Alex's lesson in caching
books = list(Book.objects.all()) 
# The echoes now captured, to be reused in silence

The Bridge of Signals

Approaching a bridge, Alex sought to update the planks with stronger wood using a powerful update() spell. Yet, upon completion, they found the bridge’s magic weakened. The enchantments (signals) protected it failed to activate.

A bridge guardian appeared, advising Alex to tend to each plank individually if they wished the bridge’s magic to thrive, preserving the integrity of signals.

# Alex's careful maintenance
for plank in Bridge.objects.filter(material='Wood'):
plank.material = 'Stone'
plank.save() 
# Each enchantment (signal) preserved

The Labyrinth of Database Design

In their pursuit of architectural mastery, Alex stumbled upon an ancient labyrinth, its paths twisted like an unoptimized database schema. Lost among redundant corridors and dead ends, progress could have been faster.

The Map:

From the labyrinth’s center, a voice-guided Alex designs each path with purpose, uses indexes as guiding lights, and chooses the suitable stones (field types) for construction, clearing the way forward.

The Fable of the Forgotten Spell: F Expressions

In the final leg of their journey, Alex faced a vast chasm. The challenge is to move a mountain of data from one side to the other. Initially, Alex ferried the data piece by piece, a backbreaking task.

The Wisdom:

A hermit, observing Alex’s toil, shared the forgotten spell of F expressions, allowing Alex to command the mountain to move, all within the realm of the database, saving immense time and effort.

from django.db.models import F
# Alex commanding the mountain
Book.objects.all().update(price=F('price') + 10)

Through these trials, Alex emerged not just as a developer but as a sage in their own right, their journey through the land of Django ORM a testament to the power of knowledge, the importance of efficiency, and the wisdom to seek guidance when the path becomes unclear. With the lessons learned and the guild of DjangoStars as their ally, Alex was ready to face even more significant challenges ahead, their code not just functional but a beacon of optimization and elegance.

As the saga of Alex’s quest through the realm of Django ORM continues, our intrepid developer faces new challenges, armed with wisdom from the guild of DjangoStars.
TOP 17 Mistakes when Working with Django ORM 2

Conclusion: The Legacy of Alex’s Quest through Django ORM

As the sun sets on the horizon of our story, the odyssey of Alex through the land of Django ORM draws to a close. What began as a solitary quest fraught with challenges and pitfalls evolved into a journey illuminated by the wisdom of Django Stars, transforming obstacles into opportunities for growth and learning. Along the way, Alex encountered the notorious N+1 queries, navigated the perils of unoptimized database designs, mastered the art of selective data retrieval, and discovered the alchemy of efficient bulk operations, among other trials.

Each chapter of Alex’s journey was not merely a lesson in coding but a testament to the power of perseverance, the value of community wisdom, and the transformative impact of adopting best practices. The challenges faced and overcome by Alex serve as a mirror to the common pitfalls that trap many developers, highlighting the importance of guidance, continuous learning, and the willingness to refactor not just code but one’s approach to problem-solving.

The tale of Alex is a narrative. It’s also an invitation to developers at all stages of their Django journey to seek out their adventures, armed with the knowledge that the path to mastery is paved with challenges and triumphs. It’s a reminder that software development’s most enduring solutions are forged in the fires of perseverance, guided by the wisdom of those who have journeyed before us.

As we bid farewell to Alex, let their journey inspire you to embrace your Django ORM challenges with a renewed sense of purpose and confidence from knowing you are part of a community rich in knowledge and support. May the legacy of Alex’s quest through Django ORM be a guiding star for your development journey, leading you to write code that functions and flourishes.

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Frequently Asked Questions
Why do developers treasure Django's Queryset methods?
In web development, Django's Queryset methods are akin to a sorcerer's spells, granting the wielder the power to communicate with databases in an elegant and efficient language. These methods allow developers to retrieve, filter, and manipulate data precisely, transforming cumbersome code into streamlined expressions of intent. The adept use of queryset methods not only elevates the quality of the code but also ensures that applications run smoothly, handling vast seas of data with grace.
What role does Django ORM play in the grand tapestry of web development?
Django ORM bridges the mystical world of databases and the pragmatic land of application development. It abstracts the complexities of SQL into intuitive Python code. This allows developers to interact with databases without delving into the arcane syntax of queries. This abstraction is crucial for accelerating development timelines as it ensures data integrity. It fosters a more accessible approach to database interactions.
How does the forgotten lore of database indexing safeguard the kingdom of performance?
Database indexing is often overlooked in the rush to deploy. It is the silent guardian of performance. Like hidden runes that speed up the search for knowledge, indexes make data retrieval swift and efficient. Neglecting this lore can lead to the dark ages of performance, where queries slow to a crawl, and applications become sluggish under the weight of unoptimized searches. Wise developers heed the call to implement indexing and ensure their applications remain swift and responsive even as they scale.
What happens when the dragon of inefficient queries is left unchecked?
Allowing the dragon of inefficient queries to roam free is akin to letting a beast of legend ravage the countryside. It consumes resources with a voracious appetite, leading to slow response times, increased server load, and a degraded user experience. The fallout is a kingdom (application) where citizens (users) grow restless, and the infrastructure crumbles under the strain. Only by wielding the sword of optimization — through techniques like indexing, query optimization, and the judicious use of Django's ORM features — can the beast be tamed, ensuring the realm thrives.
Can the magic of select_related and prefetch_related spells overcome the curse of multiple database hits?
Indeed, the incantations of select_related and prefetch_related are powerful spells in the developer's grimoire. They are designed to combat the curse of multiple database hits. Select_related weaves a spell of preloading for foreign key relationships, turning scattered queries into a single, streamlined quest. Prefetch_related, on the other hand, similarly gathers related objects but is suited for many-to-many and reverse foreign key relationships. Together, they form a potent defense against the inefficiency of numerous database calls, ensuring that the application remains swift and the server's burden light.

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