---
title: "Django performance review: review, setup & limitations · Undominated.ai"
canonical: https://undominated.ai/skills/getsentry-django-perf-review/
description: "Review Django code and report only performance issues the reviewer traced. Zero findings is an allowed result."
---

# Django performance review: review, setup & limitations · Undominated.ai

> Review Django code and report only performance issues the reviewer traced. Zero findings is an allowed result.

[← Explore all skills](/skills/)

CODE REVIEW / Functional Software, Inc. dba Sentry

# Django performance review

Review Django code and report only performance issues the reviewer traced. Zero findings is an allowed result.

 [See setup guidance ↓](#setup)[Original source ↗](https://github.com/getsentry/skills/tree/d18b7aa8ba878354e5c348310230e652f7690f9c/skills/django-perf-review)

SOURCE REVIEW

 Reviewed 2026-10-15
 Evidence 4 linked sources
 Publisher Functional Software, Inc. dba Sentry
 Licence [Apache-2.0 ↗](https://github.com/getsentry/skills/blob/d18b7aa8ba878354e5c348310230e652f7690f9c/LICENSE)
 Revision d18b7aa8ba87
 [Read what was—and wasn’t—checked ↓](#review)

“Django performance code review. Use when asked to "review Django performance", "find N+1 queries", "optimize Django", "check queryset performance", "database performance", "Django ORM issues", or audit Django code for performance problems.”

 [Functional Software, Inc. dba Sentry · upstream description ↗](https://github.com/getsentry/skills/blob/d18b7aa8ba878354e5c348310230e652f7690f9c/skills/django-perf-review/SKILL.md) Our analysis follows below.

01 / THE REASONING

## Why this made the selection.

 - N+1 and unbounded queries are the critical items, and they must be traced to a real loop and a large table.
- Micro-patterns such as count versus exists are usually not reported.

### A good fit for

 - Reviewing a Django view or serializer for N+1 queries or unbounded lists
- Checking a hot filter or order_by for a missing index on a large table
- Trace Django query multiplication through views, serializers and properties before reporting an N+1.
- Check caching and rate limiting before reporting a frequently executed Django query path.

### Weigh up before choosing

 - The skill says zero findings is acceptable and forbids manufacturing issues.
- N+1 and missing-index reports require a traced loop or hot path and a large table, with the checklists naming 1000 or 10k rows.
- count versus exists is usually skipped because the file calls the difference under a millisecond.
- This review did not execute the skill.
- Row-count thresholds in the guide are heuristics; a small hot query may still matter, while bulk writes can bypass model save hooks/signals.

02 / THE REVIEW RECORD

## What we actually inspected.

Source review has boundaries. A clear record is more useful than a “safe” badge.

### Material inspected

 - skills/django-perf-review/SKILL.md
- LICENSE
- README.md
- vercel-labs/skills@48dc9e8eb8aa19040e91cb90ba0b642c9cbad57e:README.md

### Our findings

 - The pinned frontmatter allows Read, Grep, Glob, Bash, and Task, and the body says to research before reporting.
- Priority 1 is N+1 from views, querysets, templates, or serializers, and the checklist requires an existing select_related or prefetch_related search.
- Unbounded querysets and write loops are critical or high only on user-facing paths with large or unbounded data, not on chunked jobs or one-time migrations.
- Inefficient patterns such as len on a queryset are low and included only as notes beside a real issue.
- The review checklist demands hot-path and volume evidence and permits zero findings instead of equating a code pattern with a proven incident.
- Validation requires ruling out caching and rate-limiting mitigations after tracing the data flow, existing optimizations, table volume, and call sites; the file says to omit findings if any validation step is incomplete.

### Not established by this review

 - The skill was not executed inside a host agent.
- Not executed: it was not installed or run.

The review applies to the material and revision named here. A newer upstream release can change its behavior.

03 / PUT IT TO WORK

## Add a skill to your workflow.

[Upstream setup instructions ↗](https://github.com/vercel-labs/skills/blob/48dc9e8eb8aa19040e91cb90ba0b642c9cbad57e/README.md)

DOCUMENTED COMMAND

 npx skills add getsentry/skills/skills/django-perf-review Copy command ↗

Run in your terminal to choose your AI tools, project or global scope, and installation method. This short command follows the current upstream version; the review covers the revision shown above.

 Optional: install the reviewed revision

Keeps the original source and installer version where recorded, while leaving your AI tools and installation scope for you to choose.

 npx skills add https://github.com/getsentry/skills/tree/d18b7aa8ba878354e5c348310230e652f7690f9c/skills/django-perf-review Copy reviewed-revision command ↗ - The command pins only this review skill at the reviewed commit. The installer was not executed.
- Do not use a global yes-to-all install of the repository. That would install skills this review did not select.
- For manual installation instead, download the complete bundle from https://undominated.ai/resources/skills/getsentry-django-perf-review/bundle.zip and extract it into a new directory. It holds SKILL.md unchanged at revision d18b7aa8, the upstream licence and an attribution file.
- Place the extracted directory in your host's documented skills directory, named django-perf-review. Keep SKILL.md and the licence together.

### Before you start

 - Node.js and npm
- A Django tree you are allowed to read

### Compatibility

Agent Skills hosts · Django

### Implementation

Markdown

### Review prompt. It reports patches. It does not say to migrate or open a database.

 - Read views, models, templates, and serializers
- Bash is declared in allowed-tools, but the file does not require a production database connection
- Reads Django code and may execute test queries; performance tests must use appropriate data and isolated write paths.

### Cost model

Apache-2.0 licence; no account is named.

THE COMPLETE REVIEWED DEFINITION

## Read it before you reuse it.

Original source bytes, with attribution. Review the host-specific setup notes above.

 Copy definition ↗ [Download definition + licence ↗](/resources/skills/getsentry-django-perf-review/bundle.zip)[Raw Markdown ↗](/resources/skills/getsentry-django-perf-review/definition.md)
 ---
name: django-perf-review
description: Django performance code review. Use when asked to "review Django performance", "find N+1 queries", "optimize Django", "check queryset performance", "database performance", "Django ORM issues", or audit Django code for performance problems.
allowed-tools: Read Grep Glob Bash Task
license: LICENSE
---

# Django Performance Review

Review Django code for **validated** performance issues. Research the codebase to confirm issues before reporting. Report only what you can prove.

## Review Approach

1. **Research first** - Trace data flow, check for existing optimizations, verify data volume
2. **Validate before reporting** - Pattern matching is not validation
3. **Zero findings is acceptable** - Don't manufacture issues to appear thorough
4. **Severity must match impact** - If you catch yourself writing "minor" in a CRITICAL finding, it's not critical. Downgrade or skip it.

## Impact Categories

Issues are organized by impact. Focus on CRITICAL and HIGH - these cause real problems at scale.

| Priority | Category | Impact |
|----------|----------|--------|
| 1 | N+1 Queries | **CRITICAL** - Multiplies with data, causes timeouts |
| 2 | Unbounded Querysets | **CRITICAL** - Memory exhaustion, OOM kills |
| 3 | Missing Indexes | **HIGH** - Full table scans on large tables |
| 4 | Write Loops | **HIGH** - Lock contention, slow requests |
| 5 | Inefficient Patterns | **LOW** - Rarely worth reporting |

---

## Priority 1: N+1 Queries (CRITICAL)

**Impact:** Each N+1 adds `O(n)` database round trips. 100 rows = 100 extra queries. 10,000 rows = timeout.

### Rule: Prefetch related data accessed in loops

Validate by tracing: View → Queryset → Template/Serializer → Loop access

```python
# PROBLEM: N+1 - each iteration queries profile
def user_list(request):
 users = User.objects.all()
 return render(request, 'users.html', {'users': users})

# Template:
# {% for user in users %}
# {{ user.profile.bio }} ← triggers query per user
# {% endfor %}

# SOLUTION: Prefetch in view
def user_list(request):
 users = User.objects.select_related('profile')
 return render(request, 'users.html', {'users': users})
```

### Rule: Prefetch in serializers, not just views

DRF serializers accessing related fields cause N+1 if queryset isn't optimized.

```python
# PROBLEM: SerializerMethodField queries per object
class UserSerializer(serializers.ModelSerializer):
 order_count = serializers.SerializerMethodField()

 def get_order_count(self, obj):
 return obj.orders.count() # ← query per user

# SOLUTION: Annotate in viewset, access in serializer
class UserViewSet(viewsets.ModelViewSet):
 def get_queryset(self):
 return User.objects.annotate(order_count=Count('orders'))

class UserSerializer(serializers.ModelSerializer):
 order_count = serializers.IntegerField(read_only=True)
```

### Rule: Model properties that query are dangerous in loops

```python
# PROBLEM: Property triggers query when accessed
class User(models.Model):
 @property
 def recent_orders(self):
 return self.orders.filter(created__gte=last_week)[:5]

# Used in template loop = N+1

# SOLUTION: Use Prefetch with custom queryset, or annotate
```

### Validation Checklist for N+1
- [ ] Traced data flow from view to template/serializer
- [ ] Confirmed related field is accessed inside a loop
- [ ] Searched codebase for existing select_related/prefetch_related
- [ ] Verified table has significant row count (1000+)
- [ ] Confirmed this is a hot path (not admin, not rare action)

---

## Priority 2: Unbounded Querysets (CRITICAL)

**Impact:** Loading entire tables exhausts memory. Large tables cause OOM kills and worker restarts.

### Rule: Always paginate list endpoints

```python
# PROBLEM: No pagination - loads all rows
class UserListView(ListView):
 model = User
 template_name = 'users.html'

# SOLUTION: Add pagination
class UserListView(ListView):
 model = User
 template_name = 'users.html'
 paginate_by = 25
```

### Rule: Use iterator() for large batch processing

```python
# PROBLEM: Loads all objects into memory at once
for user in User.objects.all():
 process(user)

# SOLUTION: Stream with iterator()
for user in User.objects.iterator(chunk_size=1000):
 process(user)
```

### Rule: Never call list() on unbounded querysets

```python
# PROBLEM: Forces full evaluation into memory
all_users = list(User.objects.all())

# SOLUTION: Keep as queryset, slice if needed
users = User.objects.all()[:100]
```

### Validation Checklist for Unbounded Querysets
- [ ] Table is large (10k+ rows) or will grow unbounded
- [ ] No pagination class, paginate_by, or slicing
- [ ] This runs on user-facing request (not background job with chunking)

---

## Priority 3: Missing Indexes (HIGH)

**Impact:** Full table scans. Negligible on small tables, catastrophic on large ones.

### Rule: Index fields used in WHERE clauses on large tables

```python
# PROBLEM: Filtering on unindexed field
# User.objects.filter(email=email) # full scan if no index

class User(models.Model):
 email = models.EmailField() # ← no db_index

# SOLUTION: Add index
class User(models.Model):
 email = models.EmailField(db_index=True)
```

### Rule: Index fields used in ORDER BY on large tables

```python
# PROBLEM: Sorting requires full scan without index
Order.objects.order_by('-created')

# SOLUTION: Index the sort field
class Order(models.Model):
 created = models.DateTimeField(db_index=True)
```

### Rule: Use composite indexes for common query patterns

```python
class Order(models.Model):
 user = models.ForeignKey(User)
 status = models.CharField(max_length=20)
 created = models.DateTimeField()

 class Meta:
 indexes = [
 models.Index(fields=['user', 'status']), # for filter(user=x, status=y)
 models.Index(fields=['status', '-created']), # for filter(status=x).order_by('-created')
 ]
```

### Validation Checklist for Missing Indexes
- [ ] Table has 10k+ rows
- [ ] Field is used in filter() or order_by() on hot path
- [ ] Checked model - no db_index=True or Meta.indexes entry
- [ ] Not a foreign key (already indexed automatically)

---

## Priority 4: Write Loops (HIGH)

**Impact:** N database writes instead of 1. Lock contention. Slow requests.

### Rule: Use bulk_create instead of create() in loops

```python
# PROBLEM: N inserts, N round trips
for item in items:
 Model.objects.create(name=item['name'])

# SOLUTION: Single bulk insert
Model.objects.bulk_create([
 Model(name=item['name']) for item in items
])
```

### Rule: Use update() or bulk_update instead of save() in loops

```python
# PROBLEM: N updates
for obj in queryset:
 obj.status = 'done'
 obj.save()

# SOLUTION A: Single UPDATE statement (same value for all)
queryset.update(status='done')

# SOLUTION B: bulk_update (different values)
for obj in objects:
 obj.status = compute_status(obj)
Model.objects.bulk_update(objects, ['status'], batch_size=500)
```

### Rule: Use delete() on queryset, not in loops

```python
# PROBLEM: N deletes
for obj in queryset:
 obj.delete()

# SOLUTION: Single DELETE
queryset.delete()
```

### Validation Checklist for Write Loops
- [ ] Loop iterates over 100+ items (or unbounded)
- [ ] Each iteration calls create(), save(), or delete()
- [ ] This runs on user-facing request (not one-time migration script)

---

## Priority 5: Inefficient Patterns (LOW)

**Rarely worth reporting.** Include only as minor notes if you're already reporting real issues.

### Pattern: count() vs exists()

```python
# Slightly suboptimal
if queryset.count() > 0:
 do_thing()

# Marginally better
if queryset.exists():
 do_thing()
```

**Usually skip** - difference is <1ms in most cases.

### Pattern: len(queryset) vs count()

```python
# Fetches all rows to count
if len(queryset) > 0: # bad if queryset not yet evaluated

# Single COUNT query
if queryset.count() > 0:
```

**Only flag** if queryset is large and not already evaluated.

### Pattern: get() in small loops

```python
# N queries, but if N is small (< 20), often fine
for id in ids:
 obj = Model.objects.get(id=id)
```

**Only flag** if loop is large or this is in a very hot path.

---

## Validation Requirements

Before reporting ANY issue:

1. **Trace the data flow** - Follow queryset from creation to consumption
2. **Search for existing optimizations** - Grep for select_related, prefetch_related, pagination
3. **Verify data volume** - Check if table is actually large
4. **Confirm hot path** - Trace call sites, verify this runs frequently
5. **Rule out mitigations** - Check for caching, rate limiting

**If you cannot validate all steps, do not report.**

---

## Output Format

```markdown
## Django Performance Review: [File/Component Name]

### Summary
Validated issues: X (Y Critical, Z High)

### Findings

#### [PERF-001] N+1 Query in UserListView (CRITICAL)
**Location:** `views.py:45`

**Issue:** Related field `profile` accessed in template loop without prefetch.

**Validation:**
- Traced: UserListView → users queryset → user_list.html → `{{ user.profile.bio }}` in loop
- Searched codebase: no select_related('profile') found
- User table: 50k+ rows (verified in admin)
- Hot path: linked from homepage navigation

**Evidence:**
```python
def get_queryset(self):
 return User.objects.filter(active=True) # no select_related
```

**Fix:**
```python
def get_queryset(self):
 return User.objects.filter(active=True).select_related('profile')
```
```

If no issues found: "No performance issues identified after reviewing [files] and validating [what you checked]."

**Before submitting, sanity check each finding:**
- Does the severity match the actual impact? ("Minor inefficiency" ≠ CRITICAL)
- Is this a real performance issue or just a style preference?
- Would fixing this measurably improve performance?

If the answer to any is "no" - remove the finding.

---

## What NOT to Report

- Test files
- Admin-only views
- Management commands
- Migration files
- One-time scripts
- Code behind disabled feature flags
- Tables with <1000 rows that won't grow
- Patterns in cold paths (rarely executed code)
- Micro-optimizations (exists vs count, only/defer without evidence)

### False Positives to Avoid

**Queryset variable assignment is not an issue:**
```python
# This is FINE - no performance difference
projects_qs = Project.objects.filter(org=org)
projects = list(projects_qs)

# vs this - identical performance
projects = list(Project.objects.filter(org=org))
```
Querysets are lazy. Assigning to a variable doesn't execute anything.

**Single query patterns are not N+1:**
```python
# This is ONE query, not N+1
projects = list(Project.objects.filter(org=org))
```
N+1 requires a loop that triggers additional queries. A single `list()` call is fine.

**Missing select_related on single object fetch is not N+1:**
```python
# This is 2 queries, not N+1 - report as LOW at most
state = AutofixState.objects.filter(pr_id=pr_id).first()
project_id = state.request.project_id # second query
```
N+1 requires a loop. A single object doing 2 queries instead of 1 can be reported as LOW if relevant, but never as CRITICAL/HIGH.

**Style preferences are not performance issues:**
If your only suggestion is "combine these two lines" or "rename this variable" - that's style, not performance. Don't report it.

The download contains SKILL.md . Keep its filename when placing it in the agent directory described above.

By **Functional Software, Inc. dba Sentry**. [Exact upstream source ↗](https://github.com/getsentry/skills/blob/d18b7aa8ba878354e5c348310230e652f7690f9c/skills/django-perf-review/SKILL.md) · [Licence](/resources/skills/getsentry-django-perf-review/LICENSE.txt) · [Attribution](/resources/skills/getsentry-django-perf-review/ATTRIBUTION.txt)

SHA-256 52283bff7b23f06f94bbb413d174fd1cbcf497f8e8a63d4f0d569ba6bfd949d4

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04 / FOLLOW THE EVIDENCE

## The source trail.

Our notes are separate from the original resource. Check upstream before adopting a new version.

 - [Django performance review skill ↗](https://github.com/getsentry/skills/blob/d18b7aa8ba878354e5c348310230e652f7690f9c/skills/django-perf-review/SKILL.md) Checked 2026-10-14 https://github.com/getsentry/skills/blob/d18b7aa8ba878354e5c348310230e652f7690f9c/skills/django-perf-review/SKILL.md Supports: Trace before report, Zero findings allowed
- [Apache-2.0 licence ↗](https://github.com/getsentry/skills/blob/d18b7aa8ba878354e5c348310230e652f7690f9c/LICENSE) Checked 2026-10-14 https://github.com/getsentry/skills/blob/d18b7aa8ba878354e5c348310230e652f7690f9c/LICENSE Supports: Copyright 2025 Functional Software, Inc. dba Sentry, Redistribution under Apache-2.0
- [Directory licence pointer ↗](https://github.com/getsentry/skills/blob/d18b7aa8ba878354e5c348310230e652f7690f9c/skills/django-perf-review/LICENSE) Checked 2026-10-14 https://github.com/getsentry/skills/blob/d18b7aa8ba878354e5c348310230e652f7690f9c/skills/django-perf-review/LICENSE Supports: Points at the repository root licence
- [Pinned definition review, 2026-10-15 ↗](https://raw.githubusercontent.com/getsentry/skills/d18b7aa8ba878354e5c348310230e652f7690f9c/skills/django-perf-review/SKILL.md) Checked 2026-10-15 https://raw.githubusercontent.com/getsentry/skills/d18b7aa8ba878354e5c348310230e652f7690f9c/skills/django-perf-review/SKILL.md Supports: review.findings, bestFor

KEEP COMPARING

## Other approaches to consider.

Related by category or shared topics. These are alternatives to inspect, not a measured quality order.

 [### Sentry code review ↗ Reviews a change for runtime, query, security, design, and test gaps, and does not block on style.](/skills/getsentry-code-review/)[### Cloudflare Workers Production Profiling ↗ Capture CPU or heap profiles for a specific deployed Worker or Durable Object and turn pprof evidence into a focused optimization proposal.](/skills/cloudflare-workers-profiling/)[### Code improver ↗ Pins the generic review loop that will not choose a reviewer, will not start on an unconfirmed scope, and will not commit.](/skills/trailofbits-code-improver/)

 [AI Tools ↗](/tools/)[Skills ↗](/skills/)[Agents ↗](/agents/)[MCP Servers ↗](/mcp-servers/)[Workflows ↗](/workflows/)

## Continue your investigation

 - [Choose a toolkit](/tools/)
- [Inspect execution hosts](/agents/)
- [Check tool access](/mcp-servers/)
- [Check project dependencies](/check-repo/)