test-seed-uniqueness

Ensure test seed data never causes unique constraint violations — UUID-based, timestamp-based, counter-based, or Faker patterns for any field with a UNIQUE index, primary key, or slug constraint.

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Repository: lukemcqueen/hermes-cortex
Letzte Quellaktivität: 29. Juli 2026 um 07:13
Erkannte Sprache von SKILL.md: Englisch
Sterne: 4
Forks: 1

Installationsoptionen

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npx skills add https://github.com/lukemcqueen/hermes-cortex --skill test-seed-uniqueness

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SKILL.md

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name	test-seed-uniqueness
version	1.0.0
category	software-development
description	Ensure test seed data never causes unique constraint violations — UUID-based, timestamp-based, counter-based, or Faker patterns for any field with a UNIQUE index, primary key, or slug constraint.
author	Hermes Agent
license	MIT
platforms	["linux","macos","windows"]
metadata	{"hermes":{"tags":["testing","seed-data","factories","fixtures","database","uniqueness","pytest","factory-boy"],"related_skills":["change-test-loop","subagent-driven-development","root-cause-debugging"]}}

Test Seed Data — Uniqueness Discipline

The Problem

Every test needs seed data. Agents instinctively write:

user = User.objects.create(email="alice@example.com", username="alice")

This works once. On the next test run, or when tests run in parallel, or when a second test also creates an alice:

django.db.utils.IntegrityError: duplicate key value violates unique constraint

The agent didn't do anything wrong — it just picked a natural-looking value for a field that happens to have a UNIQUE constraint. The database doesn't care how pretty the data is; it cares about uniqueness.

The Rule

Every value inserted into a uniquely-constrained field MUST be dynamically unique at runtime.

Hardcoded strings in seed data are only safe for:

Non-unique fields (e.g., display_name, bio, age)
Enum-like fields (e.g., status="active", role="admin")
Reference data that's de-duplicated by the test setup (e.g., loaded once from JSON)

Everything else — emails, usernames, slugs, external IDs, phone numbers, API keys, invite codes, profile handles — gets the dynamic treatment.

Failure Detection

When you see any of these in test output, stop and fix the seed data:

Error Pattern	Likely Source
`duplicate key value violates unique constraint`	PostgreSQL
`UNIQUE constraint failed`	SQLite
`E11000 duplicate key error`	MongoDB
`Duplicate entry '...' for key`	MySQL
`unique constraint "..." violated`	Generic ORM
`already exists.`	Rails / Active Record
`IntegrityError: (1062, "Duplicate entry`	MySQL via ORM

First debugging step when seeing these: Look at the test's seed data or fixtures. Find the field whose value is hardcoded. Make it dynamic.

❌ Anti-Pattern	Why It Fails	✅ Fix
`email="alice@example.com"`	Second test or re-run collision	`f"alice-{uuid.uuid4()}@example.com"`
`User.objects.create()` without cleanup in non-transactional tests	Data leaks between tests	Use `@pytest.mark.django_db(transaction=True)` or fixture with teardown
`User.objects.all().delete()` at start of test	Race condition in parallel tests	Use `secrets.token_hex()` or factory
Copy-pasting seed data across test files	Same hardcoded values in multiple files	Extract a shared factory or fixture
Using `datetime.now()` at second precision	Collision when tests run in same second	Use microsecond precision (`%f`) or UUID
`UserFactory()` without unique guarantees on special fields	Factory inherits hardcoded defaults	Override with `Sequence` or pass unique values

test-seed-uniqueness

Installationsoptionen

Quelldateien prüfen

Test Seed Data — Uniqueness Discipline

The Problem

The Rule

Failure Detection

Test Seed Data — Uniqueness Discipline

The Problem

The Rule

Failure Detection

Dynamic Uniqueness Patterns

Pattern 1 — UUID (Best for Primary Keys & External IDs)

Pattern 2 — Timestamp (Best for Ordered, Human-Readable Slugs)

Pattern 3 — Counter (Best for Sequential Batch Tests)

Pattern 4 — Random Hex Suffix (Best for Short, Readable Values)

Pattern 5 — Faker (Best for Realistic, Human-Readable Data)

Pattern 6 — factory_boy Sequences (Best for Complex Fixtures)

Pattern 7 — pytest Fixture with Scope

Complementary Anti-Patterns (What NOT to Do)

Model-Specific Ref Detection

Integration with change-test-loop

Verification

test-seed-uniqueness

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Installationsoptionen

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Mehr aus diesem Repository

Mehr aus diesem Repository

Test Seed Data — Uniqueness Discipline

The Problem

The Rule

Failure Detection

Test Seed Data — Uniqueness Discipline

The Problem

The Rule

Failure Detection

Dynamic Uniqueness Patterns

Pattern 1 — UUID (Best for Primary Keys & External IDs)

Pattern 2 — Timestamp (Best for Ordered, Human-Readable Slugs)

Pattern 3 — Counter (Best for Sequential Batch Tests)

Pattern 4 — Random Hex Suffix (Best for Short, Readable Values)

Pattern 5 — Faker (Best for Realistic, Human-Readable Data)

Pattern 6 — factory_boy Sequences (Best for Complex Fixtures)

Pattern 7 — pytest Fixture with Scope

Complementary Anti-Patterns (What NOT to Do)

Model-Specific Ref Detection

Integration with change-test-loop

Verification