FactoryBot.define do
factory :post do
association :author, factory: :user
sequence(:title) { |n| "Post Title #{n}" }
body { Faker::Lorem.paragraphs(number: 3).join("\n\n") }
status { :draft }
published_at { nil }
trait :published do
status { :published }
published_at { 1.day.ago }
end
trait :with_comments do
after(:create) do |post|
create_list(:comment, 3, post: post)
end
end
trait :with_tags do
after(:create) do |post|
post.tag_list.add('rails', 'ruby', 'testing')
post.save
end
end
end
end
require 'test_helper'
class PostTest < ActiveSupport::TestCase
test 'published scope returns only published posts' do
published = create(:post, :published)
draft = create(:post)
assert_includes Post.published, published
refute_includes Post.published, draft
end
test 'validates title presence' do
post = build(:post, title: nil)
refute post.valid?
assert_includes post.errors[:title], "can't be blank"
end
test 'can have multiple comments' do
post = create(:post, :with_comments)
assert_equal 3, post.comments.count
end
end
Fixtures and factories both create test data, but suit different needs. Fixtures load YAML files into the database before tests, providing fast, consistent data. I use fixtures for static reference data like countries or categories. Factories (via FactoryBot) build objects programmatically with attributes and associations. They're more flexible for test-specific scenarios and maintain referential integrity automatically. Factories support traits for variations and sequences for unique values. I prefer factories for most tests since they're more maintainable and explicit. Fixtures excel for large, static datasets. The key is consistency—mixing both approaches causes confusion. For React integration tests, I mock API responses with MSW instead of seeding data.
