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rename test_index.py to test_index_document.py
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112
.cursor/skills/tdd/SKILL.md
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112
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---
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name: tdd
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description: Strict Python TDD workflow using pytest (Red-Green-Refactor).
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---
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---
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name: tdd
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description: Test-driven development with red-green-refactor loop. Use when user wants to build features or fix bugs using TDD, mentions "red-green-refactor", wants integration tests, or asks for test-first development.
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---
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# Test-Driven Development
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## Philosophy
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**Core principle**: Tests should verify behavior through public interfaces, not implementation details. Code can change entirely; tests shouldn't.
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**Good tests** are integration-style: they exercise real code paths through public APIs. They describe _what_ the system does, not _how_ it does it. A good test reads like a specification - "user can checkout with valid cart" tells you exactly what capability exists. These tests survive refactors because they don't care about internal structure.
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**Bad tests** are coupled to implementation. They mock internal collaborators, test private methods, or verify through external means (like querying a database directly instead of using the interface). The warning sign: your test breaks when you refactor, but behavior hasn't changed. If you rename an internal function and tests fail, those tests were testing implementation, not behavior.
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See [tests.md](tests.md) for examples and [mocking.md](mocking.md) for mocking guidelines.
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## Anti-Pattern: Horizontal Slices
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**DO NOT write all tests first, then all implementation.** This is "horizontal slicing" - treating RED as "write all tests" and GREEN as "write all code."
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This produces **crap tests**:
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- Tests written in bulk test _imagined_ behavior, not _actual_ behavior
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- You end up testing the _shape_ of things (data structures, function signatures) rather than user-facing behavior
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- Tests become insensitive to real changes - they pass when behavior breaks, fail when behavior is fine
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- You outrun your headlights, committing to test structure before understanding the implementation
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**Correct approach**: Vertical slices via tracer bullets. One test → one implementation → repeat. Each test responds to what you learned from the previous cycle. Because you just wrote the code, you know exactly what behavior matters and how to verify it.
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```
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WRONG (horizontal):
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RED: test1, test2, test3, test4, test5
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GREEN: impl1, impl2, impl3, impl4, impl5
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RIGHT (vertical):
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RED→GREEN: test1→impl1
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RED→GREEN: test2→impl2
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RED→GREEN: test3→impl3
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...
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```
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## Workflow
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### 1. Planning
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Before writing any code:
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- [ ] Confirm with user what interface changes are needed
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- [ ] Confirm with user which behaviors to test (prioritize)
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- [ ] Identify opportunities for [deep modules](deep-modules.md) (small interface, deep implementation)
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- [ ] Design interfaces for [testability](interface-design.md)
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- [ ] List the behaviors to test (not implementation steps)
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- [ ] Get user approval on the plan
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Ask: "What should the public interface look like? Which behaviors are most important to test?"
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**You can't test everything.** Confirm with the user exactly which behaviors matter most. Focus testing effort on critical paths and complex logic, not every possible edge case.
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### 2. Tracer Bullet
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Write ONE test that confirms ONE thing about the system:
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```
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RED: Write test for first behavior → test fails
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GREEN: Write minimal code to pass → test passes
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```
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This is your tracer bullet - proves the path works end-to-end.
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### 3. Incremental Loop
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For each remaining behavior:
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```
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RED: Write next test → fails
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GREEN: Minimal code to pass → passes
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```
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Rules:
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- One test at a time
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- Only enough code to pass current test
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- Don't anticipate future tests
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- Keep tests focused on observable behavior
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### 4. Refactor
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After all tests pass, look for [refactor candidates](refactoring.md):
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- [ ] Extract duplication
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- [ ] Deepen modules (move complexity behind simple interfaces)
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- [ ] Apply SOLID principles where natural
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- [ ] Consider what new code reveals about existing code
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- [ ] Run tests after each refactor step
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**Never refactor while RED.** Get to GREEN first.
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## Checklist Per Cycle
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```
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[ ] Test describes behavior, not implementation
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[ ] Test uses public interface only
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[ ] Test would survive internal refactor
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[ ] Code is minimal for this test
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[ ] No speculative features added
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```
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33
.cursor/skills/tdd/deep-modules.md
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33
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# Deep Modules
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From "A Philosophy of Software Design":
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**Deep module** = small interface + lots of implementation
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```
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┌─────────────────────┐
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│ Small Interface │ ← Few methods, simple params
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├─────────────────────┤
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│ │
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│ │
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│ Deep Implementation│ ← Complex logic hidden
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│ │
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│ │
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└─────────────────────┘
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```
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**Shallow module** = large interface + little implementation (avoid)
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```
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┌─────────────────────────────────┐
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│ Large Interface │ ← Many methods, complex params
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├─────────────────────────────────┤
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│ Thin Implementation │ ← Just passes through
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└─────────────────────────────────┘
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```
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When designing interfaces, ask:
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- Can I reduce the number of methods?
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- Can I simplify the parameters?
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- Can I hide more complexity inside?
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33
.cursor/skills/tdd/interface-design.md
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33
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# Interface Design for Testability
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Good interfaces make testing natural:
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1. **Accept dependencies, don't create them**
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```python
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# Testable
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def process_order(order, payment_gateway):
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pass
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# Hard to test
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def process_order(order):
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gateway = StripeGateway()
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```
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2. **Return results, don't produce side effects**
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```python
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# Testable
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def calculate_discount(cart) -> float:
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return discount
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# Hard to test
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def apply_discount(cart) -> None:
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cart.total -= discount
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```
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3. **Small surface area**
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* Fewer methods = fewer tests needed
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* Fewer params = simpler test setup
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69
.cursor/skills/tdd/mocking.md
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69
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# When to Mock
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Mock at **system boundaries** only:
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* External APIs (payment, email, etc.)
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* Databases (sometimes - prefer test DB)
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* Time/randomness
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* File system (sometimes)
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Don't mock:
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* Your own classes/modules
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* Internal collaborators
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* Anything you control
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## Designing for Mockability
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At system boundaries, design interfaces that are easy to mock:
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**1. Use dependency injection**
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Pass external dependencies in rather than creating them internally:
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```python
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import os
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# Easy to mock
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def process_payment(order, payment_client):
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return payment_client.charge(order.total)
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# Hard to mock
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def process_payment(order):
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client = StripeClient(os.getenv("STRIPE_KEY"))
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return client.charge(order.total)
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```
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**2. Prefer SDK-style interfaces over generic fetchers**
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Create specific functions for each external operation instead of one generic function with conditional logic:
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```python
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import requests
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# GOOD: Each function is independently mockable
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class UserAPI:
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def get_user(self, user_id):
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return requests.get(f"/users/{user_id}")
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def get_orders(self, user_id):
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return requests.get(f"/users/{user_id}/orders")
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def create_order(self, data):
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return requests.post("/orders", json=data)
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# BAD: Mocking requires conditional logic inside the mock
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class GenericAPI:
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def fetch(self, endpoint, method="GET", data=None):
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return requests.request(method, endpoint, json=data)
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```
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The SDK approach means:
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* Each mock returns one specific shape
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* No conditional logic in test setup
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* Easier to see which endpoints a test exercises
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* Type safety per endpoint
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10
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10
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# Refactor Candidates
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After TDD cycle, look for:
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- **Duplication** → Extract function/class
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- **Long methods** → Break into private helpers (keep tests on public interface)
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- **Shallow modules** → Combine or deepen
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- **Feature envy** → Move logic to where data lives
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- **Primitive obsession** → Introduce value objects
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- **Existing code** the new code reveals as problematic
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60
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60
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# Good and Bad Tests
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## Good Tests
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**Integration-style**: Test through real interfaces, not mocks of internal parts.
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```python
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# GOOD: Tests observable behavior
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def test_user_can_checkout_with_valid_cart():
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cart = create_cart()
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cart.add(product)
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result = checkout(cart, payment_method)
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assert result.status == "confirmed"
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```
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Characteristics:
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* Tests behavior users/callers care about
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* Uses public API only
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* Survives internal refactors
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* Describes WHAT, not HOW
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* One logical assertion per test
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## Bad Tests
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**Implementation-detail tests**: Coupled to internal structure.
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```python
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# BAD: Tests implementation details
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def test_checkout_calls_payment_service_process():
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mock_payment = MagicMock()
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checkout(cart, mock_payment)
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mock_payment.process.assert_called_with(cart.total)
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```
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Red flags:
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* Mocking internal collaborators
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* Testing private methods
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* Asserting on call counts/order
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* Test breaks when refactoring without behavior change
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* Test name describes HOW not WHAT
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* Verifying through external means instead of interface
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```python
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# BAD: Bypasses interface to verify
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def test_create_user_saves_to_database():
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create_user({"name": "Alice"})
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row = db.query("SELECT * FROM users WHERE name = ?", ["Alice"])
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assert row is not None
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# GOOD: Verifies through interface
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def test_create_user_makes_user_retrievable():
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user = create_user({"name": "Alice"})
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retrieved = get_user(user.id)
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assert retrieved.name == "Alice"
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```
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