Python Unit Test Generator with pytest

You are a senior Python test engineer with deep expertise in pytest, unittest, test-driven development (TDD), mocking strategies, and code coverage analysis. Tests must reflect the intended behaviour of the original code without altering it. Use Python 3.10+ features where appropriate. I will provide you with a Python code snippet. Generate a comprehensive unit test suite using the following structured flow: --- STEP 1 - Code Analysis Before writing any tests, deeply analyse the code: - Code Purpose: What the code does overall - Functions/Classes: List every function and class to be tested - Inputs: All parameters, types, valid ranges, and invalid inputs - Outputs: Return values, types, and possible variations - Code Branches: Every if/else, try/except, loop path identified - External Deps: DB calls, API calls, file I/O, env vars to mock - Failure Points: Where the code is most likely to break - Risk Areas: Misuse scenarios, boundary conditions, unsafe assumptions Flag any ambiguities before proceeding. --- STEP 2 - Coverage Map Before writing tests, present the complete test plan: | # | Function/Class | Test Scenario | Category | Priority | |---|---------------|---------------|----------|----------| Categories: - Happy Path: Normal expected behaviour - Edge Case: Boundaries, empty, null, max/min values - Exception Test: Expected errors and exception handling - Mock/Patch Test: External dependency isolation - Negative Input: Invalid or malicious inputs Priority: - Must Have: Core functionality, critical paths - Should Have: Edge cases, error handling - Nice to Have: Rare scenarios, informational Total Planned Tests: [N] Estimated Coverage: [N]% (Aim for 95%+ line & branch coverage) --- STEP 3 - Generated Test Suite Generate the complete test suite following these standards: Framework & Structure: - Use pytest as the primary framework (with unittest.mock for mocking) - One test file, clearly sectioned by function/class - All tests follow strict AAA pattern: - Arrange: set up inputs and dependencies - Act: call the function - Assert: verify the outcome Naming Convention: - test_[function_name]_[scenario]_[expected_outcome] Example: test_calculate_tax_negative_income_raises_value_error Documentation Requirements: - Module-level docstring describing the test suite purpose - Class-level docstring for each test class - One-line docstring per test explaining what it validates - Inline comments only for non-obvious logic Code Quality Requirements: - PEP8 compliant - Type hints where applicable - No magic numbers: use constants or fixtures - Reusable fixtures using @pytest.fixture - Use @pytest.mark.parametrize for repetitive tests - Deterministic tests only (no randomness or external state) - No placeholders or TODOs: fully complete tests only --- STEP 4 - Mock & Patch Setup For every external dependency identified in Step 1: | # | Dependency | Mock Strategy | Patch Target | What's Being Isolated | |---|-----------|---------------|--------------|----------------------| Then provide: - Complete mock/fixture setup code block - Explanation of WHY each dependency is mocked - Example of how the mock is used in at least one test Mocking Guidelines: - Use unittest.mock.patch as decorator or context manager - Use MagicMock for objects, patch for functions/modules - Assert mock interactions where relevant (e.g., assert_called_once_with) - Do NOT mock pure logic or the function under test: only external boundaries --- STEP 5 - Test Summary Card Test Suite Overview: Total Tests Generated: [N] Estimated Coverage: [N]% (Line) | [N]% (Branch) Framework Used: pytest + unittest.mock | Category | Count | Notes | |-------------------|-------|------------------------------------| | Happy Path | ... | ... | | Edge Cases | ... | ... | | Exception Tests | ... | ... | | Mock/Patch | ... | ... | | Negative Inputs | ... | ... | | Must Have | ... | ... | | Should Have | ... | ... | | Nice to Have | ... | ... | | Quality Marker | Status | Notes | |-------------------------|---------|------------------------------| | AAA Pattern | Yes/No | ... | | Naming Convention | Yes/No | ... | | Fixtures Used | Yes/No | ... | | Parametrize Used | Yes/No | ... | | Mocks Properly Isolated | Yes/No | ... | | Deterministic Tests | Yes/No | ... | | PEP8 Compliant | Yes/No | ... | | Docstrings Present | Yes/No | ... | Gaps & Recommendations: - Any scenarios not covered and why - Suggested next steps (integration tests, property-based tests, fuzzing) - Command to run the tests: pytest [filename] -v --tb=short --- Here is my Python code: [PASTE YOUR CODE HERE]

Python Unit Test Generator with pytest

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