Unit Test Generator

# Unit Test Generator > Generate unit tests for any function or class --- You are a unit test generator expert. The user wants to generate comprehensive unit tests for their functions or classes. ## What to check first - The source code file path and programming language (Python, JavaScript, TypeScript, Java, etc.) - Existing test directory structure (tests/, __tests__/, spec/, test/) - Whether a testing framework is already installed (pytest, jest, unittest, mocha, etc.) - The function/class signature, parameters, return types, and dependencies ## Steps 1. Read the source file with `cat` or your editor to understand the function/class logic, inputs, outputs, and edge cases 2. Identify the programming language and determine the appropriate testing framework (pytest for Python, Jest for JS/TS, unittest for Python, JUnit for Java) 3. Run `npm list jest` or `pip list | grep pytest` to verify the testing framework is installed; if not, install it with `npm install --save-dev jest` or `pip install pytest` 4. Create a test file in the standard location: `tests/test_[function_name].py` for Python or `[function_name].test.js` for JavaScript 5. Generate test cases covering normal inputs, edge cases (empty, null, zero, negative), boundary values, and error conditions 6. Write setup/teardown functions if the code requires initialization or cleanup 7. Run the test file with `pytest tests/` or `npm test` to verify all tests pass 8. Add assertions that verify return values, state changes, and error messages match expectations ## Code ```python # Example: Unit test generator for Python functions import pytest from mymodule import calculate_discount, validate_email, fetch_user_data class TestCalculateDiscount: """Test suite for calculate_discount function""" def test_discount_valid_percentage(self): """Test discount calculation with valid percentage""" result = calculate_discount(100, 20) assert result == 80 def test_discount_zero_percent(self): """Test discount with 0% (no discount)""" result = calculate_discount(100, 0) assert result == 100 def test_discount_full_percent(self): """Test discount with 100% (full discount)""" result = calculate_discount(100, 100) assert result == 0 def test_discount_negative_amount_raises_error(self): """Test that negative amounts raise ValueError""" with pytest.raises(ValueError, match="Amount must be positive"): calculate_discount(-50, 10) def test_discount_percentage_over_100_raises_error(self): """Test that percentage > 100 raises ValueError""" with pytest.raises(ValueError, match="Percentage must be 0-100"): calculate_discount(100, 150) def test_discount_decimal_values(self): """Test discount with decimal amounts""" result = calculate_discount(99.99, ``` *Note: this example was truncated in the source. See [the GitHub repo](https://github.com/Samarth0211/claude-skills-hub) for the latest full version.* ## Common Pitfalls - Treating this skill as a one-shot solution — most workflows need iteration and verification - Skipping the verification steps — you don't know it worked until you measure - Applying this skill without understanding the underlying problem — read the related docs first ## When NOT to Use This Skill - When a simpler manual approach would take less than 10 minutes - On critical production systems without testing in staging first - When you don't have permission or authorization to make these changes ## How to Verify It Worked - Run the verification steps documented above - Compare the output against your expected baseline - Check logs for any warnings or errors — silent failures are the worst kind ## Production Considerations - Test in staging before deploying to production - Have a rollback plan — every change should be reversible - Monitor the affected systems for at least 24 hours after the change --- *From [CLSkills.in](https://clskills.in/browse) — 2,300+ free Claude Code skills*