pytest-ml-tester

# pytest-ml-tester ## Overview ML-specific testing skill using pytest with specialized fixtures for data validation, model loading, prediction testing, and ML pipeline verification. ## Capabilities - Data validation fixtures - Model loading fixtures - Prediction testing utilities - Performance regression tests - Integration test helpers - Coverage reporting for ML code - Property-based testing with Hypothesis - Parameterized test generation ## Target Processes - ML System Integration Testing - Model Evaluation and Validation Framework - Data Collection and Validation Pipeline ## Tools and Libraries - pytest - pytest-cov - hypothesis - great-expectations (optional) ## Input Schema ```json { "type": "object", "required": ["action"], "properties": { "action": { "type": "string", "enum": ["run", "generate", "coverage", "fixtures"], "description": "Testing action to perform" }, "testConfig": { "type": "object", "properties": { "testPath": { "type": "string" }, "markers": { "type": "array", "items": { "type": "string" } }, "verbose": { "type": "boolean" }, "failFast": { "type": "boolean" }, "parallel": { "type": "integer" } } }, "coverageConfig": { "type": "object", "properties": { "sourcePath": { "type": "string" }, "minCoverage": { "type": "number" }, "reportFormat": { "type": "string", "enum": ["html", "xml", "term"] } } },...