unit-test-design-for-cheminformatics
Summary
Design and implement pytest-based unit tests for cheminformatics converters (e.g. RDKit-based chemical structure transformations) to validate converter instantiation, conversion accuracy, and chemical correctness of outputs. This skill ensures that local molecular transformations (SMILES→InChI, etc.) produce chemically valid and structurally correct results.
When to use
When implementing a new ComputeConverter subclass for MSMetaEnhancer that performs local chemical structure conversions using RDKit (e.g., SMILES to InChI, canonical SMILES generation). Test-driven validation is essential because incorrect molecular parsing or structure generation can propagate errors through mass spectra metadata annotation workflows.
When NOT to use
- Input is a web service converter (e.g., CTS, PubChem APIs) — use integration/mock tests instead
- Testing asynchronous annotation workflows across multiple services — this skill focuses on individual converter chemistry validation, not async orchestration
- Validating .msp file format parsing or metadata curation logic — this skill is specific to chemical structure transformation correctness
Inputs
- Python module file inheriting from ComputeConverter
- Reference SMILES strings (e.g., 'c1ccccc1', 'CCO', 'CC(=O)O')
- RDKit Mol objects (parsed from SMILES input)
Outputs
- pytest test file with test_* functions
- Test execution report (pass/fail status for converter instantiation and conversion accuracy)
- Validated chemical structure output dictionaries (e.g., {'inchi': 'InChI=1S/C6H6/c1-2-4-6-5-3-1/h1-6H', 'inchikey': '...'})
How to apply
Create a pytest test file that validates: (1) converter class instantiation succeeds and internal state (conversions list, async flags) is correctly initialized; (2) each conversion method accepts valid reference SMILES inputs (e.g., benzene 'c1ccccc1', ethanol 'CCO') and produces outputs with the correct target attribute keys (e.g., 'inchi', 'inchikey'); (3) output structure matches expected schema (dictionary format with string values); (4) chemical correctness by comparing generated InChI or SMILES strings against known reference values from RDKit's own InChI generation or canonical SMILES functions. Run pytest to confirm both new converter tests and all existing MSMetaEnhancer tests pass, ensuring no regression in the broader annotation pipeline.
Related tools
- pytest (Test framework for running converter instantiation and conversion accuracy tests) — https://docs.pytest.org/en/6.2.x/contents.html
- RDKit (Reference implementation for local chemical structure conversions; provides Chem.MolFromSmiles, Chem.inchi.MolToInchi, and canonical SMILES generation for validation)
- MSMetaEnhancer (Host framework defining ComputeConverter base class and converter registration mechanism) — https://github.com/RECETOX/MSMetaEnhancer
Examples
pytest tests/test_rdkit_converter.py -v
Evaluation signals
- Converter instantiation test passes: conversions list attribute populated correctly with source and target fields
- Reference SMILES inputs (e.g., 'c1ccccc1', 'CCO') convert to output dictionaries with expected keys (e.g., 'inchi', 'inchikey')
- Generated InChI and InChIKey strings are non-empty and match reference RDKit-computed values for the same SMILES
- Output structure is dict-typed with string values (no None, Mol objects, or other types leaked)
- All existing MSMetaEnhancer pytest tests still pass after new converter tests are added (no regression)
Limitations
- RDKit chemical parsing may fail silently for malformed SMILES (e.g., unbalanced rings); tests should include explicit error-case validation
- InChI and InChIKey generation require RDKit to be compiled with InChI support; test environment must verify this dependency
- Tests validate chemistry at the structure level but do not verify behavior under edge cases (e.g., isotopes, stereochemistry variants, tautomeric forms) unless explicitly included in reference test SMILES
Evidence
- [other] Create a pytest test file that validates converter instantiation and tests conversion accuracy against reference SMILES inputs, verifying output structure and chemical correctness.: "Create a pytest test file that validates converter instantiation and tests conversion accuracy against reference SMILES inputs, verifying output structure and chemical correctness."
- [other] Implement conversion methods using RDKit to perform local molecular structure transformations (e.g., parse SMILES strings with RDKit Chem.MolFromSmiles and generate InChI with Chem.inchi.MolToInchi).: "Implement conversion methods using RDKit to perform local molecular structure transformations (e.g., parse SMILES strings with RDKit Chem.MolFromSmiles and generate InChI with Chem.inchi.MolToInchi)."
- [other] Run pytest to confirm existing tests still pass and new converter tests execute successfully.: "Run pytest to confirm existing tests still pass and new converter tests execute successfully."
- [readme] All functionality is tested with the pytest framework.: "All functionality is tested with the pytest framework."
- [other] make sure the existing tests still work by running
pytest: "make sure the existing tests still work by running pytest"
1---2name: unit-test-design-for-cheminformatics3description: Use when when implementing a new ComputeConverter subclass for MSMetaEnhancer that performs local chemical structure conversions using RDKit (e.g., SMILES to InChI, canonical SMILES generation).4license: CC-BY-4.05---67# unit-test-design-for-cheminformatics89## Summary1011Design and implement pytest-based unit tests for cheminformatics converters (e.g. RDKit-based chemical structure transformations) to validate converter instantiation, conversion accuracy, and chemical correctness of outputs. This skill ensures that local molecular transformations (SMILES→InChI, etc.) produce chemically valid and structurally correct results.1213## When to use1415When implementing a new ComputeConverter subclass for MSMetaEnhancer that performs local chemical structure conversions using RDKit (e.g., SMILES to InChI, canonical SMILES generation). Test-driven validation is essential because incorrect molecular parsing or structure generation can propagate errors through mass spectra metadata annotation workflows.1617## When NOT to use1819- Input is a web service converter (e.g., CTS, PubChem APIs) — use integration/mock tests instead20- Testing asynchronous annotation workflows across multiple services — this skill focuses on individual converter chemistry validation, not async orchestration21- Validating .msp file format parsing or metadata curation logic — this skill is specific to chemical structure transformation correctness2223## Inputs2425- Python module file inheriting from ComputeConverter26- Reference SMILES strings (e.g., 'c1ccccc1', 'CCO', 'CC(=O)O')27- RDKit Mol objects (parsed from SMILES input)2829## Outputs3031- pytest test file with test_* functions32- Test execution report (pass/fail status for converter instantiation and conversion accuracy)33- Validated chemical structure output dictionaries (e.g., {'inchi': 'InChI=1S/C6H6/c1-2-4-6-5-3-1/h1-6H', 'inchikey': '...'})3435## How to apply3637Create a pytest test file that validates: (1) converter class instantiation succeeds and internal state (conversions list, async flags) is correctly initialized; (2) each conversion method accepts valid reference SMILES inputs (e.g., benzene 'c1ccccc1', ethanol 'CCO') and produces outputs with the correct target attribute keys (e.g., 'inchi', 'inchikey'); (3) output structure matches expected schema (dictionary format with string values); (4) chemical correctness by comparing generated InChI or SMILES strings against known reference values from RDKit's own InChI generation or canonical SMILES functions. Run pytest to confirm both new converter tests and all existing MSMetaEnhancer tests pass, ensuring no regression in the broader annotation pipeline.3839## Related tools4041- **pytest** (Test framework for running converter instantiation and conversion accuracy tests) — https://docs.pytest.org/en/6.2.x/contents.html42- **RDKit** (Reference implementation for local chemical structure conversions; provides Chem.MolFromSmiles, Chem.inchi.MolToInchi, and canonical SMILES generation for validation)43- **MSMetaEnhancer** (Host framework defining ComputeConverter base class and converter registration mechanism) — https://github.com/RECETOX/MSMetaEnhancer4445## Examples4647```48pytest tests/test_rdkit_converter.py -v49```5051## Evaluation signals5253- Converter instantiation test passes: conversions list attribute populated correctly with source and target fields54- Reference SMILES inputs (e.g., 'c1ccccc1', 'CCO') convert to output dictionaries with expected keys (e.g., 'inchi', 'inchikey')55- Generated InChI and InChIKey strings are non-empty and match reference RDKit-computed values for the same SMILES56- Output structure is dict-typed with string values (no None, Mol objects, or other types leaked)57- All existing MSMetaEnhancer pytest tests still pass after new converter tests are added (no regression)5859## Limitations6061- RDKit chemical parsing may fail silently for malformed SMILES (e.g., unbalanced rings); tests should include explicit error-case validation62- InChI and InChIKey generation require RDKit to be compiled with InChI support; test environment must verify this dependency63- Tests validate chemistry at the structure level but do not verify behavior under edge cases (e.g., isotopes, stereochemistry variants, tautomeric forms) unless explicitly included in reference test SMILES6465## Evidence6667- [other] Create a pytest test file that validates converter instantiation and tests conversion accuracy against reference SMILES inputs, verifying output structure and chemical correctness.: "Create a pytest test file that validates converter instantiation and tests conversion accuracy against reference SMILES inputs, verifying output structure and chemical correctness."68- [other] Implement conversion methods using RDKit to perform local molecular structure transformations (e.g., parse SMILES strings with RDKit Chem.MolFromSmiles and generate InChI with Chem.inchi.MolToInchi).: "Implement conversion methods using RDKit to perform local molecular structure transformations (e.g., parse SMILES strings with RDKit Chem.MolFromSmiles and generate InChI with Chem.inchi.MolToInchi)."69- [other] Run pytest to confirm existing tests still pass and new converter tests execute successfully.: "Run pytest to confirm existing tests still pass and new converter tests execute successfully."70- [readme] All functionality is tested with the pytest framework.: "All functionality is tested with the pytest framework."71- [other] make sure the existing tests still work by running ``pytest``: "make sure the existing tests still work by running ``pytest``"
HolobiomicsLab 