Official Resources
- Homepage: https://gbasis.qcdevs.org/
- Documentation: https://gbasis.readthedocs.io/
- Source Repository: https://github.com/theochem/gbasis
- PyPI: https://pypi.org/project/gbasis/
- License: GNU Lesser General Public License v3.0
Overview
GBasis is a Python library for evaluating and integrating Gaussian-type orbitals and integrals. Part of the QCDevs project and originating from the HORTON project, it provides a modular framework for computing molecular integrals, densities, and related quantities needed for quantum chemistry calculations.
Scientific domain: Quantum chemistry, molecular integrals, basis set evaluation
Target user community: Quantum chemistry developers, researchers needing integral evaluation, educational users
Theoretical Methods
- Gaussian-type orbital (GTO) evaluation
- One-electron integrals
- Two-electron integrals
- Molecular orbital basis transformations
- Density and potential evaluation
- Electrostatic moments
Capabilities (CRITICAL)
- GTO basis function evaluation
- Overlap integrals
- Kinetic energy integrals
- Nuclear attraction integrals
- Electron repulsion integrals
- Electron density on grids
- Electrostatic potential
- Moments (dipole, quadrupole, etc.)
- Basis set parsing
- General contractions
Sources: GitHub repository, QCDevs project, ReadTheDocs
Key Strengths
Modular Design:
- Separate evaluation and integration
- Composable components
- Extensible architecture
- Clean API
Pure Python:
- NumPy/SciPy based
- No compilation required
- Cross-platform
- Easy installation
QCDevs Ecosystem:
- Part of larger project
- Integration with other tools
- Maintained community
- Educational focus
Comprehensive Integrals:
- All standard molecular integrals
- Grid-based quantities
- Properties and moments
- Flexible basis handling
Inputs & Outputs
-
Input formats:
- IOData molecule objects
- Basis set dictionaries
- NumPy arrays for coordinates
-
Output data types:
- Integral arrays
- Density values
- Potential values
- Moment tensors
Interfaces & Ecosystem
-
QCDevs tools:
- IOData (file I/O)
- Grid (numerical grids)
- QCSchema compatibility
-
External:
- NumPy/SciPy
- Standard basis set formats
- Interoperable with other codes
Advanced Features
Integral Evaluation:
- Cartesian and spherical GTOs
- Contracted basis functions
- General contraction support
- Efficient algorithms
Property Calculations:
- Multipole moments
- Electrostatic potential
- Electron density
- Gradient quantities
Basis Set Handling:
- Standard library formats
- Custom basis sets
- Segmented and general contractions
Performance Characteristics
- Speed: NumPy vectorized
- Accuracy: Numerical precision
- System size: Small to medium
- Memory: NumPy arrays
- Parallelization: NumPy threading
Computational Cost
- Integrals: Standard N^4 for ERIs
- Grids: Linear in grid points
- Typical: Development/research scale
Limitations & Known Constraints
- Not full QM code: Library, not standalone
- Large systems: Not optimized for production
- Speed: Python overhead
- Features: Core integrals focus
Comparison with Other Codes
- vs libint: GBasis Python, libint C++
- vs PySCF integrals: Different scope
- Unique strength: Pure Python, educational, modular
Application Areas
Code Development:
- New QM method implementation
- Testing integral routines
- Algorithm development
- Prototyping
Education:
- Teaching molecular integrals
- Understanding QM code internals
- Research training
Analysis:
- Density evaluation
- Property calculations
- Wavefunction analysis
Integration:
- Building custom QM codes
- Interfacing with other tools
- Workflow development
Best Practices
Getting Started:
- pip install gbasis
- Use IOData for molecules
- Follow documentation examples
Integral Computation:
- Select appropriate functions
- Understand basis conventions
- Validate against references
Community and Support
- Open source LGPL v3
- QCDevs community
- GitHub development
- ReadTheDocs documentation
- PyPI distribution
Verification & Sources
Primary sources:
- GitHub: https://github.com/theochem/gbasis
- Documentation: https://gbasis.readthedocs.io/
- PyPI: https://pypi.org/project/gbasis/
- QCDevs project
Confidence: VERIFIED - Active development, published
Verification status: ✅ VERIFIED
- Source code: OPEN (GitHub, LGPL v3)
- Package: PyPI
- Documentation: ReadTheDocs
- Community: QCDevs
- Specialty: Gaussian integral library, modular design