pythonocc-core is a Python binding for the OpenCASCADE Technology (OCCT) 3D CAD kernel, providing full access to OCCT's geometry, topology, visualization, and data exchange capabilities. It is a library, not a standalone application, designed for engineers and developers building CAD/CAE/PLM tools in Python. The architecture is a C++ extension module generated via SWIG, with a thin Python layer that adds convenience utilities, multiple display backends (Qt, wxPython, Tkinter, WebGL/Jupyter), and high-level helpers for shape creation, topology traversal, and file I/O (STEP, IGES, STL, glTF, OBJ, PLY). The core API mirrors OCCT's class hierarchy, while the `OCC.Extend` and `OCC.Display` packages provide Pythonic wrappers and interactive 3D viewers. The repository is actively maintained, with recent releases (7.9.3) and CI pipelines for conda packages across platforms. It includes extensive type stubs for IDE support, a comprehensive test suite, and support for offscreen rendering and Jupyter notebooks. Key entry points include `OCC.Display.SimpleGui.init_display()` for interactive viewers, `OCC.Extend.DataExchange.read_step_file()` for CAD file import, and `OCC.Core.Tesselator.ShapeTesselator` for mesh generation. The codebase demonstrates strong engineering practices with reusable patterns like the topology explorer, shape factory utilities, and a generic proxy pattern for OCCT objects. However, the SWIG-generated wrapper layer is large and fragile, requiring careful version alignment with OCCT, and some OCCT classes remain unwrapped.
PyMFEM provides Python bindings for the MFEM finite element library, enabling finite element simulations (PDE solvers) from Python. The architecture consists of SWIG-generated wrapper modules for serial (`mfem.ser`) and parallel MPI (`mfem.par`) execution, built on top of the C++ MFEM library. Key entry points include the core modules (`mfem.ser`, `mfem.par`), a suite of 30+ example scripts covering Laplace, elasticity, Maxwell, Navier-Stokes, and more, and miniapps for specialized applications (DPG, multidomain, field interpolation). The system supports JIT-compiled coefficients via Numba, complex-valued solvers via CHypre, and GPU backends (CUDA, libCEED). While primarily a software library, it has a strong research character due to its advanced numerical methods (DPG, fractional PDEs, topology optimization) and extensive example set that serves as both documentation and validation.