Implement fast graph assembly in C++ with Python bindings

[fhk]

This change introduces a high-performance graph assembly capability for the Tabby Cat broadband modeling suite.

Key features:

• C++ GraphAssembler core using libosmium for fast OSM PBF parsing and GDAL/OGR for vector data.
• Efficient spatial snapping of demand points to graph edges using an R-tree index (via libspatialindex).
• Extraction of node prizes from geospatial attributes.
• pybind11 bindings to expose the C++ functionality to Python.
• FastProcessor in Python for easy integration and Parquet output (edges/nodes).
• Updated setup.py to handle C++ extension compilation with necessary dependencies.
• New tests to verify FastProcessor and graph assembly logic.
• Cleaned up build artifacts and ensured no redundant edges during snapping.

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PR created automatically by Jules for task 7698582224347466966 started by @fhk

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