ifclite-geom

Native ifc-lite geometry tessellation for Python. It turns an IFC file into per-entity triangle meshes with no Node, no WASM, and no subprocess: the Rust geometry kernel runs directly inside the Python process.

Meshes come back welded, IFC Z-up, in absolute world metres, keyed by IFC STEP id (occurrences only). This is the analysis-ready export, distinct from the render-oriented GLB the viewer uses.

Install

pip install ifclite-geom

Prebuilt wheels ship for CPython 3.9+ on Linux (x86_64, aarch64), macOS (Apple silicon and Intel), and Windows (x64). No Rust toolchain needed.

Quick start

The module is ifclite_geom and exposes two functions. Both take the raw IFC file as bytes and return the same geometry; they differ only in the output format.

import ifclite_geom
import numpy as np

with open("model.ifc", "rb") as f:
    ifc_bytes = f.read()

data = ifclite_geom.geometry_data_buffers(ifc_bytes)

print(data["element_count"], "elements")
print("up axis:", data["up_axis"], "| units:", data["units"])
print("rtc offset:", data["rtc_offset"])

for step_id, el in data["elements"].items():
    verts = np.frombuffer(el["vertices"], dtype=np.float64).reshape(-1, 3)
    faces = np.frombuffer(el["faces"],    dtype=np.uint32 ).reshape(-1, 3)
    print(step_id, el["ifc_type"], el["global_id"], verts.shape, faces.shape)

Prefer no numpy dependency? Use the JSON variant, which returns the same data as arrays of numbers:

import ifclite_geom, json

doc = json.loads(ifclite_geom.geometry_data_json(ifc_bytes))
first = next(iter(doc["elements"].values()))
print(first["ifc_type"], first["vertices"][0])  # [x, y, z] in metres

API

geometry_data_buffers(ifc_bytes: bytes) -> dict

The fast path. Vertices and faces come back as raw little-endian byte buffers so you can hand them straight to numpy.frombuffer with zero parsing.

{
  "up_axis": "Z",            # always Z (IFC native)
  "units": "m",              # always metres
  "rtc_offset": [x, y, z],   # geo-reference offset already folded into vertices
  "element_count": 1234,
  "elements": {
    <step_id:int>: {
      "ifc_type":  "IfcWall",
      "global_id": "3vB2...",   # may be None
      "name":      "Basic Wall:...",  # may be None
      "color":     [r, g, b, a],      # 0..1
      "vertices":  <bytes>,           # f64 little-endian, xyz triplets
      "faces":     <bytes>,           # u32 little-endian, triangle indices
    },
    ...
  }
}

Decode the buffers with:

verts = np.frombuffer(el["vertices"], dtype=np.float64).reshape(-1, 3)  # (V, 3)
faces = np.frombuffer(el["faces"],    dtype=np.uint32 ).reshape(-1, 3)  # (F, 3)

geometry_data_json(ifc_bytes: bytes) -> str

The same geometry as a readable ifc-lite-geometry-data JSON document (a string; call json.loads on it). Vertices are [x, y, z] arrays and faces are [a, b, c] index arrays, so no numpy is required. Each element also carries global_id and name when the source entity has them.

Notes

  • One mesh per element. Per-material submeshes of an element are merged into a single indexed triangle soup, keyed by its IFC STEP id.
  • Coordinates are absolute world metres. The per-element local frame and the model RTC offset are folded back into every vertex. For geo-referenced models rtc_offset is non-zero; subtract it if you want f32-friendly local coordinates.
  • Welded and indexed. Coincident corners are merged (1 micron grid), so closed-mesh consumers (volume, watertightness checks) work directly.
  • Occurrences only. Type-product / RepresentationMap geometry is not emitted, matching what occurrence-based tessellators produce.
  • Errors surface as RuntimeError (geometry pipeline failure) or ValueError (JSON serialization failure).

Examples

Runnable scripts live in examples/:

License

MPL-2.0. Part of the ifc-lite project.

Project links

Data verified by PyPI on Jul 9, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

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  • Released:
Newer release available (4.4.0)

1 maintainer

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Avatar for louistrue from gravatar.com louistrue

Credits

Author: IFC-Lite Contributors

GitHub Statistics

Data verified by PyPI on Jul 9, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

MPL-2.0

Requires

Python >=3.9

Tags

ifc bim geometry tessellation

Classifiers

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