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; its analysis functions take the raw IFC file as bytes. geometry_data_buffers and geometry_data_json return the same geometry and differ only in output format; pass include_directrices=True to include analytic swept-disk paths. entity_data reads attributes and property sets instead, without tessellating. check_swept_disks checks authored swept-disk paths without tessellating, and swept_disk_definitions returns reusable raw source paths and occurrence transforms. extrusion_definitions returns exact source profiles and placed extrusion occurrences. authored_quantity_analysis reads IFC-authored quantity observations, while quantity_analysis joins them with nominal analytic source estimates. rebar_schedule combines authored bar metadata with derived source geometry.

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, quality: str | None = None, ids: set[int] | None = None, *, include_directrices: bool = False) -> 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, quality: str | None = None, ids: set[int] | None = None, *, include_directrices: bool = False) -> 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.

Analytic swept-disk paths

Pass include_directrices=True to either geometry function. The result adds swept_disks, keyed by occurrence STEP id, and directrix_diagnostics. Each occurrence can have multiple source IfcSweptDiskSolid items. A description preserves solid_id, directrix_id, Radius, InnerRadius, mapping_path, source_modified, status, an ordered Directrix of typed line and circular-arc segments, directrix_metrics, and nominal_quantities. Coordinates are in absolute IFC Z-up world metres, matching mesh vertices. For a complete description, Radius and InnerRadius are the effective world radii in metres. For an unsupported transform, they retain the authored radii converted to metres; the status indicates that no world circular radius is available. directrix_metrics gives total_length and one entry per directrix segment, with a matching segment_index and centreline length in world metres. Arc entries have a positive bend_angle in radians; line entries have bend_angle=None. The signed arc sweep_angle on Directrix still gives travel direction. These are geometric bend angles, without bend allowances or fabrication deductions. The buffer path uses integer keys; the JSON path uses string object keys.

For complete, unmodified source sweeps, nominal_quantities contains cross_section_area, nominal_volume, outer_lateral_area, and optional inner_lateral_area in m²/m³. They are calculated from the world-space radii and directrix length; they are estimates, not authored IfcElementQuantity values or net quantities. Self-overlap and mitred joins can change the physical body. The field is None for unsupported paths, CSG operands, broken joins, degenerate segments, and arcs whose radius does not exceed the disk radius. Sharp but joined mitres remain nominal estimates.

data = ifclite_geom.geometry_data_buffers(ifc_bytes, include_directrices=True)
for step_id, sweeps in data["swept_disks"].items():
    for sweep in sweeps:
        metrics = sweep["directrix_metrics"]
        if metrics is None:
            print(step_id, sweep["status"])
            continue
        print(step_id, "centreline metres:", metrics["total_length"])
        for segment, measured in zip(sweep["Directrix"], metrics["segments"]):
            if segment["type"] == "line":
                print(step_id, segment["start"], segment["end"], measured["length"])
            else:  # circular arc
                print(step_id, segment["center"], segment["radius"],
                      measured["bend_angle"])

An arc also carries normal, x_axis, start_angle, and sweep_angle to define its orientation and travel. status is {"type": "complete"} or {"type": "unsupported", "reason": ...}; unsupported paths have no partial segments and directrix_metrics=None. source_modified=True means the sweep is a source operand and later booleans may alter the final solid. Inspect that field before using the source path for fabrication. The flag does not describe cuts from external IfcRelVoidsElement openings. Extraction issues appear in directrix_diagnostics. With the flag omitted, both functions keep their existing output shape and skip this extraction.

check_swept_disks(ifc_bytes: bytes, ids: set[int] | None = None, *, zero_length_tolerance_m: float = 1e-9, gap_tolerance_m: float = 1e-6, tangent_tolerance_rad: float = 1e-6) -> dict

Run numerical checks on authored IfcSweptDiskSolid paths, without a mesh pass. The function extracts each selected occurrence once and runs the shared Rust checker on each source solid. Results are keyed by occurrence STEP id; multiple sweeps under one occurrence stay separate and retain occurrence_index, solid_id, directrix_id, and mapping_path. diagnostics reports problems traversing the representation. ids filters product occurrences as it does in the geometry functions; an empty set returns empty elements.

checks = ifclite_geom.check_swept_disks(ifc_bytes)
for step_id, entries in checks["elements"].items():
    for entry in entries:
        report = entry["report"]
        if report["skipped_reason"] is not None:
            print(step_id, "uncheckable:", report["skipped_reason"])
            continue
        for finding in report["findings"]:
            print(step_id, entry["solid_id"], finding["code"],
                  finding["segment_index"], finding["measured"])

Each finding carries a stable code, segment_index, optional next_segment_index for a join, measured value, threshold and units (m or rad). Codes are zero_length_segment, consecutive_gap, tangent_discontinuity, and arc_radius_not_greater_than_disk_radius. The defaults flag segments at or below 1 nanometre, gaps above 1 micrometre, and tangent changes above 1 microradian. Supply finite, nonnegative tolerances to suit the model; invalid values raise ValueError even when ids is empty. An unsupported analytic path has a skipped_reason and no partial findings. source_modified=True means the checker measured an authored CSG operand, which may differ from the finished body. These geometric findings do not certify fabrication compliance or calculate bend allowances. IFC allows non-tangent consecutive segments to form a miter, so tangent_discontinuity is an inspection cue rather than an automatic schema violation (IfcSweptDiskSolid).

swept_disk_definitions(ifc_bytes: bytes, ids: set[int] | None = None) -> dict

Return one source definition per representation-map path and solid, with one instance per use in a product. This is an opt-in, untessellated view; the flattened include_directrices=True contract is unchanged. sources contain authored Radius, InnerRadius, and Directrix in the IFC file's length units. instances is keyed by product STEP id and preserves deterministic ordinal, mapping_path (mapped-item STEP ids), source_modified, and status. The source key contains the SHA-256 of the IFC bytes, FILE_SCHEMA, unit scale (as 16 hex digits of its f64 bits), solid STEP id, and either a top-level representation id or ordered IfcRepresentationMap ids. Repeated MappingTargets therefore share a source without collapsing distinct uses.

world_from_source is a column-major 4×4 f64 matrix mapping source file-unit coordinates directly to absolute IFC Z-up metres. It includes the file length scale, product placement, and nested mapping transforms. The source radius is raw; a uniform instance's effective world radius also includes the matrix's uniform scale. A nonuniform instance carries status=unsupported because its world disk is not circular. An invalid matrix is None with an unsupported status. Source and instance output have independent work budgets; truncation appears in diagnostics.

view = ifclite_geom.swept_disk_definitions(ifc_bytes, ids={50})
for instance in view["instances"].get(50, []):
    print(instance["source"], instance["world_from_source"])

extrusion_definitions(ifc_bytes: bytes, ids: set[int] | None = None) -> dict

Return exact authored IfcExtrudedAreaSolid profiles once per source and a separate record for each product occurrence. Sources retain raw IFC file-length units, ProfileType, ordered line and arc loops, signed area and perimeter, authored DirectionRatios, normalized axis_unit_vector, and Depth. Complete sources with valid positive net profile area carry nominal_quantities from the shared Rust calculator: net profile area in squared file units, projected height in file units, and their nominal volume in cubed file units. Unsupported or invalid sources have nominal_quantities=None. Unsupported or tapered sources carry an explicit status; no approximate boundary is substituted. A source key uses the same model/schema/unit/context identity as swept_disk_definitions, so repeated MappingTargets share a definition while each use has its own deterministic ordinal and mapped-item path. source_modified=True marks a CSG operand whose final body can differ.

For a complete source-profile point, apply profile_position, then the extrusion's position_matrix, then the occurrence's world_from_source. Matrices are column-major f64. The first two use raw IFC file units; the last includes file-unit scale and maps to absolute IFC Z-up world metres. When an optional Position is absent, its matrix field is None (JSON null): use identity for that step when composing transforms, rather than expecting an identity array in the response. Check status before using an absent matrix; an invalid reference can also leave an unsupported source without one. A non-finite transform is None; a singular transform retains its matrix, and both have unsupported status. Source reference keys use exact IFC names: both profile and extrusion carry Position, and the extrusion carries ExtrudedDirection; the separate derived matrices keep their descriptive names. The API does not infer a post-boolean solid or a world volume from a raw source. Source and occurrence budgets are independent; truncation is reported in diagnostics.

view = ifclite_geom.extrusion_definitions(ifc_bytes, ids={50})
for instance in view["instances"].get(50, []):
    print(instance["source"], instance["world_from_source"])

authored_quantity_analysis(ifc_bytes: bytes, ids: set[int] | None = None) -> dict

Return IFC-authored quantities keyed by actual product STEP ID without meshing. Each observation retains the exact IfcElementQuantity.Name and IfcPhysicalSimpleQuantity.Name, both source entity IDs, kind, numeric value, and occurrence or inherited type origin. A same-named occurrence/type disagreement appears in conflicts; neither value is overwritten. unit records the resolved symbol, SI factor, source, and explicit unit ID where present. If a unit cannot be resolved or has the wrong dimension, unit=None and unit_diagnostic explains why. IfcQuantityCount and IFC4X3 IfcQuantityNumber are dimensionless when no unit is supplied; a resolved explicit named unit is preserved instead of being discarded.

view = ifclite_geom.authored_quantity_analysis(ifc_bytes, ids={50})
for quantity in view["products"].get(50, {}).get("authored", []):
    print(quantity["set_name"], quantity["quantity_name"], quantity["value"], quantity["unit"])

product_count counts selected IFC product entities. It is not a physical bar count, source-solid count, cutting length or material takeoff. This authored view contains no calculated estimate; use the analytic source APIs separately and keep their provenance distinct. A malformed or over-budget relationship or quantity set appears in diagnostics. An absent optional IfcTypeObject.HasPropertySets is valid; a malformed list or member is reported and its type-authored quantities are refused. Conflicting IfcRelDefinesByType assignments likewise refuse type inheritance for that product while preserving its occurrence-authored observations.

quantity_analysis(ifc_bytes: bytes, ids: set[int] | None = None) -> dict

Join authored IfcElementQuantity observations with exact analytic swept-disk and extrusion source occurrences. products is keyed by product STEP ID; authored retains exact names, IDs, units, origin and conflicts. Each entry in sources keeps its canonical source key, solid ID, mapping path, ordinal, status and nominal values with formula, origin, unit and limitation. Swept-disk centreline and section estimates use world metres; extrusion depth and profile estimates remain in raw IFC file units because an occurrence transform may scale them. Depth is an authored solid parameter, not an IfcElementQuantity value.

view = ifclite_geom.quantity_analysis(ifc_bytes, ids={50})
for source in view["products"][50]["sources"]:
    for estimate in source["quantities"]:
        print(source["solid_id"], estimate["name"], estimate["value"], estimate["unit"])

product_count counts IFC products, source_occurrence_count counts uses of analytic solids, and unique_source_count counts distinct source definitions. Mapped products can share one source. product_total is always None with an aggregate_diagnostic: source estimates exclude voids, CSG results, overlap, self-intersection and cutting allowances. They cannot establish a physical part count or final material quantity. Unsupported and source-modified sources retain explicit status; extraction failures appear in diagnostics. When a complete swept-disk occurrence has no defensible nominal section or volume estimate, status_reason explains the omission even if its centreline length remains available. Joined diagnostics have one bounded output budget.

Reinforcing-bar schedule inputs

rebar_schedule(ifc_bytes, ids=None) returns one row per selected IfcReinforcingBar, including bars with no supported swept-disk geometry. Each row exposes the occurrence's GlobalId and Name under their exact EXPRESS names. Authored attributes use exact EXPRESS names and record whether they came from the occurrence or its IfcReinforcingBarType. Numeric attributes retain their raw IFC value and an SI conversion. An authored CrossSectionArea of zero remains in the record, with a row diagnostic stating that it does not establish a physical section area. Each source sweep separately carries radius, centreline length and bend angles, geometric checks, and reusable source identity. For complete paths, radii are effective world values in metres; an unsupported transform retains source radii in metres and does not establish a world circular radius. If a file's unit conversion makes a radius non-finite, the binding raises ValueError instead of returning JSON null. Mapped repetitions remain separate, while repeated uses of one representation map share a source key. If the independent definition output budget is exhausted, source is None with a row diagnostic; the world-space schedule sweep remains available. An authored BarLength can differ from the derived centreline length; neither value is a certified cutting length. IFC bar entities and represented sweeps do not imply a physical bar count.

schedule = ifclite_geom.rebar_schedule(ifc_bytes)
for step_id, row in schedule["rows"].items():
    print(step_id, row["GlobalId"], row["Name"], row["authored"].get("BarLength"), row["sweeps"])

For project-specific comparisons, call rebar_schedule_with_preflight(ifc_bytes, min_inside_bend_radius_m, min_straight_segment_length_m, max_developed_centreline_length_m=None). The measured comparisons identify their source segments; equality passes. Inside bend radius is arc centreline radius minus swept outer radius. Modified or unsupported sources and rows without sweeps carry explicit skip reasons. For a skipped sweep, comparisons is None; an assessed sweep has a list of measured comparisons. Check skipped_reason before interpreting pass results. No result certifies a cutting length or fabrication-code compliance.

For independently optional SI policy checks use rebar_schedule_with_fabrication_precheck(ifc_bytes, ids=None, **policy). Options are min_inside_bend_radius_m, min_straight_segment_length_m, max_developed_centreline_length_m, max_nominal_geometric_diameter_delta_m, and paired min_bend_angle_rad / max_bend_angle_rad (finite, nonnegative, ordered radians). Each requested check reports pass, fail or uncheckable, with source IDs, measured value, threshold, units and reason. Missing/conflicting authored NominalDiameter, modified CSG, unsupported transforms and incomplete directrices cannot pass.

schedule = ifclite_geom.rebar_schedule_with_fabrication_precheck(
    ifc_bytes, min_inside_bend_radius_m=0.05,
    max_nominal_geometric_diameter_delta_m=0.001,
)
for row in schedule["rows"].values():
    for sweep in row["sweeps"]:
        report = sweep["fabrication_precheck"]
        print(report["outcome"], report["checks"], report["unchecked_factors"])

Every outcome is precheck_only; material, fabrication process, allowances, jurisdiction and physical bar count are unchecked. Authored BarLength is not a verified cutting length. The Revit Snowdon fixture validates source geometry but its authored schedule is not independently verified.

Tessellation quality

Both geometry functions take an optional quality label:

It scales the segment count on every curved primitive: swept-disk tubes, cylinders, revolutions, arcs, circular profiles. On curve-heavy elements the effect is large. A single IfcReinforcingBar authored as an IfcSweptDiskSolid over a composite arc tessellates to 1056 triangles at "medium" and 96 at "lowest".

data = ifclite_geom.geometry_data_buffers(ifc_bytes, "lowest")

An unrecognised label raises ValueError rather than silently falling back, so a typo cannot cost you a 10x triangle budget without saying so. This is the same knob the browser build exposes as setTessellationQuality and the server as ?tessellation_quality=; the level is model-wide, not per IFC type.

Filter by IFC STEP id

Both geometry functions accept an optional ids set. Only matching occurrence ids are tessellated, which lets you select products through entity_data first without paying to mesh the rest of the model:

entities = ifclite_geom.entity_data(ifc_bytes)
wall_ids = {
    step_id
    for step_id, row in entities["entities"].items()
    if row["ifc_type"] == "IfcWall"
}
walls = ifclite_geom.geometry_data_buffers(ifc_bytes, ids=wall_ids)

ids=None preserves the unfiltered behaviour. An empty set returns zero elements, and ids not present in the file are ignored. The pipeline still resolves relationship and representation dependencies: for example, selecting a wall keeps its unselected IfcOpeningElement cutters available to the wall's CSG operation without emitting meshes for those openings.

entity_data(ifc_bytes, placements=False, type_properties=True, attributes=True) -> dict

Attributes, property sets and quantity sets. No tessellation runs, so this is cheap compared with the geometry functions.

{
  "length_unit_scale": 0.001,      # file length unit -> metres
  "plane_angle_to_radians": 0.0174,
  "project_id": 42,                # may be None
  "entity_count": 1234,
  "entities": {
    <step_id:int>: {
      "ifc_type":      "IfcWall",
      "global_id":     "3vB2...",       # may be None
      "name":          "WALL 1",        # may be None
      "description":   None,
      "object_type":   None,
      "has_geometry":  True,
      "placement":     None,            # see below
      "property_sets": [
        {"name": "Pset_WallCommon",
         "properties": [{"name": "IsExternal", "value": "True",
                         "value_type": "IFCBOOLEAN"}]},
      ],
      "quantity_sets": [
        {"name": "Qto_WallBaseQuantities",
         "quantities": [{"name": "Length", "value": 3000.0, "kind": "Length"}]},
      ],
      "attributes": [                  # schema-declared entity attributes
        {"name": "PredefinedType", "value": "SOLIDWALL", "value_type": "IFCENUM"},
      ],
    },
    ...
  }
}

entities is keyed by IFC STEP id in file order, the same key geometry_data_buffers uses, so the two join directly. The join is one-way total: every meshed element has a row, but not every row has an element, so drive the loop from elements (or use .get()) rather than the other way round. Besides products with no geometry, an orphan IfcTypeProduct carries has_geometry: True and still never appears in elements, because the geometry functions emit occurrences only.

geom = ifclite_geom.geometry_data_buffers(ifc_bytes)
ents = ifclite_geom.entity_data(ifc_bytes)

for step_id, el in geom["elements"].items():
    row = ents["entities"].get(step_id)
    if row:
        print(el["ifc_type"], row["name"], row["property_sets"])

Pass placements=True to also resolve each product's ObjectPlacement into a list of 16 floats: a column-major 4x4, translation in metres at indices 12/13/14. It is off by default because it costs an extra decode per product.

The matrix is in the same absolute IFC world frame as geometry_data_buffers vertices, so the two line up directly. Do not fold rtc_offset into either: the geometry export already adds it back into every vertex, and the placement is never RTC-rebased. On a georeferenced model both are large absolute coordinates, and a product's placement origin lands inside its own mesh bounds.

Units, and two current limits

• Property and quantity values are in the file's own units, unlike geometry, which is always metres. A millimetre model reports a wall length of 3000. Property values are always strings; quantity values are floats.

  Converting is per dimension, not one blanket factor:

  quantity kind	to SI
  Length	value * length_unit_scale
  Area	value * length_unit_scale ** 2
  Volume	value * length_unit_scale ** 3
  Count	unchanged (dimensionless)
  angles (properties)	value * plane_angle_to_radians

  Only the length and plane-angle scales are resolved, so a model that declares an area or volume unit inconsistent with its length unit cannot be reconciled from what is returned here.

• Only IfcPropertySingleValue properties are decoded. Enumerated, list, bounded, table and reference properties are skipped; the pset still appears, with those entries missing.

Entity attributes

Note the two senses of "type" on this page. The section below concerns an IfcTypeObject, the shared definition an occurrence inherits from. This one concerns the IFC entity class (IfcWall, IfcReinforcingBar) and the attributes its schema declares. They are unrelated.

attributes is on by default. These are not property sets and no amount of pset work surfaces them, because they are declared on the entity itself:

row = ents["entities"][step_id]
{a["name"]: a["value"] for a in row["attributes"]}
# A bar with every attribute set:
# {'Tag': 'TAG-1', 'SteelGrade': 'B500B', 'NominalDiameter': '29',
#  'CrossSectionArea': '660', 'BarLength': '500',
#  'PredefinedType': 'NOTDEFINED', 'BarSurface': 'PLAIN'}
#
# A bar leaving most of them `$`, which is the common case:
# {'NominalDiameter': '29', 'CrossSectionArea': '0',
#  'PredefinedType': 'NOTDEFINED'}

Only what the file sets is returned. An attribute left $ is omitted rather than reported empty, so the list is usually shorter than the class declares, and its length varies between two entities of the same class.

Every IFC entity class has its own schema-declared attributes: IfcDoor yields OverallHeight / OverallWidth, and so on, named and ordered as the schema declares them. Entries share the {name, value, value_type} shape of a property, so one code path reads both.

Fields the row already carries (global_id, name, description, object_type) are not repeated, and reference-valued attributes are omitted rather than rendered as a dangling #123. Pass attributes=False to skip.

Type-inherited properties

type_properties is on by default. A type attaches its sets through IfcTypeObject.HasPropertySets and gets no row of its own unless it carries orphan geometry, so without this the properties authoring tools put on types are unreachable. Each occurrence therefore also carries what it inherits through IfcRelDefinesByType, merged per property:

• A type set whose name the occurrence does not use is added whole.
• A type set sharing a name contributes only the properties the occurrence does not already define. On a collision the occurrence wins, and the type-only properties beside it still survive. Replacing the whole set instead would hide them, which is the bug this rule exists to prevent.

quantity_sets inherit on exactly the same terms. A type attaches IfcElementQuantity definitions through the same HasPropertySets attribute, so they arrive by the same route and merge by the same rule: a type quantity set the occurrence does not name is added whole, and a same-named one contributes only the quantities the occurrence does not already define, so the occurrence wins a collision. type_properties governs both lists; there is no separate switch.

# Own sets only, as in 4.3.0. Affects property_sets AND quantity_sets.
ents = ifclite_geom.entity_data(ifc_bytes, type_properties=False)

This mirrors what the browser has done since the same fix landed there, so a property visible in the viewer is now visible here.

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 (pipeline failure) or ValueError (an unrecognised quality label, or JSON serialization failure).

Examples

Runnable scripts live in examples/:

• quickstart_numpy.py - load a file and inspect meshes via numpy.
• dump_json.py - write the JSON document to disk.
• export_obj.py - write every element to a single Wavefront .obj (numpy only, no extra deps).
• schedule_csv.py - join entity_data against geometry_data_buffers and write a quantity schedule to CSV (stdlib only).

License

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