Addition of logic from Beam vs Duct WIP function
build and deploy Speckle functions / publish-automate-function-version (push) Has been cancelled
build and deploy Speckle functions / publish-automate-function-version (push) Has been cancelled
This commit is contained in:
Jonathon Broughton
@@ -0,0 +1,11 @@
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*.pyc
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build/
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dist/
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*.egg-info/
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.cache/
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*.log
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.ruff_cache/
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.venv/
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.env/
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.git/
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Dockerfile copy*
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@@ -14,7 +14,7 @@ jobs:
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- uses: actions/checkout@v3.4.0
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- uses: actions/setup-python@v4
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with:
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python-version: '3.11'
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python-version: '3.10'
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- name: Install and configure Poetry
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uses: snok/install-poetry@v1
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with:
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+4
-47
@@ -175,7 +175,7 @@ ARG BRANCH=main
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ARG NUM_CORES=10
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# Clone a git repository
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RUN /bin/sh -c "git clone --single-branch -b $BRANCH https://github.com/nuvolos-cloud/PyMesh.git"
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RUN /bin/sh -c "git clone --single-branch --depth 1 -b $BRANCH https://github.com/nuvolos-cloud/PyMesh.git"
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# Set environment variables
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ENV PYMESH_PATH=/root/PyMesh
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@@ -199,69 +199,28 @@ RUN echo "deb http://ftp.us.debian.org/debian unstable main contrib non-free" >>
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# Build and install PyMesh
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WORKDIR /root/PyMesh
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# RUN git submodule update --init
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RUN git clone --depth 1 https://github.com/PyMesh/cgal.git $PYMESH_PATH/third_party/cgal
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# RUN git submodule update --init third_party/libigl
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RUN git clone --depth 1 https://github.com/PyMesh/libigl.git $PYMESH_PATH/third_party/libigl
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# RUN git submodule update --init third_party/carve
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RUN git clone --depth 1 https://github.com/PyMesh/carve.git $PYMESH_PATH/third_party/carve
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# RUN git submodule update --init third_party/cork
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RUN git clone --depth 1 https://github.com/PyMesh/cork.git $PYMESH_PATH/third_party/cork
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# RUN git submodule update --init third_party/tetgen
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RUN git clone --depth 1 https://github.com/PyMesh/tetgen.git $PYMESH_PATH/third_party/tetgen
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RUN git submodule update --init third_party/triangle
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# RUN git clone --depth 1 https://github.com/PyMesh/triangle.git $PYMESH_PATH/third_party/triangle
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# RUN git submodule update --init third_party/qhull
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RUN git clone --depth 1 https://github.com/PyMesh/qhull.git $PYMESH_PATH/third_party/qhull
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# RUN git submodule update --init third_party/Clipper
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RUN git clone --depth 1 https://github.com/PyMesh/Clipper.git $PYMESH_PATH/third_party/Clipper
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# RUN git submodule update --init third_party/eigen
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RUN git clone --depth 1 https://github.com/PyMesh/eigen.git $PYMESH_PATH/third_party/eigen
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RUN git submodule update --init third_party/quartet
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# RUN git clone --depth 1 https://github.com/PyMesh/quartet.git $PYMESH_PATH/third_party/quartet
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# RUN git submodule update --init third_party/pybind11
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RUN git clone --depth 1 https://github.com/PyMesh/pybind11.git $PYMESH_PATH/third_party/pybind11
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# RUN git submodule update --init third_party/geogram
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RUN git clone --depth 1 https://github.com/PyMesh/geogram.git $PYMESH_PATH/third_party/geogram
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# RUN git submodule update --init third_party/draco
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RUN git clone --depth 1 https://github.com/PyMesh/draco.git $PYMESH_PATH/third_party/draco
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# RUN git submodule update --init third_party/TetWild
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RUN git clone --depth 1 https://github.com/PyMesh/TetWild.git $PYMESH_PATH/third_party/TetWild
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# RUN git submodule update --init third_party/WindingNumber
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RUN git clone --depth 1 https://github.com/PyMesh/WindingNumber.git $PYMESH_PATH/third_party/WindingNumber
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# RUN git submodule update --init third_party/tbb
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RUN git clone --depth 1 https://github.com/PyMesh/tbb.git $PYMESH_PATH/third_party/tbb
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# RUN git submodule update --init third_party/jigsaw
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RUN git clone --depth 1 https://github.com/PyMesh/jigsaw.git $PYMESH_PATH/third_party/jigsaw
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RUN git submodule update --init third_party/mmg
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# RUN git clone --depth 1 https://github.com/PyMesh/mmg.git $PYMESH_PATH/third_party/mmg
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# RUN git submodule update --init third_party/fmt
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RUN git clone --depth 1 https://github.com/fmtlib/fmt.git $PYMESH_PATH/third_party/fmt
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# RUN git submodule update --init third_party/spdlog
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RUN git clone --depth 1 https://github.com/gabime/spdlog.git $PYMESH_PATH/third_party/spdlog
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RUN git submodule update --init third_party/triangle
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RUN git submodule update --init third_party/quartet
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RUN git submodule update --init third_party/mmg
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RUN git submodule update --init third_party/json
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# RUN git clone --depth 1 https://github.com/nlohmann/json.git $PYMESH_PATH/third_party/json
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RUN pip install -r $PYMESH_PATH/python/requirements.txt
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RUN ./setup.py bdist_wheel
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@@ -274,8 +233,6 @@ RUN pip install dist/pymesh2*.whl
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WORKDIR /root/PyMesh/third_party
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RUN /bin/sh -c "python ./build.py mmg && python ./build.py tetgen"
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# We install poetry to generate a list of dependencies which will be required by our application
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RUN pip install poetry
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@@ -0,0 +1,107 @@
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from typing import Tuple, Optional
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import numpy as np
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import trimesh
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from specklepy.objects import Base
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from specklepy.objects.geometry import Mesh as SpeckleMesh
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from specklepy.objects.other import Transform
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from trimesh import Trimesh
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class Element:
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def __init__(self, id, meshes):
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"""
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Initialize an Element object with an ID and a list of meshes.
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Args:
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id (str): The ID of the Element.
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meshes (List[Trimesh]): List of trimesh Mesh objects.
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"""
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self.id = id
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self.meshes = meshes
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def speckle_transform_to_trimesh_matrix(transform: Transform) -> np.ndarray:
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"""
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Convert the Speckle Transform matrix to a NumPy array format suitable for trimesh.
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Returns:
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np.ndarray: 4x4 transformation matrix in NumPy array format.
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"""
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return np.array(transform.value).reshape(4, 4)
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def speckle_to_element(
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base_with_transforms: Tuple[Base, str, Optional[Transform]]
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) -> Element:
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"""
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Convert a SpecklePy Base object and its associated Transform to an Element object.
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Args:
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base_with_transforms (tuple): Contains a SpecklePy Base object and its
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associated Transform object.
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Returns:
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Element: The resulting Element object.
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"""
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# Unpack the tuple to get the base, speckle ID, and transform.
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base, speckle_id, transform = base_with_transforms
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# To convert the Base object to a trimesh Mesh, use the displayValue property.
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# This property provides the display mesh, expected to be an iterable of
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# SpecklePy Mesh objects. However, legacy objects might be a single mesh.
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display_value = base.displayValue
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if isinstance(display_value, SpeckleMesh):
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display_value = [display_value]
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if isinstance(display_value, list):
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# Initialize an Element with an empty list of meshes.
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element = Element(speckle_id, meshes=[])
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for mesh in display_value:
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if mesh:
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# Convert the SpecklePy Mesh to a trimesh Mesh.
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t_mesh = speckle_to_trimesh(mesh)
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if not isinstance(t_mesh, Trimesh):
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continue
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# If there's a transform, apply it to the trimesh Mesh.
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if transform is not None:
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trimesh_matrix = speckle_transform_to_trimesh_matrix(transform)
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t_mesh.apply_transform(trimesh_matrix)
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# Append the trimesh Mesh to the Element's list of meshes.
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element.meshes.append(t_mesh)
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return element
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def speckle_to_trimesh(speckle_mesh: SpeckleMesh) -> Trimesh:
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"""
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Convert a SpecklePy Mesh to a trimesh Mesh object.
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Args:
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speckle_mesh: The SpecklePy Mesh to convert.
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Returns:
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trimesh.Trimesh: The resulting trimesh Mesh object.
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"""
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# Convert the list of vertices to a numpy array. Reshape it to
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# (num_vertices, 3) to fit the trimesh format.
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vertices_array = np.array(speckle_mesh.vertices).reshape((-1, 3))
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# Faces are expected to be triangular. Reshape the faces list accordingly.
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# Convert the faces list to a numpy array
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faces_array_raw = np.array(speckle_mesh.faces)
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# Remove the leading 3s by skipping every 4th value
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faces_cleaned = np.delete(faces_array_raw, np.arange(0, faces_array_raw.size, 4))
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# Reshape the array into (-1, 3) shape
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faces_array = faces_cleaned.reshape((-1, 3))
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# Return a new trimesh object using the reshaped vertices and faces.
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return trimesh.Trimesh(vertices=vertices_array, faces=faces_array)
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@@ -0,0 +1,16 @@
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import pymesh
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vertices = [
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[0, 0, 0],
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[1, 0, 0],
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[1, 1, 0],
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[0, 1, 0]
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]
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faces = [
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[0, 1, 2],
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[0, 2, 3]
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]
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mesh = pymesh.form_mesh(vertices, faces)
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@@ -1,39 +1,43 @@
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# Speckle Automate function template - Python
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[](https://github.com/specklesystems/speckle_automate-basic_clash_demo/actions/workflows/main.yml)
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This is a template repository for a Speckle Automate functions written in python
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using the [specklepy](https://pypi.org/project/specklepy/) SDK to interact with Speckle data.
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# Speckle Automate Function: Basic Clash Analysis Demo
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This template contains the full scaffolding required to publish a function to the automate environment.
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Also has some sane defaults for a development environment setups.
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## Overview
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This repository hosts the Basic Clash Analysis Demo for Speckle Automate, tailored for the AEC industry. It demonstrates automated clash detection using complex third-party libraries to analyze elements from both a static reference model and a dynamic model.
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## Getting started
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## ⚠️ Disclaimer: Conceptual Demonstration Only
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**IMPORTANT: This function is a conceptual model and is not intended for actual use in production environments. It serves as a demonstration to illustrate automated clash detection principles in Speckle Automate and the use of third-party libraries for advanced analysis.**
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1. Use this template repository to create a new repository in your own / organization's profile.
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## Functionality
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- **Element Type Selection:** Users specify element categories for clash tests.
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- **Automated Detection:** Demonstrates real-time clash detection as the dynamic model evolves.
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- **Clash Reporting:** Generates reports on detected clashes.
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- **Integration Example:** Illustrates potential integration with Speckle's platform and AEC software tools.
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- **Notification Simulation:** Simulates automated notifications about clashes.
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Register the function
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### How It Works
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The function analyzes elements from a static reference model and a dynamic model, identifying potential geometric conflicts when the dynamic model is updated.
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### Add new dependencies
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### Utilization of Third-Party Libraries
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This demo showcases the ability to incorporate complex third-party libraries for detailed analysis, extending the functionality of Speckle Automate beyond its core features. In this case a custom build of PyMesh and its c++ library dependencies are included in the Dockerfile.
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To add new python package dependencies to the project, use:
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`$ poetry add pandas`
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### Containerization and Deployment
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- **Dockerization:** The included Dockerfile demonstrates how the project can be containerized, emphasizing the ease of deployment in Speckle Automate.
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- **Automate Deployment:** Highlights the potential for easy deployment of containerized projects within the Speckle ecosystem.
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### Change launch variables
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## Note
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This function is designed for educational purposes and is not equipped for real-world AEC projects.
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describe how the launch.json should be edited
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---
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### Github Codespaces
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**Reminder:** This repository is a conceptual demonstration for automated clash detection and the use of third-party libraries in Speckle Automate.
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Create a new repo from this template, and use the create new code.
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## Using this Speckle Function
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1. **Create a New Speckle Automation**: Set up in the Speckle dashboard.
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2. **Configure the Function**: Choose the "Basic Clash Analysis" function.
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||||
3. **Run and Review**: Execute the function and review the clash reports.
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||||
|
||||
### Using this Speckle Function
|
||||
|
||||
1. [Create](https://automate.speckle.dev/) a new Speckle Automation.
|
||||
1. Select your Speckle Project and Speckle Model.
|
||||
1. Select the existing Speckle Function named [`Random comment on IFC beam`](https://automate.speckle.dev/functions/e110be8fad).
|
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1. Enter a phrase to use in the comment.
|
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1. Click `Create Automation`.
|
||||
|
||||
## Getting Started with creating your own Speckle Function
|
||||
|
||||
1. [Register](https://automate.speckle.dev/) your Function with [Speckle Automate](https://automate.speckle.dev/) and select the Python template.
|
||||
1. A new repository will be created in your GitHub account.
|
||||
|
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@@ -0,0 +1,51 @@
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# Required imports
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from typing import Callable, List, Union
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from specklepy.objects import Base
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# We're going to define a set of rules that will allow us to filter and
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# process parameters in our Speckle objects. These rules will be encapsulated
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# in a class called `ParameterRules`.
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class ElementCheckRules:
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"""A collection of rules for processing parameters in Speckle objects.
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This class provides static methods that return lambda functions. These
|
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lambda functions serve as filters or conditions we can use in our main
|
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processing logic. By encapsulating these rules, we can easily extend
|
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or modify them in the future.
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"""
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|
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@staticmethod
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def rule_combiner(*rules: Callable[[Base], bool]) -> Callable[[Base], bool]:
|
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def combined(obj: Base) -> bool:
|
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return all(rule(obj) for rule in rules)
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||||
|
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return combined
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|
||||
@staticmethod
|
||||
def is_displayable_rule() -> Callable[[Base], bool]:
|
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"""Rule: Check if a parameter is displayable."""
|
||||
return (
|
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lambda parameter: parameter.displayValue
|
||||
and parameter.displayValue is not None
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def speckle_type_rule(
|
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desired_type: Union[str, List[str]]
|
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) -> Callable[[Base], bool]:
|
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"""Rule: Check if a parameter's speckle_type matches the desired type."""
|
||||
|
||||
# Convert single string to list for consistent handling
|
||||
if isinstance(desired_type, str):
|
||||
desired_type = [desired_type]
|
||||
|
||||
print(desired_type)
|
||||
|
||||
return (
|
||||
lambda speckle_object: getattr(speckle_object, "speckle_type", None)
|
||||
in desired_type
|
||||
)
|
||||
+66
-8
@@ -1,13 +1,71 @@
|
||||
"""Helper module for a simple speckle object tree flattening."""
|
||||
|
||||
from collections.abc import Iterable
|
||||
from typing import Tuple, Optional
|
||||
|
||||
from specklepy.objects import Base
|
||||
from specklepy.objects.other import Instance, Transform
|
||||
|
||||
|
||||
def flatten_base(base: Base) -> Iterable[Base]:
|
||||
"""Take a base and flatten it to an iterable of bases."""
|
||||
if hasattr(base, "elements"):
|
||||
for element in base["elements"]:
|
||||
yield from flatten_base(element)
|
||||
yield base
|
||||
# def flatten_base(base: Base) -> Iterable[Base]:
|
||||
# """Take a base and flatten it to an iterable of bases."""
|
||||
# if hasattr(base, "elements") and base["elements"] is not None:
|
||||
# for element in base["elements"]:
|
||||
# yield from flatten_base(element)
|
||||
# yield base
|
||||
|
||||
|
||||
def extract_base_and_transform(
|
||||
base: Base,
|
||||
inherited_instance_id: Optional[str] = None,
|
||||
transform_list: Optional[List[Transform]] = None,
|
||||
) -> Tuple[Base, str, Optional[List[Transform]]]:
|
||||
"""
|
||||
Traverses Speckle object hierarchies to yield `Base` objects and their transformations.
|
||||
Tailored to Speckle's AEC data structures, it covers the newer hierarchical structures
|
||||
with Collections and also with patterns found in older Revit specific data.
|
||||
|
||||
Parameters:
|
||||
- base (Base): The starting point `Base` object for traversal.
|
||||
- inherited_instance_id (str, optional): The inherited identifier for `Base` objects without a unique ID.
|
||||
- transform_list (List[Transform], optional): Accumulated list of transformations from parent to child objects.
|
||||
|
||||
Yields:
|
||||
- tuple: A `Base` object, its identifier, and a list of applicable `Transform` objects or None.
|
||||
|
||||
The id of the `Base` object is either the inherited identifier for a definition from an instance
|
||||
or the one defined in the object.
|
||||
"""
|
||||
# Derive the identifier for the current `Base` object, defaulting to an inherited one if needed.
|
||||
current_id = getattr(base, "id", inherited_instance_id)
|
||||
transform_list = transform_list or []
|
||||
|
||||
if isinstance(base, Instance):
|
||||
# Append transformation data and dive into the definition of `Instance` objects.
|
||||
if base.transform:
|
||||
transform_list.append(base.transform)
|
||||
if base.definition:
|
||||
yield from extract_base_and_transform(
|
||||
base.definition, current_id, transform_list.copy()
|
||||
)
|
||||
else:
|
||||
# Initial yield for the current `Base` object.
|
||||
yield base, current_id, transform_list
|
||||
|
||||
# Process 'elements' and '@elements', typical containers for `Base` objects in AEC models.
|
||||
elements_attr = getattr(base, "elements", []) or getattr(base, "@elements", [])
|
||||
for element in elements_attr:
|
||||
if isinstance(element, Base):
|
||||
# Recurse into each `Base` object within 'elements' or '@elements'.
|
||||
yield from extract_base_and_transform(
|
||||
element, current_id, transform_list.copy()
|
||||
)
|
||||
|
||||
# Recursively process '@'-prefixed properties that are Base objects with 'elements'.
|
||||
# This is a common pattern in older Speckle data models, such as those used for Revit commits.
|
||||
for attr_name in dir(base):
|
||||
if attr_name.startswith("@"):
|
||||
attr_value = getattr(base, attr_name)
|
||||
# If the attribute is a Base object containing 'elements', recurse into it.
|
||||
if isinstance(attr_value, Base) and hasattr(attr_value, "elements"):
|
||||
yield from extract_base_and_transform(
|
||||
attr_value, current_id, transform_list.copy()
|
||||
)
|
||||
|
||||
@@ -1,9 +1,8 @@
|
||||
"""This module contains the business logic of the function.
|
||||
|
||||
use the automation_context module to wrap your function in an Autamate context helper
|
||||
use the automation_context module to wrap your function in an Automate context helper
|
||||
"""
|
||||
|
||||
import time
|
||||
from typing import List, Optional, Tuple
|
||||
|
||||
from pydantic import Field
|
||||
from speckle_automate import (
|
||||
@@ -11,8 +10,17 @@ from speckle_automate import (
|
||||
AutomationContext,
|
||||
execute_automate_function,
|
||||
)
|
||||
from specklepy.api import operations
|
||||
from specklepy.api.models import Branch
|
||||
from specklepy.objects import Base
|
||||
from specklepy.objects.other import Transform
|
||||
from specklepy.objects.units import Units
|
||||
from specklepy.transports.server import ServerTransport
|
||||
from trimesh import Trimesh
|
||||
|
||||
from flatten import flatten_base
|
||||
from Geometry.mesh import speckle_to_element, Element
|
||||
from Rules.checks import ElementCheckRules
|
||||
from flatten import extract_base_and_transform
|
||||
|
||||
|
||||
class FunctionInputs(AutomateBase):
|
||||
@@ -23,12 +31,22 @@ class FunctionInputs(AutomateBase):
|
||||
https://docs.pydantic.dev/latest/usage/models/
|
||||
"""
|
||||
|
||||
forbidden_speckle_type: str = Field(
|
||||
title="Forbidden speckle type",
|
||||
description=(
|
||||
"If a object has the following speckle_type,"
|
||||
" it will be marked with an error."
|
||||
),
|
||||
tolerance: float = Field(
|
||||
default=25.0,
|
||||
title="Tolerance",
|
||||
description="Specify the tolerance value for the analysis. \
|
||||
Negative values relaxes the test, positive values make it more strict.",
|
||||
)
|
||||
tolerance_unit: str = Field( # Using the SpecklePy Units enum here
|
||||
default=Units.mm,
|
||||
json_schema_extra={"examples": ["mm", "cm", "m"]},
|
||||
title="Tolerance Unit",
|
||||
description="Unit of the tolerance value.",
|
||||
)
|
||||
static_model_name: str = Field(
|
||||
...,
|
||||
title="Static Model Name",
|
||||
description="Name of the static structural model.",
|
||||
)
|
||||
|
||||
|
||||
@@ -42,59 +60,183 @@ def automate_function(
|
||||
automate_context: A context helper object, that carries relevant information
|
||||
about the runtime context of this function.
|
||||
It gives access to the Speckle project data, that triggered this run.
|
||||
It also has conveniece methods attach result data to the Speckle model.
|
||||
It also has convenience methods attach result data to the Speckle model.
|
||||
function_inputs: An instance object matching the defined schema.
|
||||
"""
|
||||
# the context provides a conveniet way, to receive the triggering version
|
||||
version_root_object = automate_context.receive_version()
|
||||
# the context provides a convenient way, to receive the triggering version
|
||||
changed_model_version = automate_context.receive_version()
|
||||
|
||||
sleep_cycles = 10
|
||||
for i in range(sleep_cycles):
|
||||
print(f"sleeping {i}/{sleep_cycles}")
|
||||
time.sleep(5)
|
||||
|
||||
count = 0
|
||||
for b in flatten_base(version_root_object):
|
||||
if b.speckle_type == function_inputs.forbidden_speckle_type:
|
||||
if not b.id:
|
||||
raise ValueError("Cannot operate on objects without their id's.")
|
||||
|
||||
automate_context.attach_error_to_objects(
|
||||
category="Forbidden speckle_type",
|
||||
object_ids=b.id,
|
||||
message="This project should not contain the type: "
|
||||
f"{b.speckle_type}",
|
||||
)
|
||||
count += 1
|
||||
|
||||
if count > 0:
|
||||
# this is how a run is marked with a failure cause
|
||||
automate_context.mark_run_failed(
|
||||
"Automation failed: "
|
||||
f"Found {count} object that have one of the forbidden speckle types: "
|
||||
f"{function_inputs.forbidden_speckle_type}"
|
||||
try:
|
||||
reference_model_version = get_reference_model(
|
||||
automate_context, function_inputs.static_model_name
|
||||
)
|
||||
|
||||
# set the automation context view, to the original model / version view
|
||||
# to show the offending objects
|
||||
automate_context.set_context_view()
|
||||
except Exception as ex:
|
||||
automate_context.mark_run_failed(status_message=str(ex))
|
||||
return
|
||||
|
||||
else:
|
||||
automate_context.mark_run_success("No forbidden types found.")
|
||||
reference_objects: tuple[
|
||||
Base,
|
||||
str,
|
||||
Optional[Transform],
|
||||
] = extract_base_and_transform(reference_model_version)
|
||||
latest_objects: tuple[
|
||||
Base,
|
||||
str,
|
||||
Optional[Transform],
|
||||
] = extract_base_and_transform(changed_model_version)
|
||||
|
||||
# if the function generates file results, this is how it can be
|
||||
# attached to the Speckle project / model
|
||||
# automate_context.store_file_result("./report.pdf")
|
||||
element_rules = ElementCheckRules()
|
||||
|
||||
beam_types = [
|
||||
"Objects.BuiltElements.Beam:Objects.BuiltElements.Revit.RevitBeam",
|
||||
]
|
||||
duct_types = [
|
||||
"Objects.BuiltElements.Duct",
|
||||
"Objects.BuiltElements.Duct:Objects.BuiltElements.Revit.RevitDuct",
|
||||
"Objects.BuiltElements.Duct:Objects.BuiltElements.Revit.RevitDuct:Objects.BuiltElements.Revit.RevitFlexDuct",
|
||||
]
|
||||
|
||||
visible_beams_rule = element_rules.rule_combiner(
|
||||
element_rules.speckle_type_rule(beam_types),
|
||||
element_rules.is_displayable_rule(),
|
||||
)
|
||||
|
||||
visible_ducts_rule = element_rules.rule_combiner(
|
||||
element_rules.speckle_type_rule(duct_types),
|
||||
element_rules.is_displayable_rule(),
|
||||
)
|
||||
|
||||
reference_displayable_objects = [
|
||||
(base_obj, id, transform)
|
||||
for base_obj, id, transform in reference_objects
|
||||
if visible_beams_rule(base_obj)
|
||||
]
|
||||
latest_displayable_objects = [
|
||||
(base_obj, id, transform)
|
||||
for base_obj, id, transform in latest_objects
|
||||
if visible_ducts_rule(base_obj)
|
||||
]
|
||||
|
||||
reference_mesh_elements = [
|
||||
speckle_to_element(obj) for obj in reference_displayable_objects
|
||||
]
|
||||
latest_mesh_elements = [
|
||||
speckle_to_element(obj) for obj in latest_displayable_objects
|
||||
]
|
||||
|
||||
# using trimesh library process all these meshes in the form of A vs B
|
||||
# and get the clashes
|
||||
|
||||
clashes = detect_clashes(
|
||||
reference_mesh_elements, latest_mesh_elements, function_inputs.tolerance
|
||||
)
|
||||
|
||||
print(len(clashes))
|
||||
|
||||
automate_context.mark_run_success(status_message="Clash detection completed.")
|
||||
|
||||
|
||||
def automate_function_without_inputs(automate_context: AutomationContext) -> None:
|
||||
"""A function example without inputs.
|
||||
|
||||
If your function does not need any input variables,
|
||||
besides what the automation context provides,
|
||||
the inputs argument can be omitted.
|
||||
def detect_clashes(
|
||||
elements_a: List[Element], elements_b: List[Element], length_tolerance: float
|
||||
) -> List[Tuple[Element, Element]]:
|
||||
"""
|
||||
pass
|
||||
Detects clashes between two sets of elements with a specified tolerance.
|
||||
|
||||
This function checks each combination of elements from `elements_a` and `elements_b`
|
||||
to see if any of their respective meshes intersect within the specified tolerance.
|
||||
If a clash is detected between any mesh from an element in `elements_a` and any mesh
|
||||
from an element in `elements_b`, the pair of elements is added to the results.
|
||||
|
||||
Args:
|
||||
- elements_a (List[Element]): A list of `Element` objects to be checked for clashes.
|
||||
- elements_b (List[Element]): A second list of `Element` objects to be checked for clashes against `elements_a`.
|
||||
- length_tolerance (float): The distance to offset mesh vertices for intersection check.
|
||||
|
||||
Returns:
|
||||
- List[Tuple[Element, Element]]: A list of tuples where each tuple contains a pair of `Element` objects that clash.
|
||||
"""
|
||||
|
||||
# Use list comprehension to get pairs of elements that have clashing meshes
|
||||
clashes = [
|
||||
(element_a, element_b)
|
||||
for element_a in elements_a
|
||||
for element_b in elements_b
|
||||
if any(
|
||||
check_intersection_with_tolerance(mesh_a, mesh_b, length_tolerance)
|
||||
for mesh_a in element_a.meshes
|
||||
for mesh_b in element_b.meshes
|
||||
)
|
||||
]
|
||||
|
||||
return clashes
|
||||
|
||||
|
||||
def check_intersection_with_tolerance(
|
||||
mesh_a: Trimesh, mesh_b: Trimesh, tolerance: float
|
||||
) -> bool:
|
||||
"""
|
||||
Checks for intersections between two meshes within a specified tolerance.
|
||||
|
||||
Args:
|
||||
- mesh_a: The first mesh to check.
|
||||
- mesh_b: The second mesh to check.
|
||||
- tolerance (float): The distance to offset mesh vertices for intersection check.
|
||||
Positive values expand the mesh, negative values contract it.
|
||||
|
||||
Returns:
|
||||
- bool: True if the meshes intersect within the specified tolerance, otherwise False.
|
||||
"""
|
||||
half_tolerance = tolerance / 2.0 # TODO: how to shrink bloat mesh?
|
||||
offset_mesh_a: Trimesh = mesh_a # mesh_a.offset_mesh(half_tolerance)
|
||||
offset_mesh_b: Trimesh = mesh_b # mesh_b.offset_mesh(half_tolerance)
|
||||
|
||||
# return offset_mesh_a.intersection(offset_mesh_b).volume > 0 TODO: Install Blender as the engine
|
||||
|
||||
# return a random boolean for testing - significantly favouring false
|
||||
import random
|
||||
|
||||
return random.random() < 0.05
|
||||
|
||||
|
||||
def get_reference_model(
|
||||
automate_context: AutomationContext, static_model_name: str
|
||||
) -> Base:
|
||||
# the static reference model will be retrieved from the project using model name stored in the inputs
|
||||
speckle_client = automate_context.speckle_client
|
||||
project_id = automate_context.automation_run_data.project_id
|
||||
remote_transport = ServerTransport(
|
||||
automate_context.automation_run_data.project_id, speckle_client
|
||||
)
|
||||
|
||||
model: Branch = speckle_client.branch.get(
|
||||
project_id, static_model_name, commits_limit=1
|
||||
) # get the latest commit of the static model
|
||||
|
||||
if not model:
|
||||
raise Exception("The static model named does not exist, skipping the function.")
|
||||
|
||||
reference_model_commits = model.commits.items
|
||||
|
||||
if not reference_model_commits:
|
||||
raise Exception("The static model has no versions, skipping the function.")
|
||||
|
||||
latest_reference_model_id = model.id
|
||||
|
||||
latest_reference_model_version_object = reference_model_commits[0].referencedObject
|
||||
|
||||
if latest_reference_model_id == automate_context.automation_run_data.model_id:
|
||||
raise Exception(
|
||||
"The static model is the same as the changed model, skipping the function."
|
||||
)
|
||||
|
||||
latest_reference_model_version = operations.receive(
|
||||
latest_reference_model_version_object,
|
||||
remote_transport,
|
||||
) # receive the static model
|
||||
|
||||
return latest_reference_model_version
|
||||
|
||||
|
||||
# make sure to call the function with the executor
|
||||
|
||||
@@ -0,0 +1,616 @@
|
||||
annotated-types==0.6.0 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43 \
|
||||
--hash=sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d
|
||||
anyio==4.0.0 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:cfdb2b588b9fc25ede96d8db56ed50848b0b649dca3dd1df0b11f683bb9e0b5f \
|
||||
--hash=sha256:f7ed51751b2c2add651e5747c891b47e26d2a21be5d32d9311dfe9692f3e5d7a
|
||||
appdirs==1.4.4 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:7d5d0167b2b1ba821647616af46a749d1c653740dd0d2415100fe26e27afdf41 \
|
||||
--hash=sha256:a841dacd6b99318a741b166adb07e19ee71a274450e68237b4650ca1055ab128
|
||||
attrs==23.1.0 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04 \
|
||||
--hash=sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015
|
||||
backoff==2.2.1 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba \
|
||||
--hash=sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8
|
||||
certifi==2023.7.22 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082 \
|
||||
--hash=sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9
|
||||
charset-normalizer==3.3.2 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:06435b539f889b1f6f4ac1758871aae42dc3a8c0e24ac9e60c2384973ad73027 \
|
||||
--hash=sha256:06a81e93cd441c56a9b65d8e1d043daeb97a3d0856d177d5c90ba85acb3db087 \
|
||||
--hash=sha256:0a55554a2fa0d408816b3b5cedf0045f4b8e1a6065aec45849de2d6f3f8e9786 \
|
||||
--hash=sha256:0b2b64d2bb6d3fb9112bafa732def486049e63de9618b5843bcdd081d8144cd8 \
|
||||
--hash=sha256:10955842570876604d404661fbccbc9c7e684caf432c09c715ec38fbae45ae09 \
|
||||
--hash=sha256:122c7fa62b130ed55f8f285bfd56d5f4b4a5b503609d181f9ad85e55c89f4185 \
|
||||
--hash=sha256:1ceae2f17a9c33cb48e3263960dc5fc8005351ee19db217e9b1bb15d28c02574 \
|
||||
--hash=sha256:1d3193f4a680c64b4b6a9115943538edb896edc190f0b222e73761716519268e \
|
||||
--hash=sha256:1f79682fbe303db92bc2b1136016a38a42e835d932bab5b3b1bfcfbf0640e519 \
|
||||
--hash=sha256:2127566c664442652f024c837091890cb1942c30937add288223dc895793f898 \
|
||||
--hash=sha256:22afcb9f253dac0696b5a4be4a1c0f8762f8239e21b99680099abd9b2b1b2269 \
|
||||
--hash=sha256:25baf083bf6f6b341f4121c2f3c548875ee6f5339300e08be3f2b2ba1721cdd3 \
|
||||
--hash=sha256:2e81c7b9c8979ce92ed306c249d46894776a909505d8f5a4ba55b14206e3222f \
|
||||
--hash=sha256:3287761bc4ee9e33561a7e058c72ac0938c4f57fe49a09eae428fd88aafe7bb6 \
|
||||
--hash=sha256:34d1c8da1e78d2e001f363791c98a272bb734000fcef47a491c1e3b0505657a8 \
|
||||
--hash=sha256:37e55c8e51c236f95b033f6fb391d7d7970ba5fe7ff453dad675e88cf303377a \
|
||||
--hash=sha256:3d47fa203a7bd9c5b6cee4736ee84ca03b8ef23193c0d1ca99b5089f72645c73 \
|
||||
--hash=sha256:3e4d1f6587322d2788836a99c69062fbb091331ec940e02d12d179c1d53e25fc \
|
||||
--hash=sha256:42cb296636fcc8b0644486d15c12376cb9fa75443e00fb25de0b8602e64c1714 \
|
||||
--hash=sha256:45485e01ff4d3630ec0d9617310448a8702f70e9c01906b0d0118bdf9d124cf2 \
|
||||
--hash=sha256:4a78b2b446bd7c934f5dcedc588903fb2f5eec172f3d29e52a9096a43722adfc \
|
||||
--hash=sha256:4ab2fe47fae9e0f9dee8c04187ce5d09f48eabe611be8259444906793ab7cbce \
|
||||
--hash=sha256:4d0d1650369165a14e14e1e47b372cfcb31d6ab44e6e33cb2d4e57265290044d \
|
||||
--hash=sha256:549a3a73da901d5bc3ce8d24e0600d1fa85524c10287f6004fbab87672bf3e1e \
|
||||
--hash=sha256:55086ee1064215781fff39a1af09518bc9255b50d6333f2e4c74ca09fac6a8f6 \
|
||||
--hash=sha256:572c3763a264ba47b3cf708a44ce965d98555f618ca42c926a9c1616d8f34269 \
|
||||
--hash=sha256:573f6eac48f4769d667c4442081b1794f52919e7edada77495aaed9236d13a96 \
|
||||
--hash=sha256:5b4c145409bef602a690e7cfad0a15a55c13320ff7a3ad7ca59c13bb8ba4d45d \
|
||||
--hash=sha256:6463effa3186ea09411d50efc7d85360b38d5f09b870c48e4600f63af490e56a \
|
||||
--hash=sha256:65f6f63034100ead094b8744b3b97965785388f308a64cf8d7c34f2f2e5be0c4 \
|
||||
--hash=sha256:663946639d296df6a2bb2aa51b60a2454ca1cb29835324c640dafb5ff2131a77 \
|
||||
--hash=sha256:6897af51655e3691ff853668779c7bad41579facacf5fd7253b0133308cf000d \
|
||||
--hash=sha256:68d1f8a9e9e37c1223b656399be5d6b448dea850bed7d0f87a8311f1ff3dabb0 \
|
||||
--hash=sha256:6ac7ffc7ad6d040517be39eb591cac5ff87416c2537df6ba3cba3bae290c0fed \
|
||||
--hash=sha256:6b3251890fff30ee142c44144871185dbe13b11bab478a88887a639655be1068 \
|
||||
--hash=sha256:6c4caeef8fa63d06bd437cd4bdcf3ffefe6738fb1b25951440d80dc7df8c03ac \
|
||||
--hash=sha256:6ef1d82a3af9d3eecdba2321dc1b3c238245d890843e040e41e470ffa64c3e25 \
|
||||
--hash=sha256:753f10e867343b4511128c6ed8c82f7bec3bd026875576dfd88483c5c73b2fd8 \
|
||||
--hash=sha256:7cd13a2e3ddeed6913a65e66e94b51d80a041145a026c27e6bb76c31a853c6ab \
|
||||
--hash=sha256:7ed9e526742851e8d5cc9e6cf41427dfc6068d4f5a3bb03659444b4cabf6bc26 \
|
||||
--hash=sha256:7f04c839ed0b6b98b1a7501a002144b76c18fb1c1850c8b98d458ac269e26ed2 \
|
||||
--hash=sha256:802fe99cca7457642125a8a88a084cef28ff0cf9407060f7b93dca5aa25480db \
|
||||
--hash=sha256:80402cd6ee291dcb72644d6eac93785fe2c8b9cb30893c1af5b8fdd753b9d40f \
|
||||
--hash=sha256:8465322196c8b4d7ab6d1e049e4c5cb460d0394da4a27d23cc242fbf0034b6b5 \
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
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|
||||
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|
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||||
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|
||||
--hash=sha256:ff8fa367d09b717b2a17a052544193ad76cd49979c805768879cb63d9ca50561
|
||||
deprecated==1.2.14 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:6fac8b097794a90302bdbb17b9b815e732d3c4720583ff1b198499d78470466c \
|
||||
--hash=sha256:e5323eb936458dccc2582dc6f9c322c852a775a27065ff2b0c4970b9d53d01b3
|
||||
exceptiongroup==1.1.3 ; python_version >= "3.10" and python_version < "3.11" \
|
||||
--hash=sha256:097acd85d473d75af5bb98e41b61ff7fe35efe6675e4f9370ec6ec5126d160e9 \
|
||||
--hash=sha256:343280667a4585d195ca1cf9cef84a4e178c4b6cf2274caef9859782b567d5e3
|
||||
gql[requests,websockets]==3.4.1 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:11dc5d8715a827f2c2899593439a4f36449db4f0eafa5b1ea63948f8a2f8c545 \
|
||||
--hash=sha256:315624ca0f4d571ef149d455033ebd35e45c1a13f18a059596aeddcea99135cf
|
||||
graphql-core==3.2.3 ; python_version >= "3.10" and python_version < "4" \
|
||||
--hash=sha256:06d2aad0ac723e35b1cb47885d3e5c45e956a53bc1b209a9fc5369007fe46676 \
|
||||
--hash=sha256:5766780452bd5ec8ba133f8bf287dc92713e3868ddd83aee4faab9fc3e303dc3
|
||||
h11==0.14.0 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d \
|
||||
--hash=sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761
|
||||
httpcore==1.0.2 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:096cc05bca73b8e459a1fc3dcf585148f63e534eae4339559c9b8a8d6399acc7 \
|
||||
--hash=sha256:9fc092e4799b26174648e54b74ed5f683132a464e95643b226e00c2ed2fa6535
|
||||
httpx==0.25.1 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:fec7d6cc5c27c578a391f7e87b9aa7d3d8fbcd034f6399f9f79b45bcc12a866a \
|
||||
--hash=sha256:ffd96d5cf901e63863d9f1b4b6807861dbea4d301613415d9e6e57ead15fc5d0
|
||||
idna==3.4 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:814f528e8dead7d329833b91c5faa87d60bf71824cd12a7530b5526063d02cb4 \
|
||||
--hash=sha256:90b77e79eaa3eba6de819a0c442c0b4ceefc341a7a2ab77d7562bf49f425c5c2
|
||||
multidict==6.0.4 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:01a3a55bd90018c9c080fbb0b9f4891db37d148a0a18722b42f94694f8b6d4c9 \
|
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
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|
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|
||||
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|
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|
||||
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|
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|
||||
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|
||||
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|
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|
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
--hash=sha256:c048099e4c9e9d615545e2001d3d8a4380bd403e1a0578734e0d31703d1b0c0b \
|
||||
--hash=sha256:c5cb09abb18c1ea940fb99360ea0396f34d46566f157122c92dfa069d3e0e982 \
|
||||
--hash=sha256:cc8e1d0c705233c5dd0c5e6460fbad7827d5d36f310a0fadfd45cc3029762258 \
|
||||
--hash=sha256:d5e3fc56f88cc98ef8139255cf8cd63eb2c586531e43310ff859d6bb3a6b51f1 \
|
||||
--hash=sha256:d6aa0418fcc838522256761b3415822626f866758ee0bc6632c9486b179d0b52 \
|
||||
--hash=sha256:d6c254ba6e45d8e72739281ebc46ea5eb5f101234f3ce171f0e9f5cc86991480 \
|
||||
--hash=sha256:d6d635d5209b82a3492508cf5b365f3446afb65ae7ebd755e70e18f287b0adf7 \
|
||||
--hash=sha256:dcfe792765fab89c365123c81046ad4103fcabbc4f56d1c1997e6715e8015461 \
|
||||
--hash=sha256:ddd3915998d93fbcd2566ddf9cf62cdb35c9e093075f862935573d265cf8f65d \
|
||||
--hash=sha256:ddff9c4e225a63a5afab9dd15590432c22e8057e1a9a13d28ed128ecf047bbdc \
|
||||
--hash=sha256:e41b7e2b59679edfa309e8db64fdf22399eec4b0b24694e1b2104fb789207779 \
|
||||
--hash=sha256:e69924bfcdda39b722ef4d9aa762b2dd38e4632b3641b1d9a57ca9cd18f2f83a \
|
||||
--hash=sha256:ea20853c6dbbb53ed34cb4d080382169b6f4554d394015f1bef35e881bf83547 \
|
||||
--hash=sha256:ee2a1ece51b9b9e7752e742cfb661d2a29e7bcdba2d27e66e28a99f1890e4fa0 \
|
||||
--hash=sha256:eeb6dcc05e911516ae3d1f207d4b0520d07f54484c49dfc294d6e7d63b734171 \
|
||||
--hash=sha256:f70b98cd94886b49d91170ef23ec5c0e8ebb6f242d734ed7ed677b24d50c82cf \
|
||||
--hash=sha256:fc35cb4676846ef752816d5be2193a1e8367b4c1397b74a565a9d0389c433a1d \
|
||||
--hash=sha256:ff959bee35038c4624250473988b24f846cbeb2c6639de3602c073f10410ceba
|
||||
pydantic-core==2.10.1 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:042462d8d6ba707fd3ce9649e7bf268633a41018d6a998fb5fbacb7e928a183e \
|
||||
--hash=sha256:0523aeb76e03f753b58be33b26540880bac5aa54422e4462404c432230543f33 \
|
||||
--hash=sha256:05560ab976012bf40f25d5225a58bfa649bb897b87192a36c6fef1ab132540d7 \
|
||||
--hash=sha256:0675ba5d22de54d07bccde38997e780044dcfa9a71aac9fd7d4d7a1d2e3e65f7 \
|
||||
--hash=sha256:073d4a470b195d2b2245d0343569aac7e979d3a0dcce6c7d2af6d8a920ad0bea \
|
||||
--hash=sha256:07ec6d7d929ae9c68f716195ce15e745b3e8fa122fc67698ac6498d802ed0fa4 \
|
||||
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|
||||
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|
||||
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|
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|
||||
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|
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|
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
pydantic==2.4.2 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:94f336138093a5d7f426aac732dcfe7ab4eb4da243c88f891d65deb4a2556ee7 \
|
||||
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|
||||
requests-toolbelt==0.10.1 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
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|
||||
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|
||||
requests==2.31.0 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
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|
||||
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|
||||
sniffio==1.3.0 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
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|
||||
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|
||||
specklepy==2.17.11 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:b903ba6848959b95e60f5e1e80bacfa9c542359f85b360afd0d84bdd66615b15 \
|
||||
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|
||||
stringcase==1.2.0 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
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|
||||
typing-extensions==4.8.0 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
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|
||||
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|
||||
ujson==5.8.0 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
urllib3==1.26.18 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
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||||
websockets==10.4 ; python_version >= "3.10" and python_version < "4.0" \
|
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
wrapt==1.16.0 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
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|
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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||||
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|
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|
||||
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||||
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|
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||||
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||||
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||||
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||||
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|
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||||
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|
||||
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|
||||
--hash=sha256:bf5703fdeb350e36885f2875d853ce13172ae281c56e509f4e6eca049bdfb136 \
|
||||
--hash=sha256:c31f72b1b6624c9d863fc095da460802f43a7c6868c5dda140f51da24fd47d7b \
|
||||
--hash=sha256:c5cd603b575ebceca7da5a3a251e69561bec509e0b46e4993e1cac402b7247b8 \
|
||||
--hash=sha256:d2efee35b4b0a347e0d99d28e884dfd82797852d62fcd7ebdeee26f3ceb72cf3 \
|
||||
--hash=sha256:d462f28826f4657968ae51d2181a074dfe03c200d6131690b7d65d55b0f360f8 \
|
||||
--hash=sha256:d5e49454f19ef621089e204f862388d29e6e8d8b162efce05208913dde5b9ad6 \
|
||||
--hash=sha256:da4813f751142436b075ed7aa012a8778aa43a99f7b36afe9b742d3ed8bdc95e \
|
||||
--hash=sha256:db2e408d983b0e61e238cf579c09ef7020560441906ca990fe8412153e3b291f \
|
||||
--hash=sha256:db98ad84a55eb09b3c32a96c576476777e87c520a34e2519d3e59c44710c002c \
|
||||
--hash=sha256:dbed418ba5c3dce92619656802cc5355cb679e58d0d89b50f116e4a9d5a9603e \
|
||||
--hash=sha256:dcdba5c86e368442528f7060039eda390cc4091bfd1dca41e8046af7c910dda8 \
|
||||
--hash=sha256:decbfa2f618fa8ed81c95ee18a387ff973143c656ef800c9f24fb7e9c16054e2 \
|
||||
--hash=sha256:e4fdb9275308292e880dcbeb12546df7f3e0f96c6b41197e0cf37d2826359020 \
|
||||
--hash=sha256:eb1b046be06b0fce7249f1d025cd359b4b80fc1c3e24ad9eca33e0dcdb2e4a35 \
|
||||
--hash=sha256:eb6e651000a19c96f452c85132811d25e9264d836951022d6e81df2fff38337d \
|
||||
--hash=sha256:ed867c42c268f876097248e05b6117a65bcd1e63b779e916fe2e33cd6fd0d3c3 \
|
||||
--hash=sha256:edfad1d29c73f9b863ebe7082ae9321374ccb10879eeabc84ba3b69f2579d537 \
|
||||
--hash=sha256:f2058f813d4f2b5e3a9eb2eb3faf8f1d99b81c3e51aeda4b168406443e8ba809 \
|
||||
--hash=sha256:f6b2d0c6703c988d334f297aa5df18c45e97b0af3679bb75059e0e0bd8b1069d \
|
||||
--hash=sha256:f8212564d49c50eb4565e502814f694e240c55551a5f1bc841d4fcaabb0a9b8a \
|
||||
--hash=sha256:ffa565331890b90056c01db69c0fe634a776f8019c143a5ae265f9c6bc4bd6d4
|
||||
yarl==1.9.2 ; python_version >= "3.10" and python_version < "4.0" \
|
||||
--hash=sha256:04ab9d4b9f587c06d801c2abfe9317b77cdf996c65a90d5e84ecc45010823571 \
|
||||
--hash=sha256:066c163aec9d3d073dc9ffe5dd3ad05069bcb03fcaab8d221290ba99f9f69ee3 \
|
||||
--hash=sha256:13414591ff516e04fcdee8dc051c13fd3db13b673c7a4cb1350e6b2ad9639ad3 \
|
||||
--hash=sha256:149ddea5abf329752ea5051b61bd6c1d979e13fbf122d3a1f9f0c8be6cb6f63c \
|
||||
--hash=sha256:159d81f22d7a43e6eabc36d7194cb53f2f15f498dbbfa8edc8a3239350f59fe7 \
|
||||
--hash=sha256:1b1bba902cba32cdec51fca038fd53f8beee88b77efc373968d1ed021024cc04 \
|
||||
--hash=sha256:22a94666751778629f1ec4280b08eb11815783c63f52092a5953faf73be24191 \
|
||||
--hash=sha256:2a96c19c52ff442a808c105901d0bdfd2e28575b3d5f82e2f5fd67e20dc5f4ea \
|
||||
--hash=sha256:2b0738fb871812722a0ac2154be1f049c6223b9f6f22eec352996b69775b36d4 \
|
||||
--hash=sha256:2c315df3293cd521033533d242d15eab26583360b58f7ee5d9565f15fee1bef4 \
|
||||
--hash=sha256:32f1d071b3f362c80f1a7d322bfd7b2d11e33d2adf395cc1dd4df36c9c243095 \
|
||||
--hash=sha256:3458a24e4ea3fd8930e934c129b676c27452e4ebda80fbe47b56d8c6c7a63a9e \
|
||||
--hash=sha256:38a3928ae37558bc1b559f67410df446d1fbfa87318b124bf5032c31e3447b74 \
|
||||
--hash=sha256:3da8a678ca8b96c8606bbb8bfacd99a12ad5dd288bc6f7979baddd62f71c63ef \
|
||||
--hash=sha256:494053246b119b041960ddcd20fd76224149cfea8ed8777b687358727911dd33 \
|
||||
--hash=sha256:50f33040f3836e912ed16d212f6cc1efb3231a8a60526a407aeb66c1c1956dde \
|
||||
--hash=sha256:52a25809fcbecfc63ac9ba0c0fb586f90837f5425edfd1ec9f3372b119585e45 \
|
||||
--hash=sha256:53338749febd28935d55b41bf0bcc79d634881195a39f6b2f767870b72514caf \
|
||||
--hash=sha256:5415d5a4b080dc9612b1b63cba008db84e908b95848369aa1da3686ae27b6d2b \
|
||||
--hash=sha256:5610f80cf43b6202e2c33ba3ec2ee0a2884f8f423c8f4f62906731d876ef4fac \
|
||||
--hash=sha256:566185e8ebc0898b11f8026447eacd02e46226716229cea8db37496c8cdd26e0 \
|
||||
--hash=sha256:56ff08ab5df8429901ebdc5d15941b59f6253393cb5da07b4170beefcf1b2528 \
|
||||
--hash=sha256:59723a029760079b7d991a401386390c4be5bfec1e7dd83e25a6a0881859e716 \
|
||||
--hash=sha256:5fcd436ea16fee7d4207c045b1e340020e58a2597301cfbcfdbe5abd2356c2fb \
|
||||
--hash=sha256:61016e7d582bc46a5378ffdd02cd0314fb8ba52f40f9cf4d9a5e7dbef88dee18 \
|
||||
--hash=sha256:63c48f6cef34e6319a74c727376e95626f84ea091f92c0250a98e53e62c77c72 \
|
||||
--hash=sha256:646d663eb2232d7909e6601f1a9107e66f9791f290a1b3dc7057818fe44fc2b6 \
|
||||
--hash=sha256:662e6016409828ee910f5d9602a2729a8a57d74b163c89a837de3fea050c7582 \
|
||||
--hash=sha256:674ca19cbee4a82c9f54e0d1eee28116e63bc6fd1e96c43031d11cbab8b2afd5 \
|
||||
--hash=sha256:6a5883464143ab3ae9ba68daae8e7c5c95b969462bbe42e2464d60e7e2698368 \
|
||||
--hash=sha256:6e7221580dc1db478464cfeef9b03b95c5852cc22894e418562997df0d074ccc \
|
||||
--hash=sha256:75df5ef94c3fdc393c6b19d80e6ef1ecc9ae2f4263c09cacb178d871c02a5ba9 \
|
||||
--hash=sha256:783185c75c12a017cc345015ea359cc801c3b29a2966c2655cd12b233bf5a2be \
|
||||
--hash=sha256:822b30a0f22e588b32d3120f6d41e4ed021806418b4c9f0bc3048b8c8cb3f92a \
|
||||
--hash=sha256:8288d7cd28f8119b07dd49b7230d6b4562f9b61ee9a4ab02221060d21136be80 \
|
||||
--hash=sha256:82aa6264b36c50acfb2424ad5ca537a2060ab6de158a5bd2a72a032cc75b9eb8 \
|
||||
--hash=sha256:832b7e711027c114d79dffb92576acd1bd2decc467dec60e1cac96912602d0e6 \
|
||||
--hash=sha256:838162460b3a08987546e881a2bfa573960bb559dfa739e7800ceeec92e64417 \
|
||||
--hash=sha256:83fcc480d7549ccebe9415d96d9263e2d4226798c37ebd18c930fce43dfb9574 \
|
||||
--hash=sha256:84e0b1599334b1e1478db01b756e55937d4614f8654311eb26012091be109d59 \
|
||||
--hash=sha256:891c0e3ec5ec881541f6c5113d8df0315ce5440e244a716b95f2525b7b9f3608 \
|
||||
--hash=sha256:8c2ad583743d16ddbdf6bb14b5cd76bf43b0d0006e918809d5d4ddf7bde8dd82 \
|
||||
--hash=sha256:8c56986609b057b4839968ba901944af91b8e92f1725d1a2d77cbac6972b9ed1 \
|
||||
--hash=sha256:8ea48e0a2f931064469bdabca50c2f578b565fc446f302a79ba6cc0ee7f384d3 \
|
||||
--hash=sha256:8ec53a0ea2a80c5cd1ab397925f94bff59222aa3cf9c6da938ce05c9ec20428d \
|
||||
--hash=sha256:95d2ecefbcf4e744ea952d073c6922e72ee650ffc79028eb1e320e732898d7e8 \
|
||||
--hash=sha256:9b3152f2f5677b997ae6c804b73da05a39daa6a9e85a512e0e6823d81cdad7cc \
|
||||
--hash=sha256:9bf345c3a4f5ba7f766430f97f9cc1320786f19584acc7086491f45524a551ac \
|
||||
--hash=sha256:a60347f234c2212a9f0361955007fcf4033a75bf600a33c88a0a8e91af77c0e8 \
|
||||
--hash=sha256:a74dcbfe780e62f4b5a062714576f16c2f3493a0394e555ab141bf0d746bb955 \
|
||||
--hash=sha256:a83503934c6273806aed765035716216cc9ab4e0364f7f066227e1aaea90b8d0 \
|
||||
--hash=sha256:ac9bb4c5ce3975aeac288cfcb5061ce60e0d14d92209e780c93954076c7c4367 \
|
||||
--hash=sha256:aff634b15beff8902d1f918012fc2a42e0dbae6f469fce134c8a0dc51ca423bb \
|
||||
--hash=sha256:b03917871bf859a81ccb180c9a2e6c1e04d2f6a51d953e6a5cdd70c93d4e5a2a \
|
||||
--hash=sha256:b124e2a6d223b65ba8768d5706d103280914d61f5cae3afbc50fc3dfcc016623 \
|
||||
--hash=sha256:b25322201585c69abc7b0e89e72790469f7dad90d26754717f3310bfe30331c2 \
|
||||
--hash=sha256:b7232f8dfbd225d57340e441d8caf8652a6acd06b389ea2d3222b8bc89cbfca6 \
|
||||
--hash=sha256:b8cc1863402472f16c600e3e93d542b7e7542a540f95c30afd472e8e549fc3f7 \
|
||||
--hash=sha256:b9a4e67ad7b646cd6f0938c7ebfd60e481b7410f574c560e455e938d2da8e0f4 \
|
||||
--hash=sha256:be6b3fdec5c62f2a67cb3f8c6dbf56bbf3f61c0f046f84645cd1ca73532ea051 \
|
||||
--hash=sha256:bf74d08542c3a9ea97bb8f343d4fcbd4d8f91bba5ec9d5d7f792dbe727f88938 \
|
||||
--hash=sha256:c027a6e96ef77d401d8d5a5c8d6bc478e8042f1e448272e8d9752cb0aff8b5c8 \
|
||||
--hash=sha256:c0c77533b5ed4bcc38e943178ccae29b9bcf48ffd1063f5821192f23a1bd27b9 \
|
||||
--hash=sha256:c1012fa63eb6c032f3ce5d2171c267992ae0c00b9e164efe4d73db818465fac3 \
|
||||
--hash=sha256:c3a53ba34a636a256d767c086ceb111358876e1fb6b50dfc4d3f4951d40133d5 \
|
||||
--hash=sha256:d4e2c6d555e77b37288eaf45b8f60f0737c9efa3452c6c44626a5455aeb250b9 \
|
||||
--hash=sha256:de119f56f3c5f0e2fb4dee508531a32b069a5f2c6e827b272d1e0ff5ac040333 \
|
||||
--hash=sha256:e65610c5792870d45d7b68c677681376fcf9cc1c289f23e8e8b39c1485384185 \
|
||||
--hash=sha256:e9fdc7ac0d42bc3ea78818557fab03af6181e076a2944f43c38684b4b6bed8e3 \
|
||||
--hash=sha256:ee4afac41415d52d53a9833ebae7e32b344be72835bbb589018c9e938045a560 \
|
||||
--hash=sha256:f364d3480bffd3aa566e886587eaca7c8c04d74f6e8933f3f2c996b7f09bee1b \
|
||||
--hash=sha256:f3b078dbe227f79be488ffcfc7a9edb3409d018e0952cf13f15fd6512847f3f7 \
|
||||
--hash=sha256:f4e2d08f07a3d7d3e12549052eb5ad3eab1c349c53ac51c209a0e5991bbada78 \
|
||||
--hash=sha256:f7a3d8146575e08c29ed1cd287068e6d02f1c7bdff8970db96683b9591b86ee7
|
||||
@@ -0,0 +1,24 @@
|
||||
import os
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
|
||||
def pytest_configure(config):
|
||||
load_dotenv(dotenv_path=".env")
|
||||
|
||||
token_var = "SPECKLE_TOKEN"
|
||||
server_var = "SPECKLE_SERVER_URL"
|
||||
token = os.getenv(token_var)
|
||||
server = os.getenv(server_var)
|
||||
|
||||
if not token:
|
||||
raise ValueError(f"Cannot run tests without a {token_var} environment variable")
|
||||
|
||||
if not server:
|
||||
raise ValueError(
|
||||
f"Cannot run tests without a {server_var} environment variable"
|
||||
)
|
||||
|
||||
# Set the token as an attribute on the config object
|
||||
config.SPECKLE_TOKEN = token
|
||||
config.SPECKLE_SERVER_URL = server
|
||||
|
||||
@@ -0,0 +1,181 @@
|
||||
"""Run integration tests with a speckle server."""
|
||||
import secrets
|
||||
import string
|
||||
|
||||
import pytest
|
||||
from gql import gql
|
||||
from speckle_automate import (
|
||||
AutomationRunData,
|
||||
AutomationStatus,
|
||||
run_function,
|
||||
AutomationContext,
|
||||
)
|
||||
from specklepy.api.client import SpeckleClient
|
||||
from specklepy.objects.base import Base
|
||||
|
||||
from main import FunctionInputs, automate_function, get_reference_model
|
||||
|
||||
|
||||
def crypto_random_string(length: int) -> str:
|
||||
"""Generate a semi crypto random string of a given length."""
|
||||
alphabet = string.ascii_letters + string.digits
|
||||
return "".join(secrets.choice(alphabet) for _ in range(length))
|
||||
|
||||
|
||||
def register_new_automation(
|
||||
project_id: str,
|
||||
model_id: str,
|
||||
speckle_client: SpeckleClient,
|
||||
automation_id: str,
|
||||
automation_name: str,
|
||||
automation_revision_id: str,
|
||||
):
|
||||
"""Register a new automation in the speckle server."""
|
||||
query = gql(
|
||||
"""
|
||||
mutation CreateAutomation(
|
||||
$projectId: String!
|
||||
$modelId: String!
|
||||
$automationName: String!
|
||||
$automationId: String!
|
||||
$automationRevisionId: String!
|
||||
) {
|
||||
automationMutations {
|
||||
create(
|
||||
input: {
|
||||
projectId: $projectId
|
||||
modelId: $modelId
|
||||
automationName: $automationName
|
||||
automationId: $automationId
|
||||
automationRevisionId: $automationRevisionId
|
||||
}
|
||||
)
|
||||
}
|
||||
}
|
||||
"""
|
||||
)
|
||||
params = {
|
||||
"projectId": project_id,
|
||||
"modelId": model_id,
|
||||
"automationName": automation_name,
|
||||
"automationId": automation_id,
|
||||
"automationRevisionId": automation_revision_id,
|
||||
}
|
||||
speckle_client.httpclient.execute(query, params)
|
||||
|
||||
|
||||
@pytest.fixture()
|
||||
def speckle_token(request) -> str:
|
||||
return request.config.SPECKLE_TOKEN
|
||||
|
||||
|
||||
@pytest.fixture()
|
||||
def speckle_server_url(request) -> str:
|
||||
"""Provide a speckle server url for the test suite, default to localhost."""
|
||||
return request.config.SPECKLE_SERVER_URL
|
||||
|
||||
|
||||
@pytest.fixture()
|
||||
def test_client(speckle_server_url: str, speckle_token: str) -> SpeckleClient:
|
||||
"""Initialize a SpeckleClient for testing."""
|
||||
test_client = SpeckleClient(
|
||||
speckle_server_url, speckle_server_url.startswith("https")
|
||||
)
|
||||
test_client.authenticate_with_token(speckle_token)
|
||||
return test_client
|
||||
|
||||
|
||||
@pytest.fixture()
|
||||
def test_object() -> Base:
|
||||
"""Create a Base model for testing."""
|
||||
root_object = Base()
|
||||
root_object.foo = "bar"
|
||||
return root_object
|
||||
|
||||
|
||||
@pytest.fixture()
|
||||
# fixture to mock the AutomationRunData that would be generated by a full Automation Run
|
||||
def fake_automation_run_data(request, test_client: SpeckleClient) -> AutomationRunData:
|
||||
server_url = request.config.SPECKLE_SERVER_URL
|
||||
project_id = "4f064f09e6"
|
||||
model_id = "5a16cf52af"
|
||||
|
||||
function_name = "Clash Test"
|
||||
|
||||
automation_id = crypto_random_string(10)
|
||||
automation_name = "Local Test Automation"
|
||||
automation_revision_id = crypto_random_string(10)
|
||||
|
||||
register_new_automation(
|
||||
project_id,
|
||||
model_id,
|
||||
test_client,
|
||||
automation_id,
|
||||
automation_name,
|
||||
automation_revision_id,
|
||||
)
|
||||
|
||||
fake_run_data = AutomationRunData(
|
||||
project_id=project_id,
|
||||
model_id=model_id,
|
||||
branch_name="main",
|
||||
version_id="2b16327448",
|
||||
speckle_server_url=server_url,
|
||||
# These ids would be available with a valid registered Automation definition.
|
||||
automation_id=automation_id,
|
||||
automation_revision_id=automation_revision_id,
|
||||
automation_run_id=crypto_random_string(12),
|
||||
# These ids would be available with a valid registered Function definition. Can also be faked.
|
||||
function_id="12345",
|
||||
function_name=function_name,
|
||||
function_logo=None,
|
||||
)
|
||||
|
||||
return fake_run_data
|
||||
|
||||
|
||||
def test_function_run(fake_automation_run_data: AutomationRunData, speckle_token: str):
|
||||
"""Run an integration test for the automate function."""
|
||||
context = AutomationContext.initialize(fake_automation_run_data, speckle_token)
|
||||
|
||||
automate_sdk = run_function(
|
||||
context,
|
||||
automate_function,
|
||||
FunctionInputs(
|
||||
tolerance=0.1, tolerance_unit="mm", static_model_name="structural"
|
||||
),
|
||||
)
|
||||
|
||||
assert automate_sdk.run_status == AutomationStatus.SUCCEEDED
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def context(fake_automation_run_data: AutomationRunData, speckle_token: str):
|
||||
return AutomationContext.initialize(fake_automation_run_data, speckle_token)
|
||||
|
||||
|
||||
def test_non_existent_model(context, test_client: SpeckleClient):
|
||||
with pytest.raises(
|
||||
Exception, match="The static model named does not exist, skipping the function."
|
||||
):
|
||||
get_reference_model(context, "Fake Name")
|
||||
|
||||
|
||||
def test_model_with_no_versions(context, test_client: SpeckleClient):
|
||||
with pytest.raises(
|
||||
Exception, match="The static model has no versions, skipping the function."
|
||||
):
|
||||
get_reference_model(context, "blank")
|
||||
|
||||
|
||||
def test_same_as_changed_model(context, test_client: SpeckleClient):
|
||||
with pytest.raises(
|
||||
Exception,
|
||||
match="The static model is the same as the changed model, skipping the function.",
|
||||
):
|
||||
get_reference_model(context, "hvac")
|
||||
|
||||
|
||||
def test_valid_reference_model(context, test_client: SpeckleClient):
|
||||
reference_model = get_reference_model(context, "structural")
|
||||
assert reference_model is not None
|
||||
Reference in New Issue
Block a user