devcontainer setup
This commit is contained in:
Gergő Jedlicska
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// For format details, see https://aka.ms/devcontainer.json. For config options, see the
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// README at: https://github.com/devcontainers/templates/tree/main/src/python
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{
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"name": "Python 3",
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// Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile
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"image": "mcr.microsoft.com/devcontainers/python:1-3.11-bullseye",
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"features": {
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"ghcr.io/devcontainers-contrib/features/poetry:2": {}
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},
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"remoteEnv": {
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"SPECKLE_TOKEN": "foobar"
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},
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"containerEnv": {
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"SPECKLE_TOKEN": "asdfasdf"
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},
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// Features to add to the dev container. More info: https://containers.dev/features.
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// "features": {},
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// Use 'forwardPorts' to make a list of ports inside the container available locally.
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// "forwardPorts": [],
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// Use 'postCreateCommand' to run commands after the container is created.
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"postCreateCommand": "cp .env.example .env && POETRY_VIRTUALENVS_IN_PROJECT=true poetry install --no-root",
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// Configure tool-specific properties.
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"customizations": {
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"vscode": {
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// Add the IDs of extensions you want installed when the container is created.
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"extensions": [
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"ms-python.vscode-pylance",
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"ms-python.python",
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"ms-python.black-formatter",
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"streetsidesoftware.code-spell-checker",
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"mikestead.dotenv"
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]
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}
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}
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// Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
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// "remoteUser": "root"
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}
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@@ -0,0 +1 @@
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SPECKLE_TOKEN=mytoken
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Vendored
+11
-5
@@ -5,12 +5,18 @@
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"version": "0.2.0",
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"configurations": [
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{
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"name": "Python: Current File",
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"name": "Speckle Automate function",
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"type": "python",
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"request": "launch",
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"program": "${file}",
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"program": "main.py",
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"console": "integratedTerminal",
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"justMyCode": false
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}
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"justMyCode": true,
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"envFile": "${workspaceFolder}/.env",
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"args": [
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"{\"projectId\": \"843d07eb10\", \"modelId\": \"base design\", \"versionId\": \"2a32ccfee1\", \"speckleServerUrl\": \"https://latest.speckle.systems\"}",
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// make sure to use camelCase for variable names
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"{\"speckleTypeToCount\": \"Objects.Geometry.Brep\"}"
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],
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},
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]
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}
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}
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Vendored
+7
-1
@@ -1,3 +1,9 @@
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{
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"cSpell.words": ["camelcase", "pydantic", "stringcase", "typer"]
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"cSpell.words": [
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"camelcase",
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"pydantic",
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"stringcase",
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"typer"
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],
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"python.defaultInterpreterPath": ".venv/bin/python"
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}
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@@ -0,0 +1,45 @@
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from pydantic import BaseModel, ConfigDict
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from stringcase import camelcase
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from specklepy.transports.memory import MemoryTransport
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from specklepy.transports.server import ServerTransport
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from specklepy.api.operations import receive
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from specklepy.api.client import SpeckleClient
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from flatten import flatten_base
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from speckle_project_data import SpeckleProjectData
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class FunctionInputs(BaseModel):
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"""
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These are function author defined values, automate will make sure to supply them.
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"""
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speckle_type_to_count: str
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model_config = ConfigDict(alias_generator=camelcase)
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def automate_function(
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project_data: SpeckleProjectData,
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function_inputs: FunctionInputs,
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speckle_token: str,
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):
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client = SpeckleClient(project_data.speckle_server_url)
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client.authenticate_with_token(speckle_token)
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commit = client.commit.get(project_data.project_id, project_data.version_id)
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memory_transport = MemoryTransport()
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server_transport = ServerTransport(project_data.project_id, client)
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if not commit.referencedObject:
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raise ValueError("The commit has no root referencedObject.")
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base = receive(commit.referencedObject, server_transport, memory_transport)
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count = 0
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for b in flatten_base(base):
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if b.speckle_type == function_inputs.speckle_type_to_count:
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count += 1
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print(
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f"Found {count} object that match the queried speckle type: ",
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"{function_inputs.speckle_type_to_count}",
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)
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+2
-2
@@ -4,6 +4,6 @@ from specklepy.objects import Base
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def flatten_base(base: Base) -> Iterable[Base]:
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if hasattr(base, "elements"):
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for element in base.elements:
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for element in base["elements"]:
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yield from flatten_base(element)
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yield base
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yield base
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@@ -1,68 +1,17 @@
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import typer
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from pydantic import BaseModel, ConfigDict
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from stringcase import camelcase
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from specklepy.transports.memory import MemoryTransport
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from specklepy.transports.server import ServerTransport
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from specklepy.api.operations import receive
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from specklepy.api.client import SpeckleClient
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import random
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from flatten import flatten_base
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from make_comment import make_comment
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import os
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from speckle_project_data import SpeckleProjectData
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from automate_function import FunctionInputs, automate_function
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class SpeckleProjectData(BaseModel):
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"""Values of the project / model that triggered the run of this function."""
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def main(speckle_project_data: str, function_inputs: str, speckle_token: str = ""):
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speckle_token = speckle_token if speckle_token else os.environ.get("SPECKLE_TOKEN")
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if not speckle_token:
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raise ValueError("The supplied speckle token is not valid")
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project_id: str
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model_id: str
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version_id: str
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speckle_server_url: str
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model_config = ConfigDict(alias_generator=camelcase, protected_namespaces=())
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class FunctionInputs(BaseModel):
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"""
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These are function author defined values, automate will make sure to supply them.
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"""
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comment_text: str
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class Config:
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alias_generator = camelcase
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def main(speckle_project_data: str, function_inputs: str, speckle_token: str):
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project_data = SpeckleProjectData.model_validate_json(speckle_project_data)
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inputs = FunctionInputs.model_validate_json(function_inputs)
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client = SpeckleClient(project_data.speckle_server_url, use_ssl=False)
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client.authenticate_with_token(speckle_token)
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commit = client.commit.get(project_data.project_id, project_data.version_id)
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branch = client.branch.get(project_data.project_id, project_data.model_id, 1)
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memory_transport = MemoryTransport()
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server_transport = ServerTransport(project_data.project_id, client)
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base = receive(commit.referencedObject, server_transport, memory_transport)
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random_beam = random.choice(
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[b for b in flatten_base(base) if b.speckle_type == "IFCBEAM"]
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)
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make_comment(
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client,
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project_data.project_id,
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branch.id,
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project_data.version_id,
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inputs.comment_text,
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random_beam.id,
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)
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print(
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"Ran function with",
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f"{speckle_project_data} {function_inputs}",
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)
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automate_function(project_data, inputs, speckle_token)
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if __name__ == "__main__":
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-103
@@ -1,103 +0,0 @@
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from specklepy.api.client import SpeckleClient
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from gql import gql
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def make_comment(
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client: SpeckleClient,
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project_id: str,
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model_id: str,
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version_id: str,
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comment_text: str,
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selected_object_id: str,
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) -> None:
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client.httpclient.execute(
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gql(
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"""
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mutation createComment($input: CreateCommentInput!) {
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commentMutations {
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create(input: $input) {
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id
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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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"input": {
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"content": {
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"blobIds": [],
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"doc": {
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"content": [
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{
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"content": [{"text": comment_text, "type": "text"}],
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"type": "paragraph",
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}
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],
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"type": "doc",
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},
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},
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"projectId": project_id,
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"resourceIdString": model_id,
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"screenshot": None,
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"viewerState": {
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"projectId": project_id,
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"resources": {
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"request": {
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"resourceIdString": f"{model_id}@{version_id}",
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"threadFilters": {},
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}
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},
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"sessionId": "fooobarbaz",
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"ui": {
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"camera": {
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"isOrthoProjection": False,
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"position": [
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-13.959975903859306,
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109.21340462426888,
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19.00868018548827,
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],
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"target": [
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-28.304303646087646,
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99.69336318969727,
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2.3997000455856323,
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],
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"zoom": 1,
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},
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"explodeFactor": 0,
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"filters": {
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"hiddenObjectIds": [],
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"isolatedObjectIds": [selected_object_id],
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"propertyFilter": {"isApplied": False, "key": None},
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"selectedObjectIds": [selected_object_id],
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},
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"lightConfig": {
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"azimuth": 0.75,
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"castShadow": True,
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"color": 16777215,
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"elevation": 1.33,
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"enabled": True,
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"indirectLightIntensity": 1.2,
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"intensity": 5,
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"radius": 0,
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"shadowcatcher": True,
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},
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"sectionBox": None,
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"selection": [
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-31.355755138199026,
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101.06821903317298,
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4.250507316347136,
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],
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"spotlightUserSessionId": None,
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"threads": {
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"openThread": {
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"isTyping": False,
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"newThreadEditor": True,
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"threadId": None,
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}
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},
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},
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"viewer": {"metadata": {"filteringState": {}}},
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},
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}
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},
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)
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@@ -0,0 +1,13 @@
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from pydantic import BaseModel, ConfigDict
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from stringcase import camelcase
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class SpeckleProjectData(BaseModel):
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"""Values of the project / model that triggered the run of this function."""
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project_id: str
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model_id: str
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version_id: str
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speckle_server_url: str
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model_config = ConfigDict(alias_generator=camelcase, protected_namespaces=())
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