ci(github action): use Speckle's GitHub Composite Action

.devcontainer/devcontainer.json

@@ -1,40 +0,0 @@
-// For format details, see https://aka.ms/devcontainer.json. For config options, see the
-// README at: https://github.com/devcontainers/templates/tree/main/src/python
-{
-  "name": "Python 3",
-  // Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile
-  "image": "mcr.microsoft.com/devcontainers/python:1-3.11-bullseye",
-
-  "remoteEnv": {
-    "SPECKLE_TOKEN": "foobar"
-  },
-  "containerEnv": {
-    "SPECKLE_TOKEN": "asdfasdf"
-  },
-
-  // Features to add to the dev container. More info: https://containers.dev/features.
-  // "features": {},
-
-  // Use 'forwardPorts' to make a list of ports inside the container available locally.
-  // "forwardPorts": [],
-
-  // Use 'postCreateCommand' to run commands after the container is created.
-  "postCreateCommand": "cp .env.example .env && python -m venv .venv && . .venv/bin/activate && pip install --upgrade pip && pip install .[dev]",
-
-  // Configure tool-specific properties.
-  "customizations": {
-    "vscode": {
-      // Add the IDs of extensions you want installed when the container is created.
-      "extensions": [
-        "ms-python.vscode-pylance",
-        "ms-python.python",
-        "ms-python.black-formatter",
-        "streetsidesoftware.code-spell-checker",
-        "mikestead.dotenv"
-      ]
-    }
-  }
-
-  // Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
-  // "remoteUser": "root"
-}

.env.example

@@ -1,4 +0,0 @@
-SPECKLE_TOKEN="mytoken"
-SPECKLE_SERVER_URL="http://127.0.0.1:3000"
-SPECKLE_PROJECT_ID=""
-SPECKLE_AUTOMATION_ID=""

.github/dependabot.yml

@@ -1,10 +0,0 @@
-version: 2
-updates:
-  - package-ecosystem: "github-actions"
-    directory: "/"
-    schedule:
-      interval: "daily"
-  - package-ecosystem: "pip"
-    directory: "/"
-    schedule:
-      interval: "weekly"

.github/workflows/main.yml

@@ -1,32 +1,41 @@
-name: "build and deploy Speckle functions"
-on:
-  workflow_dispatch:
+name: 'build and deploy Speckle functions'
+on: # rebuild any PRs and any branch changes
+  pull_request:
   push:
-    tags:
-      - "*"
+    branches:
+      - main
 
 jobs:
   publish-automate-function-version: # make sure the action works on a clean machine without building
-    env:
-      FUNCTION_SCHEMA_FILE_NAME: functionSchema.json
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v5.0.0
-      - uses: actions/setup-python@v5
+      - uses: actions/checkout@v3.4.0
+      - uses: actions/checkout@v3.4.0
         with:
-          python-version: "3.13"
-      - name: Install dependencies
-        run: |
-          pip install .[dev]
+          repository: 'specklesystems/speckle-automate-github-composite-action'
+          path: 'github-action'
+          ref: main
+
+      - uses: actions/setup-python@v4
+        with:
+          python-version: '3.11'
+      - name: Install and configure Poetry
+        uses: snok/install-poetry@v1
+        with:
+          version: 1.3.2
+          virtualenvs-create: false
+          virtualenvs-in-project: false
+          installer-parallel: true
+      - name: Restore dependencies
+        run: poetry install --no-root
       - name: Extract functionInputSchema
-        id: extract_schema
         run: |
-          python main.py generate_schema ${HOME}/${{ env.FUNCTION_SCHEMA_FILE_NAME }}
-      - name: Speckle Automate Function - Build and Publish
-        uses: specklesystems/speckle-automate-github-composite-action@0.8.1
+          echo "function_input_schema=$(python schema_generation.py)" >> "$GITHUB_ENV"
+      - uses: ./github-action
+        id: function_publish
         with:
-          speckle_automate_url: ${{ env.SPECKLE_AUTOMATE_URL || vars.SPECKLE_AUTOMATE_URL || 'https://automate.speckle.dev' }}
-          speckle_token: ${{ secrets.SPECKLE_FUNCTION_TOKEN }}
-          speckle_function_id: ${{ secrets.SPECKLE_FUNCTION_ID }}
-          speckle_function_input_schema_file_path: ${{ env.FUNCTION_SCHEMA_FILE_NAME }}
-          speckle_function_command: "python -u main.py run"
+          speckle_server_url: 'https://automate.speckle.dev'
+          speckle_token: ${{ secrets.SPECKLE_AUTOMATE_FUNCTION_PUBLISH_TOKEN }}
+          speckle_function_id: ${{ secrets.SPECKLE_AUTOMATE_FUNCTION_ID }}
+          speckle_function_input_schema: ${{ env.function_input_schema }}
+          speckle_function_command: 'python main.py'

.gitignore

@@ -1,13 +1,6 @@
 # Created by https://www.toptal.com/developers/gitignore/api/visualstudiocode,python,pycharm
 # Edit at https://www.toptal.com/developers/gitignore?templates=visualstudiocode,python,pycharm
 
-function_inputs.json
-
-**/.env
-**/.envrc
-
-**/.tool-versions
-
 ### PyCharm ###
 # Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio, WebStorm and Rider
 # Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839

.tool-versions

@@ -0,0 +1 @@
+python 3.11.0

.vscode/launch.json

@@ -5,14 +5,12 @@
   "version": "0.2.0",
   "configurations": [
     {
-      "name": "Speckle Automate function",
-      "type": "debugpy",
+      "name": "Python: Current File",
+      "type": "python",
       "request": "launch",
-      "program": "main.py",
+      "program": "${file}",
       "console": "integratedTerminal",
-      "justMyCode": true,
-      "envFile": "${workspaceFolder}/.env",
-      "args": ["run", "function_inputs.json"]
+      "justMyCode": false
     }
   ]
-}
+}

.vscode/settings.json

@@ -1,9 +1,3 @@
 {
-  "cSpell.words": [
-    "camelcase",
-    "pydantic",
-    "stringcase",
-    "typer"
-  ],
-  "python.defaultInterpreterPath": ".venv/bin/python"
+  "cSpell.words": ["camelcase", "pydantic", "stringcase", "typer"]
 }

Dockerfile

@@ -1,16 +1,7 @@
-# We use the official Python 3.11 image as our base image and will add our code to it. For more details, see https://hub.docker.com/_/python
-FROM python:3.13-slim
+FROM python:3.11-slim
 
-# We set the working directory to be the /home/speckle directory; all of our files will be copied here.
-WORKDIR /home/speckle
+RUN pip install poetry
 
-# Copy pyproject.toml first to leverage Docker layer caching
-COPY pyproject.toml /home/speckle/
-
-# Install the required Python packages (production dependencies only)
-RUN pip install --no-cache-dir .
-
-# Copy all of our code and assets from the local directory into the /home/speckle directory of the container.
-# We also ensure that the user 'speckle' owns these files, so it can access them
-# This assumes that the Dockerfile is in the same directory as the rest of the code
-COPY . /home/speckle
+COPY . .
+RUN poetry export -f requirements.txt --output requirements.txt && pip install -r requirements.txt
+# RUN poetry install --no-root --no-dev

LICENSE

@@ -1,208 +0,0 @@
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-   with us via [email](mailto:hello@speckle.systems).

README.md

@@ -1,174 +1 @@
-# Speckle Automate function template - Python
-
-This template repository is for a Speckle Automate function written in Python
-using the [specklepy](https://pypi.org/project/specklepy/) SDK to interact with Speckle data.
-
-This template contains the full scaffolding required to publish a function to the Automate environment.
-It also has some sane defaults for development environment setups.
-
-## Getting started
-
-1. Use this template repository to create a new repository in your own / organization's profile.
-1. Register the function
-
-### Add new dependencies
-
-To add new Python package dependencies to the project, edit the `pyproject.toml` file:
-
-**For packages your function needs to run** (like pandas, requests, etc.):
-```toml
-dependencies = [
-    "specklepy==3.0.0",
-    "pandas==2.1.0",  # Add production dependencies here
-]
-```
-
-**For development tools** (like testing or formatting tools):
-```toml
-[project.optional-dependencies]
-dev = [
-    "black==23.12.1",
-    "pytest-mock==3.11.1",  # Add development dependencies here
-    # ... other dev tools
-]
-```
-
-**How to decide which section?**
-- If your `main.py` (or other function logic) imports it → `dependencies`
-- If it's just a tool to help you code → `[project.optional-dependencies].dev`
-
-Example:
-```python
-# In your main.py
-import pandas as pd  # ← This goes in dependencies
-import specklepy     # ← This goes in dependencies
-
-# You won't import these in main.py:
-# pytest, black, mypy ← These go in [project.optional-dependencies].dev
-```
-
-### Change launch variables
-
-Describe how the launch.json should be edited.
-
-### GitHub Codespaces
-
-Create a new repo from this template, and use the create new code.
-
-### 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 deployed Speckle Function.
-1. Enter a phrase to use in the comment.
-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.
-1. Make changes to your Function in `main.py`. See below for the Developer Requirements and instructions on how to test.
-1. To create a new version of your Function, create a new [GitHub release](https://docs.github.com/en/repositories/releasing-projects-on-github/managing-releases-in-a-repository) in your repository.
-
-## Developer Requirements
-
-1. Install the following:
-    - [Python 3.11+](https://www.python.org/downloads/)
-1. Run the following to set up your development environment:
-    ```bash
-    python -m venv .venv
-    # On Windows
-    .venv\Scripts\activate
-    # On macOS/Linux
-    source .venv/bin/activate
-
-    pip install --upgrade pip
-    pip install .[dev]
-    ```
-
-**What this installs:**
-- All the packages your function needs to run (`dependencies`)
-- Plus development tools like testing and code formatting (`[project.optional-dependencies].dev`)
-
-**Why separate sections?**
-- `dependencies`: Only what gets deployed with your function (lightweight)
-- `dev` dependencies: Extra tools to help you write better code locally
-
-## Building and Testing
-
-The code can be tested locally by running `pytest`.
-
-### Alternative dependency managers
-
-This template uses the modern **PEP 621** standard in `pyproject.toml`, which works with all modern Python dependency managers:
-
-#### Using Poetry
-```bash
-poetry install  # Automatically reads pyproject.toml
-```
-
-#### Using uv
-```bash
-uv sync  # Automatically reads pyproject.toml
-```
-
-#### Using pip-tools
-```bash
-pip-compile pyproject.toml  # Generate requirements.txt from pyproject.toml
-pip install -r requirements.txt
-```
-
-#### Using pdm
-```bash
-pdm install  # Automatically reads pyproject.toml
-```
-
-**Advantage**: All tools read the same `pyproject.toml` file, so there's no need to keep multiple files in sync!
-
-### Building and running the Docker Container Image
-
-Running and testing your code on your machine is a great way to develop your Function; the following instructions are a bit more in-depth and only required if you are having issues with your Function in GitHub Actions or on Speckle Automate.
-
-#### Building the Docker Container Image
-
-The GitHub Action packages your code into the format required by Speckle Automate. This is done by building a Docker Image, which Speckle Automate runs. You can attempt to build the Docker Image locally to test the building process.
-
-To build the Docker Container Image, you must have [Docker](https://docs.docker.com/get-docker/) installed.
-
-Once you have Docker running on your local machine:
-
-1. Open a terminal
-1. Navigate to the directory in which you cloned this repository
-1. Run the following command:
-
-    ```bash
-    docker build -f ./Dockerfile -t speckle_automate_python_example .
-    ```
-
-#### Running the Docker Container Image
-
-Once the GitHub Action has built the image, it is sent to Speckle Automate. When Speckle Automate runs your Function as part of an Automation, it will run the Docker Container Image. You can test that your Docker Container Image runs correctly locally.
-
-1. To then run the Docker Container Image, run the following command:
-
-    ```bash
-    docker run --rm speckle_automate_python_example \
-    python -u main.py run \
-    '{"projectId": "1234", "modelId": "1234", "branchName": "myBranch", "versionId": "1234", "speckleServerUrl": "https://speckle.xyz", "automationId": "1234", "automationRevisionId": "1234", "automationRunId": "1234", "functionId": "1234", "functionName": "my function", "functionLogo": "base64EncodedPng"}' \
-    '{}' \
-    yourSpeckleServerAuthenticationToken
-    ```
-
-Let's explain this in more detail:
-
-`docker run—-rm speckle_automate_python_example` tells Docker to run the Docker Container Image we built earlier. `speckle_automate_python_example` is the name of the Docker Container Image. The `--rm` flag tells Docker to remove the container after it has finished running, freeing up space on your machine.
-
-The line `python -u main.py run` is the command run inside the Docker Container Image. The rest of the command is the arguments passed to the command. The arguments are:
-
-- `'{"projectId": "1234", "modelId": "1234", "branchName": "myBranch", "versionId": "1234", "speckleServerUrl": "https://speckle.xyz", "automationId": "1234", "automationRevisionId": "1234", "automationRunId": "1234", "functionId": "1234", "functionName": "my function", "functionLogo": "base64EncodedPng"}'` - the metadata that describes the automation and the function.
-- `{}` - the input parameters for the function the Automation creator can set. Here, they are blank, but you can add your parameters to test your function.
-- `yourSpeckleServerAuthenticationToken`—the authentication token for the Speckle Server that the Automation can connect to. This is required to interact with the Speckle Server, for example, to get data from the Model.
-
-## Resources
-
-- [Learn](https://speckle.guide/dev/python.html) more about SpecklePy and interacting with Speckle from Python.
+# Go Automate Go

example.function_inputs.json

@@ -1,20 +0,0 @@
-{
-  "speckleToken": "YOUR SPEKCLE TOKEN",
-  "functionInputs": {
-    "whisperMessage": "you are doing something weird",
-    "forbiddenSpeckleType": "wall"
-  },
-  "automationRunData": {
-    "project_id": "project id",
-    "speckle_server_url": "https://latest.speckle.systems",
-    "automation_id": "automation id",
-    "automation_run_id": "automation run id",
-    "function_run_id": "function run id",
-    "triggers": [
-      {
-        "payload": { "modelId": "model id", "versionId": "version id" },
-        "triggerType": "versionCreation"
-      }
-    ]
-  }
-}

flatten.py

@@ -1,27 +1,9 @@
-"""Helper module for a simple speckle object tree flattening."""
-
-from collections.abc import Iterable
-
+from typing import Iterable
 from specklepy.objects import Base
 
 
 def flatten_base(base: Base) -> Iterable[Base]:
-    """Flatten a base object into an iterable of bases.
-
-    This function recursively traverses the `elements` or `@elements` attribute of the
-    base object, yielding each nested base object.
-
-    Args:
-        base (Base): The base object to flatten.
-
-    Yields:
-        Base: Each nested base object in the hierarchy.
-    """
-    # Attempt to get the elements attribute, fallback to @elements if necessary
-    elements = getattr(base, "elements", getattr(base, "@elements", None))
-
-    if elements is not None:
-        for element in elements:
+    if hasattr(base, "elements"):
+        for element in base.elements:
             yield from flatten_base(element)
-
-    yield base
+    yield base

main.py

@@ -1,103 +1,75 @@
-"""This module contains the function's business logic.
-
-Use the automation_context module to wrap your function in an Automate context helper.
-"""
-
-from pydantic import Field, SecretStr
-from speckle_automate import (
-    AutomateBase,
-    AutomationContext,
-    execute_automate_function,
-)
+import typer
+from pydantic import BaseModel
+from stringcase import camelcase
+from specklepy.transports.memory import MemoryTransport
+from specklepy.transports.server import ServerTransport
+from specklepy.api.operations import receive
+from specklepy.api.client import SpeckleClient
+import random
 
 from flatten import flatten_base
+from make_comment import make_comment
 
 
-class FunctionInputs(AutomateBase):
-    """These are function author-defined values.
+class SpeckleProjectData(BaseModel):
+    """Values of the project / model that triggered the run of this function."""
 
-    Automate will make sure to supply them matching the types specified here.
-    Please use the pydantic model schema to define your inputs:
-    https://docs.pydantic.dev/latest/usage/models/
+    project_id: str
+    model_id: str
+    version_id: str
+    speckle_server_url: str
+
+    class Config:
+        alias_generator = camelcase
+
+
+class FunctionInputs(BaseModel):
+    """
+    These are function author defined values, automate will make sure to supply them.
     """
 
-    # An example of how to use secret values.
-    whisper_message: SecretStr = Field(title="This is a secret message")
-    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."
-        ),
+    comment_text: str
+
+    class Config:
+        alias_generator = camelcase
+
+
+def main(speckle_project_data: str, function_inputs: str, speckle_token: str):
+    project_data = SpeckleProjectData.parse_raw(speckle_project_data)
+    inputs = FunctionInputs.parse_raw(function_inputs)
+
+    client = SpeckleClient(project_data.speckle_server_url, use_ssl=False)
+    client.authenticate_with_token(speckle_token)
+    commit = client.commit.get(project_data.project_id, project_data.version_id)
+    branch = client.branch.get(project_data.project_id, project_data.model_id, 1)
+
+    memory_transport = MemoryTransport()
+    server_transport = ServerTransport(project_data.project_id, client)
+    base = receive(commit.referencedObject, server_transport, memory_transport)
+
+    random_beam = random.choice(
+        [b for b in flatten_base(base) if b.speckle_type == "IFCBEAM"]
+    )
+
+    make_comment(
+        client,
+        project_data.project_id,
+        branch.id,
+        project_data.version_id,
+        inputs.comment_text,
+        random_beam.id,
+    )
+
+    print(
+        "Ran function with",
+        f"{speckle_project_data} {function_inputs}",
     )
 
 
-def automate_function(
-    automate_context: AutomationContext,
-    function_inputs: FunctionInputs,
-) -> None:
-    """This is an example Speckle Automate function.
-
-    Args:
-        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 convenient methods for attaching results to the Speckle model.
-        function_inputs: An instance object matching the defined schema.
-    """
-    # The context provides a convenient way to receive the triggering version.
-    version_root_object = automate_context.receive_version()
-
-    objects_with_forbidden_speckle_type = [
-        b
-        for b in flatten_base(version_root_object)
-        if b.speckle_type == function_inputs.forbidden_speckle_type
-    ]
-    count = len(objects_with_forbidden_speckle_type)
-
-    if count > 0:
-        # This is how a run is marked with a failure cause.
-        automate_context.attach_error_to_objects(
-            category="Forbidden speckle_type"
-            f" ({function_inputs.forbidden_speckle_type})",
-            affected_objects=objects_with_forbidden_speckle_type,
-            message="This project should not contain the type: "
-            f"{function_inputs.forbidden_speckle_type}",
-        )
-        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}"
-        )
-
-        # Set the automation context view to the original model/version view
-        # to show the offending objects.
-        automate_context.set_context_view()
-
-    else:
-        automate_context.mark_run_success("No forbidden types found.")
-
-    # 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")
-
-
-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.
-    """
-    pass
-
-
-# make sure to call the function with the executor
 if __name__ == "__main__":
-    # NOTE: always pass in the automate function by its reference; do not invoke it!
-
-    # Pass in the function reference with the inputs schema to the executor.
-    execute_automate_function(automate_function, FunctionInputs)
-
-    # If the function has no arguments, the executor can handle it like so
-    # execute_automate_function(automate_function_without_inputs)
+    # main(
+    #     '{"projectId":"bbb3aba8d4", "modelId":"automateTest", "versionId": "d37ee808db", "speckleServerUrl": "http://hyperion:3000" }',
+    #     '{"commentText": "automate made me to do this"}',
+    #     "c3e6536e570a94e5d84590c51b29198b26dce89439",
+    # )
+    typer.run(main)

make_comment.py

@@ -0,0 +1,103 @@
+from specklepy.api.client import SpeckleClient
+from gql import gql
+
+
+def make_comment(
+    client: SpeckleClient,
+    project_id: str,
+    model_id: str,
+    version_id: str,
+    comment_text: str,
+    selected_object_id: str,
+) -> None:
+    client.httpclient.execute(
+        gql(
+            """
+            mutation createComment($input: CreateCommentInput!) {
+                commentMutations {
+                    create(input: $input) {
+                    id
+                    }
+                }
+            }
+        """
+        ),
+        {
+            "input": {
+                "content": {
+                    "blobIds": [],
+                    "doc": {
+                        "content": [
+                            {
+                                "content": [{"text": comment_text, "type": "text"}],
+                                "type": "paragraph",
+                            }
+                        ],
+                        "type": "doc",
+                    },
+                },
+                "projectId": project_id,
+                "resourceIdString": model_id,
+                "screenshot": None,
+                "viewerState": {
+                    "projectId": project_id,
+                    "resources": {
+                        "request": {
+                            "resourceIdString": f"{model_id}@{version_id}",
+                            "threadFilters": {},
+                        }
+                    },
+                    "sessionId": "fooobarbaz",
+                    "ui": {
+                        "camera": {
+                            "isOrthoProjection": False,
+                            "position": [
+                                -13.959975903859306,
+                                109.21340462426888,
+                                19.00868018548827,
+                            ],
+                            "target": [
+                                -28.304303646087646,
+                                99.69336318969727,
+                                2.3997000455856323,
+                            ],
+                            "zoom": 1,
+                        },
+                        "explodeFactor": 0,
+                        "filters": {
+                            "hiddenObjectIds": [],
+                            "isolatedObjectIds": [selected_object_id],
+                            "propertyFilter": {"isApplied": False, "key": None},
+                            "selectedObjectIds": [selected_object_id],
+                        },
+                        "lightConfig": {
+                            "azimuth": 0.75,
+                            "castShadow": True,
+                            "color": 16777215,
+                            "elevation": 1.33,
+                            "enabled": True,
+                            "indirectLightIntensity": 1.2,
+                            "intensity": 5,
+                            "radius": 0,
+                            "shadowcatcher": True,
+                        },
+                        "sectionBox": None,
+                        "selection": [
+                            -31.355755138199026,
+                            101.06821903317298,
+                            4.250507316347136,
+                        ],
+                        "spotlightUserSessionId": None,
+                        "threads": {
+                            "openThread": {
+                                "isTyping": False,
+                                "newThreadEditor": True,
+                                "threadId": None,
+                            }
+                        },
+                    },
+                    "viewer": {"metadata": {"filteringState": {}}},
+                },
+            }
+        },
+    )

mise.toml

@@ -1,2 +0,0 @@
-[tools]
-python = '3.13'

poetry.lock

@@ -0,0 +1,997 @@
+# This file is automatically @generated by Poetry and should not be changed by hand.
+
+[[package]]
+name = "appdirs"
+version = "1.4.4"
+description = "A small Python module for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
+category = "main"
+optional = false
+python-versions = "*"
+files = [
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+    {file = "appdirs-1.4.4.tar.gz", hash = "sha256:7d5d0167b2b1ba821647616af46a749d1c653740dd0d2415100fe26e27afdf41"},
+]
+
+[[package]]
+name = "backoff"
+version = "2.2.1"
+description = "Function decoration for backoff and retry"
+category = "main"
+optional = false
+python-versions = ">=3.7,<4.0"
+files = [
+    {file = "backoff-2.2.1-py3-none-any.whl", hash = "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"},
+    {file = "backoff-2.2.1.tar.gz", hash = "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba"},
+]
+
+[[package]]
+name = "black"
+version = "23.3.0"
+description = "The uncompromising code formatter."
+category = "dev"
+optional = false
+python-versions = ">=3.7"
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+
+[package.extras]
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+jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
+uvloop = ["uvloop (>=0.15.2)"]
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+[[package]]
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+category = "main"
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+python-versions = ">=3.6"
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+    {file = "yarl-1.9.2.tar.gz", hash = "sha256:04ab9d4b9f587c06d801c2abfe9317b77cdf996c65a90d5e84ecc45010823571"},
+]
+
+[package.dependencies]
+idna = ">=2.0"
+multidict = ">=4.0"
+
+[metadata]
+lock-version = "2.0"
+python-versions = "^3.10"
+content-hash = "7ffd5d54004c7dda13d1ed708f52cada666c771dcb6eacf3204612384cb33be3"

pyproject.toml

@@ -1,37 +1,23 @@
-[project]
-name = "speckle-automate-function"
+[tool.poetry]
+name = "speckle-automate-py"
 version = "0.1.0"
-requires-python = ">=3.13"
-authors = [{ name = "Speckle Systems", email = "hello@speckle.systems" }]
-maintainers = [{ name = "Speckle Systems", email = "hello@speckle.systems" }]
-description = "A Speckle Automate function template using specklepy"
+description = "Example function for Speckle Automate using specklepy"
+authors = ["Gergő Jedlicska <gergo@jedlicska.com>"]
 readme = "README.md"
-license = "Apache-2.0"
-keywords = ["speckle", "automate", "bim", "aec"]
+packages = [{include = "src/speckle_automate_py"}]
 
-dependencies = ["specklepy==3.2.4"]
+[tool.poetry.dependencies]
+python = "^3.10"
+specklepy = "^2.14.1"
+typer = "^0.9.0"
+pydantic = "^1.10.8"
+stringcase = "^1.2.0"
 
-[project.optional-dependencies]
-dev = [
-    "mypy==1.13.0",
-    "pytest==7.4.4",
-    "ruff==0.11.12",
-]
+[tool.poetry.group.dev.dependencies]
+black = "^23.3.0"
+mypy = "^1.3.0"
+ruff = "^0.0.271"
 
-[tool.ruff]
-exclude = [".venv", "**/*.yml"]
-
-[tool.ruff.lint]
-select = [
-    "E",  # pycodestyle
-    "F",  # pyflakes
-    "UP", # pyupgrade
-    "D",  # pydocstyle
-    "I",  # isort
-]
-
-[tool.ruff.lint.pydocstyle]
-convention = "google"
-
-[tool.setuptools]
-py-modules = []
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"

schema_generation.py

@@ -0,0 +1,6 @@
+import json
+from main import FunctionInputs
+
+
+if __name__ == "__main__":
+    print(json.dumps(FunctionInputs.schema()))

tests/__init__.py

@@ -1 +0,0 @@
-"""Tests for the automate function."""

tests/test_function.py

@@ -1,31 +0,0 @@
-"""Run integration tests with a speckle server."""
-
-from pydantic import SecretStr
-from speckle_automate import (
-    AutomationContext,
-    AutomationRunData,
-    AutomationStatus,
-    run_function,
-)
-from speckle_automate.fixtures import *  # noqa: F403
-
-from main import FunctionInputs, automate_function
-
-
-def test_function_run(
-    test_automation_run_data: AutomationRunData, test_automation_token: str
-):
-    """Run an integration test for the automate function."""
-    automation_context = AutomationContext.initialize(
-        test_automation_run_data, test_automation_token
-    )
-    automate_sdk = run_function(
-        automation_context,
-        automate_function,
-        FunctionInputs(
-            forbidden_speckle_type="None",
-            whisper_message=SecretStr("testing automatically"),
-        ),
-    )
-
-    assert automate_sdk.run_status == AutomationStatus.SUCCEEDED