gjedlicska / gergo-hello-aec-tech-function

Speckle Automate function template - Python

This is a template repository for a Speckle Automate functions written in python using the specklepy SDK to interact with Speckle data.

This template contains the full scaffolding required to publish a function to the automate environment. Also has some sane defaults for a development environment setups.

Getting started

1. Use this template repository to create a new repository in your own / organization's profile.

Register the function

Add new dependencies

To add new python package dependencies to the project, use: $ poetry add pandas

Change launch variables

describe how the launch.json should be edited

Github Codespaces

create new repo from template, and use the create new code

Local dev environment

Archive

This is a simple example of how to use the Speckle Automate Python package to automate the creation of a Speckle stream.

Using this Speckle Function

1. Create a new Speckle Automation.
2. Select your Speckle Project and Speckle Model.
3. Select the existing Speckle Function named Random comment on IFC beam.
4. Enter a phrase to use in the comment.
5. Click Create Automation.

Getting Started with creating your own Speckle Function

1. Fork this repository.
2. Clone your forked repository to your development environment, or use GitHub CodeSpaces.
3. Register your Function with Speckle Automate.
4. After completing the registration of the Function you will be shown a Function Publish Token and a Function ID. You will need these later.
5. Save your Function Publish Token as a GitHub Action Secret named SPECKLE_AUTOMATE_FUNCTION_PUBLISH_TOKEN.
6. Save your Function ID as a GitHub Action Secret named SPECKLE_AUTOMATE_FUNCTION_ID.
7. Make changes to your Function in main.py. See below for the Developer Requirements, and instructions on how to test.
8. Every commit to main branch will create a new version of your Speckle Function.

Developer Requirements

1. Install the following:
   • Python 3
   • Poetry
2. Run poetry shell && poetry install to install the required Python packages.

Building and Testing

The code can be tested locally by running poetry run pytest. The code should also be packaged into the format required by Speckle Automate, a Docker Container Image, and that should also be tested.

Resources

• Learn more about SpecklePy, and interacting with Speckle from Python.