1 Commits

Author SHA1 Message Date
Iain Sproat 54cd1e585a ci(github action): use Speckle's GitHub Composite Action 2023-08-03 19:50:23 +01:00
16 changed files with 548 additions and 953 deletions
-43
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@@ -1,43 +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",
"features": {
"ghcr.io/devcontainers-contrib/features/poetry:2": {}
},
"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 && POETRY_VIRTUALENVS_IN_PROJECT=true poetry install --no-root",
// 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"
}
-1
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@@ -1 +0,0 @@
SPECKLE_TOKEN=mytoken
+18 -15
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@@ -1,17 +1,21 @@
name: 'build and deploy Speckle functions'
on:
workflow_dispatch:
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@v3.4.0
- uses: actions/checkout@v3.4.0
with:
repository: 'specklesystems/speckle-automate-github-composite-action'
path: 'github-action'
ref: main
- uses: actions/setup-python@v4
with:
python-version: '3.11'
@@ -25,14 +29,13 @@ jobs:
- 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@0.6.7
echo "function_input_schema=$(python schema_generation.py)" >> "$GITHUB_ENV"
- uses: ./github-action
id: function_publish
with:
speckle_automate_url: ${{ env.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 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: ${{ env.function_input_schema }}
speckle_function_command: 'python main.py'
-5
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@@ -1,11 +1,6 @@
# Created by https://www.toptal.com/developers/gitignore/api/visualstudiocode,python,pycharm
# Edit at https://www.toptal.com/developers/gitignore?templates=visualstudiocode,python,pycharm
**/.env
**/.envrc
**/.tool-versions
### PyCharm ###
# Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio, WebStorm and Rider
# Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839
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@@ -0,0 +1 @@
python 3.11.0
+4 -11
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@@ -5,19 +5,12 @@
"version": "0.2.0",
"configurations": [
{
"name": "Speckle Automate function",
"name": "Python: Current File",
"type": "python",
"request": "launch",
"program": "main.py",
"program": "${file}",
"console": "integratedTerminal",
"justMyCode": true,
"envFile": "${workspaceFolder}/.env",
"args": [
"run",
"{\"projectId\": \"843d07eb10\", \"modelId\": \"base design\", \"versionId\": \"2a32ccfee1\", \"speckleServerUrl\": \"https://latest.speckle.systems\"}",
// make sure to use camelCase for variable names
"{\"forbiddenSpeckleType\": \"Objects.Geometry.Brep\"}"
]
"justMyCode": false
}
]
}
}
+1 -7
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@@ -1,9 +1,3 @@
{
"cSpell.words": [
"camelcase",
"pydantic",
"stringcase",
"typer"
],
"python.defaultInterpreterPath": ".venv/bin/python"
"cSpell.words": ["camelcase", "pydantic", "stringcase", "typer"]
}
+1
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@@ -4,3 +4,4 @@ RUN pip install poetry
COPY . .
RUN poetry export -f requirements.txt --output requirements.txt && pip install -r requirements.txt
# RUN poetry install --no-root --no-dev
+1 -73
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@@ -1,73 +1 @@
# Speckle Automate function template - Python
This is a template repository for a Speckle Automate functions written in python
using the [specklepy](https://pypi.org/project/specklepy/) SDK to interact with Speckle data.
This template contains the full scaffolding required to publish a function to the automate environment.
Also has some sane defaults for a development environment setups.
## Getting started
1. Use this template repository to create a new repository in your own / organization's profile.
Register the function
### Add new dependencies
To add new python package dependencies to the project, use:
`$ 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](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).
1. Enter a phrase to use in the comment.
1. Click `Create Automation`.
## Getting Started with creating your own Speckle Function
1. [Fork](https://docs.github.com/en/get-started/quickstart/fork-a-repo) this repository.
1. [Clone](https://docs.github.com/en/get-started/quickstart/fork-a-repo#cloning-your-forked-repository) your forked repository to your development environment, or use [GitHub CodeSpaces](https://github.com/features/codespaces).
1. [Register](https://automate.speckle.dev/) your Function with [Speckle Automate](https://automate.speckle.dev/).
1. After completing the registration of the Function you will be shown a Function Publish Token and a Function ID. You will need these later.
1. Save your Function Publish Token as a [GitHub Action Secret](https://docs.github.com/en/actions/security-guides/encrypted-secrets#creating-encrypted-secrets-for-a-repository) named `SPECKLE_AUTOMATE_FUNCTION_PUBLISH_TOKEN`.
1. Save your Function ID as a [GitHub Action Secret](https://docs.github.com/en/actions/security-guides/encrypted-secrets#creating-encrypted-secrets-for-a-repository) named `SPECKLE_AUTOMATE_FUNCTION_ID`.
1. Make changes to your Function in `main.py`. See below for the Developer Requirements, and instructions on how to test.
1. Every commit to `main` branch will create a new version of your Speckle Function.
## Developer Requirements
1. Install the following:
- [Python 3](https://www.python.org/downloads/)
- [Poetry](https://python-poetry.org/docs/#installing-with-the-official-installer)
1. 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](https://speckle.guide/dev/python.html) more about SpecklePy, and interacting with Speckle from Python.
# Go Automate Go
+3 -7
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@@ -1,13 +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]:
"""Take a base and flatten it to an iterable of bases."""
if hasattr(base, "elements"):
for element in base["elements"]:
for element in base.elements:
yield from flatten_base(element)
yield base
yield base
+64 -86
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@@ -1,97 +1,75 @@
"""This module contains the business logic of the function.
use the automation_context module to wrap your function in an Autamate context helper
"""
from pydantic import Field
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.
"""
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 conveniece 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()
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}"
)
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)
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@@ -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": {}}},
},
}
},
)
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@@ -7,27 +7,17 @@ readme = "README.md"
packages = [{include = "src/speckle_automate_py"}]
[tool.poetry.dependencies]
python = "^3.11"
specklepy = "^2.17.5"
python = "^3.10"
specklepy = "^2.14.1"
typer = "^0.9.0"
pydantic = "^1.10.8"
stringcase = "^1.2.0"
[tool.poetry.group.dev.dependencies]
black = "^23.3.0"
mypy = "^1.3.0"
ruff = "^0.0.271"
pytest = "^7.4.2"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
[tool.ruff]
select = [
"E", # pycodestyle
"F", # pyflakes
"UP", # pyupgrade
"D", # pydocstyle
"I", # isort
]
[tool.ruff.pydocstyle]
convention = "google"
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@@ -0,0 +1,6 @@
import json
from main import FunctionInputs
if __name__ == "__main__":
print(json.dumps(FunctionInputs.schema()))
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"""Run integration tests with a speckle server."""
import os
import secrets
import string
import pytest
from gql import gql
from speckle_automate import (
AutomationRunData,
AutomationStatus,
run_function,
)
from specklepy.api import operations
from specklepy.api.client import SpeckleClient
from specklepy.objects.base import Base
from specklepy.transports.server import ServerTransport
from main import FunctionInputs, automate_function
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() -> str:
"""Provide a speckle token for the test suite."""
env_var = "SPECKLE_TOKEN"
token = os.getenv(env_var)
if not token:
raise ValueError(f"Cannot run tests without a {env_var} environment variable")
return token
@pytest.fixture()
def speckle_server_url() -> str:
"""Provide a speckle server url for the test suite, default to localhost."""
return os.getenv("SPECKLE_SERVER_URL", "http://127.0.0.1:3000")
@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()
def automation_run_data(
test_object: Base, test_client: SpeckleClient, speckle_server_url: str
) -> AutomationRunData:
"""Set up an automation context for testing."""
project_id = test_client.stream.create("Automate function e2e test")
branch_name = "main"
model = test_client.branch.get(project_id, branch_name, commits_limit=1)
model_id: str = model.id
root_obj_id = operations.send(
test_object, [ServerTransport(project_id, test_client)]
)
version_id = test_client.commit.create(project_id, root_obj_id)
automation_name = crypto_random_string(10)
automation_id = crypto_random_string(10)
automation_revision_id = crypto_random_string(10)
register_new_automation(
project_id,
model_id,
test_client,
automation_id,
automation_name,
automation_revision_id,
)
automation_run_id = crypto_random_string(10)
function_id = crypto_random_string(10)
function_revision = crypto_random_string(10)
return AutomationRunData(
project_id=project_id,
model_id=model_id,
branch_name=branch_name,
version_id=version_id,
speckle_server_url=speckle_server_url,
automation_id=automation_id,
automation_revision_id=automation_revision_id,
automation_run_id=automation_run_id,
function_id=function_id,
function_revision=function_revision,
)
def test_function_run(automation_run_data: AutomationRunData, speckle_token: str):
"""Run an integration test for the automate function."""
automate_sdk = run_function(
automate_function,
automation_run_data,
speckle_token,
FunctionInputs(forbidden_speckle_type="Base"),
)
assert automate_sdk.run_status == AutomationStatus.FAILED