Jonathon Broughton
a999f18e00
build and deploy Speckle functions / publish-automate-function-version (push) Has been cancelled
70 lines
2.6 KiB
Python
70 lines
2.6 KiB
Python
from pydantic import Field
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from speckle_automate import AutomationContext, AutomateBase, execute_automate_function
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from Utilities.helpers import flatten_base, speckle_print
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from rules import RevitRules
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from Utilities.helpers import flatten_base, speckle_print
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from Utilities.spreadsheet import read_rules_from_spreadsheet
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from Workshop.Exercise_4.rules import apply_rules_to_objects
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class FunctionInputs(AutomateBase):
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"""These are function author defined values.
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Automate will make sure to supply them matching the types specified here.
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Please use the pydantic model schema to define your inputs:
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https://docs.pydantic.dev/latest/usage/models/
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"""
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# In this exercise, we will move rules to an external source so not to hardcode them.
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spreadsheet_url: str = Field(
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title="Spreadsheet URL",
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description="This is the URL of the spreadsheet to check. It should be a TSV format data source.",
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)
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def automate_function(
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automate_context: AutomationContext,
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function_inputs: FunctionInputs,
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) -> None:
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"""This version of the function will add a check for the new provide inputs.
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Args:
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automate_context: A context helper object, that carries relevant information
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about the runtime context of this function.
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It gives access to the Speckle project data, that triggered this run.
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It also has convenience methods attach result data to the Speckle model.
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function_inputs: An instance object matching the defined schema.
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"""
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# the context provides a convenient way, to receive the triggering version
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version_root_object = automate_context.receive_version()
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# We can continue to work with a flattened list of objects.
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flat_list_of_objects = list(flatten_base(version_root_object))
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# read the rules from the spreadsheet
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rules = read_rules_from_spreadsheet(function_inputs.spreadsheet_url)
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# apply the rules to the objects
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apply_rules_to_objects(flat_list_of_objects, rules, automate_context)
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# set the automation context view, to the original model / version view
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automate_context.set_context_view()
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# report success
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automate_context.mark_run_success(
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f"Successfully applied rules to {len(flat_list_of_objects)} objects."
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)
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# make sure to call the function with the executor
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if __name__ == "__main__":
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# NOTE: always pass in the automate function by its reference, do not invoke it!
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# pass in the function reference with the inputs schema to the executor
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execute_automate_function(automate_function, FunctionInputs)
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