87 lines
3.0 KiB
Python
87 lines
3.0 KiB
Python
"""Import tickets, for use in script task."""
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import csv
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from flask_bpmn.models.db import db
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from spiffworkflow_backend.models.process_instance import ProcessInstanceModel
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from spiffworkflow_backend.models.user import UserModel
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from spiffworkflow_backend.services.process_instance_processor import (
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ProcessInstanceProcessor,
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)
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from spiffworkflow_backend.services.process_instance_service import (
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ProcessInstanceService,
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)
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from spiffworkflow_backend.services.process_model_service import ProcessModelService
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process_model_identifier_ticket = "ticket"
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db.session.query(ProcessInstanceModel).filter(
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ProcessInstanceModel.process_model_identifier == process_model_identifier_ticket
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).delete()
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db.session.commit()
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"""Print process instance count."""
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process_instances = ProcessInstanceModel.query.filter_by(
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process_model_identifier=process_model_identifier_ticket
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).all()
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process_instance_count = len(process_instances)
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print(f"process_instance_count: {process_instance_count}")
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process_model = ProcessModelService().get_process_model(process_model_identifier_ticket)
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columns_to_data_key_mappings = {
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"Month": "month",
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"MS": "milestone",
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"ID": "req_id",
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"Dev Days": "dev_days",
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"Feature": "feature",
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"Priority": "priority",
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}
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columns_to_header_index_mappings = {}
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user = UserModel.query.filter_by(username="test_user1").first()
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with open("tests/files/tickets.csv") as infile:
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reader = csv.reader(infile, delimiter=",")
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# first row is garbage
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next(reader)
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header = next(reader)
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for column_name in columns_to_data_key_mappings:
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columns_to_header_index_mappings[column_name] = header.index(column_name)
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id_index = header.index("ID")
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priority_index = header.index("Priority")
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print(f"header: {header}")
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for row in reader:
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ticket_identifier = row[id_index]
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priority = row[priority_index]
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print(f"ticket_identifier: {ticket_identifier}")
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print(f"priority: {priority}")
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process_instance = ProcessInstanceService.create_process_instance(
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process_model_identifier_ticket, user
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)
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processor = ProcessInstanceProcessor(process_instance)
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processor.do_engine_steps()
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# processor.save()
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for column_name, desired_data_key in columns_to_data_key_mappings.items():
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appropriate_index = columns_to_header_index_mappings[column_name]
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print(f"appropriate_index: {appropriate_index}")
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processor.bpmn_process_instance.data[desired_data_key] = row[
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appropriate_index
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]
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# you at least need a month, or else this row in the csv is considered garbage
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month_value = processor.bpmn_process_instance.data["month"]
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if month_value == "" or month_value is None:
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db.delete(process_instance)
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db.session.commit()
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continue
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processor.save()
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process_instance_data = processor.get_data()
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print(f"process_instance_data: {process_instance_data}")
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