It now adds the dmn file to the DB.
Added annotations. Still need to move it out of a script. Maybe a new API endpoint and a new method in file_service
This commit is contained in:
mike cullerton
parent
e8ea9776a5
commit
64576ee8fd
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@ -1,15 +1,30 @@
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from crc.models.workflow import WorkflowSpecModel
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from crc.scripts.script import Script
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from crc import app
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from crc.services.file_service import FileService
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from crc import app, session
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from lxml import etree
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from io import StringIO, BytesIO
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import pandas as pd
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import os
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import random
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import string
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class DMNFromSpreadSheet(Script):
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def _get_random_string(self, length):
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return ''.join(
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[random.choice(string.ascii_letters + string.digits) for n in range(length)])
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def _row_has_value(self, values):
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for item in values:
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if not pd.isnull(item):
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return True
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return False
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def get_description(self):
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"""Create a DMN table from a spreadsheet"""
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@ -18,20 +33,92 @@ class DMNFromSpreadSheet(Script):
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def do_task(self, task, study_id, workflow_id, *args, **kwargs):
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# dmn_template_path = os.path.join(app.root_path, 'static', 'templates', 'dmn_template.xml')
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dmn_template_path = os.path.join(app.root_path, 'static', 'templates', 'diagram_1.dmn')
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ss_file_path = os.path.join(app.root_path, 'static', 'spreadsheet_to_dmn.xlsx')
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f_open = open(dmn_template_path, 'r')
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xml_template = f_open.read()
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tree = etree.parse(StringIO(xml_template))
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# ss_file_path = os.path.join(app.root_path, 'static', 'spreadsheet_to_dmn.xlsx')
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# ss_file_path = os.path.join(app.root_path, 'static', 'New_test_budget_spreadsheet.xlsx')
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ss_file_path = os.path.join(app.root_path, 'static', 'large_test_spreadsheet.xlsx')
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df = pd.read_excel(ss_file_path, header=None)
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root = etree.Element("definitions",
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xmlns="http://www.omg.org/spec/DMN/20151101/dmn.xsd",
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id='Definitions',
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name="DRD",
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namespace="http://camunda.org/schema/1.0/dmn")
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decision_name = df.iat[0, 1]
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decision_id = df.iat[1, 1]
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decision = etree.SubElement(root, "decision",
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id=decision_id,
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name=decision_name
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)
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decision_table = etree.SubElement(decision, 'decisionTable', id='decisionTable_1')
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input_output = df.iloc[2][1:]
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for index, item in input_output:
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count = 1
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input_count = 1
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output_count = 1
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for item in input_output:
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if item == 'Input':
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print('input')
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if item == 'Output':
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print('output')
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label = df.iloc[3, count]
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input_ = etree.SubElement(decision_table, 'input', id=f'input_{input_count}', label=label)
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type_ref = df.iloc[5, count]
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input_expression = etree.SubElement(input_, 'inputExpression', id=f'inputExpression_{input_count}',
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typeRef=type_ref)
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expression = df.iloc[4, count]
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expression_text = etree.SubElement(input_expression, 'text')
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expression_text.text = expression
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print(df)
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input_count += 1
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elif item == 'Output':
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label = df.iloc[3, count]
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name = df.iloc[4, count]
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type_ref =df.iloc[5, count]
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decision_table.append(etree.Element('output', id=f'output_{output_count}',
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label=label, name=name, typeRef=type_ref))
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output_count += 1
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elif item == 'Annotation':
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column_count = count
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break
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count += 1
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row = 6
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while row < df.shape[0]:
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column = 1
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row_values = df.iloc[row].values[1:column_count]
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if self._row_has_value(row_values):
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rando = self._get_random_string(7).lower()
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rule = etree.SubElement(decision_table, 'rule', id=f'DecisionRule_{rando}')
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i = 1
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while i < input_count:
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input_entry = etree.SubElement(rule, 'inputEntry', id=f'UnaryTests_{self._get_random_string(7)}')
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text_element = etree.SubElement(input_entry, 'text')
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text_element.text = str(df.iloc[row, column]) if not pd.isnull(df.iloc[row, column]) else ''
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i += 1
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column += 1
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i = 1
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while i < output_count:
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output_entry = etree.SubElement(rule, 'outputEntry', id=f'LiteralExpression_{self._get_random_string(7)}')
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text_element = etree.SubElement(output_entry, 'text')
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text_element.text = str(df.iloc[row, column]) if not pd.isnull(df.iloc[row, column]) else ''
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i += 1
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column += 1
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description = etree.SubElement(rule, 'description')
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text = df.iloc[row, column] if not pd.isnull(df.iloc[row, column]) else ''
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description.text = text
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row += 1
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filename = 'test_dmn.dmn'
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primary = False
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content_type = 'text/xml'
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prefix = b'<?xml version="1.0" encoding="UTF-8"?>'
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file_data = prefix + etree.tostring(root)
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data = {'file': (BytesIO(file_data), filename)}
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file = BytesIO(file_data)
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workflow_spec = session.query(WorkflowSpecModel).first()
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file_model = FileService.add_workflow_spec_file(workflow_spec, filename, content_type,
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file.read(), primary=primary)
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print('dmn from spreadsheet')
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