Removed script used in development

This commit is contained in:
mike cullerton 2021-09-07 15:36:50 -04:00
parent 7211a1de46
commit a690535c2d
1 changed files with 0 additions and 134 deletions

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@ -1,134 +0,0 @@
from crc.models.file import FileModel, FileDataModel
from crc.models.workflow import WorkflowSpecModel
from crc.scripts.script import Script
from crc.services.file_service import FileService
from crc import app, session
from lxml import etree
from io import StringIO, BytesIO
import pandas as pd
import os
import random
import string
class DMNFromSpreadSheet(Script):
def _get_random_string(self, length):
return ''.join(
[random.choice(string.ascii_letters + string.digits) for n in range(length)])
def _row_has_value(self, values):
for item in values:
if not pd.isnull(item):
return True
return False
def get_description(self):
"""Create a DMN table from a spreadsheet"""
def do_task_validate_only(self, task, study_id, workflow_id, *args, **kwargs):
pass
def do_task(self, task, study_id, workflow_id, *args, **kwargs):
# ss_file_path = os.path.join(app.root_path, 'static', 'spreadsheet_to_dmn.xlsx')
# ss_file_path = os.path.join(app.root_path, 'static', 'New_test_budget_spreadsheet.xlsx')
# ss_file_path = os.path.join(app.root_path, 'static', 'large_test_spreadsheet.xlsx')
# ss_file_path = os.path.join(app.root_path, 'static', 'DMN_Upload_CRC_Orgs.xlsx')
# ss_file_path = os.path.join(app.root_path, 'static', 'DMN_Upload_Org_Enums.xlsx')
file_id = kwargs['file_id']
dmn_name = kwargs['dmn_name']
file_data_model = session.query(FileDataModel).filter(FileDataModel.file_model_id == file_id).first()
file_data = file_data_model.data
df = pd.read_excel(file_data, header=None)
root = etree.Element("definitions",
xmlns="http://www.omg.org/spec/DMN/20151101/dmn.xsd",
id='Definitions',
name="DRD",
namespace="http://camunda.org/schema/1.0/dmn")
decision_name = df.iat[0, 1]
decision_id = df.iat[1, 1]
decision = etree.SubElement(root, "decision",
id=decision_id,
name=decision_name
)
decision_table = etree.SubElement(decision, 'decisionTable', id='decisionTable_1')
input_output = df.iloc[2][1:]
count = 1
input_count = 1
output_count = 1
for item in input_output:
if item == 'Input':
label = df.iloc[3, count]
input_ = etree.SubElement(decision_table, 'input', id=f'input_{input_count}', label=label)
type_ref = df.iloc[5, count]
input_expression = etree.SubElement(input_, 'inputExpression', id=f'inputExpression_{input_count}',
typeRef=type_ref)
expression = df.iloc[4, count]
expression_text = etree.SubElement(input_expression, 'text')
expression_text.text = expression
input_count += 1
elif item == 'Output':
label = df.iloc[3, count]
name = df.iloc[4, count]
type_ref =df.iloc[5, count]
decision_table.append(etree.Element('output', id=f'output_{output_count}',
label=label, name=name, typeRef=type_ref))
output_count += 1
elif item == 'Annotation':
column_count = count
break
count += 1
row = 6
while row < df.shape[0]:
column = 1
row_values = df.iloc[row].values[1:column_count]
if self._row_has_value(row_values):
rando = self._get_random_string(7).lower()
rule = etree.SubElement(decision_table, 'rule', id=f'DecisionRule_{rando}')
i = 1
while i < input_count:
input_entry = etree.SubElement(rule, 'inputEntry', id=f'UnaryTests_{self._get_random_string(7)}')
text_element = etree.SubElement(input_entry, 'text')
text_element.text = str(df.iloc[row, column]) if not pd.isnull(df.iloc[row, column]) else ''
i += 1
column += 1
i = 1
while i < output_count:
output_entry = etree.SubElement(rule, 'outputEntry', id=f'LiteralExpression_{self._get_random_string(7)}')
text_element = etree.SubElement(output_entry, 'text')
text_element.text = str(df.iloc[row, column]) if not pd.isnull(df.iloc[row, column]) else ''
i += 1
column += 1
description = etree.SubElement(rule, 'description')
text = df.iloc[row, column] if not pd.isnull(df.iloc[row, column]) else ''
description.text = text
row += 1
filename = 'test_dmn.dmn'
primary = False
content_type = 'text/xml'
prefix = b'<?xml version="1.0" encoding="UTF-8"?>'
file_data = prefix + etree.tostring(root)
data = {'file': (BytesIO(file_data), filename)}
file = BytesIO(file_data)
workflow_spec = session.query(WorkflowSpecModel).first()
uploaded = session.query(FileModel).filter(FileModel.workflow_spec_id == workflow_spec.id).filter(FileModel.name == filename).first()
if uploaded:
file_model = FileService.update_file(uploaded, file.read(), content_type)
else:
file_model = FileService.add_workflow_spec_file(workflow_spec, filename, content_type,
file.read(), primary=primary)
print('dmn from spreadsheet')