Merge pull request #369 from sartography/dmn-from-spreadsheet-395
Dmn from spreadsheet #395
This commit is contained in:
Mike Cullerton
GitHub
commit
787614ee91
31
crc/api.yml
31
crc/api.yml
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@ -1030,6 +1030,37 @@ paths:
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type: string
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format: binary
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example: '<?xml version="1.0" encoding="UTF-8"?><bpmn:definitions></bpmn:definitions>'
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/dmn_from_ss:
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# parameters:
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# - name: workflow_spec_id
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# in: query
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# required: true
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# description: The unique id of a workflow specification
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# schema:
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# type: string
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post:
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operationId: crc.api.file.dmn_from_ss
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summary: Create a DMN table from a spreadsheet
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tags:
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- Files
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requestBody:
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content:
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multipart/form-data:
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schema:
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type: object
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properties:
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file:
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type: string
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format: binary
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responses:
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'200':
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description: DMN file for workflow spec
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content:
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application/octet-stream:
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schema:
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type: string
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format: binary
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example: '<?xml version="1.0" encoding="UTF-8"?><bpmn:definitions></bpmn:definitions>'
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/task_events:
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parameters:
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- name: action
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@ -1,4 +1,5 @@
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import io
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from datetime import datetime
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from typing import List
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import connexion
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@ -171,3 +172,15 @@ def update_file_info(file_id, body):
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def delete_file(file_id):
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FileService.delete_file(file_id)
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def dmn_from_ss():
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file = connexion.request.files['file']
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result = FileService.dmn_from_spreadsheet(file)
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return send_file(
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io.BytesIO(result),
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attachment_filename='temp_dmn.dmn',
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mimetype='text/xml',
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cache_timeout=-1, # Don't cache these files on the browser.
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last_modified=datetime.now()
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)
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@ -1,7 +1,10 @@
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import hashlib
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import io
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import json
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import os
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from datetime import datetime
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import random
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import string
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import pandas as pd
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from github import Github, GithubObject, UnknownObjectException
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@ -436,3 +439,109 @@ class FileService(object):
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branch=target_branch
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)
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return {'updated': True}
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@staticmethod
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def dmn_from_spreadsheet(ss_data):
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def _get_random_string(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(values):
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for value_item in values:
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if not pd.isnull(value_item):
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return True
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return False
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df = pd.read_excel(io.BytesIO(ss_data.read()), header=None)
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xml_ns = "https://www.omg.org/spec/DMN/20191111/MODEL/"
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dmndi_ns = "https://www.omg.org/spec/DMN/20191111/DMNDI/"
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dc_ns = "http://www.omg.org/spec/DMN/20180521/DC/"
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dmndi = "{%s}" % dmndi_ns
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dc = "{%s}" % dc_ns
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nsmap = {None: xml_ns, 'dmndi': dmndi_ns, 'dc': dc_ns}
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root = etree.Element("definitions",
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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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nsmap=nsmap,
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)
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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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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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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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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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break
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count += 1
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row = 6
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column_count = count
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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 _row_has_value(row_values):
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rando = _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_{_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_{_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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dmndi_root = etree.SubElement(root, dmndi + "DMNDI")
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dmndi_diagram = etree.SubElement(dmndi_root, dmndi + "DMNDiagram")
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# rando = _get_random_string(7).lower()
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dmndi_shape = etree.SubElement(dmndi_diagram, dmndi + "DMNShape",
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dmnElementRef=decision_id)
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bounds = etree.SubElement(dmndi_shape, dc + "Bounds",
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height='80', width='180', x='100', y='100')
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prefix = b'<?xml version="1.0" encoding="UTF-8"?>'
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dmn_file = prefix + etree.tostring(root)
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return dmn_file
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Binary file not shown.
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@ -0,0 +1,27 @@
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from tests.base_test import BaseTest
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from crc import app
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import io
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from lxml import etree
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import os
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class TestDMNFromSS(BaseTest):
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def test_dmn_from_ss(self):
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filepath = os.path.join(app.root_path, '..', 'tests', 'data',
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'dmn_from_spreadsheet', 'large_test_spreadsheet.xlsx')
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f_handle = open(filepath, 'br')
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ss_data = f_handle.read()
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data = {'file': (io.BytesIO(ss_data), 'test.xlsx')}
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rv = self.app.post('/v1.0/dmn_from_ss', data=data, follow_redirects=True,
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content_type='multipart/form-data', headers=self.logged_in_headers())
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dmn_xml = rv.stream.response.data
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root = etree.fromstring(dmn_xml)
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children = root.getchildren()
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self.assertEqual('{https://www.omg.org/spec/DMN/20191111/MODEL/}decision', children[0].tag)
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self.assertEqual('{https://www.omg.org/spec/DMN/20191111/DMNDI/}DMNDI', children[1].tag)
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