diff --git a/crc/scripts/dmn_from_spreadsheet.py b/crc/scripts/dmn_from_spreadsheet.py
deleted file mode 100644
index 13a490bf..00000000
--- a/crc/scripts/dmn_from_spreadsheet.py
+++ /dev/null
@@ -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')