Granta MI Scripting Toolkit 4.1

Importing and exporting tabular data

Last update: 16.07.2025

View tabular data information, and export the values from a record. Create a new record containing tabular data, and import this into a Granta MI database.

This example demonstrates:

  • Get tabular data attribute information from a Granta MI database
  • Export tabular data from a record
  • Import a new record and contains tabular data
  • Update tabular data for a record in a database

Create a Granta MI Session

Import the GRANTA_MIScriptingToolkit package, and create a connection to a Granta MI server.

import datetime
import GRANTA_MIScriptingToolkit as gdl

session = gdl.GRANTA_MISession('http://my.server.name/mi_servicelayer', autoLogon=True)

Get tabular data attribute information

Search for the record "Shore A75, flame retarded" in the "MI_Training" database.

dbKey = "MI_Training"
tableName = "MaterialUniverse"
recordName = "Shore A75, flame retarded"

req = gdl.RecordNameSearchRequest(caseSensitiveNames=False, searchShortNames=True, recordName=recordName)
req.table = gdl.TableReference(DBKey=dbKey, name=tableName)
resp = session.searchService.RecordNameSearch(req)
record = resp.searchResults[0]

Use the browse service to get the column headers for the tabular data attribute "Specifications".

attribName = "Restricted substances that may be associated with this material"

a = gdl.AttributeReference(name=attribName, 
                           partialTableReference=gdl.PartialTableReference(tableName=tableName), 
                           DBKey=dbKey)

resp = session.browseService.GetAttributeDetails(gdl.GetAttributeDetailsRequest([a]))
for col in resp.attributeDetails[0].tabular.columns:
    print(col.name)

Previous cell output:

Substance name
CAS number
Amount
Substance rating
Legislation name
Legislation rating
Effective date
Category
Function
Comments

Export tabular data

Perform a data export request to get column data for the tabular data attribute.

dataExportRequest = gdl.GetRecordAttributesByRefRequest(recordReferences=[record.recordReference],
                                                        attributeReferences=[a])

dataExportResponse = session.dataExportService.GetRecordAttributesByRef(dataExportRequest)
myRecordData = dataExportResponse.recordData

for rec in myRecordData:
    for attr in rec.attributeValues:
        if attr.attributeName == attribName:
            if not attr.dataType == "TABL":
                raise TypeError("No tables found! Check your record.")
            myTable = attr.tabularDataType
            print("Table found.")

Previous cell output:

Table found.

Print the data exported from the Granta MI database for this record. Note that attribute values, row cells, and list items all have a dataType attribute to help you pick the right data member to inspect.

i = 1
for row in myTable.tabularDataRows:
    if len(row.cells[0].listDataValue.items) > 0:
        print("Row {0}:".format(i))
        print("\t{0}".format(row.cells[0].listDataValue.items[0].shortTextDataValue.value))
        print("\t{0}".format(row.cells[1].listDataValue.items[0].shortTextDataValue.value))
        print("\t{0}-{1}".format(row.cells[2].rangeDataValue.low, row.cells[2].rangeDataValue.high))
        print("\t{0}".format(row.cells[3].discreteDataValue.discreteValues[0].value))
        print("\t{0}".format(row.cells[4].shortTextDataValue.value))
        i = i + 1

Previous cell output:

Row 1:
	Bis (2-ethyl(hexyl)phthalate) (DEHP)
	117-81-7
	0.0-50.0
	To be phased-out
	
Row 2:
	Dibutyl phthalate
	84-74-2
	0.0-50.0
	To be phased-out
	
Row 3:
	Alkanes, C10-13, chloro;  (Short chain chlorinated paraffins )
	85535-84-8
	0.0-50.0
	High risk of phase-out

Import tabular data

Search the database for a parent record under which you can create a new record.

dbKey = "MI_Training"
tableName = "Training Exercise for Import"
recordName = "Metal"

req = gdl.RecordNameSearchRequest(caseSensitiveNames=False, searchShortNames=True, recordName=recordName)
req.table = gdl.TableReference(DBKey=dbKey, name=tableName)
resp = session.searchService.RecordNameSearch(req)
destination = resp.searchResults[0]

Create an empty data structure, and populate it with tabular data values.

newTable = gdl.TabularDataType()
newTable.AddColumn("Order")
newTable.AddColumn("Notes")


newRow = newTable.CreateRow()
newInt = gdl.IntegerDataType(value=1)
newRow.cells[0].data = newInt

newText = gdl.LongTextDataType(value="Some notes about a material")
newRow.cells[1].data = newText

print("Created a table with cell data {0} and {1}".format(newInt.value, newText.value))

Previous cell output:

Created a table with cell data 1 and Some notes about a material

Create a new import attribute, "Characterization of this material", that contains these tabular data values.

attribName = "Characterization of this material"

a = gdl.AttributeReference(name=attribName,
                           partialTableReference=gdl.PartialTableReference(tableName=tableName),
                           DBKey=dbKey)

importAtribute = gdl.ImportAttributeValue(attributeReference=a)
importAtribute.tabularDataValue = newTable

Create a new import record.

now = datetime.datetime.now()
currentTime = now.strftime("%d/%m/%Y %H:%M:%S")
recName = "Import-test@{0}".format(currentTime)

importRecord = gdl.ImportRecord(recordName=recName,
                                existingRecord=destination.recordReference,
                                importAttributeValues=[importAtribute])
print(recName)

Previous cell output:

Import-test@30/10/2024 16:12:47

Import the record to a Granta MI database.

setRecordAttributesRequest = gdl.SetRecordAttributesRequest(importRecords=[importRecord])
response = session.dataImportService.SetRecordAttributes(setRecordAttributesRequest)
recordsImported = response.recordsImported

print("{0} records imported".format(len(recordsImported)))

Previous cell output:

1 records imported

Update the record

Retrieve the row ID of the data that you want to update.

dataExportRequest = gdl.GetRecordAttributesByRefRequest(recordReferences=[response.recordsImported[0].recordReference],  
                                                        attributeReferences=[a])
dataExportResponse = session.dataExportService.GetRecordAttributesByRef(dataExportRequest)
myRecordData = dataExportResponse.recordData[0]
attribute = myRecordData.attributeValues[0].tabularDataType

aid = attribute.tabularDataRows[0].Id

print("This row's ID is {0}".format(aid))

Previous cell output:

This row's ID is 94427

Create a table containing the values you want to update. You only need to specify the columns that contain updated data values.

updatedValue = gdl.IntegerDataType(value=newInt.value * 1000)
print("Updated previous value to {0}".format(updatedValue.value))

tableUpdates = gdl.TabularDataType()
tableUpdates.AddColumn("Order")

changetype = gdl.TabularDataType.ChangeType.Update

rowChange = tableUpdates.CreateUpdateRow(changetype, aid)
rowChange.cells[0].data = updatedValue

Previous cell output:

Updated previous value to 1000

Import the updated data into Granta MI using SetRecordAttributes.

attribute = gdl.ImportAttributeValue(attributeReference=a)
attribute.tabularDataValue = tableUpdates

updateRecord = gdl.ImportRecord(importRecordMode="Update", 
                                existingRecord=recordsImported[0].recordReference,
                                importAttributeValues=[attribute])

setRecordAttributesRequest = gdl.SetRecordAttributesRequest(importRecords=[updateRecord])
response = session.dataImportService.SetRecordAttributes(setRecordAttributesRequest)

print("Use MI Viewer to view {0} and check that the Order in 'Characterization of this material' is {1}".format(recName, updatedValue.value))

Previous cell output:

Use MI Viewer to view Import-test@30/10/2024 16:12:47 and check that the Order in 'Characterization of this material' is 1000

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