Have Docker running in Ubuntu and successfully downloaded IRIS Healthcare ML Community to local machine.

Cannot figure out how to launch IRIS...help!

Thanks, all...

Martin Arnold

Hi All,

We're doing our first babysteps with embedded Python and IRIS with an interoperability solution. We want to convert a CSV file to an Excel xlt file.

As service we've got a EnsLib.File.PassthroughService which picks up a csv file

As operation we've got a EnsLib.File.PassthroughOperation which writes the Excel file.

In the middle:

We've created an Business Process with an %Stream.GlobalCharacter in the Request and a %Stream.GlobalCharacter  in the Response.

But how do we get the %Stream.GlobalCharacter in the Python ClassMethod? Ideally I don't would like to write the stream first to a temp file, give the temp file to Python and let Python write the XLT file and read that XLT file into a %Stream.GlobalCharacter.

Any ideas? See the code snipped below. This one works but will first create a string from the Stream but will fail when the csv is bigger then the Intersystems string limit

Class ZORG.BP.CsvToExcel Extends Ens.BusinessProcess
{

Method OnRequest(pRequest As ZORG.BP.CsvToExcel.CsvToExcelReq, Output pResponse As ZORG.BP.CsvToExcel.CsvToExcelResp) As %Status
{
    Set tsc = $$$OK
	; Create the response class
	Set pResponse = ##class(ZORG.BP.CsvToExcel.CsvToExcelResp).%New()
	Set pResponse.outputStream = ##class(%Stream.GlobalCharacter).%New()
	
	$$$TRACE("Size of Stream: "_pRequest.inputStream.SizeGet())
    Set XlsString=..convertCSVtoXLS(pRequest.inputStream.Read($$$MaxStringLength))
	Do pResponse.outputStream.Write(XlsString)
	
	return tsc
}

ClassMethod convertCSVtoXLS(csvFile As %String(MAXLEN="")) As %String [ Language = python ]
{

	"""
    This function takes a CSV string as input and converts it into an XLS string.
    
    Parameters:
    csv_string (str): The CSV string to be converted
    
    Returns:
    str: Th
	"""
	import pandas
	import xlwt
	import sys
	import csv
	import tempfile
	from io import StringIO
	
	# Read the CSVdata into a Pandas DataFrame
	
	df = pandas.read_csv(StringIO(csvFile), delimiter=";", decimal=",", dtype={'patno':str} )	
	# Create an instance of Workbook class from xlwt library	
	workbook = xlwt.Workbook()

    # Add a sheet to the workbook
	sheet = workbook.add_sheet('Sheet1')

    # Write the DataFrame values to the sheet
	for i, column in enumerate(df.columns):
		sheet.write(0, i, column)  # Write column headers
		for j, value in enumerate(df[column]):
			if ( str(value) != 'nan' ):       #catch empty cells
				sheet.write(j + 1, i, value)  # Write cell values

	# Write workbook to temporary file
	file = tempfile.TemporaryFile()
	
	# Save Workbook
	workbook.save(file)
	
	#Go to the beginning of the file
	file.seek(0)

	#Read from temporary File and return
	data = file.read()
	return(data)
}
}