Hi Jared,
I haven't yet found a solution, but I did find a workaround. The intent behind uploading the .csv was to use it as an input for a custom geoprocessing tool. The workaround:
-Create the tool in a Python Toolbox (.pyt), not as a Python Script (.py). If I tried it as a .py tool, I was still getting errors. I don't remember exactly why, but I think it had something to do with reading parameter inputs
-Set up an input parameter with a datatype of GPRecordSet
-Fetch the parameter as text, then use the csv module to read the contents. In my case, I skipped the header row. I'm not sure if that makes a difference
-Published the tool to Enterprise, with the Upload capability set to True, Execution set to Synchronous, and cleared the default value of that parameter. When I tried publishing without clearing the default, then the .csv to be uploaded had to have a header row that exactly matched the .csv I had used while testing the tool.
-Added the Analysis widget to ExB, and set the custom tool as the utility. Allowed an uploaded file to serve as the input in the widget settings
This has been working for my purposes. The end user is uploading a .csv with only a single column of data, so I don't know if anything would need to change if numerous columns were required
Relevant snippet of my .pyt code:
class custom_tool(object):
def __init__(self):
self.label = 'Custom tool'
self.description = 'Tool uploaded to Enterprise'
self.canRunInBackground = False
# === Did not include isLicensed, updateParameters,
# and updateMessages in this snippet ===
def getParameterInfo(self):
params = []
param0 = arcpy.Parameter(
displayName = 'Uploaded CSV',
name = 'uploaded_csv',
datatype = 'GPRecordSet', #GPFeatureRecordSetLayer did not work
parameterType = 'Required',
direction = 'Input'
)
params.append(param0)
return params
def execute(self, parameters, messages):
input_csv = parameters[0].valueAsText #parameters[0].value did not work
input_data = []
with open(input_csv, 'r') as f:
reader = csv.reader(f)
next(reader)
for row in reader:
input_data.append(row[0])
# === Begin Analysis of input data ===
