Latest Contributions by JamesCrandall

Edit: I didn't notice at first and still can't quite tell if you are actually implementing jcornet's solution from GitHub, but it looks to be pretty close to what you need.  Just publish the GP service on your ArcGIS Server and it looks like they also supply a widget (I think that's what it is) you can add to your WAB solution. There's likely a few things to consider but without looking at anything specific you have it will be difficult to locate the issue(s) you've run into.  Just some things to keep in mind: 1. Perhaps there is an alternative way to perform your task client-side.  I'd personally go down the path of just building a new widget that you can add to the WAB app.  The JavaScript API is quite powerful but you'd have to migrate everything to that language and I'm unsure if all of the tools you'd need are available but it's probably worth the time to investigate. 2. I do beleive the ArcGIS Server would need to be setup to allow uploads (your csv), although I have not gone down this route to see what is involved.  3. I see that there is an input parameter type "File" available. That's where I'd start. 4. The output parameter should be set to Feature Layer. 5. Perform the conversion from your CSV to Featuer Layer and then create an arcpy.FeatureSet variable that you would set the output parameter to. feature_class = "tmpfc" arcpy.Clip_analysis(lyr1, lyr2, feature_class) feature_class_lyr = arcpy.MakeFeatureLayer_management (feature_class, "feature_class_lyr") feature_set = arcpy.FeatureSet(feature_class) arcpy.SetParameter(1, feature_set)‍‍‍‍‍‍‍‍‍‍ 6. Run the tool in ArcMap and see if it successfully adds your feature layer to the TOC.  If so, publish it. 7. Add the Geoprocessing widget to your WAB and specify the url pointing to the GP service you just published and it should automatically understand the input/output parameters required. ... View more

thank you! ... View more

I get an error running your .json sample ValueError: Expecting : delimiter: line 1 column 14 (char 13) filename = r'H:\input.json' with open(filename, 'r') as fp:     jData = json.loads('{ "features" " ' + fp.read().decode("utf-8-sig").encode("utf-8") + '}') print json.dumps(jData, indent=4, sort_keys=False)‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍ This happens with the input.json sample you provided as well as the contents of the .json file I am working with: [   {     "Arrow Size": "0.60",     "Color": "icon20",     "Date": "March 3, 2017",     "Desciption": "ff00ffff",     "Flow": "80",     "Heading": "315",     "Lat": "46.60",     "Long": "-50.44",     "Name": "Some Name1",     "table": "<TABLE>\n<tr><td>G310-P:</td><td style=\"text-align: right\">84 cfs; Mar 2, 17</td></tr>\n<tr><td>G251-P:</td><td style=\"text-align: right\">0 cfs; Mar 2, 17</td></tr>\n</TABLE><a href=\"http://my.sfwmd.gov/dbhydroGraph/servlet/DbhydroGraphServlet.do?v_report_type=format6&v_period=1week&v_dbkey=64308/64267/65115\">Hydrograph</a>"   },   {       "Arrow Size": "0.60",       "Color": "icon20",       "Date": "March 3, 2017",       "Desciption": "ff00ffff",       "Flow": "80",       "Heading": "315",       "Lat": "42.30",       "Long": "-53.42",       "Name": "Some Name2",       "table": "<TABLE>\n<tr><td>G310-P:</td><td style=\"text-align: right\">84 cfs; Mar 2, 17</td></tr>\n<tr><td>G251-P:</td><td style=\"text-align: right\">0 cfs; Mar 2, 17</td></tr>\n</TABLE><a href=\"http://my.sfwmd.gov/dbhydroGraph/servlet/DbhydroGraphServlet.do?v_report_type=format6&v_period=1week&v_dbkey=64308/64267/65115\">Hydrograph</a>"   },   {       "Arrow Size": "0.60",       "Color": "icon20",       "Date": "March 3, 2017",       "Desciption": "ff00ffff",       "Flow": "80",       "Heading": "315",       "Lat": "45.50",       "Long": "-55.44",       "Name": "Some Name3",       "table": "<TABLE>\n<tr><td>G310-P:</td><td style=\"text-align: right\">84 cfs; Mar 2, 17</td></tr>\n<tr><td>G251-P:</td><td style=\"text-align: right\">0 cfs; Mar 2, 17</td></tr>\n</TABLE><a href=\"http://my.sfwmd.gov/dbhydroGraph/servlet/DbhydroGraphServlet.do?v_report_type=format6&v_period=1week&v_dbkey=64308/64267/65115\">Hydrograph</a>"   } ]‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍ ... View more

Good stuff.  I appreciate it and will try to implement something today! ... View more

I appreciate it.  However, I don't see where you are starting your input.json file from.  In my OP above, that's what I'm starting with and I need to get it into the geoJSON format that you show! Interestingly, I cannot seem to access individual attributes like you are showing either.  I get this error when I try to access the "Name" attribute:  TypeError: string indices must be integers, not str But it validates in a JSON formatter tool. This is what I have so far that will convert a csv file into the JSON output I posted in my OP: csvfile = open('H:\MyFile.csv', 'r') reader = csv.DictReader(csvfile) fieldnames = ('Name', 'Flow', 'Arrow Size', 'Date', 'Lat', 'Long', 'Heading', 'Color', 'Desciption', 'table') output = [] for each in reader:   row = {}   for field in fieldnames:     if not field == 'Coords':         row[field] = each[field]      output.append(row) jData = json.dumps(output)    json.dump(output, jsonfile, indent=2, sort_keys=True)‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍ ... View more

What do you think would be the best plan of attack on this one? 1. Attempt to churn the supplied JSON into a well-formatted esri-JSON object, minus that table column. 2. Just parse out the table column into new columns, effectively just making them new attribute fields. I'm thinking for now I should just go with the #2 option to manipulate the csv and just convert that to a feature class.  Open to suggestions. ... View more

That "tables" originally comes in as a string (really it's an html table stored in that column of the csv file) and I had converted it to a list like that.  If it's a problem then I can revert it back to its original string value and deal with it later (as you suggested, make it it's own table). ... View more

They're just input parameters.  I could manually set these to some value and still get the same behavior. However, the issue I was having was due to the fact that this is the source to a GP service and it needed to be stopped in order to run this script. Thanks for your input ... View more

Not a complete solution but might be something to look into.  numpy and pandas have much better grouping functions.  Challenge is to get the result back into your arcpy.da cursor and update the desired column. nparr = arcpy.da.FeatureClassToNumPyArray(fc,["Account", "Acres"]) pdarr = pd.DataFrame(nparr) counts = pdarr.groupby(["Account", "Acres"]).size() pddups = pd.DataFrame(counts, columns = ['size']) pddups = pddups[pddups.size>1] print pddups‍‍‍‍‍‍ ... View more

fc = r'H:\Documents\ArcGIS\Default.gdb\MyFeatureClass' fields= ["OBJECTID", "Field1", "Field2"] with arcpy.da.SearchCursor(fc, fields) as cursor: for row in cursor:   if row[1]==row[2]:    sql = "OBJECTID=" + str(row[0])    with arcpy.da.UpdateCursor(fc, "Field3", sql) as ucur:     for urow in ucur:      urow[0]=0      ucur.updateRow(urow)‍‍‍‍‍‍‍‍‍‍ ... View more