Latest Contributions by JakeSkinner

Can you share the CSV you're using to one of the AGOL groups you invited me to? ... View more

@WGIS with SAML enabled, you can still create a built-in Administrator account and use that.  An Administrator account is not required, but the tool would have to be re-written in a few places so that a Publisher could execute it successfully.  However, it may be worth given some thought if you want a non-admin promoting content to your Production environment.   ... View more

Hi @g1omaa, These tools here will do exactly what you're looking for. ... View more

@Sibe I currently don't have plans to implement this.  To do this, you would need to query the manifest.json or manifest.xml files located at \arcgisserver\config-store\services\<service name>\esriinfo\manifest.  These files hold information of the feature classes/tables used in the services. ... View more

@FredMitchell , Try the following:   import arcpy, os, uuid import pandas as pd import datetime from datetime import timedelta from arcgis.features import GeoAccessor, FeatureLayer from arcgis.gis import GIS # Variables url = 'https://kirklandwa.maps.arcgis.com' username = 'user' password = 'pw' hostedTableID = '78e4a92c5c324dd18cc6eee11cb6b2f7' outputCSVFile = r'local path to CSV' # get table from AGOL gis = GIS(url, username, password) CrimeTrendsTable = gis.content.get(hostedTableID) CrimeTrendsTableLyr = CrimeTrendsTable.tables[0] crimeLayer = FeatureLayer(CrimeTrendsTableLyr.url, gis=gis) # Truncate table CrimeTrendsTableLyr.manager.truncate() # import feature class and create slice of the data set in a new dataframe df = pd.DataFrame.spatial.from_featureclass(r"local path of larger feature class from sde") df = df.sort_values(['OFFENSES_YEAR', 'CRIME_STAT_TYPE', 'FROM_DATE'], ascending= [True, True, True], ignore_index=True) df = df.loc[:, ['OFFENSES_YEAR', 'CRIME_STAT_TYPE', 'FROM_DATE']] # set variables for today and the previous 5 years today = datetime.datetime.today() todate1 = today - timedelta(365) todate2 = today - timedelta(730) todate3 = today - timedelta(1095) todate4 = today - timedelta(1460) todate5 = today - timedelta(1825) this_year = datetime.datetime.today().year one_year_ago = this_year - 1 two_years_ago = this_year - 2 three_years_ago = this_year - 3 four_years_ago = this_year - 4 five_years_ago = this_year - 5 # create new dataframes for current and each previous year to date df0 = df.loc[(df['OFFENSES_YEAR']==this_year) & (df['FROM_DATE'] < today)] df1 = df.loc[(df['OFFENSES_YEAR']==one_year_ago) & (df['FROM_DATE'] < todate1)] df2 = df.loc[(df['OFFENSES_YEAR']==two_years_ago) & (df['FROM_DATE'] < todate2)] df3 = df.loc[(df['OFFENSES_YEAR']==three_years_ago) & (df['FROM_DATE'] < todate3)] df4 = df.loc[(df['OFFENSES_YEAR']==four_years_ago) & (df['FROM_DATE'] < todate4)] df5 = df.loc[(df['OFFENSES_YEAR']==five_years_ago) & (df['FROM_DATE'] < todate5)] # create tables for each current and previous year grouped by crime type, add together previous year tables and average table0 = df0.groupby('CRIME_STAT_TYPE')['OFFENSES_YEAR'].count().reset_index()\ .rename(columns={"OFFENSES_YEAR" : this_year}) table1 = df1.groupby('CRIME_STAT_TYPE')['OFFENSES_YEAR'].count() table2 = df2.groupby('CRIME_STAT_TYPE')['OFFENSES_YEAR'].count() table3 = df3.groupby('CRIME_STAT_TYPE')['OFFENSES_YEAR'].count() table4 = df4.groupby('CRIME_STAT_TYPE')['OFFENSES_YEAR'].count() table5 = df5.groupby('CRIME_STAT_TYPE')['OFFENSES_YEAR'].count() avgtable = pd.concat([table1, table2, table3, table4, table5]).groupby('CRIME_STAT_TYPE').mean().reset_index()\ .rename(columns={"OFFENSES_YEAR" : "previous5yearAverage"}) trendstable = avgtable.join(table0.set_index('CRIME_STAT_TYPE'), on='CRIME_STAT_TYPE').fillna(0) trendstable.to_csv(outputCSVFile, sep='\t', encoding='utf-8') # update hosted table from csv file csvDF = GeoAccessor.from_table(outputCSVFile) adds_fs = csvDF.spatial.to_featureset() adds_dict = adds_fs.to_dict() adds = adds_dict["features"] crimeLayer.edit_features(adds=adds)   ... View more

@FredMitchell can you share the service to an AGOL group and invite my account (jskinner_rats)?  I can take a look to see if anything jumps out at me. ... View more

Hi @GeorgeClark , I use the following script to execute the webgisdr.  Windows Task Scheduler executes the script each night, and the script will execute a BAT file to run the webgisdr.  You may want to try this to see if it gives successful results. ... View more

I can't reproduce this.  I'm working with Pro 3.2.2 and a File Geodatabase.  ... View more

@kapalczynski you can run the Calculate Field on the feature layer and the edits will be reflected in the service: # Variables portalURL = 'https://gis.esri.com/portal' username = 'portaladmin' password = 'p0rt@l@dmin1' featureServiceURL = 'https://gis.esri.com/server/rest/services/pipes/FeatureServer/0' whereClause = "Imported = 'No'" # Sign into Portal arcpy.SignInToPortal(portalURL, username, password) # Make Feature Layer arcpy.MakeFeatureLayer_management(featureServiceURL, "fLyr", whereClause) # Calculate Field arcpy.management.CalculateField( in_table="fLyr", field="FLAGFIELD", expression="'YES'", expression_type="PYTHON3", code_block="", field_type="TEXT", enforce_domains="NO_ENFORCE_DOMAINS" ) ... View more

@Tim-Woodfield  I can't say for sure why this is occurring, but if you are working with Portal, it may be just as fast to execute ArcGIS Pro's Delete Features and Append tools. ... View more

I tend to stick to arcpy when the functionality is available in both arcpy and ArcGIS API for Python.  It minimizes the code you will have to write.   For the WHERE clause, you can first create a Feature Layer using the Make Feature Layer tool. ... View more

@Eliot_Reid I had a feeling this may be the case.  SAML is not supported.  If you can, create a built-in Administrator account and use that instead. ... View more