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You code seems pretty close: max_value = -99999999 with arcpy.da.SearchCursor(centerline, "SAMPINS") as cursor: for row in cursor: max_value = max(int(row[0]), max_value) # do something w …

This is the same problem as covered in Arcpy: MakeFeatureLayer_management: Where is the file? …

You don't need to use selections in your search cursor, you can grab the geometry of each feature in FC1: with arcpy.da.SearchCursor(fc1, ["SHAPE@", "MY_DEBUG_FIELD", "SOME_OTHER_FIELD") as searc …

arcpy.Exists tells you if a dataset exists somewhere. Starting with a dictionary of default values, you could update the dictionary where a value exists in your table, then create the output list in …

I'm not sure why it works once, but I think the problem has something to do with that df.zoomToSelectedFeatures() zooms to features that are selected inside the dataframe. But if NP_Allowances is als …

Based on your description are you looking for Get Count? Returns the total number of rows for a table. If the input is a layer or table view containing a selected set of records, only the select …

If you want to do something like getValue() with arcpy.da cursors, you can do something like this: mylist = [] with arcpy.da.SearchCursor(FC, '*') as rows: idx = rows.fields.index("Coolfield") …

import arcpy arcpy.env.overwriteOutput=True arcpy.env.workspace = "Database Connections\\CNTM_MAC_GIS(EPRD-SHS12-LTR,62246).sde" arcpy.MakeFeatureLayer_management("CMTEN_MAC_GIS.dbo.tben_SCSGPSData", … gps_points')[0], 'points selected' saved_to="W:\MAC\GIS\Client_Requests\Stats\gps.gdb\gpspoints" arcpy.CopyFeatures_management("gps_points", saved_to) print "done" Or maybe this approach: import arcpy …

When working with arcpy cursors it's often easier to just grab all the records and work with the data using basic Python functions. … Note: I don't have Arc anymore so I wrote this example from memory and some of the arcpy-specific code might not be right. …

In this type of analysis it can be nice to jump out of nested cursors and buffers and work directly on the data with a spatial index. In doing similar work I've found that using the rtree library cuts …

Lack of a spatial index. You're evaluating every point for intersection whether or not it's likely to be a candidate. If you want to do it in Python, you should use something like Rtree to quickly we …

Unless you need to skip a row, row1 = cursor1.next() isn't needed when you're already in a loop like for row1 in cursor1:. The loop will automatically go to the next record for you. Next problem is t …

An alternative to doing the looping would be to use a sql query in one of the search cursors (untested): with arcpy.da.InsertCursor(newtable_path) as output_cursor: with arcpy.da.SearchCursor(sta …

I suspect it doesn't run on OID #3 because when it joins the statistics table on OID #2 the field names get modified internally. Try removing the join in your cleanup step. If you don't need the sele …

You might be able to convert the table to a numpy array: import numpy ... np = arcpy.da.TableToNumPyArray("distanceTable", ["Distance"]) buffer_distance= np["Distance"].max()