Select by Attribute and Calculate from old AML

AmyDoyle

Hello,

I am not a person who works with Python but I am trying to convert an old AML into Python. Right now I am going line by line in the command prompt to see what works and then save that to a file.  What i need to do is a simple select by attribute and calculate an item based on the selected set. Is there no straight forward way to do this?  I am in v 10.1 if that matters.

the original AML querry and calc was simple
Select: >= 30 AND (( [PF] is null ) AND  ( [MC] = 300 ))
Calc: [PF] = 'Char'


To attempt to duplicate this in Python, I've done the following:

import arcpy
FPlan = "C:\\path\<mine>.mdb\\FP
arcpy.MakeFeatureLayer_management = (FPlan, "F")
arcpy.SelectLayerByAttribute_management ("F", "NEW_SELECTION", " >= 30 AND ( [PF] = '' AND [MC] = 300) ")
- I think this is selecting items, all it returns is <Result 'F'>

arcpy.CalculateField_management(calcF, "P", "Char")
-and this statement errors out.


Please, can anyone tell me how to determin if A) features are selected and how to correctly calc the selected set into the
item .

Thank you very much!
Amy

curtvprice

the original AML querry and calc was simple
Select:

>= 30 AND (( [PF] is null ) AND  ( [MC] = 300 ))
Calc: [PF] = 'Char'

Amy,

I knew AML. AML was a friend of mine. This is not AML. Avenue, VBA maybe?

Please, can anyone tell me how to determin if A) features are selected and how to correctly calc the selected set into the
item

.

Here's a direct answer to your question

arcpy.env.workspace = "myfile.mdb" 
pvar = arcpy.AddFieldDelimeters("P") # 
 for mdb, "P" otherwise
pfvar = arcpy.AddFieldDelimeters("PF")
mcvar = arcpy.AddFieldDelimeters("MC")
where = '{0} > 30 AND (({1} IS NULL) AND ({2} = 300))'.format(pvar,pfvar,mcvar)
lyr = arcpy.MakeFeatureLayer_management(features, "lyr", where)
result = arcpy.GetCount_management(lyr)
nselect = int(result.getOutput(0))
print str(nselect), " selected"
arcpy.CalculateField_management(lyr, "P", "'Char'", "PYTHON_9.3")
arcpy.Delete_management(lyr) # clean up