The InsertCursor() function is used to create an InsertCursor object that allows you to programmatically add new records to feature classes and tables. The insertRow() method on the InsertCursor object adds the row. A row, in the form of a list or tuple, is passed into the insertRow() method. The values in the list must correspond to the field values defined when the InsertCursor object was created. Just as with the other types of cursors, you can also limit the field names returned using the second parameter of the method. This function supports geometry tokens as well.

The following code example illustrates how you can use InsertCursor to insert new rows into a feature class. Here, we are inserting two new wildfire points into the California feature class. The row values to be inserted are defined in a list variable. Then, an InsertCursor object is created, passing in the feature class and fields. Finally, the new rows are inserted into the feature class using the insertRow() method:

rowValues = [{'Bastrop','N',3000,(-105.345,32.234)),('Ft Davis','N', 456, (-109.456,33.468))]
fc = "c:/data/wildfires.gdb/California"
fields["FIRE_NAME", "FIRE_CONTAINED", "ACRES", "SHAPE@XY"]
with arcpy.da.InsertCursor(fc, fields) as cursor:
  for row in rowValues:
    cursor.insertRow(row)

In this recipe, you will use InsertCursor to add wildfires retrieved from a text file into a point feature class. When inserting rows into a feature class, you will need to know how to add the geometric representation of a feature into the feature class. This can be accomplished using InsertCursor along with two miscellaneous objects: Array and Point. In this exercise, we will add point features in the form of wildfire incidents to an empty point feature class. In addition, you will use Python file manipulation techniques to read the coordinate data from a text file.

We will be importing North American wildland fire incident data from a single day in October, 2007. This data is contained in a comma-delimited text file containing one line for each fire incident on that particular day. Each fire incident has a latitude/longitude coordinate pair separated by commas along with a confidence value. This data was derived by automated methods that use remote sensing data to derive the presence or absence of a wildfire. Confidence values can range from 0 to 100. Higher numbers represent a greater confidence that this is indeed a wildfire:

Some additional explanation may be needed here. The lstFires variable contains a list of all the wildfires that were contained in the comma-delimited text file. The for statement will loop through each of these records one by one, inserting each individual record into the fire variable. We also include an if statement that is used to skip the first record in the file, which serves as the header. As I explained earlier, we then pull out the individual latitude, longitude, and confidence value items from the vals variable, which is just a Python list object and assign them to variables called latitude, longitude, and confid. We then place these values into a new list variable called rowValue in the order that we defined when we created InsertCursor. That is, the latitude and longitude pair should be placed first, followed by the confidence value. Finally, we call the insertRow() function on the InsertCursor object assigned to the variable cur, passing in the new rowValue variable. We close by printing a message that indicates the progress of the script and also creating our except and finally blocks to handle errors and close the text file. Placing the file.close() method in the finally block ensures that it will execute, and close the file, even if there is an error in the previous try statement.