We will create a python scripts to parse a KML to CSV file. We use the external shared libraries GEOS and GDAL in GeoDjango to perform.

GEOS is a C++ library for performing geometric operations, and is the default internal geometry representation used by GeoDjango.

GDAL stands for Geospatial Data Abstraction Library, and is a veritable “Swiss army knife” of GIS data functionality.

Import Libraries

from django.contrib.gis.gdal import DataSource
from django.contrib.gis.geos import GEOSGeometry
import csv

• DataSource is a wrapper for the OGR data source object that supports reading data from a variety of OGR-supported geospatial file formats and data sources using a simple, consistent interface.
• GEOSGeometry is the base class for all GEOS geometry objects.
• csv implements classes to read and write tabular data in CSV format.

Append data to CSV File

Make a function which append the new row to CSV file.

def writerow_append_csv(csvfile, row):
    with open(csvfile, "a") as output:
        writer = csv.writer(output, lineterminator='\n')
        writer.writerow(row)

Extracting Layer Features from GDAL DataSource

Make a function extracting the layer features (layer_name, geom_type, Name, description) from GDAL DataSource. We only get GEOM type name starts with Point and LineString. Then use writerow_append_csv function to write features to CSV file.

def write_layer_features_to_csv(layer):
    for feat in layer:
        if(feat.geom.geom_type.name.startswith('Point')):
            r_point = []
            r_point += [feat.layer_name,
                        feat.geom.geom_type.name,
                        feat.geom.coords,
                        feat.get('Name'),
                        feat.get('description')]
            # write point to csv
            writerow_append_csv(pointsFile, r_point)
        elif(feat.geom.geom_type.name.startswith('LineString')):
            line_string = []                                     
            line_string += [feat.layer_name,
                            feat.geom.geom_type.name,
                            feat.geom.coords,
                            feat.get('Name'),
                            feat.get('description')]
            # write line string to csv
            writerow_append_csv(lineStringsFile, line_string)
        else:
            print(feat.geom.geom_type.name, feat.get('Name'))    

Iteration via DataSource Layer

pointsFile = "points.csv"
lineStringsFile = "lineStrings.csv"

# define the column header of csv
header =  ['layer_name', 'geom_type', 'coords', 'name', 'description']
for csvfile in [pointsFile, lineStringsFile]:
    with open(csvfile, "w") as output:
        writer = csv.writer(output, lineterminator='\n')
        writer.writerow(header)

source = DataSource('My_KML_File.kml')

# iteration via layer in source if found Point or lineStrings writer it to csv file
for layer in source:
    write_layer_features_to_csv(layer)