gistfile1.py

# 15 statement in this Fiona script, 12 after I move the prop_type function to Fiona.
# Compare to 31 statements for the ogr.py script at
# http://pcjericks.github.io/py-gdalogr-cookbook/layers.html#create-a-new-shapefile-and-add-data.
# The difference is that Fiona's schema and feature definition are declarative (using dict 
# literals and comprehensions, not imperative (CreateField, SetField, etc) and that Fiona
# is designed to allow concise code.

from csv import DictReader
import fiona
from fiona.crs import from_epsg

# Open a collection for writing.
with fiona.open(
        'volcanoes.shp', 'w', 
        crs=from_epsg(4326), 
        driver='ESRI Shapefile', 
        schema={
            'geometry': 'Point', 
            'properties': {
                'Name': 'str:24', 
                'Region': 'str:24', 
                'Latitude': 'float', 
                'Longitude': 'float', 
                'Elevation': 'float' }}
        ) as output:
    
    # Make a mapping of property names to their Python types. This is used to
    # convert text values from the input to proper Python values.
    ptypes = {k: fiona.prop_type(v) for k, v in output.schema['properties'].items()}
    
    def feature(row):
        """Converts a table row and its index to a Fiona feature dict."""
        geom = {
            'type': 'Point', 
            'coordinates': [float(row['Longitude']), float(row['Latitude'])] }
        props = {k: ptypes[k](v) for k, v in row.items()}
        return {
            'type': 'Feature',
            'geometry': geom, 
            'properties': props }
    
    # Read rows and write all feature records in one go, using the feature()
    # function defined above.
    reader = DictReader(open("volcano_data.txt"), delimiter='\t')
    output.writerecords(map(feature, reader))