Added command arguments: CSV file, output file, CSV columns. Now CSV …

…column order is not fixed but comes from CSV header.

README.md

@@ -5,6 +5,21 @@ This python script takes data in csv format and converts to geoJSON format for u
 
 Two sample CSV documents, sample.csv and country_cap_latlon.csv, are included that can be used to show how the utility works. 
 
-The script currently requires that CSV data be in the format specified in the sample data 'sample.csv', however, this could be easily adapted to fit other formats. 
+By default, the script expects CSV data be in the format specified in the sample data 'sample.csv'. However, you can specify other formats in the program arguments. 
+
+csvToGeoJSON arguments (all optional):
+
+  -h, --help         Show this help message and exit
+  --verbose, --v     Show parameters, detailed messages and geoJSON output
+  --csv CSV          Filepath/name of CVS input file
+                     Default: sample.csv
+  --output OUTPUT    Filepath/name of GeoJSON output file
+                     Default: output.geojson
+  --columns COLUMNS  JSON-formatted dictionary that maps CSV column names to
+                     GeoJSON fields.
+                     Default: "{ 'id':'id', 'latitude':'lat', 'longitude':'lon', 'name':'name', 'value':'pop' }"
+                     where each name:value pair is {geoJSON-column}:{CSV-column}
+                     Note: CSV columns don't have to appear in a particular order since the position of the data columns will be determined from their order in the CSV header (first row).
+                     If CSV contains no ID field, specifying 'id':'-auto-' will automatically generate an ID value based on the row # of the CSV. Otherwise, the ID value will be 0.
 
 Questions and comments to [email protected]

csv/alternative-columns-test.csv

@@ -0,0 +1,4 @@
+pointid,label,lat,long,GDP
+4,Afghanistan,65.216,33.677,250B
+8,Albania,20.068,41.143,315B
+894,Zambia,26.32,-14.614,114B

csvToGeoJSON.py

@@ -1,50 +1,190 @@
 import csv
+import argparse
+import json
 
-# Read in raw data from csv
-rawData = csv.reader(open('sample.csv', 'rb'), dialect='excel')
-
-# the template. where data from the csv will be formatted to geojson
-template = \
-    ''' \
-    { "type" : "Feature",
-        "id" : %s,
-            "geometry" : {
-                "type" : "Point",
-                "coordinates" : ["%s","%s"]},
-        "properties" : { "name" : "%s", "value" : "%s"}
-        },
-    '''
-
-# the head of the geojson file
-output = \
-    ''' \
-{ "type" : "Feature Collection",
-    {"features" : [
-    '''
-
-# loop through the csv by row skipping the first
-iter = 0
-for row in rawData:
-    iter += 1
-    if iter >= 2:
-        id = row[0]
-        lat = row[1]
-        lon = row[2]
-        name = row[3]
-        pop = row[4]
-        output += template % (row[0], row[1], row[2], row[3], row[4])
-
-# the tail of the geojson file
-output += \
-    ''' \
-    ]
-}
-    '''
+#### ========================================================================
+#### csvToGeoJSON
+####  - Tool to convert CSV file of geographic data into
+####    JSON-formatted file of GeoJSON features                 
+#### ========================================================================
+
+class GeoFeature:
+    ''' Object to hold properties of GeoJSON Feature '''
+    def __init__(self):
+        self.id = 0
+        self.latitude = 0
+        self.longitude = 0
+        self.name = "-NA-"
+        self.value = "-NA-"
+    def print(self):
+        print( "{ id = %s, latitude = %s, longitude = %s, name = %s, value = %s }" 
+        % (self.id, self.latitude, self.longitude, self.name, self.value)
+            )
+
+class GeoFeatureColumn:
+    ''' Object to hold mapping of GeoJSON fields to CSV field columns/indexes '''
+    def __init__(self, geoJSONField, CSVName, CSVIndex ):
+        self.geoJSONField = geoJSONField    # name of GeoJSON property
+        self.CSVName = CSVName              # name of CSV column for this property
+        self.CSVIndex = CSVIndex            # index of CSV column for this property
+
+def main():
+
+    # parse program arguments
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--verbose', '--v', action="store_true", help="Show parameters, detailed messages and geoJSON output")
+    parser.add_argument('--csv', type=str, help="Filepath/name of CVS input file", default="sample.csv" )
+    parser.add_argument('--output', type=str, help="Filepath/name of GeoJSON output file", default="output.geojson" )
+    parser.add_argument('--columns',type=str, help="JSON-formatted dictionary that maps CSV column names to GeoJSON fields.", 
+        default="{ 'id': 'id', 'latitude': 'lat', 'longitude': 'lon', 'name': 'name', 'value': 'pop' }")
+    args = parser.parse_args()
+
+    if args.verbose:
+        print( "Arguments:" )
+        print( "  Output = %s" % args.output )
+        print( "  CSV = %s" % args.csv )
+        print( "  Columns = %s" % args.columns )
+        print()
+
+    # parse "columns" argument into dictionary of CSV column names mapped to GeoJSON properties
+    args.columns = args.columns.replace("'","\"")
+    diCSVColumns = json.loads(args.columns)
+    # print ("Columns = %s"  % json.dumps(diCSVColumns))
+
+    # dictionary of all GeoFeatureColumns and their default mapping to CSV columns
+    diGeoColumns = { 
+        "id": GeoFeatureColumn("id","id",-1),
+        "latitude": GeoFeatureColumn("latitude","lat",-1),
+        "longitude": GeoFeatureColumn("longitude","long",-1),
+        "name": GeoFeatureColumn("name","name",-1),
+        "value": GeoFeatureColumn("value","value",-1)
+    }
+
+    # set the CSVNames of all diGeoColumns given in the "columns" argument
+    if ( "id" in diCSVColumns ): diGeoColumns["id"].CSVName = diCSVColumns["id"]
+    if ( "latitude" in diCSVColumns ): diGeoColumns["latitude"].CSVName = diCSVColumns["latitude"]
+    if ( "longitude" in diCSVColumns ): diGeoColumns["longitude"].CSVName = diCSVColumns["longitude"]
+    if ( "name" in diCSVColumns ): diGeoColumns["name"].CSVName = diCSVColumns["name"]
+    if ( "value" in diCSVColumns ): diGeoColumns["value"].CSVName = diCSVColumns["value"]
+
+    errors = [] # list of errors found, if any
+    error = ""
+
+    # Read in raw data from csv
+    rawData = csv.reader(open(args.csv, 'r'), dialect='excel')
+
+    # the template. where data from the csv will be formatted to geojson
+    template = """
+            {   "type" : "Feature",
+                "id" : %s,
+                "geometry" : {
+                    "type" : "Point",
+                    "coordinates" : ["%s","%s"]
+                },
+                "properties" : {
+                    "name" : "%s", 
+                    "value" : "%s" 
+                }
+            }"""
+
+    # the head of the geojson file
+    output = """{ "type" : "Feature Collection",
+    { "features" : ["""
+
+    # loop through the csv by row skipping the first
+    iRow = 0
+    for row in rawData:
+        if iRow == 0: # If first row (CSV header)
+            # determine column indexes of the values we need for GeoJSON
+            iCol = 0
+            if args.verbose: print( "CSV Columns:")
+
+            for col in row:
+                for fld in diGeoColumns:
+                    # if CSV header column matches CSV field, remember this field's index
+                    geoJSONField = ""
+                    if col == diGeoColumns[fld].CSVName:
+                        diGeoColumns[fld].CSVIndex = iCol
+                        geoJSONField = " = geoJSON \"" + diGeoColumns[fld].geoJSONField + "\""
+                        break
+                if args.verbose: print( f'  column[{iCol}] = {quote(col):10}{geoJSONField}' )
+                iCol+=1
+
+            if args.verbose: print()
+
+            # report geoJSON columns that are missing from CSV header as errors
+            for fld in diGeoColumns:
+                if diGeoColumns[fld].CSVIndex < 0: 
+                    error = "No '%s' column in CSV header" % diGeoColumns[fld].geoJSONField
+                    if diGeoColumns[fld].geoJSONField == "id" and diGeoColumns[fld].CSVName == "-auto-":
+                        error += " (using row # since -auto- was specified)"
+                    errors.append(error)
+
+        else:  # if this is a data row
+            # populate a GeoFeature from its corresponding columns in the data row
+            featureRow = GeoFeature()
+
+            # if CSV row contains GeoJSON column, set GeoFeature property to its value
+            # otherwise, property's value is GeoFeature default
+
+            # set GeoFeature.id from CSV column or from row # if set to "-auto-"
+            if diGeoColumns["id"].CSVIndex >= 0: featureRow.id = row[diGeoColumns["id"].CSVIndex]
+            elif diGeoColumns["id"].CSVName == "-auto-": featureRow.id = iRow
+            # set GeoFeature.latitude from CSV column
+            if diGeoColumns["latitude"].CSVIndex >= 0: featureRow.latitude = row[diGeoColumns["latitude"].CSVIndex]
+            # set GeoFeature.longitude from CSV column
+            if diGeoColumns["longitude"].CSVIndex >= 0: featureRow.longitude = row[diGeoColumns["longitude"].CSVIndex]
+            # set GeoFeature.name from CSV column
+            if diGeoColumns["name"].CSVIndex >= 0: featureRow.name = row[diGeoColumns["name"].CSVIndex]
+            # set GeoFeature.value from CSV column
+            if diGeoColumns["value"].CSVIndex >= 0: featureRow.value = row[diGeoColumns["value"].CSVIndex]
+
+            # append comma between features (but not at end)
+            if iRow > 1: output += ","
+
+            # append formated GeoJSON Feature
+            output += template % (
+                    featureRow.id, 
+                    featureRow.latitude, 
+                    featureRow.longitude, 
+                    featureRow.name,
+                    featureRow.value
+                )
+        iRow += 1
+
+    # the tail of the geojson file
+    output += """
+        ]
+    }
+}"""
 
-# opens an geoJSON file to write the output to
-outFileHandle = open("output.geojson", "w")
-outFileHandle.write(output)
-outFileHandle.close()
+    # print any errors that were found
+    if len(errors):
+        print("Errors:")
+        for error in errors:
+            print("  %s" % error)
+        print()
+
+    if args.verbose:
+        print("GeoJSON Output:")
+        print("=========================================================================")
+        print(output)
+        print("=========================================================================")
+
+    # opens an geoJSON file to write the output to
+    outFileHandle = open(args.output, "w")
+    outFileHandle.write(output)
+    outFileHandle.close()
+
+# end main()
+
+# Utility functions
+
+def quote(s):
+    ''' return string argument wrapped in double-quotes '''
+    return "\"" + s + "\""
+
+main()
 
 
 

output/alternative-columns-test.geoJSON

@@ -0,0 +1,38 @@
+{ "type" : "Feature Collection",
+    { "features" : [
+            {   "type" : "Feature",
+                "id" : 1,
+                "geometry" : {
+                    "type" : "Point",
+                    "coordinates" : ["65.216","33.677"]
+                },
+                "properties" : {
+                    "name" : "Afghanistan", 
+                    "value" : "250B" 
+                }
+            },
+            {   "type" : "Feature",
+                "id" : 2,
+                "geometry" : {
+                    "type" : "Point",
+                    "coordinates" : ["20.068","41.143"]
+                },
+                "properties" : {
+                    "name" : "Albania", 
+                    "value" : "315B" 
+                }
+            },
+            {   "type" : "Feature",
+                "id" : 3,
+                "geometry" : {
+                    "type" : "Point",
+                    "coordinates" : ["26.32","-14.614"]
+                },
+                "properties" : {
+                    "name" : "Zambia", 
+                    "value" : "114B" 
+                }
+            }
+        ]
+    }
+}