v1.2 released! This closes #2, #7 and #8.

.gitignore

@@ -13,4 +13,6 @@ Thumbs.db
 *.pyc
 admin1CodesASCII.txt
 admin2Codes.txt
-cities1000.zip
+cities1000.zip
+.python-version
+__pycache__

README.md

@@ -2,7 +2,7 @@ Reverse Geocoder
 =================
 A Python library for offline reverse geocoding. It improves on an existing library called [reverse_geocode](https://pypi.python.org/pypi/reverse_geocode/1.0) developed by [Richard Penman](https://bitbucket.org/richardpenman/reverse_geocode).
 
-*Update*: v1.1 released! Python 3 not supported still.
+*UPDATE*: v1.2 released with Python3 support and more accurate geocoding! See release notes below.
 
 ### About
 Ajay Thampi | [@thampiman](https://twitter.com/thampiman) | [opensignal.com](http://opensignal.com) | [ajaythampi.com](http://ajaythampi.com)
@@ -14,13 +14,22 @@ Ajay Thampi | [@thampiman](https://twitter.com/thampiman) | [opensignal.com](htt
 The K-D tree is populated with cities that have a population > 1000. The source of the data is [GeoNames](http://download.geonames.org/export/dump/).
 
 ## Installation
+For first time installation use,
 ```
 $ pip install reverse_geocoder
 ```
 
+Or upgrade an existing installation using,
+```
+$ pip install --upgrade reverse_geocoder
+```
+
 Package can be found on [PyPI](https://pypi.python.org/pypi/reverse_geocoder/).
 
-*Update*: v1.1 released containing [Brandon](https://github.com/bdon)'s and [David](https://github.com/DavidJFelix)'s fixes
+### Release Notes
+1. v1.0 - First version with support for only Python2
+2. v1.1 - Fix for issue [#1](https://github.com/thampiman/reverse-geocoder/issues/1) by [Brandon](https://github.com/bdon)
+3. v1.2 - Support for Python 3, conversion of [Geodetic](http://en.wikipedia.org/wiki/Geodetic_datum) coordinates to [ECEF](http://en.wikipedia.org/wiki/ECEF) for use in K-D trees to find nearest neighbour using the Euclidean distance function. This release fixes issues [#2](https://github.com/thampiman/reverse-geocoder/issues/2) and [#8](https://github.com/thampiman/reverse-geocoder/issues/8). Special thanks to [David](https://github.com/DavidJFelix) for his help in partly fixing [#2](https://github.com/thampiman/reverse-geocoder/issues/2).
 
 ## Usage
 The library supports two modes:
@@ -31,7 +40,7 @@ The library supports two modes:
 ```python
 import reverse_geocoder as rg
 
-coordinates = (51.5214588,-0.1729636),(13.9280531,100.3735803)
+coordinates = (51.5214588,-0.1729636),(9.936033, 76.259952),(37.38605,-122.08385)
 
 results = rg.search(coordinates) # default mode = 2
 
@@ -40,18 +49,24 @@ print results
 
 The above code will output the following:
 ```
-	[{'admin1': 'England',
-  	  'admin2': 'Greater London',
-  	  'cc': 'GB',
-  	  'lat': '51.51116',
-  	  'lon': '-0.18426',
-  	  'name': 'Bayswater'},
- 	 {'admin1': 'Nonthaburi',
-  	  'admin2': '',
-  	  'cc': 'TH',
-  	  'lat': '13.91783',
-  	  'lon': '100.42403',
-  	  'name': 'Bang Bua Thong'}]
+	[{'name': 'Barbican', 
+	  'cc': 'GB', 
+	  'lat': '51.51988',
+	  'lon': '-0.09446', 
+	  'admin1': 'England', 
+	  'admin2': 'Greater London'}, 
+	 {'name': 'Cochin', 
+	  'cc': 'IN', 
+	  'lat': '9.93988',
+	  'lon': '76.26022', 
+	  'admin1': 'Kerala', 
+	  'admin2': 'Ernakulam'},
+	 {'name': 'Mountain View', 
+	  'cc': 'US', 
+	  'lat': '37.38605',
+	  'lon': '-122.08385', 
+	  'admin1': 'California', 
+	  'admin2': 'Santa Clara County'}]
 ```
 
 If you'd like to use the single-threaded K-D tree, set mode = 1 as follows:

README.txt

@@ -6,6 +6,8 @@ This library improves on an existing library called reverse_geocode developed by
 2. The performance is much faster since a parallelized K-D tree is implemeneted 
 (See https://github.com/thampiman/reverse-geocoder for performance comparison)
 
+Supports Python 2 and 3.
+
 Example usage:
     >>> import reverse_geocoder as rg
     >>> coordinates = (51.5214588,-0.1729636),(13.9280531,100.3735803)
@@ -21,4 +23,4 @@ Example usage:
   	  'cc': 'TH',
   	  'lat': '13.91783',
   	  'lon': '100.42403',
-  	  'name': 'Bang Bua Thong'}]
+  	  'name': 'Bang Bua Thong'}]

reverse_geocoder/__init__.py

@@ -5,14 +5,11 @@
 import os
 import sys
 import csv
-csv.field_size_limit(sys.maxint)
-import urllib
+csv.field_size_limit(sys.maxsize)
 import zipfile
-import collections
 from scipy.spatial import cKDTree as KDTree
-import time
-import cKDTree_MP as KDTree_MP
-import multiprocessing as mp
+from reverse_geocoder import cKDTree_MP as KDTree_MP
+import numpy as np
 
 GN_URL = 'http://download.geonames.org/export/dump/'
 GN_CITIES1000 = 'cities1000'
@@ -59,6 +56,9 @@
 
 RG_FILE = 'rg_cities1000.csv'
 
+A = 6378.137 # major axis in kms
+E2 = 0.00669437999014
+
 def singleton(cls):
     instances = {}
     def getinstance(mode=2):
@@ -92,7 +92,7 @@ def query(self,coordinates):
     def extract(self,local_filename):
         if os.path.exists(local_filename):
             print('Loading formatted geocoded file...')
-            rows = csv.DictReader(open(local_filename,'rb'))
+            rows = csv.DictReader(open(local_filename,'rt'))
         else:
             gn_cities1000_url = GN_URL + GN_CITIES1000 + '.zip'
             gn_admin1_url = GN_URL + GN_ADMIN1
@@ -103,29 +103,37 @@ def extract(self,local_filename):
 
             if not os.path.exists(cities1000_zipfilename):
                 print('Downloading files from Geoname...')
-                urllib.urlretrieve(gn_cities1000_url,cities1000_zipfilename)
-                urllib.urlretrieve(gn_admin1_url,GN_ADMIN1)
-                urllib.urlretrieve(gn_admin2_url,GN_ADMIN2)
+                try: # Python 3
+                    import urllib.request
+                    urllib.request.urlretrieve(gn_cities1000_url,cities1000_zipfilename)
+                    urllib.request.urlretrieve(gn_admin1_url,GN_ADMIN1)
+                    urllib.request.urlretrieve(gn_admin2_url,GN_ADMIN2)
+                except ImportError: # Python 2
+                    import urllib
+                    urllib.urlretrieve(gn_cities1000_url,cities1000_zipfilename)
+                    urllib.urlretrieve(gn_admin1_url,GN_ADMIN1)
+                    urllib.urlretrieve(gn_admin2_url,GN_ADMIN2)
+
 
             print('Extracting cities1000...')
             z = zipfile.ZipFile(open(cities1000_zipfilename,'rb'))
             open(cities1000_filename,'wb').write(z.read(cities1000_filename))
 
             print('Loading admin1 codes...')
             admin1_map = {}
-            t_rows = csv.reader(open(GN_ADMIN1,'rb'),delimiter='\t')
+            t_rows = csv.reader(open(GN_ADMIN1,'rt'),delimiter='\t')
             for row in t_rows:
                 admin1_map[row[ADMIN_COLUMNS['concatCodes']]] = row[ADMIN_COLUMNS['asciiName']]
 
             print('Loading admin2 codes...')
             admin2_map = {}
-            for row in csv.reader(open(GN_ADMIN2,'rb'),delimiter='\t'):
+            for row in csv.reader(open(GN_ADMIN2,'rt'),delimiter='\t'):
                 admin2_map[row[ADMIN_COLUMNS['concatCodes']]] = row[ADMIN_COLUMNS['asciiName']]
 
             print('Creating formatted geocoded file...')
-            writer = csv.DictWriter(open(local_filename,'wb'),fieldnames=RG_COLUMNS)
+            writer = csv.DictWriter(open(local_filename,'wt'),fieldnames=RG_COLUMNS)
             rows = []
-            for row in csv.reader(open(cities1000_filename,'rb'),delimiter='\t',quoting=csv.QUOTE_NONE):
+            for row in csv.reader(open(cities1000_filename,'rt'),delimiter='\t',quoting=csv.QUOTE_NONE):
                 lat = row[GN_COLUMNS['latitude']]
                 lon = row[GN_COLUMNS['longitude']]
                 name = row[GN_COLUMNS['asciiName']]
@@ -154,26 +162,46 @@ def extract(self,local_filename):
             os.remove(cities1000_filename)
 
         # Load all the coordinates and locations
-        coordinates,locations = [],[]
+        geo_coords,locations = [],[]
         for row in rows:
-            coordinates.append((row['lat'],row['lon']))
+            geo_coords.append((row['lat'],row['lon']))
             locations.append(row)
-        return coordinates,locations
+        ecef_coords = geodetic_in_ecef(geo_coords)
+        return ecef_coords,locations
+
+def geodetic_in_ecef(geo_coords):
+    geo_coords = np.asarray(geo_coords).astype(np.float)
+    lat = geo_coords[:,0]
+    lon = geo_coords[:,1]
+
+    lat_r = np.radians(lat)
+    lon_r = np.radians(lon)
+    normal = A / (np.sqrt(1 - E2*(np.sin(lat_r) ** 2)))
+    x = normal * np.cos(lat_r) * np.cos(lon_r)
+    y = normal * np.cos(lat_r) * np.sin(lon_r)
+    z = normal * (1 - E2) * np.sin(lat)
+    return np.column_stack([x,y,z])
 
 def rel_path(filename):
     return os.path.join(os.getcwd(), os.path.dirname(__file__), filename)
 
-def get(coordinate,mode=2):
+def get(geo_coord,mode=2):
     rg = RGeocoder(mode=mode)
-    return rg.query([coordinate])[0]
+    return rg.query(geodetic_in_ecef([geo_coord]))[0]
 
-def search(coordinates,mode=2):
+def search(geo_coords,mode=2):
     rg = RGeocoder(mode=mode)
-    return rg.query(coordinates)
+    return rg.query(geodetic_in_ecef(geo_coords))
 
 if __name__ == '__main__':
+    print('Testing single coordinate...')
+    city = (37.38605,-122.08385)
+    print('Reverse geocoding 1 city...')
+    result = get(city)
+    print(result)
+
     print('Testing coordinates...')
-    cities = [(-37.81, 144.96),(31.76, 35.21)]
-
+    cities = [(51.5214588,-0.1729636),(9.936033, 76.259952),(37.38605,-122.08385)]
     print('Reverse geocoding %d cities...' % len(cities))
     results = search(cities)
+    print(results)

reverse_geocoder/cKDTree_MP.py

@@ -82,7 +82,7 @@ def pquery(self,x_list,k=1,eps=0,p=2,
         for p in pool: p.start()
         for p in pool: p.join()
         if ierr.value != 0:
-            raise RuntimeError, ('%d errors in worker processes' % (ierr.value))
+            raise RuntimeError('%d errors in worker processes' % (ierr.value))
 
         return _d.copy(),_i.astype(int).copy()
 
@@ -98,7 +98,7 @@ def __init__(self,ndata,nprocs):
     def __iter__(self):
         return self
 
-    def next(self):
+    def next(self): # Python 2 support
         self._lock.acquire()
         ndata = self._ndata.value
         start = self._start.value
@@ -117,4 +117,26 @@ def next(self):
             return slice(s0, s1)
         else:
             self._lock.release()
-            raise StopIteration 
+            raise StopIteration  
+
+    def __next__(self): # Python 3 support
+        self._lock.acquire()
+        ndata = self._ndata.value
+        start = self._start.value
+        chunk = self._chunk 
+        if ndata:
+            if chunk > ndata:
+                s0 = start
+                s1 = start + ndata
+                self._ndata.value = 0
+            else:
+                s0 = start
+                s1 = start + chunk
+                self._ndata.value = ndata - chunk
+                self._start.value = start + chunk
+            self._lock.release()
+            return slice(s0, s1)
+        else:
+            self._lock.release()
+            raise StopIteration 
+