first approach to consume foursquare API via search and explore verbs

offset-range-top-venues.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Sat Jun 20 15:23:29 2015
+
+@author: daviz
+"""
+
+import foursquare as fq
+import json
+import csv
+import os
+
+# Construct the client object
+
+client = fq.Foursquare(client_id = os.environ.get('FOURSQUARE_CLIENT_ID'),
+                       client_secret = os.environ.get('FOURSQUARE_CLIENT_SECRET'))
+
+
+# print json.dumps(response['groups'] ,indent=2, separators=(',', ': '))
+offset_range= range(0,11,1)
+with open('dataset/offset_top_venues.csv', 'w') as csvfile:
+    fieldnames = ['name', 'rating', 'price', 'phone', 'city', 'merchant_zipcode',
+                  'address', 'latitude', 'longitude', 'category']
+    writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
+    writer.writeheader()
+
+    for offset in offset_range:
+        response = client.venues.explore(params= {'ll': '41.3879, 2.1699',
+                                          'offset': str(offset),
+                                          'limit': '50'})
+        for groups in response['groups']:
+            for group in groups['items']:
+                venue = group['venue']
+                venue_row = { 'name': None, 'rating': None, 'price': None, 'phone': None,
+                          'city': None, 'merchant_zipcode': None, 'address': None,
+                          'latitude': None, 'longitude': None, 'category': None }
+                venue_row['name'] = venue['name']
+                if 'rating' in venue:
+                    venue_row['rating'] = venue['rating']
+                if 'price' in venue:
+                     #1 is < $10 an entree, 2 is $10-$20 an entree, 3 is $20-$30 an entree, 4 is > $30
+                    venue_row['price'] = venue['price']['tier']
+                if 'phone' in venue['contact']:
+                    venue_row['phone']= venue['contact']['phone']
+                if 'city' in venue['location']:
+                    venue_row['city'] = venue['location']['city']
+                if 'postalCode' in venue['location']:
+                    venue_row['merchant_zipcode'] = venue['location']['postalCode']
+                if 'address' in venue['location']:
+                    venue_row['address'] = venue['location']['address']
+                if 'lat' in venue['location']:
+                    venue_row['latitude'] = venue['location']['lat']
+                if 'lng' in venue['location']:
+                    venue_row['longitude'] = venue['location']['lng']
+                for categories in venue['categories']:
+                    category_list = []
+                    if 'name' in categories:
+                        category_list.append(categories['name'])
+                    venue_row['category'] = ",".join(category_list)
+
+                writer.writerow(venue_row)

search_venues.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Sat Jun 20 15:23:29 2015
+
+@author: daviz
+"""
+
+import foursquare as fq
+import json
+import csv
+import os
+
+# Construct the client object
+
+client = fq.Foursquare(client_id = os.environ.get('FOURSQUARE_CLIENT_ID'),
+                       client_secret = os.environ.get('FOURSQUARE_CLIENT_SECRET'))
+
+
+# Must provide parameters (ll and radius) or (sw and ne) or (near and radius)
+
+
+# print json.dumps(response['groups'] ,indent=2, separators=(',', ': '))
+offset_range= range(0,11,1)
+with open('dataset/venues_search.csv', 'w') as csvfile:
+    fieldnames = ['name', 'rating', 'price', 'phone', 'city', 'merchant_zipcode',
+                  'address', 'latitude', 'longitude', 'category']
+    writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
+    writer.writeheader()
+    #'ne': "41.443441, 2.184005", 'sw': '41.353175, 2.147098'
+    for offset in offset_range:
+        response = client.venues.search(params= {'ll': '41.3879, 2.1699', 'radius': '10000',
+                                             'intent': 'browse', 'llAcc': '10', 'limit': '10',
+                                             'offset': str(offset) })
+
+        for venue in response['venues']:
+            venue_row = { 'name': None, 'rating': None, 'price': None, 'phone': None,
+                      'city': None, 'merchant_zipcode': None, 'address': None,
+                      'latitude': None, 'longitude': None, 'category': None }
+            venue_row['name'] = venue['name']
+            if 'rating' in venue:
+                venue_row['rating'] = venue['rating']
+            if 'price' in venue:
+                 #1 is < $10 an entree, 2 is $10-$20 an entree, 3 is $20-$30 an entree, 4 is > $30
+                venue_row['price'] = venue['price']['tier']
+            if 'phone' in venue['contact']:
+                venue_row['phone']= venue['contact']['phone']
+            if 'city' in venue['location']:
+                venue_row['city'] = venue['location']['city']
+            if 'postalCode' in venue['location']:
+                venue_row['merchant_zipcode'] = venue['location']['postalCode']
+            if 'address' in venue['location']:
+                venue_row['address'] = venue['location']['address']
+            if 'lat' in venue['location']:
+                venue_row['latitude'] = venue['location']['lat']
+            if 'lng' in venue['location']:
+                venue_row['longitude'] = venue['location']['lng']
+            for categories in venue['categories']:
+                category_list = []
+                if 'name' in categories:
+                    category_list.append(categories['name'])
+                venue_row['category'] = ",".join(category_list)
+
+            writer.writerow(venue_row)

top_venues.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Sat Jun 20 15:23:29 2015
+
+@author: daviz
+"""
+
+import foursquare as fq
+#import json
+import csv
+import os
+import pandas as pd
+
+# Construct the client object
+os.environ.get('FOURSQUARE_CLIENT_ID')
+client = fq.Foursquare(client_id = os.environ.get('FOURSQUARE_CLIENT_ID'),
+                       client_secret = os.environ.get('FOURSQUARE_CLIENT_SECRET'))
+
+bcn_zipcodes = ['08001', '08002', '08003', '08004', '08005', '08006', '08007',
+                '08008', '08009', '08010', '08011', '08012', '08013', '08014',
+                '08015', '08016', '08017', '08018', '08019', '08020', '08021',
+                '08022', '08023', '08024', '08025', '08026', '08027', '08028',
+                '08029', '08030', '08031', '08032', '08033', '08034', '08035',
+                '08036', '08037', '08038', '08039', '08040', '08041', '08042']
+
+# print json.dumps(response['groups'] ,indent=2, separators=(',', ': '))
+
+with open('dataset/top_venues.csv', 'w') as csvfile:
+    fieldnames = ['name', 'rating', 'price', 'phone', 'city', 'merchant_zipcode',
+                  'address', 'latitude', 'longitude', 'category']
+    writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
+    writer.writeheader()
+    for zipcode in bcn_zipcodes:
+        response = client.venues.explore(params= {'near': zipcode + ", Barcelona, Cataluña", 'limit': 50})
+        for groups in response['groups']:
+            for group in groups['items']:
+                venue = group['venue']
+                venue_row = { 'name': None, 'rating': None, 'price': None, 'phone': None,
+                          'city': None, 'merchant_zipcode': None, 'address': None,
+                          'latitude': None, 'longitude': None, 'category': None }
+                venue_row['name'] = venue['name']
+                if 'rating' in venue:
+                    venue_row['rating'] = venue['rating']
+                if 'price' in venue:
+                     #1 is < $10 an entree, 2 is $10-$20 an entree, 3 is $20-$30 an entree, 4 is > $30
+                    venue_row['price'] = venue['price']['tier']
+                if 'phone' in venue['contact']:
+                    venue_row['phone']= venue['contact']['phone']
+                if 'city' in venue['location']:
+                    venue_row['city'] = venue['location']['city']
+                if 'postalCode' in venue['location']:
+                    venue_row['merchant_zipcode'] = venue['location']['postalCode']
+                if 'address' in venue['location']:
+                    venue_row['address'] = venue['location']['address']
+                if 'lat' in venue['location']:
+                    venue_row['latitude'] = venue['location']['lat']
+                if 'lng' in venue['location']:
+                    venue_row['longitude'] = venue['location']['lng']
+                for categories in venue['categories']:
+                    category_list = []
+                    if 'name' in categories:
+                        category_list.append(categories['name'])
+                    venue_row['category'] = ",".join(category_list)
+
+                writer.writerow(venue_row)
+top_venues = pd.read_csv("dataset/top_venues.csv")
+top_venues.drop_duplicates(inplace=True)
+top_venues.to_csv("dataset/top_venues.csv")