python如何解决从json字典中提取时的KeyError

{'meta': {'code': 200, 'requestId': '5e4330219fcb92001bd8a847'}, 'response': {'warning': {'text': 'There aren\'t a lot of results for "(\'Bookstore\', \'Comic Shop\', \'Used Bookstore\', \'Library\')." Try something more general, reset your filters, or expand the search area.'}, 'headerLocation': 'University Park', 'headerFullLocation': 'University Park, Portland', 'headerLocationGranularity': 'neighborhood', 'query': 'bookstore comic shop used bookstore library', 'totalResults': 0, 'suggestedBounds': {'ne': {'lat': 45.5830000045, 'lng': -122.72538279609336}, 'sw': {'lat': 45.573999995499996, 'lng': -122.73821720390666}}, 'groups': [{'type': 'Recommended Places', 'name': 'recommended', 'items': []}]}}

{'meta': {'code': 200, 'requestId': '5e4335769da7ee001b203b56'}, 'response': {'warning': {'text': 'There aren\'t a lot of results for "(\'Bookstore\', \'Comic Shop\', \'Used Bookstore\', \'Library\')." Try something more general, reset your filters, or expand the search area.'}, 'headerLocation': 'Cathedral Park', 'headerFullLocation': 'Cathedral Park, Portland', 'headerLocationGranularity': 'neighborhood', 'query': 'bookstore comic shop used bookstore library', 'totalResults': 2, 'suggestedBounds': {'ne': {'lat': 45.5928000045, 'lng': -122.7515716757994}, 'sw': {'lat': 45.583799995499994, 'lng': -122.76440832420062}}, 'groups': [{'type': 'Recommended Places', 'name': 'recommended', 'items': [{'reasons': {'count': 0, 'items': [{'summary': 'This spot is popular', 'type': 'general', 'reasonName': 'globalInteractionReason'}]}, 'venue': {'id': '5632a8dc498e5636877e4fa3', 'name': 'Comic Cave PDX', 'location': {'address': '1920 N. Kirkpatrick', 'crossStreet': 'Denver', 'lat': 45.59002437301252, 'lng': -122.75552067488051, 'labeledLatLngs': [{'label': 'display', 'lat': 45.59002437301252, 'lng': -122.75552067488051}], 'distance': 271, 'postalCode': '97217', 'cc': 'US', 'city': 'Portland', 'state': 'OR', 'country': 'United States', 'formattedAddress': ['1920 N. Kirkpatrick (Denver)', 'Portland, OR 97217', 'United States']}, 'categories': [{'id': '52f2ab2ebcbc57f1066b8b18', 'name': 'Comic Shop', 'pluralName': 'Comic Shops', 'shortName': 'Comic Shop', 'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/comic_', 'suffix': '.png'}, 'primary': True}], 'photos': {'count': 0, 'groups': []}}, 'referralId': 'e-0-5632a8dc498e5636877e4fa3-0'}, {'reasons': {'count': 0, 'items': [{'summary': 'This spot is popular', 'type': 'general', 'reasonName': 'globalInteractionReason'}]}, 'venue': {'id': '5d617b8e228cfc0008fb1f9f', 'name': 'Two Rivers Bookstore', 'location': {'address': '8836 N Lombard St', 'lat': 45.591434, 'lng': -122.75648600000001, 'labeledLatLngs': [{'label': 'display', 'lat': 45.591434, 'lng': -122.75648600000001}], 'distance': 368, 'postalCode': '97203', 'cc': 'US', 'city': 'Portland', 'state': 'OR', 'country': 'United States', 'formattedAddress': ['8836 N Lombard St', 'Portland, OR 97203', 'United States']}, 'categories': [{'id': '4bf58dd8d48988d114951735', 'name': 'Bookstore', 'pluralName': 'Bookstores', 'shortName': 'Bookstore', 'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/bookstore_', 'suffix': '.png'}, 'primary': True}], 'photos': {'count': 0, 'groups': []}}, 'referralId': 'e-0-5d617b8e228cfc0008fb1f9f-1'}]}]}}

def getNearbyVenues(names, latitudes, longitudes, limit=500): venues_list=[] for name, lat, lng in zip(names, latitudes, longitudes): print(name) url = 'https://api.foursquare.com/v2/venues/explore?&client_id={}&client_secret={}&ll={},{}&v={}&query={}&radius={}&limit={}'.format( CLIENT_ID, CLIENT_SECRET, VERSION, lat, lng, query, radius, LIMIT) try: results = requests.get(url, "none").json()['response']['groups'][0]['items'] venues_list.extend([( name, lat, lng, v['venue']['name'], v['venue']['location']['lat'], v['venue']['location']['lng'], v['venue']['categories'][0]['name']) for v in results]) except KeyError: venues_list.extend([( name, lat, lng, np.nan, np.nan, np.nan, np.nan)]) nearby_venues = pd.DataFrame(venues_list, columns = ['Neighborhood', 'Neighborhood Latitude', 'Neighborhood Longitude', 'Venue', 'Venue Latitude', 'Venue Longitude', 'Venue Category']) return(nearby_venues)

--------------------------------------------------------------------------- KeyError Traceback (most recent call last) <ipython-input-16-66be6cf8c7d3> in <module> 1 PDX_venues = getNearbyVenues(names=PDX_NeighDF['Neighborhood'], 2 latitudes=PDX_NeighDF['Latitude'], ----> 3 longitudes=PDX_NeighDF['Longitude'] 4 ) 5 <ipython-input-15-dab42c6d540d> in getNearbyVenues(names, latitudes, longitudes, limit) 15 16 #try: ---> 17 results = requests.get(url, "none").json()['response']['groups'][0]['items'] 18 19 KeyError: 'groups'

PDX_venues = getNearbyVenues(names=PDX_NeighDF['Neighborhood'], latitudes=PDX_NeighDF['Latitude'], longitudes=PDX_NeighDF['Longitude'] ) PDX_venues.head() output: (structured in a pandas df normally) Neighborhood Neighborhood Latitude Neighborhood Longitude Venue Venue Latitude Venue Longitude Venue Category 0 CATHEDRAL PARK 45.58830 -122.75799 NaN NaN NaN NaN 1 UNIVERSITY PARK 45.57850 -122.73180 NaN NaN NaN NaN 2 PIEDMONT 45.56510 -122.66820 NaN NaN NaN NaN 3 WOODLAWN 45.56970 -122.65240 NaN NaN NaN NaN 4 ARBOR LODGE 45.57354 -122.69240 NaN NaN NaN NaN

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1楼 · 发布于 2024-06-17 08:11:24

有几种不同的选择

访问dict时，可以在dict上使用get函数。此函数提取值，但也可以设置默认值

results = requests.get(url, "none").json().get('response', {})('groups', [])

但是Python并没有列表的等价物，所以在这种情况下，您必须编写一些if语句来查看列表是否有要提取的元素

另一个选择是增加更多的支票，如果该项目不存在，则尽早退出

jsonBlob = requests.get(url, "none").json()
if 'response' not in jsonBlob or 'groups' not in jsonBlob['response']:
    return False

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