import pip
import numpy as np
import pandas as pd
from pandas.io.json import json_normalize
# In[6]:
pip.main(["install", "yelp3"])
# In[19]:
from yelp3.client import Client
apikey = 'FGMU22xaV1_98Pwz4dJTmJ9CGiQqQcRVRXFA22B--jnc5GbG6H0fwAXv_NC43G-7vQ3STBQQOljpWpeD776KItOFdeEte5Vj7Ps71Ox2pinPS_tUGTmg80qemx2PWnYx'
api = Client(apikey)
# In[20]:
params = {'term': 'Indian', 'limit': 50, 'offset': 0}
val = api.business_search(location='New Jersey', **params)
df = json_normalize(val, 'businesses')
df2 = json_normalize(val)
# In[21]:
#pip.main(['install','uszipcode'])
from uszipcode import ZipcodeSearchEngine
search = ZipcodeSearchEngine()
res = search.by_state(state='New Jersey', returns=0)
import numpy as np
import pandas as pd
from pandas.io.json import json_normalize
import pip
pip.main(['install', 'yelp3'])
from yelp3.client import Client
apikey = 'HsoG8rJLtpsvMaQ5_fjUvTSKuFg20fMAzKWWD-4NPSthNeTP3p2yNGSviZ9bmZ0z17vOW1k0Kzpx_FW8qAgSLrHLOYv1kT6Zx9qJUN3jshfcBWy2hcfpQmhk2l-oWnYx'
api = Client(apikey)
val = api.business_search(location="Newark, NJ")
dd = json_normalize(val)
dd.head()
df = json_normalize(val, 'businesses')
df.head()
df.columns
df[['name', 'rating', 'categories']]
df2 = pd.DataFrame(df['categories'].values.tolist(),
columns=['cat1', 'cat2', 'cat3'])
df2.head()
dfcat1 = df2['cat1'].apply(pd.Series)
dfcat1
params = {'term': 'sushi', 'limit': 50}
val2 = api.business_search(location="Newark, NJ", term='sushi', limit=50)
val2 = api.business_search(location="Newark, NJ", **params)
self.assertTrue(resp['total'] >= 0)
def test_autocomplete(self):
resp = self.client.autocomplete(text="pizz",
longitude="40.721769",
latitude="-73.993114")
self.assertTrue(len(resp['businesses']) >= 0)
if __name__ == '__main__':
parser = argparse.ArgumentParser("test.py")
parser.add_argument("yelp_token", type=str, help="Yelp API access token.")
args = parser.parse_args()
yelp_token = args.yelp_token
client = Client(yelp_token, debug=True)
TestYelp.client = client
t = TestYelp()
suite = unittest.TestSuite()
suite.addTest(t)
unittest.TextTestRunner(verbosity=2).run(suite)
import numpy as np
import pandas as pd
from pandas.io.json import json_normalize
import pip
pip.main(['install', 'yelp3'])
from yelp3.client import Client
apikey = 'BRfu2UBbZYf-2r2vUVHDOX7C0DWoNgUqfNXioJ_SjwbwUqRYIZ76YuRWc5IWNMKYPO7O9nXQnuzM_lh2mKiYBaE4laA4_GP610DGckhj8BR3Wz2fOo1L0_2LJx2PWnYx'
api = Client(apikey)
val = api.business_search(location='Charlotte, NC')
val
dd = json_normalize(val)
dd
dd.head(5)
df = json_normalize(val, 'businesses')
df.head()
df.columns
df[['name', 'rating', 'categories']]
df['categories'].values.tolist()
df2 = pd.DataFrame(df['categories'].values.tolist(),
columns=['cat1', 'cat2', 'cat3'])
df2
dfcat1 = df2['cat1'].apply(pd.Series)
dfcat1
from yelp3.client import Client
app = Flask(__name__)
# Time (in s) after which we forget the context for a given user
CONTEXT_LIFESPAN = 90
# Load credentials
with open("keys.json", "r") as fi:
keys = json.load(fi)
fb_token = keys["facebook_messenger"]["page_access_token"]
# Setup Yelp fusion API client
app_id = keys["yelp_fusion"]["app_id"]
app_secret = keys["yelp_fusion"]["app_secret"]
yelp_client = Client(app_id, app_secret)
# Setup Wit API client
wit_interface = WitInterface(yelp_client, keys["wit"]["server_side_token"],
fb_token)
# Setup user_to_current_context dictionary
user_to_current_context = defaultdict(dict)
user_to_last_message = defaultdict(int)
def extract_messages_payload(payload):
"""Generate dictionaries of input data from the
provided payload.
"""
data = json.loads(payload)
from yelp3.client import Client YELP_ACCESS_TOKEN = "YOUR-ACCESS-TOKEN" client = Client(YELP_ACCESS_TOKEN) resp = client.business_search(location="New York") print(resp)