gistfile1.txt

def request(host, path, url_params=None):
    """Prepares OAuth authentication and sends the request to the API.
    Args:
        host (str): The domain host of the API.
        path (str): The path of the API after the domain.
        url_params (dict): An optional set of query parameters in the request.
    Returns:
        dict: The JSON response from the request.
    Raises:
        urllib2.HTTPError: An error occurs from the HTTP request.
    """
    url_params = url_params or {}
    url = 'https://{0}{1}?'.format(host, urllib.quote(path.encode('utf8')))
    consumer = oauth2.Consumer(CONSUMER_KEY, CONSUMER_SECRET)
    oauth_request = oauth2.Request(
        method="GET", url=url, parameters=url_params)
    oauth_request.update(
        {
            'oauth_nonce': oauth2.generate_nonce(),
            'oauth_timestamp': oauth2.generate_timestamp(),
            'oauth_token': TOKEN,
            'oauth_consumer_key': CONSUMER_KEY
        }
    )

    token = oauth2.Token(TOKEN, TOKEN_SECRET)
    oauth_request.sign_request(
        oauth2.SignatureMethod_HMAC_SHA1(), consumer, token)
    print oauth_request, "48"
    signed_url = oauth_request.to_url()
    print u'Querying {0} ...'.format(url)
    print signed_url
    print "-----"
    conn = urllib2.urlopen(signed_url, None)
    try:
        response = json.loads(conn.read())
    finally:
        conn.close()

    return response


def search_yelp(offset):
	url_params = {
	'term':'gyms', 'location': 'New York, NY', 'offset':offset, 'limit':SEARCH_LIMIT
	}
	print urllib.urlencode(url_params)
	return request(API_HOST, SEARCH_PATH, url_params=url_params)

def query_api():
	n_businesses = 1 
	df=pandas.DataFrame(data=None)
	offset = 0
	while (n_businesses > 0): #run the cycle till the API gets results back.
		response = search_yelp(offset) 
		print response
		offset = offset + 20 
		businesses = response.get('businesses')
		df2 = pandas.DataFrame(businesses)
		df = df.append(df2, ignore_index=True)
		n_businesses = len(businesses)
		print n_businesses

	return df