In [1]:

    

import pandas as pd
import json
import requests
import numpy as np


    

In [2]:

    

url = 'http://api.yummly.com/v1/api/metadata/'
headers= {'X-Yummly-App-ID':'79663a75', 'X-Yummly-App-Key':'02b233108f476f3110e0f65437c4d6dd'}


    

In [3]:

    

meta_cuisine = requests.get('http://api.yummly.com/v1/api/metadata/cuisine?', headers=headers)


    

In [4]:

    

meta_course = requests.get('http://api.yummly.com/v1/api/metadata/course?', headers=headers)


    

In [5]:

    

response_course = meta_course.text[23:-2]
response_cuisine = meta_cuisine.text[24:-2]


    

In [6]:

    

course_list = json.loads(response_course)


    

In [7]:

    

courses = []
for course in course_list:
    courses.append(course.get('description'))


    

In [9]:

    

courses_series = pd.Series(courses)


    

In [10]:

    

courses_series


    

    
Out[10]:





0               Main Dishes
1                  Desserts
2               Side Dishes
3                Appetizers
4                    Salads
5      Breakfast and Brunch
6                    Breads
7                     Soups
8                 Beverages
9     Condiments and Sauces
10                Cocktails
11                   Snacks
12                    Lunch
dtype: object

In [11]:

    

courses_series.to_csv('course_headers.csv', encoding='utf-8')


    

In [12]:

    

cuisine_list = json.loads(response_cuisine)


    

In [13]:

    

cuisine = []
for cuis in cuisine_list:
    cuisine.append(cuis.get('description'))


    

In [14]:

    

cuisine_series = pd.Series(cuisine)


    

In [15]:

    

cuisine_series.to_csv('cuisine_headers.csv', encoding='utf-8')