import requests
import json
from bs4 import BeautifulSoup as b


# with open('cat_list') as jf:
#     cat_list = json.load(jf)
departments = ["3034","93427"]
# keywords = input('keyword search: ')
for categoryID in departments:
    params = {
        "OPERATION-NAME":"findItemsByCategory",
        "SECURITY-APPNAME":"scottbea-xlister-PRD-6796e0ff6-14862949", 
        "SERVICE-VERSION":"1.13.0",
        "RESPONSE-DATA-FORMAT":"JSON",
        "categoryId":categoryID ,
        "paginationInput.entriesPerPage":"100",
        "outputSelector":"AspectHistogram"
        }

    response = requests.get("https://svcs.ebay.com/services/search/FindingService/v1", params=params) # 
    data = response.json()
    pretty_data = json.dumps(data, indent=2)

    
# header_dict = dict(response.headers)
# pretty_header = json.dumps(header_dict, indent=2)

# results = data['findItemsByCategoryResponse'][0]['searchResult'][0]['item']



# Before moving onto to the Trading api make sure you check to see if the Finding api will
# output the labels you need. Look into "outputselector" and "aspectfilter" on the 
# Finding api --> "finditembykeyword" or other specific calls


# I think you'll have to paginate the results to output an aspecthistogram cause you might be getting too many results per call.

# Additional problem you will run into when getting labeled data is shoe types and features not in features, accents, styles, categories or subcategories.

# Also, if you can filter by category ids after conducting a very broad search maybe that will be a good way to return the aspect histogram. But you may have to just to a search for each ctegory and return the item specifics, create a giant pandas df and find make a list from the unique specifics/ labels