42 lines
1.7 KiB
Python
42 lines
1.7 KiB
Python
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import requests
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import json
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from bs4 import BeautifulSoup as b
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# with open('cat_list') as jf:
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# cat_list = json.load(jf)
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departments = ["3034","93427"]
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# keywords = input('keyword search: ')
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for categoryID in departments:
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params = {
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"OPERATION-NAME":"findItemsByCategory",
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"SECURITY-APPNAME":"scottbea-xlister-PRD-6796e0ff6-14862949",
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"SERVICE-VERSION":"1.13.0",
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"RESPONSE-DATA-FORMAT":"JSON",
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"categoryId":categoryID ,
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"paginationInput.entriesPerPage":"100",
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"outputSelector":"AspectHistogram"
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}
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response = requests.get("https://svcs.ebay.com/services/search/FindingService/v1", params=params) #
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data = response.json()
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pretty_data = json.dumps(data, indent=2)
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# header_dict = dict(response.headers)
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# pretty_header = json.dumps(header_dict, indent=2)
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# results = data['findItemsByCategoryResponse'][0]['searchResult'][0]['item']
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# Before moving onto to the Trading api make sure you check to see if the Finding api will
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# output the labels you need. Look into "outputselector" and "aspectfilter" on the
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# Finding api --> "finditembykeyword" or other specific calls
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# I think you'll have to paginate the results to output an aspecthistogram cause you might be getting too many results per call.
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# Additional problem you will run into when getting labeled data is shoe types and features not in features, accents, styles, categories or subcategories.
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# 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
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