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ebay_api_test.py

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+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