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around line 37, creating itemId list to pipe into shopping api call/class

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spbeach46 2020-10-07 18:53:19 -07:00
parent b5afa5cfc0
commit 3b0b96fd92
2 changed files with 71 additions and 21 deletions
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43
finding_api.py Normal file
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@ -0,0 +1,43 @@
import requests
import json
from bs4 import BeautifulSoup as b
import pandas as p
# keywords = input('keyword search: ')
with open('cat_list.txt') as jf:
cat_list = json.load(jf)
finding_service = ['findItemsAdvanced', 'findCompletedItems', 'findItemsByKeywords', 'findItemsIneBayStores', 'findItemsByCategory', 'findItemsByProduct']
pageNumber = list(range(1, 63))
# departments = ["3034","93427"]
def get_ids():
itemid_results_list = []
for categoryID in cat_list[0:2]:
params = {
"OPERATION-NAME":finding_service[4],
"SECURITY-APPNAME":"scottbea-xlister-PRD-6796e0ff6-14862949",
"SERVICE-VERSION":"1.13.0",
"RESPONSE-DATA-FORMAT":"JSON",
"categoryId":categoryID ,
"paginationInput.entriesPerPage":"100",
"paginationInput.PageNumber":pageNumber[0]
}
# extract item id here for piping into shopping_test.py
response = requests.get("https://svcs.ebay.com/services/search/FindingService/v1", params=params)
data = response.json()
pretty_data = json.dumps(data, indent=2)
return data
# can use pandas.json_normalize(custom dict cobbled from respons.json())
# Additional problem you will run into when getting labeled data is shoe types and features not in features, accents, styles, categories or subcategories.
# also limited to 5000 calls per day. This leaves you with 500k listings
# If you want to split up each cat equally with their respective maxes then use 62 pages with 100
# Entries per page. At this amount you'll have the max number of calls you can make on the
# shopping api.

49
shopping_api.py
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@ -1,37 +1,45 @@
import requests
import json
from bs4 import BeautifulSoup as b
import requests
import pandas as pd
# OPEN CSV AS VARIALBE RIGHT HERE
with open('cat_list.txt') as jf:
cat_list = json.load(jf)
finding_service = ['findItemsAdvanced', 'findCompletedItems', 'findItemsByKeywords', 'findItemsIneBayStores', 'findItemsByCategory', 'findItemsByProduct']
class Finding_api:
class FindingApi:
finding_service = [
'findItemsAdvanced', 'findCompletedItems',
'findItemsByKeywords', 'findItemsIneBayStores', 'findItemsByCategory',
'findItemsByProduct'
]
pageNumber = list(range(1, 63))
# departments = ["3034","93427"]
def get_ids(self):
itemid_results_list = []
for categoryID in cat_list[0:2]:
params = {
"OPERATION-NAME":finding_service[4],
"SECURITY-APPNAME":"scottbea-xlister-PRD-6796e0ff6-14862949",
"SERVICE-VERSION":"1.13.0",
"RESPONSE-DATA-FORMAT":"JSON",
"categoryId":categoryID ,
"paginationInput.entriesPerPage":"100",
"paginationInput.PageNumber":pageNumber[0]
}
# extract item id here for piping into shopping_test.py
for category_id in cat_list:
for i in FindingApi.pageNumber:
params = {
"OPERATION-NAME":FindingApi.finding_service[4],
"SECURITY-APPNAME":"scottbea-xlister-PRD-6796e0ff6-14862949",
"SERVICE-VERSION":"1.13.0",
"RESPONSE-DATA-FORMAT":"JSON",
"categoryId":category_id,
"paginationInput.entriesPerPage":"100",
"paginationInput.PageNumber":FindingApi.pageNumber[i]
}
# extract item id here for piping into shopping_test.py
response = requests.get("https://svcs.ebay.com/services/search/FindingService/v1", params=params)
data = response.json()
pretty_data = json.dumps(data, indent=2)
return data
response = requests.get("https://svcs.ebay.com/services/search/FindingService/v1", params=params)
data = response.json()
pretty_data = json.dumps(data, indent=2)
itemid_results_list.append(
item_id_results = map(str, itemid_results_list))
item_id_results = ','.join(item_id_results) # you will have to split this into 20 item lists strings to feed into ItemID param. Consider making a list of str lists.
return item_id_results
class Shopping_api:
class ShoppingApi:
def get_item(self):
@ -46,7 +54,6 @@ class Shopping_api:
response = requests.get("https://open.api.ebay.com/shopping?", params=params)
data = response.json()
pretty_data = json.dumps(data, indent=2)
names = []
values = []