scott/ebay-ml-lister
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

corrected update_df to iterate over items and nvl kv pairs. and began check for repeat results

Browse Source
This commit is contained in:
spbeach46 2020-10-24 03:36:31 -07:00
parent b64e2f74c1
commit 47b77600a5
1 changed files with 13 additions and 12 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

25
ebay_api.py
View File

@ -45,12 +45,13 @@ class FindingApi:
try:# TODO run pdb here to see how to extract itemId before update_df
training = pd.read_csv('training.csv')
for item in data['findItemsByCategoryResponse'][0]['searchResult'][0]['item']:
if item not in training.values:
if item not in training.values not in itemid_results_list:# TODO need to figure out syntax to check if item_id is present in both list and training set. (list to avoid repeat results)
itemid_results_list.append(item['itemId'][0]) # itemId
# values are in lists for some reason
except (pd.errors.EmptyDataError, FileNotFoundError):
for item in data['findItemsByCategoryResponse'][0]['searchResult'][0]['item']:
itemid_results_list.append(item['itemId'][0])
if item not in itemid_results_list:
itemid_results_list.append(item['itemId'][0])
item_id_results = [','.join(itemid_results_list[n:n+20]) for n in list(range(0,
len(itemid_results_list), 20))]
@ -87,17 +88,17 @@ class CurateData:
'''
Extracts itemIds and name-value list , creates new dict and appends df
'''
names = []
values = []
nvl = data['Item'][0]['ItemSpecifics']['NameValueList'][0]# TODO is this only for one item?
for item in data:
names = []
values = []
nvl = data['Item'][0]['ItemSpecifics']['NameValueList']
for nvl_dict in nvl:
names.append(nvl_dict['Name'])
values.append(nvl_dict['Value'])
# TODO Also append itemId and value to the dictionary somewhere
for nvl_dict in nvl:
names.append(nvl_dict['Name'])
values.append(nvl_dict['Value'])
# TODO Also append itemId and value to the dictionary
nvl_dict = dict(zip(names, values))
data.update(nvl_dict)
nvl_dict = dict(zip(names, values))
data.update(nvl_dict)
df = pd.json_normalize(data)
df.to_csv('training.csv', mode='a')