# read in uom and LOV files
uom_df = pd.DataFrame()
#uom_groups_url = 'https://raw.githubusercontent.com/gamut-code/attribute_mapping/master/UOM_data_sheet.csv'
# create df of the uom groupings (ID and UOMs for each group)
#data_file = requests.get(uom_groups_url).content
#uom_df = pd.read_csv(io.StringIO(data_file.decode('utf-8')))
# get uom list
filename = 'C:/Users/xcxg109/NonDriveFiles/reference/UOM_data_sheet.csv'
uom_df = pd.read_csv(filename)
# create df of the lovs and their concat values
lov_df, lov_list = q.get_LOVs()
data_type = fd.search_type()
print('working...')
if data_type == 'grainger_query':
search_level = fd.blue_search_level()
search_data = fd.data_in(data_type, settings.directory_name)
if search_level == 'cat.CATEGORY_ID':
for level_1 in search_data:
grainger_df = q.gcom.grainger_q(grainger_attr_ETL_query,
search_level, level_1)
print('k = ', level_1)
if grainger_df.empty == False:
df_upload, gamut_dict = attribute_process(
def generate_data():
gcom = GraingerQuery()
#request the type of data to pull: blue or yellow, SKUs or node, single entry or read from file
data_type = fd.search_type()
search_level = 'cat.CATEGORY_ID'
#if Blue is chosen, determine the level to pull L1 (segment), L2 (family), or L1 (category)
if data_type == 'node':
search_level = fd.blue_search_level()
#ask user for node number/SKU or pull from file if desired
search_data = fd.data_in(data_type, settings.directory_name)
sku_status = skus_to_pull(
) #determine whether or not to include discontinued items in the data pull
grainger_df = pd.DataFrame()
if data_type == 'node':
for k in search_data:
if sku_status == 'filtered':
temp_df = gcom.grainger_q(grainger_basic_query, search_level,
k)
temp_df = gcom.grainger_q(grainger_basic_query, search_level,
k)
elif sku_status == 'all':
temp_df = gcom.grainger_q(grainger_discontinued_query,
search_level, k)
grainger_df = pd.concat([grainger_df, temp_df], axis=0)
print(k)
elif data_type == 'yellow':
for k in search_data:
if isinstance(k, int): #k.isdigit() == True:
pass
else:
k = "'" + str(k) + "'"
if sku_status == 'filtered':
temp_df = gcom.grainger_q(grainger_basic_query,
'yellow.PROD_CLASS_ID', k)
elif sku_status == 'all':
temp_df = gcom.grainger_q(grainger_discontinued_query,
'yellow.PROD_CLASS_ID', k)
grainger_df = pd.concat([grainger_df, temp_df], axis=0)
print(k)
elif data_type == 'sku':
sku_str = ", ".join("'" + str(i) + "'" for i in search_data)
if sku_status == 'filtered':
grainger_df = gcom.grainger_q(grainger_basic_query,
'item.MATERIAL_NO', sku_str)
elif sku_status == 'all':
grainger_df = gcom.grainger_q(grainger_discontinued_query,
'item.MATERIAL_NO', sku_str)
elif data_type == 'supplier':
for k in search_data:
if sku_status == 'filtered':
temp_df = gcom.grainger_q(grainger_basic_query,
'supplier.SUPPLIER_NO', k)
elif sku_status == 'all':
temp_df = gcom.grainger_q(grainger_discontinued_query,
'supplier.SUPPLIER_NO', k)
grainger_df = pd.concat([grainger_df, temp_df], axis=0)
print(k)
return [grainger_df, search_level]