def get_search_list(self, keyword):
kwd = keyword
keyword = quote(keyword, encoding='cp949')
r = self.get(self.search_url + keyword)
soup = BeautifulSoup(r.content, 'html.parser')
table_titles = []
product_tables = []
for subheader in soup('div', {'class': 'subheader'}):
inuse = subheader.text.strip()
if "유통" in inuse:
if '유통중인' in inuse:
inuse = "유통중"
else:
inuse = "미확인"
table_titles.append(inuse)
for table in soup('table'):
for tr in table('tr'):
if table('table'):
continue
header = tr.text.strip().split('\n')
if header == [
'제품명', '임부', '보험코드', '판매사', '성분/함량', '구분', '보험', '약가',
'조회수', '대체', '수정'
]:
product_tables.append(table)
if len(table_titles) != len(product_tables):
print('유통 정보와 테이블이 맞지 않습니다')
return Listorm()
lst_result = Listorm()
kwd = kwd[:15] + '...' if len(kwd) > 15 else kwd
for inuse, table in zip(table_titles, product_tables):
pw = ParseWebPage(str(table))
lst = Listorm(pw.ext_tables('제품명', '임부', '보험코드', only_data=False))
lst = lst.add_columns(유통정보=lambda row: inuse, 검색어=lambda row: kwd)
lst_result += lst
return lst_result
def get_context_data(self, **kwargs):
context = super(StockInPLVano, self).get_context_data(**kwargs)
queryset = self.get_queryset().order_by('drug')
if queryset.exists():
ediset = Listorm(queryset.values(
'drug__edi').distinct()).column_values('drug__edi')
Info = queryset.first().drug.__class__
drugset = {edi: Info.objects.get(edi=edi) for edi in ediset}
else:
ediset = []
drugset = {}
aggset = queryset.values('buyitem__drug').annotate(
total_amount=Sum('amount'))
aggset = Listorm(aggset)
aggset = aggset.add_columns(
total_price=lambda row: drugset.get(row.buyitem__drug
).price * row.total_amount,
drug=lambda row: drugset.get(row.buyitem__drug))
context['object_list'] = aggset
context['total_price'] = aggset.apply_column('total_price', sum)
return context
def get_drug_search_list(**kwargs):
search_result_page = retrieve_search_drug.get_search(**kwargs)
drug_countset = parse_search_drug.get_count(search_result_page)
ret = Listorm()
for pro, cnt in drug_countset.items():
if pro == 'proy':
attr_id = 'result_recorded'
pro_yn = 'Y'
else:
attr_id = 'result_unrecorded'
pro_yn = 'N'
records = Listorm(
parse_search_drug.parse(search_result_page, 'article', id=attr_id))
retrieve_count = len(records)
if cnt > retrieve_count:
search_more_result_page = retrieve_search_drug.get_search_more(
cnt, proYN=pro_yn, **kwargs)
records = Listorm()
for page in range(1,
cnt // DRUG_SEARCH_MORE_FORM['rowLength'] + 2):
search_more_result_page = retrieve_search_drug.get_search_more(
cnt, proYN=pro_yn, pageNo=page, **kwargs)
page_records = Listorm(
parse_search_drug.parse(search_more_result_page,
'article',
id='resultMoreTable'))
records += page_records
records = records.add_columns(pro_yn=lambda row: pro_yn)
ret += records
return ret.distinct('drug_cd')