def get_patient_dict(self, source_url, target_url, scr):
# 発生状況等の取得
url = scr.getTargetUrl(source_url, target_url)
soup = scr.getContent(url)
# テーブル情報を取得する
try:
dataset = scr.parseSingleTable(soup)
except ValueError as e:
raise e
# pdf格納folderの作成
path_op = PathOperator()
path_op.create_path('pdf')
# 県外事例は除外
inside_checker = StringUtil()
patient_data_tmp = []
for data in dataset:
if inside_checker.exclude_outside(data[0]):
# 格納先のファイル名を作成
file_name = path_op.set_downlaod_file_name(
'pdf', path_op.get_file_name(data[3]))
scr.downloadPdf(data[3], file_name)
output_file = os.path.splitext(os.path.basename(file_name))[0]
output_path = os.path.join('./text', output_file + '.txt')
is_duplicated, number_char = StringUtil(
).is_duplicate_data(data[0])
# 重複している場合
if is_duplicated:
for n in number_char:
patient_data_tmp.append(
{"No": n, "発生判明日": data[2].strip(), "link": output_path})
# 単一の場合
else:
patient_data_tmp.append(
{"No": number_char, "発生判明日": data[2].strip(), "link": output_path})
# convertの実行
path_op.create_path('text')
PdfParser.execute_pdf2text()
# patientの作成
for tmp in patient_data_tmp:
# テキストからjsonの作成
result = TextParser.text2dict(tmp['No'], tmp['link'])
result.update(tmp)
result.update({'退院': None})
del result['link']
self.patient_list.append(result)
# Noに数字が入らない場合の処理（例："再陽性"）
nan_patient_list = list(filter(lambda x: re.search(
r'\d', x['No']) is None, self.patient_list))
number_patient_list = list(filter(lambda x: re.search(
r'\d', x['No']) is not None, self.patient_list))
insert_patient_list = sorted(number_patient_list, key=lambda x: int(
re.sub(r'県|内|例|目|第\d報', '', x['No'])))
insert_patient_list.extend(nan_patient_list)
self.patients['data'] = insert_patient_list
# patients_summaryの作成
self.create_patients_summary_dict(insert_patient_list)
return self.patients, self.patients_summary_data
def getPatientDict(index_html, scr, update_datetime):
# 発生状況等の取得
url = scr.getTargetUrl(index_html, 'info_coronavirus_prevention.html')
soup = scr.getContent(url)
# テーブル情報を取得する
try:
dataset = scr.parseSingleTable(soup)
except ValueError as e:
raise e
# pdf格納folderの作成
path_op = PathOperator()
path_op.create_path('pdf')
# 県外事例は除外
inside_checker = StringUtil()
patient_data_tmp = []
patients_summary_tmp = []
for data in dataset:
if inside_checker.exclude_outside(data[0]):
# 格納先のファイル名を作成
file_name = path_op.set_downlaod_file_name(
'pdf', path_op.get_file_name(data[3]))
scr.downloadPdf(data[3], file_name)
output_file = os.path.splitext(os.path.basename(file_name))[0]
output_path = os.path.join('./text', output_file + '.txt')
is_duplicated, number_char = StringUtil().is_duplicate_data(
data[0])
# 重複している場合
if is_duplicated:
for n in number_char:
# print('No:{} リリース日:{} 判明日:{} Link:{}'.format(n, data[1].strip(), data[2].strip(), output_path))
patient_data_tmp.append({
"No": n,
"リリース日": data[1].strip(),
"link": output_path
})
patients_summary_tmp.append(data[2].strip())
# 単一の場合
else:
# print('No:{} リリース日:{} 判明日:{} Link:{}'.format(number_char, data[1].strip(), data[2].strip(), output_path))
patient_data_tmp.append({
"No": number_char,
"リリース日": data[1].strip(),
"link": output_path
})
patients_summary_tmp.append(data[2].strip())
# convertの実行
path_op.create_path('text')
convert_txt = PdfParser()
convert_txt.executeConvert()
# テキストからjsonの作成
parser = TextParser()
patient_list = []
# patientの作成
for tmp in patient_data_tmp:
result = parser.text2dict(tmp['No'], tmp['link'])
result.update(tmp)
result.update({'退院': None})
del result['link']
patient_list.append(result)
patients = {}
patients['__comments'] = "陽性患者の属性"
patients['date'] = update_datetime
# Noに数字が入らない場合の処理（例："再陽性"）
nan_patient_list = list(
filter(lambda x: re.search(r'\d', x['No']) is None, patient_list))
number_patient_list = list(
filter(lambda x: re.search(r'\d', x['No']) is not None, patient_list))
insert_patient_list = sorted(
number_patient_list,
key=lambda x: int(re.sub(r'県|内|例|目', '', x['No'])))
insert_patient_list.extend(nan_patient_list)
patients['data'] = insert_patient_list
# patients_summaryの作成
patients_summary_data = {}
patients_summary_data['__comments'] = "陽性患者数"
patients_summary_data['date'] = update_datetime
patients_summary = TimeUtil().create_dt_dict(datetime.datetime.now())
for k, g in groupby(patients_summary_tmp):
patients_summary = list(
map(
lambda x: {
"日付": x["日付"],
"小計": len(list(g)) if x['日付'] == k else x['小計']
}, patients_summary))
# 小計が0とならない最新の日付までのリストにする
patients_summary = sorted(patients_summary, key=lambda x: x['日付'])
jc = JsonChecker()
patients_summary = jc.exclude_zero_max_date(patients_summary)
patients_summary_data['data'] = patients_summary
return patients, patients_summary_data