async def post(self):
"""
:return:
"""
time = datetime.datetime.now()
export_time = datetime2str(time, date_format='%Y-%m-%d %H:%M:%S')
order = self.get_argument('order', '')
chart_name = self.get_argument('chart_name', '')
# 答题活跃度的数据
data_dict = self.get_argument('data', '')
data_list = []
condition_title_list = []
# 没有筛选条件的总体活跃度
if data_dict:
data_dict = json.loads(data_dict)
condition_title_list = list(data_dict.keys())
data_list = list(data_dict.values())
# 有筛选条件的数据
if '总体活跃度' in condition_title_list:
position = condition_title_list.index('总体活跃度')
else:
position = data_list.index(max(sum(data_list)))
if len(data_list) > position:
condition_title_list.remove(condition_title_list[position])
# 可管理的省份名称
manage_region_title_list = []
manage_region_code_list = self.current_user.manage_region_code_list
if manage_region_code_list:
for manage_region_code in manage_region_code_list:
manage_region_province = await AdministrativeDivision.find_one(
{
'code': manage_region_code,
'record_flag': 1,
'parent_code': None
})
if manage_region_province:
manage_region_title_list.append(
manage_region_province.title)
else:
manage_region_city = await AdministrativeDivision.find_one(
{
'code': manage_region_code,
'record_flag': 1
})
province = await manage_region_city.parent
manage_region_title_list.append(province.title)
try:
output = BytesIO()
workbook = Workbook(output, {'in_memory': True})
title_format = workbook.add_format({
'font_size': 12,
'bold': '1',
'valign': 'vcenter',
'align': 'center',
'font_name': 'Microsoft YaHei',
'border': 1
})
data_format = workbook.add_format({
'valign': 'vcenter',
'align': 'left',
'font_name': 'Microsoft YaHei',
'border': 1
})
data_center_format = workbook.add_format({
'valign': 'vcenter',
'align': 'center',
'font_name': 'Microsoft YaHei',
'border': 1
})
if order == "1" and chart_name:
pass
# 公民科学素质学习答题趋势统计
if order == '2' and chart_name:
answer_tendency_date = self.get_argument(
'answer_tendency_date', '')
answer_tendency_data = self.get_argument(
'answer_tendency_data', '')
answer_tendency_data = json.loads(answer_tendency_data)
answer_tendency_date = json.loads(answer_tendency_date)
answer_tendency_date = deal_with_data(answer_tendency_date)
if answer_tendency_date and answer_tendency_data:
worksheet = workbook.add_worksheet(name=chart_name)
worksheet.merge_range(1,
2,
1,
5,
'导出时间' + export_time,
cell_format=title_format)
worksheet.merge_range(0,
0,
0,
2,
chart_name,
cell_format=title_format)
worksheet.merge_range(1,
0,
1,
1,
'筛选条件',
cell_format=title_format)
worksheet.merge_range(2,
0,
3,
1,
'总体答题次数',
cell_format=title_format)
worksheet.write_string(2, 2, '日期', cell_format=data_format)
worksheet.write_string(3,
2,
'答题次数',
cell_format=data_format)
answer_tendency_title = list(answer_tendency_data.keys())
answer_data_list = list(answer_tendency_data.values())
# 有筛选条件的数据
if '总体答题次数' in answer_tendency_title:
position = answer_tendency_title.index('总体答题次数')
else:
position = answer_data_list.index(
max(sum(answer_data_list)))
if len(answer_data_list) > position:
answer_tendency_title.remove(
answer_tendency_title[position])
for index, date in enumerate(answer_tendency_date):
worksheet.write_string(2, 3 + index, date)
if '总体答题次数' in list(answer_tendency_data.keys()):
worksheet.write_string(
3,
3 + index,
str(answer_tendency_data['总体答题次数'][index]),
cell_format=data_center_format)
else:
max_data_list = max(sum(answer_data_list))
worksheet.write_string(
3,
2 + order,
max_data_list[index - 1],
cell_format=data_center_format)
if answer_tendency_title:
# 有筛选条件得数据写入到excel
for index, condition_title in enumerate(
answer_tendency_title):
worksheet.merge_range(2 * (index + 2) + index + 1,
0,
2 * (index + 2) + 2 + index,
1,
condition_title,
cell_format=title_format)
worksheet.write_string(2 * (index + 2) + index + 1,
2,
'日期',
cell_format=data_format)
worksheet.write_string(2 * (index + 2) + index + 2,
2,
'答题次数',
cell_format=data_format)
for condition_index, data in enumerate(
answer_tendency_data[condition_title]):
worksheet.write_string(2 * (index + 2) +
index + 2,
2 + condition_index + 1,
str(data),
cell_format=data_format)
worksheet.write_string(
2 * (index + 2) + index + 1,
2 + condition_index + 1,
answer_tendency_date[condition_index],
cell_format=data_format)
if order == '3' and chart_name and data_dict:
# 活跃度的导出excel
worksheet = workbook.add_worksheet(name=chart_name)
for order in range(1, 31):
worksheet.write_string(2,
2 + order,
str(order),
cell_format=data_center_format)
if '总体活跃度' in list(data_dict.keys()):
worksheet.write_string(3,
2 + order,
data_dict['总体活跃度'][order - 1] +
'%',
cell_format=data_center_format)
else:
max_data_list = max(sum(data_list))
worksheet.write_string(3,
2 + order,
max_data_list[order - 1] + '%',
cell_format=data_center_format)
worksheet.merge_range(1,
2,
1,
5,
'导出时间' + export_time,
cell_format=title_format)
worksheet.merge_range(0,
0,
0,
2,
chart_name,
cell_format=title_format)
worksheet.merge_range(1,
0,
1,
1,
'筛选条件',
cell_format=title_format)
worksheet.merge_range(2,
0,
3,
1,
'总体活跃度(%)',
cell_format=title_format)
worksheet.write_string(2, 2, '活跃天数', cell_format=data_format)
worksheet.write_string(3, 2, '活跃度(%)', cell_format=data_format)
if condition_title_list:
# 有筛选条件得数据写入到excel
for index, condition_title in enumerate(
condition_title_list):
worksheet.merge_range(2 * (index + 2) + index + 1,
0,
2 * (index + 2) + 2 + index,
1,
condition_title,
cell_format=title_format)
worksheet.write_string(2 * (index + 2) + index + 1,
2,
'活跃天数',
cell_format=data_format)
for order in range(1, 31):
worksheet.write_string(2 * (index + 2) + index + 1,
2 + order,
str(order),
cell_format=data_format)
worksheet.write_string(2 * (index + 2) + index + 2,
2,
'活跃度(%)',
cell_format=data_format)
for condition_index, data in enumerate(
data_dict[condition_title]):
worksheet.write_string(2 * (index + 2) + index + 2,
2 + condition_index + 1,
data,
cell_format=data_format)
# 每日参与top5的导出数据
if order == '4' and chart_name:
# 每日参与top_5的数据
stat_category = self.get_argument('stat_category', '')
top_five_data_list = self.get_argument('top_five_data', '')
if top_five_data_list:
top_five_data_list = json.loads(top_five_data_list)
date_list = self.get_argument('date', '')
if date_list:
date_list = json.loads(date_list)
date_list = deal_with_data(date_list)
if stat_category and top_five_data_list and date_list:
data_series_dict, province_and_city_dict = deal_with_data_excel(
date_list, top_five_data_list)
# {'江苏': ['南京', '苏州‘], '浙江':['杭州']}
total_data_dict = {}
# 某个省下面的所有的市 报表中有数据的市
city_title_list = []
# 报表中省的列表
province_title_list = []
# 省和市的列表
total_title = []
show_name_list = []
show_data_list = []
# 需要添加undefined的省份
need_append_undifend_province_list = []
for top_five_data in top_five_data_list:
temple_data = []
temple_name = []
for index, data in enumerate(top_five_data):
total_title.append(data['name'])
if data['name'] and data['value']:
temple_name.append(
{date_list[index]: data['name']})
temple_data.append(
{date_list[index]: data['value']})
show_name_list.append(temple_name)
show_data_list.append(temple_data)
total_title = [title for title in total_title if title]
for total in total_title:
if ' ' in total:
province_title_list.append(total.split(' ')[0])
city_title_list.append(total.split(' ')[1])
if total.split(' ')[1] == 'undefined':
need_append_undifend_province_list.append(
total.split(' ')[0])
province_title_list = list(set(province_title_list))
city_title_list = list(
set([city for city in city_title_list if city]))
for province_title in province_title_list:
total_data_dict[province_title] = city_title_list
province = await AdministrativeDivision.find_one({
'title':
province_title,
'parent_code':
None
})
if province:
belong_provice_city_title_list = await AdministrativeDivision.distinct(
'title', {'parent_code': province.code})
total_data_dict[province_title] = list(
set(city_title_list)
& set(belong_provice_city_title_list))
total_data_dict[province_title] = list(
set(city_title_list)
& set(belong_provice_city_title_list))
# 各个省的市的个数
length_list = []
for index, city_title in enumerate(
list(total_data_dict.values())):
if list(total_data_dict.keys()
)[index] in need_append_undifend_province_list:
total_data_dict.get(
list(total_data_dict.keys())[index]).append(
'undefined')
for index, city_title in enumerate(
list(total_data_dict.values())):
if city_title:
length_list.append(len(city_title))
province_length = sum(length_list) + len(
list(total_data_dict.values()))
if province_length == 0:
province_length = 10
worksheet = workbook.add_worksheet(name=chart_name + '(' +
stat_category + ')')
worksheet.merge_range(0,
0,
province_length,
0,
'每日参与' + stat_category,
cell_format=data_format)
worksheet.merge_range(1,
1,
province_length,
1,
'导出时间: ' + export_time,
cell_format=data_format)
worksheet.merge_range(0,
2,
0,
4,
'日期',
cell_format=data_center_format)
for index, date in enumerate(date_list):
worksheet.write_string(0,
5 + index,
date,
cell_format=data_format)
worksheet.merge_range(1,
2,
province_length,
2,
'省份',
cell_format=data_center_format)
city_map = {}
province_map = {}
if total_data_dict:
choice_city_title_list = list(total_data_dict.values())
for index, data in enumerate(choice_city_title_list):
if index == 0:
worksheet.merge_range(
1,
3,
1 + len(data),
3,
list(total_data_dict.keys())[index],
cell_format=data_center_format)
else:
worksheet.merge_range(
1 + sum(length_list[:index]) + index,
3,
sum(length_list[:index + 1]) + index + 1,
3,
list(total_data_dict.keys())[index],
cell_format=data_center_format)
if index == 0:
for city_index, city in enumerate(data):
if city == 'undefined':
city = '_'
worksheet.write_string(
1,
4,
list(total_data_dict.keys())[index],
cell_format=data_center_format)
worksheet.write_string(
2 + city_index,
4,
city,
cell_format=data_center_format)
worksheet.write_string(
1, 5, '6666', cell_format=data_format)
city_map[city] = 2 + city_index
province_map[list(
total_data_dict.keys())[index]] = 1
Position(city, 2 + city_index, 4)
Position(
list(total_data_dict.keys())[index], 1,
4)
else:
for city_index, city in enumerate(data):
if city == 'undefined':
city = '_'
worksheet.write_string(
sum(length_list[:index]) + index + 1,
4,
list(total_data_dict.keys())[index],
cell_format=data_center_format)
worksheet.write_string(
sum(length_list[:index]) + index + 2 +
city_index,
4,
city,
cell_format=data_center_format)
city_map[city] = sum(
length_list[:index]
) + 2 + index + city_index
province_map[list(
total_data_dict.keys())[index]] = sum(
length_list[:index]) + index + 1
Position(
city,
sum(length_list[:index]) + 2 + index +
city_index, 4)
Position(
list(total_data_dict.keys())[index],
sum(length_list[:index]) + index + 1,
4)
for index, data in enumerate(choice_city_title_list):
if index == 0:
for key, value in data_series_dict.items():
if key.split(' ')[0] == 'undefined':
position = Position(
key.split(' ')[0], city_map['_'],
4)
else:
position = Position(
key.split(' ')[0],
city_map[key.split(' ')[0]], 4)
if position:
order = date_list.index(
key.split(' ')[1])
worksheet.write_number(
position.row, 5 + order,
int(value))
else:
for key, value in data_series_dict.items():
if key.split(' ')[0] == 'undefined':
position = Position(
key.split(' ')[0], city_map['_'],
4)
else:
position = Position(
key.split(' ')[0],
city_map[key.split(' ')[0]], 4)
if position:
order = date_list.index(
key.split(' ')[1])
worksheet.write_number(
position.row, 5 + order,
int(value))
for order, date in enumerate(date_list):
for index, value in enumerate(
list(province_map.values())):
if index != len(list(
province_map.values())) - 1:
first = value + 2
end = list(province_map.values())[index +
1]
else:
first = list(
province_map.values())[index] + 2
end = province_length + 1
col = 5 + order
col = convert(col)
first = col + str(first)
end = col + str(end)
worksheet.write_formula(
value, 5 + order,
'=SUM(' + first + ':' + end + ')')
# 学习近况的导出数据
if order == '1' and chart_name:
# 取前一天凌晨12点之前的数据
time_match = get_yesterday()
time_match_stage = MatchStage(
{'updated_dt': {
'$lt': time_match
}})
province_code_list, city_code_list, _ = await do_different_administrative_division2(
self.current_user.manage_region_code_list)
month_stage_list = []
member_stage_list = []
accuracy_stage_list = []
if province_code_list:
month_stage_list.append(
MatchStage(
{'province_code': {
'$in': province_code_list
}}))
member_stage_list.append(
MatchStage(
{'province_code': {
'$in': province_code_list
}}))
accuracy_stage_list.append(
MatchStage(
{'province_code': {
'$in': province_code_list
}}))
if city_code_list:
month_stage_list.append(
MatchStage({'city_code': {
'$in': city_code_list
}}))
member_stage_list.append(
MatchStage({'city_code': {
'$in': city_code_list
}}))
accuracy_stage_list.append(
MatchStage({'city_code': {
'$in': city_code_list
}}))
add_fields_stage = AddFieldsStage(
t_accuracy={
'$cond': {
'if': {
'$eq': ['$t_total', 0]
},
'then': 0,
'else': {
'$divide': ['$t_correct', '$t_total']
}
}
})
member_stage_list.append(
MatchStage({'status': STATUS_USER_ACTIVE}))
month_group_stage = GroupStage(
{
'province_code': '$province_code',
'created_dt': {
"$dateToString": {
"format": "%Y-%m",
"date": "$created_dt"
}
}
},
sum={'$sum': '$learn_times'})
lookup_stage = LookupStage(AdministrativeDivision, '_id',
'post_code', 'ad_list')
member_group_stage = GroupStage(
{
'province_code': '$province_code',
'created_dt': {
"$dateToString": {
"format": "%Y-%m",
"date": "$created_dt"
}
}
},
sum={'$sum': 1})
accuracy_group_stage = GroupStage(
{
'province_code': '$province_code',
'created_dt': {
"$dateToString": {
"format": "%Y-%m",
"date": "$created_dt"
}
}
},
t_total={'$sum': '$total'},
t_correct={'$sum': '$correct'})
group_stage = GroupStage('province_code',
t_total={'$sum': '$total'},
t_correct={'$sum': '$correct'})
month_sort_stage = SortStage([('_id.created_dt', ASC)])
# 次数
month_stage_list.extend([
time_match_stage, month_group_stage, lookup_stage,
month_sort_stage
])
# 人数
member_stage_list.extend([
time_match_stage, member_group_stage, lookup_stage,
month_sort_stage
])
accuracy_province_stage_list = copy.deepcopy(
accuracy_stage_list)
accuracy_province_stage_list.extend([
time_match_stage, group_stage, lookup_stage,
add_fields_stage, month_sort_stage
])
# 省和月份共同筛选的正确率
accuracy_stage_list.extend([
time_match_stage, accuracy_group_stage, lookup_stage,
add_fields_stage, month_sort_stage
])
# 只有省的正确率
month_province_list = MemberLearningDayStatistics.aggregate(
month_stage_list)
member_province_list = Member.aggregate(member_stage_list)
accuracy_province_list = MemberSubjectStatistics.aggregate(
accuracy_stage_list)
total_accuracy = MemberSubjectStatistics.aggregate(
accuracy_province_stage_list)
month_province_dict = {}
member_province_dict = {}
accuracy_province_dict = {}
date_list = []
province_title_list = []
province_map = {}
member_date_list = []
accuracy_date_list = []
# 次数
while await month_province_list.fetch_next:
month_province = month_province_list.next_object()
if month_province:
province_dt = month_province.id if month_province.id else '000000'
province = await AdministrativeDivision.find_one({
'code':
province_dt.get('province_code'),
'record_flag':
1,
'parent_code':
None
})
if province_dt.get('created_dt') not in date_list:
date_list.append(province_dt.get('created_dt'))
province_title = ''
if province:
province_title = province.title
province_title_list.append(province_title)
province_title_list = list(set(province_title_list))
dt = province_dt.get('created_dt')
month_province_dict[province_title + ' ' +
dt] = month_province.sum
# 人数
while await member_province_list.fetch_next:
member_province = member_province_list.next_object()
if member_province:
member_province_id = member_province.id if member_province.id else ''
province = await AdministrativeDivision.find_one({
'code':
member_province_id.get('province_code'),
'record_flag':
1,
'parent_code':
None
})
province_title = ''
if province:
province_title = province.title
dt = member_province_id.get('created_dt')
if member_province_id.get(
'created_dt') not in member_date_list:
member_date_list.append(
member_province_id.get('created_dt'))
member_province_dict[province_title + ' ' +
dt] = member_province.sum
# 正确率
while await accuracy_province_list.fetch_next:
accuracy_province = accuracy_province_list.next_object()
if accuracy_province:
accuracy_province_id = accuracy_province.id if accuracy_province.id else ''
province = await AdministrativeDivision.find_one({
'code':
accuracy_province_id.get('province_code'),
'record_flag':
1,
'parent_code':
None
})
province_title = ''
if province:
province_title = province.title
dt = accuracy_province_id.get('created_dt')
if accuracy_province_id.get(
'created_dt') not in accuracy_date_list:
accuracy_date_list.append(
accuracy_province_id.get('created_dt'))
if accuracy_province.t_total == 0:
accuracy_province_dict[province_title + ' ' +
dt] = 0
else:
accuracy_province_dict[
province_title + ' ' +
dt] = (accuracy_province.t_correct /
accuracy_province.t_total) * 100
province_dict = {}
# 总的题目
total_quantity_list = []
# 总的答对题目
correct_quantity_list = []
# 总的正确率
while await total_accuracy.fetch_next:
province_stat = total_accuracy.next_object()
if province_stat:
province_code = province_stat.id if province_stat.id else '000000'
total = province_stat.t_total if province_stat.t_total else 0
correct = province_stat.t_correct if province_stat.t_correct else 0
province = await AdministrativeDivision.find_one({
'code':
province_code,
'record_flag':
1,
'parent_code':
None
})
province_title = ''
if province:
province_title = province.title
province_dict[province_title] = round(
correct / total * 100 if total > 0 else 0, 2)
total_quantity_list.append(total)
correct_quantity_list.append(correct)
# 次数的sheet
print(date_list)
worksheet = workbook.add_worksheet(name='次数')
worksheet.merge_range(0,
0,
0,
len(date_list) + 1,
'公民参与科学素质学习状况',
cell_format=title_format)
worksheet.write_string(1,
0,
'已累计次数',
cell_format=data_center_format)
worksheet.merge_range(1,
2,
1,
len(date_list) + 1,
'导出时间:' + export_time,
cell_format=data_center_format)
worksheet.merge_range(2,
0,
3,
0,
'省份',
cell_format=data_center_format)
worksheet.merge_range(2,
1,
3,
1,
'人数汇总(人)',
cell_format=data_center_format)
worksheet.merge_range(2,
2,
2,
6,
'每月新增人数(人)',
cell_format=data_center_format)
insert_excel(date_list, worksheet, data_center_format,
province_title_list, province_map,
month_province_dict)
# 人数的sheet
worksheet = workbook.add_worksheet(name='人数')
worksheet.merge_range(0,
0,
0,
len(member_date_list) + 1,
'公民参与科学素质学习状况',
cell_format=title_format)
worksheet.write_string(1,
0,
'已累计人数',
cell_format=data_center_format)
worksheet.merge_range(1,
2,
1,
len(member_date_list) + 1,
'导出时间：' + export_time,
cell_format=data_center_format)
worksheet.merge_range(2,
0,
3,
0,
'省份',
cell_format=data_center_format)
worksheet.merge_range(2,
1,
3,
1,
'人数汇总(人/次)',
cell_format=data_center_format)
worksheet.merge_range(2,
2,
2,
6,
'每月新增人数(人/次)',
cell_format=data_center_format)
insert_excel(member_date_list, worksheet, data_center_format,
province_title_list, province_map,
member_province_dict)
# 正确率的sheet
worksheet = workbook.add_worksheet(name='正确率')
total_province_accuracy = round(
sum(correct_quantity_list) / sum(total_quantity_list) *
100, 2)
worksheet.merge_range(0,
0,
0,
len(date_list) + 1,
'公民参与科学素质学习状况',
cell_format=title_format)
worksheet.merge_range(1,
0,
1,
1,
'总体正确率' + str(total_province_accuracy) +
'%',
cell_format=data_center_format)
worksheet.merge_range(1,
2,
1,
len(date_list) + 1,
'导出时间:' + export_time,
cell_format=data_center_format)
worksheet.merge_range(2,
0,
3,
0,
'省份',
cell_format=data_center_format)
worksheet.merge_range(2,
1,
3,
1,
'正确率',
cell_format=data_center_format)
worksheet.merge_range(2,
2,
2,
6,
'每月正确率波动(%)',
cell_format=data_center_format)
for index, date in enumerate(accuracy_date_list):
worksheet.write_string(3,
2 + index,
date,
cell_format=data_center_format)
for index, province_title in enumerate(province_title_list):
worksheet.write_string(4 + index,
0,
province_title,
cell_format=data_center_format)
worksheet.write_string(4 + index,
1,
str(province_dict[province_title]),
cell_format=data_center_format)
province_map[province_title] = 4 + index
for month_province, value in accuracy_province_dict.items():
value = round(value, 2)
position = Position(
month_province.split(' ')[0],
province_map[month_province.split(' ')[0]], 0)
order = accuracy_date_list.index(
month_province.split(' ')[1])
worksheet.write_string(position.row, 2 + order, str(value))
workbook.close()
self.set_header(
'Content-Type',
'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet'
)
self.set_header(
'Content-Disposition',
"attachment;filename*=utf-8''{}.xlsx".format(
quote(chart_name.encode('utf-8'))))
self.write(output.getvalue())
self.finish()
except Exception:
logger.error(traceback.format_exc())
async def __do_get_report_data(self):
subject_dimension_list = await SubjectDimension.aggregate([
MatchStage({'parent_cid': None}),
SortStage([('ordered', ASC)]),
LookupStage(SubjectDimension, 'cid', 'parent_cid', 'sub_list')
]).to_list(None)
match_dict = {}
search_arguments = {}
# 地方科协不会开放此权限，因此导出全部省份数据
# m_province_code_list, m_city_code_list, _ = await do_different_administrative_division2(
# self.current_user.manage_region_code_list)
# if m_province_code_list:
# match_dict['province_code'] = {'$in': m_province_code_list}
# if m_city_code_list:
# match_dict['city_code'] = {'$in': m_city_code_list}
# 维度信息
dimension_dict = {}
for dimension in subject_dimension_list:
t_dimension = self.get_argument(dimension.cid, '')
if t_dimension:
dimension_dict['%s' % dimension.cid] = t_dimension
search_arguments[dimension.cid] = t_dimension
# 默认只显示，状态启用，并且不是基准测试或毕业测试的题目
match_dimension = {'$and': [
{'status': STATUS_SUBJECT_ACTIVE},
{'category_use': {
'$nin': [CATEGORY_SUBJECT_BENCHMARK, CATEGORY_SUBJECT_GRADUATION]}}
]}
if dimension_dict:
match_dimension['$and'].extend([{'dimension_dict.%s' % k: v} for k, v in dimension_dict.items()])
subject_cid_list = await Subject.distinct('cid', match_dimension)
if subject_cid_list:
match_dict['subject_cid'] = {'$in': subject_cid_list}
query_params = {}
s_province = self.get_argument('province', '')
if s_province:
query_params['province_code'] = s_province
search_arguments['province'] = s_province
s_city = self.get_argument('city', '')
if s_city:
query_params['city_code'] = s_city
search_arguments['city'] = s_city
s_age_group = self.get_argument('age_group', '')
if s_age_group:
query_params['age_group'] = int(s_age_group)
search_arguments['age_group'] = s_age_group
s_gender = self.get_argument('gender', '')
if s_gender:
query_params['gender'] = int(s_gender)
search_arguments['gender'] = s_gender
s_education = self.get_argument('education', '')
if s_education:
query_params['education'] = int(s_education)
search_arguments['education'] = s_education
manage_stage = MatchStage(match_dict)
query_stage = MatchStage(query_params)
group_stage = GroupStage('subject_cid', t_total={'$sum': '$total'}, t_correct={'$sum': '$correct'})
project_stage = ProjectStage(
total='$t_total', correct='$t_correct',
percent={
'$cond': {
'if': {'$eq': ['$t_total', 0]},
'then': 0,
'else': {
'$divide': ['$t_correct', '$t_total']
}
}
}
)
s_lookup_stage = LookupStage(Subject, '_id', 'cid', 'subject_list')
so_lookup_stage = LookupStage(SubjectOption, '_id', 'subject_cid', 'subject_option_list')
not_null_match = MatchStage({
'subject_list': {'$ne': []},
'subject_option_list': {'$ne': []}
})
final_project = ProjectStage(**{
'custom_code': {'$arrayElemAt': ['$subject_list.custom_code', 0]},
'code': {'$arrayElemAt': ['$subject_list.code', 0]},
'title': {'$arrayElemAt': ['$subject_list.title', 0]},
'subject_list': '$subject_list',
'subject_option_list': '$subject_option_list',
'dimension': {'$arrayElemAt': ['$subject_list.dimension_dict', 0]},
'total': '$total',
'correct': '$correct',
'percent': '$percent'
})
sort_list = []
sort = self.get_argument('sort')
if sort:
sort = int(sort)
else:
sort = 1
search_arguments['sort'] = sort
if sort == 1:
sort_list.append('-percent')
elif sort == 2:
sort_list.append('percent')
sort_list.append('-total')
return MemberSubjectStatistics.aggregate([
manage_stage, query_stage, group_stage, project_stage, s_lookup_stage, so_lookup_stage, not_null_match,
final_project
])