def __init__(self, text, lang):
self.lang = lang
self.stem = text.strip().split('\t')[0]
# [[query, freq, timestamp]]
self.query_items = map(
lambda t: t.strip().split(':'), text.strip().split('\t')[1:])
self.querys = [item[0] for item in self.query_items]
self.querys = list(set(self.querys))
self.this_year = when.past(years=0).strftime("%Y")
self.last_year = when.past(years=1).strftime("%Y")
self.next_year = when.future(years=1).strftime("%Y")
self.year_before_last = when.past(years=2).strftime("%Y")
self.recent_three_month = [
self.month_name_helper(i) for i in xrange(3)]
self.total_freq = 0
self.this_year_freq = 0
self.last_year_freq = 0
self.recent_three_month_freq = 0
self.month_freq_dict = defaultdict(int)
self.processors = []
self.main_request_type = None
self.main_request_degree = 0
for i in dir(self):
if i.startswith('general_processor'):
self.add_analyze_processor(getattr(self, i))
for i in dir(self):
if i.startswith(self.lang + '_processor'):
self.add_analyze_processor(getattr(self, i))
def test_past_years(self):
nums = [random.randint(1, 1000) for range_index in xrange(1000)]
for num in nums:
past = when.past(years=num)
leap_days = when.how_many_leap_days(past, self.now)
now_plus = when.now() - self.one_day * (num * 365 + leap_days)
self.assertTrue(past - now_plus < self.one_second)
def test_past_months(self):
nums = [random.randint(1, 1000) for range_index in xrange(1000)]
for num in nums:
past = when.past(months=num)
now_minus = when.now() - self.one_month * num
self.assertTrue(
(past - now_minus) < self.one_day * 3 * num)
def get_30days_start_end_time(st, ed):
today = when.today()
thirty_days_ago = when.past(days=30).date()
format_str = '%s %s'
if st < ed:
st_time_str = format_str % (thirty_days_ago, st)
ed_time_str = format_str % (today, ed)
return st_time_str, ed_time_str
tomorrow = when.tomorrow()
st_time_str = format_str % (thirty_days_ago, st)
ed_time_str = format_str % (tomorrow, ed)
return st_time_str, ed_time_str
def month_re_cal():
"""每天重复计算一个月内的数据"""
db = Session()
var_obj = db.execute('select code, exchange from varieties ')
var_vals = var_obj.fetchall()
exchange_map = dict(var_vals)
db.close()
now = datetime.now()
last_month = when.past(months=1)
for i in range((now - last_month).days + 1):
date = str(last_month + timedelta(days=i))[:10]
# ctp日数据
for varieties in DAY_VARIEYIES_DICT.keys():
exchange = exchange_map.get(varieties.lower())
if not exchange:
exchange = exchange_map.get(varieties.upper())
cal_day_info(varieties, date, exchange)
# 总资产
update_output(date)
def get(self, request):
u"""
获取预警提示,主力合约,预警类别信息
---
parameters:
- name: alert_id
description: 预警的id
paramType: query
required: true
- name: limit
description: 数据条数
paramType: query
required: false
"""
query_dict = request.query_params.dict().copy()
alert_id = query_dict.get('alert_id', None)
limit = int(query_dict.get('limit', 3))
logger.info('查看预警历史数据, 预警id: %s, 查看数量: %s' % (alert_id, limit))
leta = math.floor(limit / 30)
if leta < 1:
leta = 1
# now = datetime.datetime.strptime(str(datetime.datetime.now())[10] + ' 00:00:00', '%Y-%m-%d %H:%M:%S')
past_day = datetime.datetime.strptime(
str(when.past(months=leta))[:10] + ' 00:00:00',
'%Y-%m-%d %H:%M:%S')
today = datetime.datetime.today()
if not alert_id:
return BackstageHTTPResponse(
code=BackstageHTTPResponse.API_HTTP_CODE_INVILID_PARAMS,
message=u'预警id不存在').to_response()
alert_obj = Alert.objects.get(pk=alert_id)
variety = alert_obj.variety
price = alert_obj.price
# source = alert_obj.source
# exchange = alert_obj.exchange
contract = alert_obj.contract
_y = []
data, date_time = get_history_data(variety,
'CLOSE',
limit=limit,
contract=contract,
start=past_day,
end=today)
y = list(zip(date_time, data))
# for i in range(len(data)):
# if datetime.datetime.fromtimestamp(date_time[i]/1000) < past_day:
# break
# y.append([date_time[i], data[i]])
new_vals = Ship(variety,
price,
start=None,
end=None,
limit=None,
offset=None,
desc=True)
para_unit = new_vals.unit or ''
y.reverse()
res = {
'y': y,
'y_max': max(data),
'y_min': min(data),
'y_name': '主力合约',
'y_unit': '元',
'_y_name': para_name_map[price],
'_y_unit': para_unit,
'para_type': price,
'date_end': str(datetime.datetime.now())[:10],
'date_start': str(past_day)[:10],
}
if price == 'CROSS_STAR':
para_vals = get_cross_star(variety, past_day, limit)
res.update({
'_y': para_vals,
'_y_max': None,
'_y_min': None,
})
else:
para_data, para_date_time = get_history_data(variety,
price,
limit=limit,
start=past_day,
end=today)
# for i in range(len(para_data)-1):
# # print(datetime.datetime.fromtimestamp(para_date_time[i] / 1000))
# if datetime.datetime.fromtimestamp(para_date_time[i] / 1000) < past_day:
# break
# _y.append([para_date_time[i], para_data[i]])
_y = list(zip(para_date_time, para_data))
_y.reverse()
res.update({
'_y': _y,
'_y_max': max(para_data),
'_y_min': min(para_data),
})
logger.info('正常返回预警详细数据')
return BackstageHTTPResponse(data=res,
message=u'正常返回预警详细数据').to_response()
import when
datadir = '../data/'
mid_datadir = '../mid_data/'
final_datadir = '../final_data/'
dict_dir = '../dict/'
file_suffix = when.now().strftime("%Y%m%d")
newest_time = when.past(0, 3).strftime("%Y%m%d")
gentime_type = {'year': ['1', '0'], 'newest': ['3', newest_time],
'2014': ['2', '0'], '2013': ['3', '20130101']}
def month_name_helper(self, i):
return when.past(months=i).strftime('%Y%m')
