def default_value(cls):
dt_now = datetime.datetime.now()
yesterday = dt_now - datetime.timedelta(days=1)
to_day = "{0}-{1}-{2}".format(dt_now.year, dt_now.month, dt_now.day)
yesterday = "{0}-{1}-{2}".format(yesterday.year, yesterday.month,
yesterday.day)
last_week_start, last_week_end = last_week()
last_month_start, last_month_end = last_month()
# SQL里的变量, 需要再加
"""
SELECT id AS ID, name AS 名称 FROM table WHERE dt_created > {today_start} AND dt_created < {today_end};
"""
SQL_VARIABLE = {
"today_start": f"{to_day} 00:00:00",
"today_end": f"{to_day} 23:59:59",
"yesterday_start": f"{yesterday} 00:00:00",
"yesterday_end": f"{yesterday} 23:59:59",
"last_week_start": f"{last_week_start} 00:00:00",
"last_week_end": f"{last_week_end} 23:59:59",
"last_month_start": f"{last_month_start} 00:00:00",
"last_month_end": f"{last_month_end} 23:59:59",
}
return SQL_VARIABLE
def get_curr_fund_value(fund_name_list):
unit_values = {}
for fund in fund_name_list:
fund_id = db.get_fund_id(fund)
data_dict, last_date = get_mf_data(fund_id, utils.last_month(), utils.today())
unit_values[fund] = data_dict[max(data_dict)]
return unit_values
def get_timeline(cls, proj, typ, tag=None):
# todo: the f**k, how could u hard code these things.
prv_obj = cls.get_obj(proj, utils.slashify(typ, "hour_by_month", utils.month_tag(utils.last_month())))
obj = cls.get_obj(proj, utils.slashify(typ, "hour_by_month", utils.month_tag()))
def fill_entries(lst, ms, hrs):
if len(lst) < last_month_hrs:
lst.extend([str(utils.add_hrs(j, ms)), [0, 0]] for j in range(len(lst), last_month_hrs))
return lst
last_month_hrs = utils.last_month().day * 24
ms = utils.month_start(now=utils.last_month())
def normalize(res, ms, last_month_hrs):
for i in res:
res[i] = fill_entries(res[i], ms, last_month_hrs)
return res
if not prv_obj and not obj:
return {}
if prv_obj:
res = normalize(json.loads(prv_obj.stat), ms, last_month_hrs)
if obj:
nres = json.loads(obj.stat)
if not prv_obj:
res = nres
else:
for t in nres:
if not t in res:
res[t] = fill_entries([], ms, last_month_hrs)
res[t].extend(nres[t])
if tag:
return res[tag]
return res
def generate_reference_xls():
existing_rows = []
#open the reference.xls file
global date
excel_fp = os.path.join(REFERENCE_DIR, 'reference_' + date + '.xls')
#create the xls file and the read_worksheet if it doesn't yet exist
if not os.path.exists(excel_fp):
write_workbook = xlwt.Workbook()
write_workbook.add_sheet('all')
write_workbook.save(excel_fp)
#get the baseline existing_rows from the xls file
read_workbook = xlrd.open_workbook(excel_fp)
read_worksheet = read_workbook.sheet_by_name('all')
rows = read_worksheet.nrows
for i in range(0, rows):
existing_rows.append(read_worksheet.row_values(i))
#existing_rows.sort(comp)
insert_log(
LOG_FILE, 'Read ' + format(read_worksheet.nrows, "") +
' rows from file ' + excel_fp)
write_workbook = copy(read_workbook)
write_worksheet = write_workbook.get_sheet('all')
#to skip the existing data we need to have the existing_rows of ID in existing_rows
#we already know the format of existing_rows is [[id1, x, y, z, ...], [id2, x, y, z, ...] ...]
ids_in_worksheet = []
for i in existing_rows:
ids_in_worksheet.append(i[0])
#get all stock info
stock_info = tushare.get_stock_basics()
insert_log(
LOG_FILE, 'There are ' + format(len(stock_info), "") +
' items from tushare.get_stock_basics()')
count = 0
for id in stock_info.index:
count += 1
insert_log(LOG_FILE, 'processing ' + format(count, "") + ': ' + id)
if id in ids_in_worksheet:
insert_log(LOG_FILE, 'Already has ' + id + ' skip it')
continue
#test code
if count > 20:
break
month = utils.last_month()
try:
history_data = tushare.get_hist_data(
id,
start=utils.first_date_of_last_month(),
retry_count=5,
pause=1)
#print history_data.columns
#print history_data[0:4]
close_price = history_data[u'close']
print history_data
except Exception:
## nothing to handle
insert_log(LOG_FILE, 'Exception when handling ' + id)
info = sys.exc_info()
print(info[0], ':', info[1])
continue
continous_up = False
continous_down = False
#only need to analyze if we have at least 4 sample
if (len(close_price) >= 4):
continous_up = True
continous_down = True
for i in range(0, 3):
if (close_price[i] < close_price[i + 1]):
continous_up = False
break
for i in range(0, 3):
if (close_price[i] > close_price[i + 1]):
continous_down = False
break
#row = read_worksheet.nrows
#read_worksheet.write(row, 0, id)
try:
record = []
date = close_price.keys()[0]
three_days_ago = 'NA'
if len(close_price.keys()) >= 4:
three_days_ago = close_price.keys()[3]
open_price = history_data[u'open'][0]
high = history_data[u'high'][0]
low = history_data[u'low'][0]
price_change = history_data[u'price_change'][0]
volume = history_data[u'volume'][0]
p_change = history_data[u'p_change'][0]
ma5 = history_data[u'ma5'][0]
ma10 = history_data[u'ma10'][0]
ma20 = history_data[u'ma20'][0]
v_ma5 = history_data[u'v_ma5'][0]
v_ma10 = history_data[u'v_ma10'][0]
v_ma20 = history_data[u'v_ma20'][0]
turnover = history_data[u'turnover'][0]
trend = ''
#
#[id, 3_day_trend, date, open price, close price, high, low, volume, price_change, p_change, ma5, ma10, ma20, v_ma5, v_ma10, v_ma20, turnover]
#
if (continous_up):
trend = 'up'
elif (continous_down):
trend = 'down'
else:
trend = 'NA'
record.append(id)
record.append(trend)
record.append(date)
record.append(three_days_ago)
record.append(open_price)
record.append(close_price[0])
record.append(high)
record.append(low)
record.append(volume)
record.append(price_change)
record.append(p_change)
record.append(ma5)
record.append(ma10)
record.append(ma20)
record.append(v_ma5)
record.append(v_ma10)
record.append(v_ma20)
record.append(turnover)
for i in range(len(record)):
write_worksheet.write(rows, i, record[i])
rows += 1
write_workbook.save(excel_fp)
insert_log(LOG_FILE, 'written to file ' + excel_fp)
except Exception, e:
insert_log(LOG_FILE, 'Exception when handling id ' + id)
info = sys.exc_info()
print traceback.print_exc()
continue
#existing_rows.append([id, trend, date, open_price, close_price[0], high, low, price_change, ma5, ma10, ma20, v_ma5, v_ma10, v_ma20, turnover])
insert_log(LOG_FILE, id + ' 3 day trend is ' + trend)