def test_short_compute5():
"""
做多场2，考虑异常情况下的卖出
"""
busi_date = "2017-03-20"
data = {}
data["trade_id"] = "trade_id"
data["secu_acc_id"] = "secu_acc_id"
data["prd_no"] = "prd_no"
data['open_date'] = "2017-03-10"
data["busi_date"] = busi_date
data['liab_qty'] = 0
data['mkt_val'] = 0.
data["trd_detail"] = []
data['now_trd'] = [{
"trd_qty": 800,
"trd_cash_flow": 4000,
"timestamp": 1489626000
}, {
"trd_qty": -150,
"trd_cash_flow": -1200,
"timestamp": 1489626001
}, {
"trd_qty": 150,
"trd_cash_flow": 1000,
"timestamp": 1489626002
}]
data["total_in"] = 0.
data["total_out"] = 0.
re = short_compute(data, busi_date)
assert_equal(re['exception_label'], 1)
assert_less(0.0 - float(re["trd_detail"][0]["return"]), 1e-4)
assert_less(0.0 - float(re["trd_detail"][1]["return"]), 1e-4)
assert_less(200.0 - float(re["trd_detail"][2]["return"]), 1e-4)
def test_short_compute():
"""
做空场景1，考虑正常情况下，在计算日无交易
"""
busi_date = "2017-03-20"
data = {}
data["trade_id"] = "trade_id"
data["secu_acc_id"] = "secu_acc_id"
data["prd_no"] = "prd_no"
data['open_date'] = "2017-03-10"
data["busi_date"] = busi_date
data['liab_qty'] = -950
data['mkt_val'] = -10000.
data["trd_detail"] = [{
"trd_amt": "-8000",
"trd_qty": "-800",
"trd_date": "2017-03-10",
"return": "0.0"
}, {
"trd_amt": "-2000",
"trd_qty": "-150",
"trd_date": "2017-03-12",
"return": "0.0"
}]
data['now_trd'] = None
data["total_in"] = 0.
data["total_out"] = 0.
re = short_compute(data, busi_date)
assert_equal(re['total_in'], 0.)
assert_equal(re['total_out'], 10000.)
assert_equal(re['remain_val'], -10000.)
assert_equal(re['remain_liab_qty'], -950)
def test_short_compute4():
"""
做多场2，考虑金额正常卖出
"""
busi_date = "2017-03-20"
data = {}
data["trade_id"] = "trade_id"
data["secu_acc_id"] = "secu_acc_id"
data["prd_no"] = "prd_no"
data['open_date'] = "2017-03-10"
data["busi_date"] = busi_date
data['liab_qty'] = 0
data['mkt_val'] = 0.
data["trd_detail"] = [{
"trd_amt": "-8000",
"trd_qty": "-800",
"trd_date": "2017-03-10",
"return": "0.0"
}, {
"trd_amt": "-2000",
"trd_qty": "-150",
"trd_date": "2017-03-12",
"return": "0.0"
}]
data['now_trd'] = [{
"trd_qty": 800,
"trd_cash_flow": 4000,
"timestamp": 1489626002
}, {
"trd_qty": 150,
"trd_cash_flow": 1000,
"timestamp": 1489626001
}]
data["total_in"] = 0.
data["total_out"] = 0.
re = short_compute(data, busi_date)
assert_equal(re['return_rate'], 1.)
assert_equal(re['total_in'], 5000.)
assert_equal(re['total_out'], 10000.)
assert_equal(re['exception_label'], 0)
def daily_compute(self, busi_date):
"""
"""
spark = self.spark
yesterday = get_date(self.date_order, self.order_date, busi_date, -1)
unclose = spark.sql("select * from %s.%s where busi_date='%s'" %
(self.fdata, self.unclose_table, yesterday))
trd = spark.sql("select * from %s.%s where busi_date='%s'" %
(self.odata, self.cash_flow_table, busi_date))
trd = trd.filter("trd_type='short_related' and prd_no!='0.0'")
trd = trd.withColumn(
"now_trd", func.struct("trd_qty", "trd_cash_flow", "timestamp"))
trd = trd.groupBy("trade_id", "secu_acc_id", "prd_no") \
.agg(func.collect_list("now_trd").alias("now_trd"))
trd.persist(StorageLevel.DISK_ONLY)
trd.count()
debt = spark.sql("select * from %s.%s where busi_date='%s'" %
(self.odata, self.debt_table, busi_date))
debt = debt.select("trade_id", "secu_acc_id", "prd_no", "liab_qty",
"mkt_val")
debt = debt.filter("prd_no!='0.0'")
df = full_outer_join(unclose, trd,
["trade_id", "secu_acc_id", "prd_no"])
df = full_outer_join(df, debt, ["trade_id", "secu_acc_id", "prd_no"])
df.persist(StorageLevel.DISK_ONLY)
df.count()
data = df.rdd.map(lambda x: Row(**short_compute(
x.asDict(recursive=True), busi_date)))
if data.count() > 0:
data = data.toDF()
close = data.filter("remain_liab_qty = 0")
close = close.withColumn("close_date", close.busi_date)
self.check_data(close)
unclose = data.filter("remain_liab_qty != 0")
self.save_close_data(close, busi_date)
self.save_unclose_data(unclose, busi_date)
else:
print "清仓股票收益做空没有数据输出"