def test_mfundinfo():
zogqb.bcmkset(xa.cashinfo())
assert round(zogqb.total_annualized_returns('2018-08-01'), 3) == 0.036
with pytest.raises(FundTypeError) as excinfo:
xa.fundinfo("001211")
assert str(excinfo.value
) == "This code seems to be a mfund, use mfundinfo instead"
def test_customize_fee():
df = pd.DataFrame(
{"date": ["2020-05-28", "2020-06-01"], "519732": [500.005, -0.505]}
)
df["date"] = pd.to_datetime(df["date"])
dqzf = xa.trade(xa.fundinfo("519732"), df)
assert dqzf.dailyreport("2020-06-02")["基金分红与赎回"].iloc[0] == 2.22
assert dqzf.dailyreport("2020-05-31")["持有份额"].iloc[0] == 116.5
# issue 59
df = pd.DataFrame(
{"date": ["2020-05-28", "2020-06-01"], "519732": [10000.005, -0.505]}
)
df["date"] = pd.to_datetime(df["date"])
dqzf = xa.trade(xa.fundinfo("519732"), df)
assert round(dqzf.dailyreport("2020-05-28").iloc[0]["基金现值"], 0) == 10000.0
def test_fund_update():
zghl = xa.fundinfo("164906", **ioconf)
len1 = len(zghl.price)
delete_csvlines(path=ioconf["path"] + "164906.csv", lines=83)
zghl = xa.fundinfo("164906", **ioconf)
len2 = len(zghl.price)
assert len1 == len2
jxzl = xa.mfundinfo("002758", **ioconf)
netvalue = jxzl.price.iloc[-1]["netvalue"]
len3 = len(jxzl.price)
delete_csvlines(path=ioconf["path"] + "002758.csv", lines=9)
jxzl = xa.mfundinfo("002758", **ioconf)
netvalue2 = jxzl.price.iloc[-1]["netvalue"]
len4 = len(jxzl.price)
assert len3 == len4
assert round(netvalue, 4) == round(netvalue2, 4)
def test_fund():
assert hs300.round_label == 1
assert hs300.name == "景顺长城沪深300指数增强" ## "景顺长城沪深300增强", 蜜汁改名。。。
assert hs300.fenhongdate[1] == pd.Timestamp("2017-08-15")
assert hs300.get_holdings(2019, 4).iloc[0]["name"] == "中国平安"
assert (
float(hs300.special[hs300.special["date"] == "2017-08-04"]["comment"]) == 0.19
)
hs300.rate = 0.12
hs300.segment = [[0, 7], [7, 365], [365, 730], [730]]
with pytest.raises(Exception) as excinfo:
hs300.shuhui(
100,
"2014-01-04",
[[pd.Timestamp("2014-01-03"), 200], [pd.Timestamp("2017-01-03"), 200]],
)
assert str(excinfo.value) == "One cannot move share before the lastest operation"
assert (
hs300.shuhui(
320,
"2018-01-01",
[[pd.Timestamp("2011-01-03"), 200], [pd.Timestamp("2017-12-29"), 200]],
)[1]
== 685.72
)
assert hs300.shengou(200, "2018-07-20")[2] == 105.24
with pytest.raises(FundTypeError) as excinfo:
xa.mfundinfo("000311")
assert str(excinfo.value) == "This code seems to be a fund, use fundinfo instead"
hs300.info()
dax = xa.fundinfo("510030") # test empty shuhuifei and shengoufei case
assert dax.feeinfo == ["小于7天", "1.50%", "大于等于7天", "0.00%"]
def index(request):
code = request.GET.get('code')
try:
zzcm = xa.fundinfo(code)
except Exception:
return JsonResponse({'code': 500, 'msg': '基金代码错误'})
# 分红再投入
zzcm.dividend_label = 1
orgin_start = request.GET.get('start')
orgin_end = request.GET.get('end')
amount = request.GET.get('amount')
freq = request.GET.get('freq')
offset = request.GET.get('offset')
start = datetime.strptime(orgin_start, '%Y-%m-%d')
end = datetime.strptime(orgin_end, '%Y-%m-%d')
new_start = start - timedelta(days=100)
new_end = end + timedelta(days=100)
rng = pd.date_range(new_start, new_end, freq=freq) + \
pd.DateOffset(days=int(offset))
rng = rng[rng <= end] # 过滤超出范围的日期
rng = rng[rng >= start]
price = zzcm.price[(zzcm.price["date"] >= start)
& (zzcm.price["date"] <= end)]
# 有价格的起始日期
priceStart = price.iloc[0].date
priceEnd = price.iloc[-1].date
# 需要判断rng的时间是否合法，是否都在有价格的区间
datel = []
isSmall = False
for date in rng:
if date >= priceStart and date <= priceEnd:
datel.append(date)
elif date < priceStart:
isSmall = True
if isSmall:
try:
thing_index = datel.index(priceStart)
except ValueError:
thing_index = -1
if thing_index == -1:
datel.insert(0, priceStart)
status = pd.DataFrame(data={
"date": datel,
zzcm.code: [float(amount)] * len(datel)
})
cm_t3 = xa.trade(zzcm, status)
dailyreport = cm_t3.dailyreport(orgin_end)
cftable = cm_t3.cftable
del cftable['share']
cftable['date'] = cftable['date'].astype('datetime64[ns]')
cash_flow = cftable.values.tolist()
fv = dailyreport['基金现值'][0]
cash_flow.append([end, fv])
rate = xirr(cash_flow)
return JsonResponse({
'code': 0,
'xirr': rate,
'dailyreport': dailyreport.to_dict()
})
def f(trade_info, code): #某个基金的交易信息
fundinfo = xa.fundinfo(code)
buy, sell = 0, 0
fe = 0
for index, row in trade_info.iterrows():
date = row.get('date')
dwjz = get_jz(code, date)
v = row.get(code)
if v > 0:
# print('申购费率:{}'.format(fundinfo.rate))
buy += v
# buy += v
else:
sell += v
fe += v * (1 - fundinfo.rate / 100.) / dwjz #份额变动 要考虑申购费率
last_trade_day = datetime.strftime(datetime.now() - timedelta(1),
'%Y-%m-%d')
dqjz = get_jz(code, last_trade_day) #api接口到24点以后才更新净值,所以做多只能取到昨日净值
# print(dqjz)
dqye = fe * dqjz + sell #包括当前持有金额以及已卖出金额之和
syl = dqye / buy - 1 #收益率
# print('{},{}--份额:{},昨日净值{},当前余额{},总投入{},收益率{},盈利{}'.format(fundinfo.name,last_trade_day,fe,dqjz,dqye,buy,syl,dqye-buy))
print('{},当前余额{:.2f},总投入{:.2f},收益率{:.3f},盈利{:.2f}'.format(
fundinfo.name, dqye, buy, syl, dqye - buy))
return (fe, dqjz, dqye, buy, syl)
def test_weekly_price():
# see https://github.com/refraction-ray/xalpha/issues/27
ryjh = xa.fundinfo("008969")
bah = xa.policy.buyandhold(ryjh, start="2019-01-01", totmoney=100000)
bah.sellout("2020-05-12") # 选定日期全部卖出
jshstrade = xa.trade(ryjh, bah.status)
assert round(jshstrade.xirrrate("2020-05-01", startdate="2020-02-01"), 1) == 0.2
def test_csvio():
hs300 = xa.fundinfo('000311', **ioconf)
len1 = len(hs300.price)
hs300 = xa.fundinfo('000311', **ioconf)
len2 = len(hs300.price)
delete_csvlines(path=ioconf['path'] + '000311.csv')
hs300 = xa.fundinfo('000311', **ioconf)
len3 = len(hs300.price)
assert len1 == len2
assert len1 == len3
delete_csvlines(path=ioconf['path'] + '001211.csv')
zogqb2 = xa.mfundinfo('001211', **ioconf)
assert round(zogqb.price.iloc[-1].netvalue,
5) == round(zogqb2.price.iloc[-1].netvalue, 5)
delete_csvlines(path=ioconf['path'] + '0000827.csv')
zzhb2 = xa.indexinfo('0000827', **ioconf)
assert len(zzhb2.price) == len(zzhb.price)
def test_fund_update():
zghl = xa.fundinfo(
"501029", **ioconf) # 164906 maybe possible remainning issue for qdii?
len1 = len(zghl.price)
delete_csvlines(path=ioconf["path"] + "501029.csv", lines=83)
zghl = xa.fundinfo("501029", **ioconf)
len2 = len(zghl.price)
assert len1 == len2
jxzl = xa.mfundinfo("002758", **ioconf)
netvalue = jxzl.price.iloc[-1]["netvalue"]
len3 = len(jxzl.price)
delete_csvlines(path=ioconf["path"] + "002758.csv", lines=9)
jxzl = xa.mfundinfo("002758", **ioconf)
netvalue2 = jxzl.price.iloc[-1]["netvalue"]
len4 = len(jxzl.price)
assert len3 == len4
assert round(netvalue, 4) == round(netvalue2, 4)
def test_fund_holdings():
f = xa.fundinfo("F519732")
df = f.get_stock_holdings(2020, 2)
assert df.iloc[0]["code"] == "300413"
d = f.get_industry_holdings(2020, 2)
assert d["交通运输"] == 5.48
d = f.get_portfolio_holdings("20180101")
assert d["stock_ratio"] == 68.62
df = f.get_bond_holdings(2020, 2)
assert df.iloc[0]["code"] == "190307"
assert f.which_industry() == "宽基基金"
def test_fund_update():
zghl = xa.fundinfo(
"501029", **ioconf) # 164906 maybe possible remainning issue for qdii?
len1 = len(zghl.price)
delete_csvlines(path=ioconf["path"] + "501029.csv", lines=83)
zghl = xa.fundinfo("501029", **ioconf)
len2 = len(zghl.price)
assert (len1 == len2) or (len1 - len2 == -1) # similar fix up
jxzl = xa.mfundinfo("002758", **ioconf)
netvalue = jxzl.price.iloc[-1]["netvalue"]
len3 = len(jxzl.price)
delete_csvlines(path=ioconf["path"] + "002758.csv", lines=9)
jxzl = xa.mfundinfo("002758", **ioconf)
netvaluel = [
round(jxzl.price.iloc[-1]["netvalue"], 4),
round(jxzl.price.iloc[-2]["netvalue"], 4),
]
len4 = len(jxzl.price)
assert (len3 == len4) or (len3 - len4 == -1)
assert round(netvalue, 4) in netvaluel ##天天基金的总量 API 更新越来越慢了。。。
def test_csvio():
hs300 = xa.fundinfo("000311", **ioconf)
len1 = len(hs300.price)
hs300 = xa.fundinfo("000311", **ioconf)
len2 = len(hs300.price)
delete_csvlines(path=ioconf["path"] + "000311.csv")
hs300 = xa.fundinfo("000311", **ioconf)
len3 = len(hs300.price)
assert (len1 == len2) or (len1 - len2 == -1) # temp fixup
# there may be time lag for update of .js API, i.e. 天天基金的该 API 不一定能保证更新昨天的净值，即使不是 QDII
assert (len1 == len3) or (len1 - len3 == -1)
delete_csvlines(path=ioconf["path"] + "001211.csv")
zogqb2 = xa.mfundinfo("001211", **ioconf)
assert round(zogqb.price.iloc[-1].netvalue, 5) in [
round(zogqb2.price.iloc[-1].netvalue, 5),
round(zogqb2.price.iloc[-2].netvalue, 5),
]
delete_csvlines(path=ioconf["path"] + "0000827.csv")
zzhb2 = xa.indexinfo("0000827", **ioconf)
assert (len(zzhb2.price) == len(
zzhb.price)) or ((len(zzhb2.price) - len(zzhb.price)) == 1)
def get_jz(code, date):
fundinfo = xa.fundinfo(code)
df = fundinfo.price
# print(df)
#获取某一日期净值 如果没有则返回最后一个交易日净值
if df[df['date'] == date].empty:
dwjz = df.tail(1)['netvalue']
else:
dwjz = df[df['date'] == date]['netvalue']
for index in dwjz.index:
# print('{},date:{}单位净值为:{}'.format(fundinfo.name,date,dwjz.get(index)))
return dwjz.get(index)
def get_fund_history(self):
'''下载历史数据
'''
now = datetime.datetime.now()
fund_day_start = now + datetime.timedelta(days=-60)
fund_day_start = fund_day_start.strftime('%Y-%m-%d')
# 获取数据
groups = []
for fund_code in tqdm(self.load(self.SELECT_FUND_LIST_CODE_FILE)):
try:
fund_data = xa.fundinfo(fund_code, fetch=False, save=False)
fund_data.price.reset_index(drop=True, inplace=True)
fund_data.rsi(30)
fund_data = fund_data.price
fund_data.loc[:, "code"] = fund_code
fund_data = fund_data.loc[fund_data["date"] >= fund_day_start]
group = fund_data
group.sort_values("date", inplace=True)
group.loc[:, "netvalue"] = (group["netvalue"] - group["netvalue"].shift(periods=1)) / group[
"netvalue"].shift(periods=1)
group.dropna(axis=0, inplace=True)
group.loc[:, 'MA3'] = group["netvalue"].rolling(window=3).mean()
group.sort_values('date', ascending=False, inplace=True)
down_count = 0
for ele in group["MA3"]:
if ele < 0:
down_count += 1
else:
break
groups.append(
(fund_code, down_count, group.loc[group.index[0], "MA3"], group.loc[group.index[0], "RSI30"]))
except Exception as e:
continue
fund_history = pd.DataFrame(groups, columns=['code', 'down_count', 'MA3', 'RSI30'])
fund_history.sort_values("down_count", ascending=False, inplace=True)
fund_em_fund_name_df = task.load(task.ALL_MARKET_FUND_INFO_FILE)
fund_history = fund_history.merge(fund_em_fund_name_df, left_on='code', right_on='基金代码')
fund_history = fund_history.loc[:, ['基金代码', '基金简称', '基金类型', 'down_count', 'MA3', 'RSI30']]
fund_history = fund_history.loc[
(~fund_history['基金类型'].isin(["债券型", '定开债券'])) & (~fund_history['基金简称'].str.contains("债|年|月|量化"))]
joblib.dump(fund_history, self.FUND_HISTORY_DATA_FILE)
return self
def get_year_rate(code):
last_trade_day = datetime.strftime(datetime.now() - timedelta(1),
'%Y-%m-%d')
first_day_of_year = '2020-01-02'
fake_buy = 10000 #假设买入10000元
b_jz = get_jz(code, first_day_of_year)
e_jz = get_jz(code, last_trade_day)
buy_fe = fake_buy / b_jz
current_money = e_jz * buy_fe
fundinfo = xa.fundinfo(code)
#考虑分红情况
fenghong = get_fenhong(code)
fenghong_zonge = fenghong * buy_fe
add = (fenghong_zonge + current_money - fake_buy) / fake_buy
# print('{},{},add={}',b_jz,e_jz,add)
return add
def cal_fenhong(code):
fundinfo = xa.fundinfo(code)
total_fenhong = 0
# print(fundinfo.fenhongdate)
if (fundinfo.fenhongdate):
s = fundinfo.special
dates = s[s.date > np.datetime64('2020-01-01 00:00:00')]['date'] #
fenhongs = s[s.date > np.datetime64('2020-01-01 00:00:00')]['comment']
# print(tmp.date)
for index, date in dates.items():
# print(type(date))
# print(str(date)[:10])
fener = get_fener(date, code) #计算分红日持有份额
fenhong_per_fener = fenhongs[index] #分红日每一份额分红金额
total_fenhong += fenhong_per_fener * fener
print('总计分红{}'.format(total_fenhong))
return total_fenhong
def get_fenhong(code):
fundinfo = xa.fundinfo(code)
# print(fundinfo.fenhongdate)
if (fundinfo.fenhongdate):
# print(fundinfo.special.loc[])
s = fundinfo.special
# print(s.dtypes)
# print(s[s['date']])
tmp = s[s.date > np.datetime64('2020-01-01 00:00:00')]
# print(tmp)
comment = tmp['comment']
fenhong = comment.sum()
print('分红总额为{}'.format(fenhong))
for _, value in comment.items():
print(value)
return fenhong
else:
print('分红总额为{}'.format(0))
return 0
def fake_trade_300(fake_code):
read = xa.record("./tests/fund_2020.csv", skiprows=1)
jjcode_list = list(read.status.columns.values)[1:] #持有的全部基金列表
t_buy, t_get = 0, 0 #总计买入,总计剩余(包括当前剩余及赎回)
for code in jjcode_list:
trade_info = read.status.loc[:, ['date', code]]
# print(trade_info)
buy, sell = 0, 0
fe = 0
fundinfo = xa.fundinfo(fake_code)
shengoufeilv = fundinfo.rate / 100.
for index, row in trade_info.iterrows():
date = row.get('date')
dwjz = get_jz(fake_code, date) #假设买的全是hs300
v = row.get(code)
if v > 0:
buy += v
else:
sell += v
fe += v * (1 - shengoufeilv) / dwjz #份额变动
last_trade_day = datetime.strftime(datetime.now() - timedelta(1),
'%Y-%m-%d')
dqjz = get_jz(fake_code, last_trade_day)
# print(dqjz)
dqye = fe * dqjz + sell #包括当前持有金额以及已卖出金额之和
syl = dqye / buy - 1 #收益率
# print('{},{}--份额:{},昨日净值{},当前余额{},总投入{},收益率{},盈利{}'.format(fundinfo.name,last_trade_day,fe,dqjz,dqye,buy,syl,dqye-buy))
print('{},当前余额{},总投入{},收益率{},盈利{}'.format(fake_code, dqye, buy, syl,
dqye - buy))
t_buy += buy
t_get += dqye
print('假设全部买入{},总投入:{},总回报:{},整体收益率:{:.3f},盈利{}\n'.format(
fake_code, t_buy, t_get, t_get / t_buy - 1, t_get - t_buy))
def get_fener(deadline_date, code):
read = xa.record("./tests/fund_2020.csv", skiprows=1)
trade_info = read.status.loc[:, ['date', code]]
trade_info = trade_info[trade_info.date < np.datetime64(deadline_date)]
# print(trade_info)
fundinfo = xa.fundinfo(code)
#计算份额变动
fe = 0
for _, row in trade_info.iterrows():
date = row.get('date')
dwjz = get_jz(code, date)
v = row.get(code) #买入或者卖出金额
if v > 0:
# print('申购费率:{}'.format(fundinfo.rate))
fe += v * (1 - fundinfo.rate / 100.) / dwjz
else:
fe += v / dwjz #这里没有考虑赎回的费率 注意这里不是减法 卖出的话v为负值
print('截止{}持有份额{}'.format(deadline_date, fe))
return fe
import sys
sys.path.insert(0, "../")
import xalpha as xa
import pytest
import pandas as pd
path = 'demo.csv'
path1 = 'demo1.csv'
cm = xa.fundinfo('164818')
statb = xa.record(path).status
statl = xa.record(path1, format="list").status
cm_t = xa.trade(cm, statb)
ioconf = {'save': True, 'fetch': True, 'path': 'pytest', 'form': 'csv'}
def test_trade():
assert cm_t.cftable.loc[2, 'share'] == -129.14
assert round(cm_t.xirrrate('2018-03-03'), 3) == -0.24
assert cm_t.dailyreport('2018-07-29').iloc[0]['单位成本'] == 1.346
cm_t.v_tradecost('2018-08-01')
cm_t.v_totvalue('2018-07-31')
cm_t.v_tradevolume(freq='M')
def test_mul():
with pytest.raises(Exception) as excinfo:
cm_m = xa.mulfix(cm_t, totmoney=200)
assert str(excinfo.value) == 'You cannot sell first when you never buy'
with pytest.raises(Exception) as excinfo:
cm_m = xa.mulfix(cm_t, totmoney=300)
import sys
sys.path.insert(0, "../")
import xalpha as xa
from xalpha.exceptions import FundTypeError
import pandas as pd
import pytest
ioconf = {"save": True, "fetch": True, "path": "pytest", "form": "csv"}
ca = xa.cashinfo(interest=0.0002, start="2015-01-01")
zzhb = xa.indexinfo("0000827", **ioconf)
hs300 = xa.fundinfo("000311")
zogqb = xa.mfundinfo("001211", **ioconf)
def test_fundreport():
# somehow fragile, to be checked
r = xa.FundReport("000827")
assert r.get_report()[0][:2] == "广发"
assert r.analyse_report(1)["bank"][:2] == "兴业"
assert r.show_report_list(type_=0)[0]["FUNDCODE"] == "000827"
assert r.get_report(id_="AN202003171376532533")[0][:2] == "广发"
def test_cash():
assert (
round(ca.price[ca.price["date"] == "2018-01-02"].iloc[0].netvalue, 4) == 1.2453
)
assert ca.code == "mf"
date, value, share = ca.shuhui(
300, "2018-01-01", [[pd.Timestamp("2017-01-03"), 200]]
import sys
sys.path.insert(0, "../")
import xalpha as xa
import pytest
import pandas as pd
path = "demo.csv"
path1 = "demo1.csv"
cm = xa.fundinfo("164818")
statb = xa.record(path).status
statl = xa.record(path1, format="list").status
cm_t = xa.trade(cm, statb)
ioconf = {"save": True, "fetch": True, "path": "pytest", "form": "csv"}
def test_trade():
assert cm_t.cftable.loc[2, "share"] == -129.14
assert round(cm_t.xirrrate("2018-03-03"), 3) == -0.24
assert cm_t.dailyreport("2018-07-29").iloc[0]["单位成本"] == 1.346
cm_t.v_tradecost("2018-08-01")
cm_t.v_totvalue("2018-07-31")
cm_t.v_tradevolume(freq="M")
def test_mul():
with pytest.raises(Exception) as excinfo:
cm_m = xa.mulfix(cm_t, totmoney=200)
assert str(excinfo.value) == "You cannot sell first when you never buy"
with pytest.raises(Exception) as excinfo:
cm_m = xa.mulfix(cm_t, totmoney=300)
import sys
sys.path.insert(0, "../")
import xalpha as xa
from xalpha.exceptions import FundTypeError
import pandas as pd
import pytest
ioconf = {'save': True, 'fetch': True, 'path': 'pytest', 'form': 'csv'}
ca = xa.cashinfo(interest=0.0002, start='2015-01-01')
zzhb = xa.indexinfo('0000827', **ioconf)
hs300 = xa.fundinfo('000311')
zogqb = xa.mfundinfo('001211', **ioconf)
def test_cash():
assert round(ca.price[ca.price['date'] == '2018-01-02'].iloc[0].netvalue,
4) == 1.2453
assert ca.code == 'mf'
date, value, share = ca.shuhui(300, '2018-01-01',
[[pd.Timestamp('2017-01-03'), 200]])
assert date == pd.Timestamp('2018-01-02')
assert value == 249.06
assert share == -200
ca.bcmkset(ca)
assert ca.alpha() == 0
assert round(ca.total_annualized_returns('2018-01-01'), 4) == 0.0757
def test_index():
assert round(
