async def test_get_bars_with_turnover(self):
code = "000001.XSHE"
start = arrow.get("2020-01-03").date()
stop = arrow.get("2020-1-16").date()
frame_type = FrameType.DAY
expected = [
0.5752,
0.4442,
0.3755,
0.4369,
0.5316,
0.3017,
0.4494,
0.6722,
0.4429,
0.5298,
]
sec = Security(code)
bars = await sec.load_bars(start, stop, frame_type, turnover=True)
for i, bar in enumerate(bars):
self.assertAlmostEqual(expected[i], bar["turnover"], places=3)
start = arrow.get("2020-11-02 15:00:00").datetime
stop = arrow.get("2020-11-06 14:30:00").datetime
frame_type = FrameType.MIN30
sec = Security(code)
bars = await sec.load_bars(start, stop, frame_type, turnover=True)
expected = [0.02299885, 0.02921041]
self.assertAlmostEqual(expected[0], bars["turnover"][-2], places=3)
self.assertAlmostEqual(expected[1], bars["turnover"][-1], places=3)
def test_000_properties(self):
sec = Security("000001.XSHE")
for key, value in zip(
"display_name ipo_date end_date".split(" "),
"平安银行 1991-04-03 2200-01-01".split(" "),
):
self.assertEqual(str(getattr(sec, key)), value)
sec = Security("399001.XSHE")
print(sec)
async def test_buy_limit_events(self):
end = arrow.get('2020-8-7').date()
start = tf.day_shift(end, -9)
sec = Security('603390.XSHG')
bars = await sec.load_bars(start, end, FrameType.DAY)
count, indices = count_buy_limit_event(sec, bars)
self.assertEqual(count, 1)
self.assertEqual(
arrow.get('2020-7-28').date(), bars['frame'][indices[0]])
sec = Security('000070.XSHE')
start = tf.day_shift(end, -29)
bars = await sec.load_bars(start, end, FrameType.DAY)
count_buy_limit_event(sec, bars)
async def add_monitor(request):
"""
supported cmd:
add, remove,list
Args:
request:
Returns:
"""
params = request.json
code = params.get("code")
plot = params.get('plot')
if all([code is None, plot is None]):
return response.text("必须指定要监控的股票代码", status=401)
try:
del params['plot']
await mm.add_monitor(plot, **params)
display_name = Security(code).display_name
return response.text(f"{display_name}已加入{plot}监控", status=200)
except Exception as e:
logger.exception(e)
return response.text(e, status=500)
async def copy(self,
code: str,
frame_type: Union[str, FrameType],
frame: Union[str, Frame],
ma_wins=None):
frame_type = FrameType(frame_type)
frame = arrow.get(frame, tzinfo=cfg.tz)
ma_wins = ma_wins or [5, 10, 20]
fit_win = 7
stop = frame
start = tf.shift(stop, -fit_win - max(ma_wins), frame_type)
sec = Security(code)
bars = await sec.load_bars(start, stop, frame_type)
features = []
for win in ma_wins:
ma = signal.moving_average(bars['close'], win)
if len(ma) < fit_win:
raise ValueError(
f"{sec.display_name} doesn't have enough bars for "
f"extracting features")
err, (a, b, c), (vx,
_) = signal.polyfit(ma[-fit_win:] / ma[-fit_win])
features.append((err, (a, b, c), vx))
return features
async def evaluate(self,
code: str,
frame_type: FrameType,
dt: Frame = None):
logger.debug("测试%s, 参数:%s %s", code, frame_type, dt)
win = 10
sec = Security(code)
end = dt or arrow.now(tz=cfg.tz).datetime
start = tf.shift(dt, -29, frame_type)
bars = await sec.load_bars(start, end, frame_type)
feat = features.ma_lines_trend(bars, [5, 10, 20])
ma5, ma10 = feat["ma5"][0], feat["ma10"][0]
# 判断是否存在vcross
vcrossed, (idx0, idx1) = signal.vcross(ma5[-win:], ma10[-win:])
if not vcrossed:
return
else:
dt1, dt2 = bars[-win:][idx0]['frame'], bars[-win:][idx1]['frame']
logger.info("%s vcross(5,10): %s, %s", sec, dt1, dt2)
# 月线要向上且形成支撑作用
err, a, b, vx, fit_win, war = feat["ma20"][1]
if err < self.err_20 and war > self.war_20:
logger.info("%s月线向上，war:%s", code, war)
await emit.emit(Events.sig_long, {
"code": code,
"plot": self.name,
"desc": f"{sec.display_name}发出老鸭头信号"
})
async def list_momentum_pool(day_offset: int = 1, sort_by='y'):
start = tf.day_shift(arrow.now().date(), -day_offset)
key = f"plots.momentum.pool"
recs = await cache.sys.hgetall(key)
data = []
for k, v in recs.items():
frame, code = k.split(":")
if arrow.get(frame) < arrow.get(start):
continue
sec = Security(code)
v = json.loads(v)
frame_type = FrameType(v.get("frame_type"))
fired = tf.int2time(frame) if frame_type in tf.minute_level_frames else \
tf.int2date(frame)
data.append({
"name": sec.display_name,
"code": code,
"fired": fired,
"frame": frame_type.value,
"y": round(v.get("y"), 2),
"vx": round(v.get("vx"), 1),
"a": round(v.get("a"), 4),
"b": round(v.get("b"), 4),
"err": round(v.get("err"), 4)
})
if len(data) == 0:
print("no data")
else:
df = DataFrame(data)
df.set_index('fired', inplace=True)
display(df.sort_values(sort_by))
async def evaluate(self,
code,
frame_type,
flag,
ma_win: int = 20,
slp=1e-2):
"""
当股价回归到指定的均线上时，发出信号
Args:
code:
frame_type:
flag:
ma:需要监控的均线
Returns:
"""
bars = await self.get_bars(code, ma_win + 10, frame_type)
ma = signal.moving_average(bars['close'], ma_win)
err, (a, b, c), (vx, _) = signal.polyfit(ma[-7:] / ma[-7])
p = np.poly1d((a, b, c))
if (p(11) / p(6) - 1) / 5 < slp:
return
sec = Security(code)
alarm = f"{sec.display_name}触达{ma_win}均线。"
await emit.emit(Events.sig_long, {"alarm": alarm})
async def scan(self, stop: Frame = None):
start = tf.shift(stop, -26, FrameType.WEEK)
ERR = {5: 0.008, 10: 0.004, 20: 0.004}
for code in Securities().choose(['stock']):
#for code in ['002150.XSHE']:
sec = Security(code)
bars = await sec.load_bars(start, stop, FrameType.WEEK)
if bars[-1]['frame'] != stop:
raise ValueError("")
t1, t2, t3 = False, False, False
params = []
for win in [5, 10, 20]:
ma = signal.moving_average(bars['close'], win)
err, (a, b, c), (vx, _) = signal.polyfit(ma[-7:] / ma[-7])
if err > ERR[win]:
continue
p = np.poly1d((a, b, c))
slp3 = round(p(9) / p(6) - 1, 2)
params.append(np.round([slp3, a, b], 4))
if win == 5:
t1 = slp3 >= 0.03 and a > 0.005
if win == 10:
t2 = slp3 >= 0.02 and (b > abs(10 * a) or a > 0.0005)
if win == 20:
t3 = slp3 >= -1e-6 and a >= 0
if all([t1, t2, t3]):
print(sec.display_name, params)
async def list_monitors(plot: str = None, code: str = None):
monitors = {}
for item in await request("monitor", "list", plot=plot, code=code):
code = item[1].get("code")
item[1]['name'] = Security(code).display_name
item[1]['triggers'] = item[2]
recs = monitors.get(item[0], [])
recs.append(item[1])
monitors[item[0]] = recs
pd.set_option('max_rows', 100)
if plot is not None:
plots = [plot]
else:
plots = monitors.keys()
for plot in plots:
recs = monitors.get(plot)
df = DataFrame(
recs,
columns=["name", "code", "frame_type", "flag", "win", "triggers"])
df.columns = ["name", "code", "frame", "flag", "win", "trigger"]
print(plot)
display(df)
async def list_stock_pool(plot=None, time_offset: int = 3):
now = arrow.now().date()
start = tf.day_shift(now, -time_offset)
if plot is None:
keys = await cache.sys.keys("plots.*.pool")
else:
keys = [f"plots.{plot}.pool"]
results = []
for key in keys:
recs = await cache.sys.hgetall(key)
data = []
for k, v in recs.items():
_frame, code = k.split(":")
if len(_frame) == 8:
frame = tf.int2date(int(_frame))
else:
frame = tf.int2time(int(_frame))
if arrow.get(frame) < arrow.get(start):
continue
sec = Security(code)
row = {"name": sec.display_name, "code": code, "frame": frame}
row.update(json.loads(v))
data.append(row)
print(f"----------{key.lower()}----------")
df = DataFrame(data=data)
df.set_index('frame', inplace=True)
display(df)
results.append(df)
return results
def translate_monitor(self, job_name, params: dict, trigger: dict):
_flag_map = {"both": "双向监控", "long": "做多信号", "short": "做空信号"}
_frame_type_map = {
"1d": "日线",
"1w": "周线",
"1M": "月线",
"30m": "30分钟线",
"60m": "60分钟线",
"120m": "120分钟线"
}
items = {"key": job_name}
for k, v in params.items():
if k == "flag":
items['flag'] = _flag_map[v]
elif k == "code":
items['代码'] = v.split(".")[0]
items['名称'] = Security(v).display_name
elif k == "frame_type":
items['周期'] = _frame_type_map[v]
elif k == "win":
items['均线'] = f"MA{v}"
items['监控计划'] = mm.translate_trigger(trigger)
return items
async def test_price_change(self):
sec = Security("000001.XSHG")
frame_type = FrameType.DAY
start = arrow.get("2020-07-29").date()
end = arrow.get("2020-8-7").date()
pc = await sec.price_change(start, end, frame_type, False)
self.assertAlmostEqual(pc, 3354.04 / 3294.55 - 1, places=3)
async def test_004_fq(self):
"""测试复权"""
sec = Security("002320.XSHE")
start = arrow.get("2020-05-06").date()
stop = tf.shift(start, -249, FrameType.DAY)
start, stop = stop, start
# bars with no fq
bars1 = await sec.load_bars(start, stop, FrameType.DAY, fq=False)
bars2 = await sec.load_bars(start, stop, FrameType.DAY)
self.assertEqual(250, len(bars1))
expected1 = [
[
arrow.get("2019-04-24").date(),
16.26,
16.38,
15.76,
16.00,
5981087.0,
9.598480e07,
3.846000,
],
[
arrow.get("2020-05-06").date(),
10.94,
11.22,
10.90,
11.15,
22517883.0,
2.488511e08,
8.849346,
],
]
expected2 = [
[
arrow.get("2019-04-24").date(),
7.07,
7.12,
6.85,
6.95,
13762015.0,
9.598480e07,
3.846000,
],
[
arrow.get("2020-05-06").date(),
10.94,
11.22,
10.90,
11.15,
22517883.0,
2.488511e08,
8.849346,
],
]
self.assert_bars_equal(expected2, bars2)
self.assert_bars_equal(expected1, bars1)
async def predict(self, code, x_end_date: datetime.date, max_error: float = 0.01):
sec = Security(code)
start = tf.day_shift(x_end_date, -29)
bars = await sec.load_bars(start, x_end_date, FrameType.DAY)
features = self.extract_features(bars, max_error)
if len(features) == 0:
logger.warning("cannot extract features from %s(%s)", code, x_end_date)
else:
return self.model.predict([features])
async def summary(code: str,
end: Frame,
frame: FrameType = FrameType.DAY,
win: int = 7):
sec = Security(code)
start = tf.shift(end, -(60 + 19), frame)
bars = await sec.load_bars(start, end, frame)
end_dt = bars['date'].iat[-1]
ma5 = np.array(signal.moving_average(bars['close'], 5))
ma10 = np.array(signal.moving_average(bars['close'], 10))
ma20 = np.array(signal.moving_average(bars['close'], 20))
ma60 = np.array(signal.moving_average(bars['close'], 60))
_ma5, _ma10, _ma20 = ma5[-win:], ma10[-win:], ma20[-win:]
xlen = 20
ax_x = [i for i in range(xlen - win, xlen + 1)] # 回归线的坐标
# 5日均线及拟合点、预测点
color = '#b08080'
lw = 0.5
err5, coef5, vertex5 = signal.polyfit(_ma5)
vx, vy = vertex5
vx = xlen - win + vx
plt.plot(vx, vy * 0.995, "^", color=color) # 5日低点
plt.plot(ma5[-xlen:], color=color, linewidth=lw) # 均线
p5 = np.poly1d(coef5)
y5 = [p5(i) for i in range(win + 1)]
c0 = bars['close'].iat[-1]
pred_c = y5[-1] * 5 - bars['close'][-4:].sum()
plt.gcf().text(0.15, 0.85,
f"{code} {end_dt} ^{100 * (pred_c / c0 - 1):.02f}%")
plt.plot(ax_x, y5, 'o', color=color, mew=0.25, ms=2.5) # 回归均线
# 10日均线及回归线
color = '#00ff80'
err10, coef10, vertex10 = signal.polyfit(_ma10)
p10 = np.poly1d(coef10)
y10 = [p10(i) for i in range(win + 1)]
plt.plot(ma10[-xlen:], color=color, linewidth=lw)
plt.plot(ax_x, y10, 'o', color=color, mew=0.25, ms=2.5)
# 20日均线及回归线
color = '#00ffff'
err20, coef20, vertex20 = signal.polyfit(_ma20)
p20 = np.poly1d(coef20)
y20 = [p20(i) for i in range(win + 1)]
plt.plot(ma20[-xlen:], color=color, linewidth=lw)
plt.plot(ax_x, y20, 'o', color=color, mew=0.25, ms=2.5)
# 60日均线
color = "#2222ff"
plt.plot(ma60[-xlen:], color=color, linewidth=lw)
async def get_bars(self,
code: str,
n: int,
frame_type: FrameType,
end_dt: Frame = None):
end_dt = end_dt or arrow.now(tz=cfg.tz)
sec = Security(code)
start = tf.shift(tf.floor(end_dt, frame_type), -n + 1, frame_type)
return await sec.load_bars(start, end_dt, frame_type)
async def test_cross(self):
end = arrow.get('2020-7-24').date()
start = tf.day_shift(end, -270)
sec = Security('000035.XSHE')
jlkg = await sec.load_bars(start, end, FrameType.DAY)
ma5 = signal.moving_average(jlkg['close'], 5)
ma250 = signal.moving_average(jlkg['close'], 250)
flag, idx = signal.cross(ma5[-10:], ma250[-10:])
self.assertEqual(flag, -1)
self.assertEqual(idx, 8)
async def plot_ma(code: str,
groups=None,
end: Frame = None,
frame_type: FrameType = FrameType.DAY):
groups = groups or [5, 10, 20, 60, 120]
sec = Security(code)
end = end or tf.floor(arrow.now(), frame_type)
start = tf.shift(end, -(groups[-1] + 19), frame_type)
bars = await sec.load_bars(start, end, frame_type)
for win in groups:
ma = signal.moving_average(bars['close'], win)
plt.plot(ma[-20:])
async def _build_train_data(self, frame_type: FrameType,
n: int, max_error: float = 0.01):
"""
从最近的符合条件的日期开始，遍历股票，提取特征和标签，生成数据集。
Args:
n: 需要采样的样本数
Returns:
"""
watch_win = 5
max_curve_len = 5
max_ma_win = 20
# y_stop = arrow.get('2020-7-24').date()
y_stop = tf.floor(arrow.now(tz=cfg.tz), frame_type)
y_start = tf.shift(y_stop, -watch_win + 1, frame_type)
x_stop = tf.shift(y_start, -1, frame_type)
x_start = tf.shift(x_stop, -(max_curve_len + max_ma_win - 1), frame_type)
data = []
while len(data) < n:
for code in Securities().choose(['stock']):
#for code in ['000601.XSHE']:
try:
sec = Security(code)
x_bars = await sec.load_bars(x_start, x_stop, FrameType.DAY)
y_bars = await sec.load_bars(y_start, y_stop, FrameType.DAY)
# [a, b, axis] * 3
x = self.extract_features(x_bars, max_error)
if len(x) == 0: continue
y = np.max(y_bars['close']) / x_bars[-1]['close'] - 1
if np.isnan(y): continue
feature = [code, tf.date2int(x_stop)]
feature.extend(x)
data.append(feature)
except Exception as e:
logger.warning("Failed to extract features for %s (%s)",
code,
x_stop)
logger.exception(e)
if len(data) >= n:
break
if len(data) % 500 == 0:
logger.info("got %s records.", len(data))
y_stop = tf.day_shift(y_stop, -1)
y_start = tf.day_shift(y_start, -1)
x_stop = tf.day_shift(y_start, -1)
x_start = tf.day_shift(x_start, -1)
return data
async def test_001_choose(self):
s = Securities()
result = s.choose(["stock", "index"])
self.assertEqual("000001.XSHE", result[0])
result = s.choose(["stock"], exclude_300=True)
self.assertTrue(all([not x.startswith("300") for x in result]))
result = s.choose(["stock"], exclude_st=True)
for code in result:
sec = Security(code)
self.assertTrue(sec.display_name.upper().find("ST") == -1)
result = s.choose(["stock"], exclude_688=True)
self.assertTrue(all([not x.startswith("688") for x in result]))
async def read_fired_signal_msg(msg: dict):
plot, flag, code = msg.get("plot"), msg.get("flag"), msg.get("code")
plot_name = msg.get("name")
sec = Security(code)
if flag == "long":
sig_name = "发出买入信号"
elif flag == "short":
sig_name = "发出卖出信号"
else:
sig_name = "触发"
text = f"{plot_name}监控策略在{sec.display_name}上{sig_name}"
msg.update({"股票名": sec.display_name})
await read_msg(text)
async def find_by_moving_average(self):
result = []
for code in Securities().choose(['stock']):
day = arrow.now().date()
sec = Security(code)
try:
signal, fit = await self.test_signal(sec, day)
if abs(signal) == 1:
result.append([code, day, signal, fit])
except Exception as e:
logger.info(e)
continue
# reporter.info("%s,%s,%s,%s,%s,%s,%s,%s,%s",
# code, day, signal, *fit[0], *fit[1], *fit[2])
return result
async def test_load_bars_batch(self):
codes = ["000001.XSHE", "000001.XSHG"]
# end = arrow.now(tz=cfg.tz).datetime
# async for code, bars in Security.load_bars_batch(codes, end, 10,
# FrameType.MIN30):
# print(bars[-2:])
# self.assertEqual(10, len(bars))
#
# codes = ['000001.XSHE', '000001.XSHG']
end = arrow.get("2020-08-27").datetime
async for code, bars in Security.load_bars_batch(
codes, end, 5, FrameType.DAY):
print(code, bars[-2:])
self.assertEqual(5, len(bars))
self.assertEqual(bars[-1]["frame"], end.date())
if code == "000001.XSHG":
self.assertAlmostEqual(3350.11, bars[-1]["close"], places=2)
async def evaluate(self,
code: str,
frame_type: FrameType,
dt: Frame = None,
win=15):
sec = Security(code)
end = dt or arrow.now(tz=cfg.tz)
start = tf.shift(tf.floor(end, frame_type), -win - 20, frame_type)
bars = await sec.load_bars(start, end, frame_type)
if len(bars) < win + 20:
return
# 使用股价重心而不是收盘价来判断走势
o, c = bars[-1]['open'], bars[-1]['close']
feat = features.ma_lines_trend(bars, [5, 10, 20])
ma5, ma10, ma20 = feat["ma5"][0], feat["ma10"][0], feat["ma20"][0]
if np.any(np.isnan(ma5)):
return
mas = np.array([ma5[-1], ma10[-1], ma20[-1]])
# 起涨点：一阳穿三线来确认
if not (np.all(o <= mas) and np.all(c >= mas)):
return
# 三线粘合：三线距离小于self.max_distance
distance = self.distance(ma5[:-1], ma10[:-1], ma20[:-1])
if distance > self.max_distance:
return
# 月线要拉直，走平或者向上
err, (a, b) = signal.polyfit((ma20 / ma20[0]), deg=1)
if err > self.fiterr_ma20 and a < self.fitslp_ma20:
return
logger.info("%s",
f"{sec.display_name}\t{distance:.3f}\t{a:.3f}\t{err:.3f}")
await self.fire("long",
code,
dt,
frame_type=frame_type.value,
distance=distance)
async def test_screen(self):
import cfg4py
import os
from alpha.config import get_config_dir
os.environ[cfg4py.envar] = 'PRODUCTION'
cfg4py.init(get_config_dir())
await omicron.init()
code = '300023.XSHE'
sec = Security(code)
stop = arrow.now().datetime
start = tf.day_shift(stop, -3)
bars = await sec.load_bars(start, stop, FrameType.DAY)
print(bars)
if np.all(bars['close'] > bars['open']):
print(sec.display_name, "\t",
100 * (bars[-1]['close'] / bars[-2]['close'] - 1))
async def test_005_realtime_bars(self):
"""测试获取实时行情"""
sec = Security("000001.XSHE")
frame_type = FrameType.MIN15
logger.info("scenario: get realtime bars")
start = arrow.get("2020-05-06 10:15:00", tzinfo=cfg.tz).datetime
stop = arrow.get("2020-05-06 10:25:00", tzinfo=cfg.tz).datetime
await cache.clear_bars_range(sec.code, frame_type)
bars = await sec.load_bars(start, stop, frame_type)
self.assertEqual(start, bars[0]["frame"])
self.assertEqual(stop, bars[-1]["frame"])
# now we've cached bars at 2020-05-06 10:15:00
bars = await sec.load_bars(start, stop, frame_type)
self.assertEqual(start, bars[0]["frame"])
self.assertEqual(stop, bars[-1]["frame"])
async def predict_ma(code: str,
frame_type: FrameType = FrameType.DAY,
end: Frame = None):
"""
预测ma5、ma10、ma20的下一个数据
Args:
code:
frame_type:
end:
Returns:
"""
sec = Security(code)
start = tf.shift(end, -29, frame_type)
bars = await sec.load_bars(start, end, frame_type)
c0 = bars['close'][-1]
target = [c0 * (1 + f / 100) for f in range(-3, 3)]
for c in target:
close = np.append(bars['close'], c)
ma5 = signal.moving_average(close, 5)
ma10 = signal.moving_average(close, 10)
ma20 = signal.moving_average(close, 20)
fig = plt.figure()
axes = plt.subplot(111)
axes.plot([i for i in range(27)],
close[-27:],
color='#000000',
linewidth=0.5) # len(ma5) == 27
axes.plot(ma5)
axes.plot([i for i in range(5, len(ma10) + 5)], ma10)
axes.text(26, ma10[-1], f"{ma10[-1]:.2f}")
axes.plot([i for i in range(15, len(ma20) + 15)], ma20)
axes.text(26, c, f"{c:.2f}")
axes.text(
0.5, 3450,
f"{100 * (c / c0 - 1):.2f}% {c:.2f} {ma5[-1]:.2f} {ma10[-1]:.2f}")
async def fire_long(self,
end: Frame,
frame_type: FrameType.DAY,
win=60,
adv=0.03):
secs = Securities()
results = []
for code in secs.choose(['stock']):
#for code in ['601238.XSHG']:
sec = Security(code)
if sec.name.find("ST") != -1 or sec.code.startswith("688"):
continue
start = tf.shift(end, -win + 1, frame_type)
bars = await sec.load_bars(start, end, frame_type)
ilow = np.argmin(bars['low'])
if ilow > win // 2: #创新低及后面的反弹太近，信号不可靠
continue
low = bars['low'][ilow]
last = bars['low'][-5:]
if np.count_nonzero((last > low) & (last < low * 1.02)) < 3:
# 对新低的测试不够
continue
c1, c0 = bars['close'][-2:]
# 今天上涨幅度是否大于adv?
if c0 / c1 - 1 < adv:
continue
# 是否站上5日线10日线？
ma5 = signal.moving_average(bars['close'], 5)
ma10 = signal.moving_average(bars['close'], 10)
if c0 < ma5[-1] or c0 < ma10[-1]: continue
price_change = await sec.price_change(end, tf.day_shift(end, 5),
frame_type)
print(f"FIRED:{end}\t{code}\t{price_change:.2f}")
results.append([end, code, price_change])
return results
async def test_003_slice(self):
sec = Security("000001.XSHE")
start = arrow.get("2020-01-03").date()
stop = arrow.get("2020-01-16").date()
await sec.load_bars(start, stop, FrameType.DAY)
bars = sec[0:]
expected = [
[
start, 16.94, 17.31, 16.92, 17.18, 1.11619481e8, 1914495474.63,
118.73
],
[
stop, 16.52, 16.57, 16.2, 16.33, 1.02810467e8, 1678888507.83,
118.73
],
]
self.assert_bars_equal(expected, bars)
expected = [
[
arrow.get("2020-01-03").date(),
16.94,
17.31,
16.92,
17.18,
1.11619481e8,
1914495474.63,
118.73,
],
[
arrow.get("2020-01-06").date(),
17.01,
17.34,
16.91,
17.07,
86208350.0,
1477930193.19,
118.73,
],
]
self.assert_bars_equal(expected, sec[0:2])
