def before_ranking(date, ranking_type, before=1):
d = utils.to_datetime(date) - utils.relativeterm(before, with_time=True)
while not utils.is_weekday(d):
d = d - utils.relativeterm(1, with_time=True)
d = utils.to_format(d)
stocks = Loader.ranking(d, ranking_type)
return stocks
def convert_pdf():
title, head_image, article = get_content()
if is_weekday():
logger.warning("周末不发版")
return "周末不发版"
year, month, day = get_now_day()
directory = get_today_directory()
filename = f'{directory}/{year}{month}{day}.pdf'
html = pre.format(title=title, article=article, head_image=head_image)
pdfkit.from_string(html, filename, configuration=config, options=options)
def job():
if utils.is_weekday():
logging.info(
"*********************************************************************"
)
if utils.need_update_data():
logging.info("更新数据")
process.run()
stocks = utils.get_stocks()
m_filter = strategy(end_date=None)
results = list(filter(m_filter, stocks))
logging.info('选股结果：{0}'.format(results))
logging.info(
"*********************************************************************"
)
def simulates(self,
strategy_setting,
data,
start_date,
end_date,
with_closing=True,
ignore_manda=True):
self.log("simulating %s %s" % (start_date, end_date))
self.stats = SimulatorStats()
args = data["args"]
stocks = data["data"]
index = data["index"]
codes = self.get_targets(args, [], start_date)
# シミュレーター準備
combination, simulators = self.create_simulator(
args, codes, stocks, start_date, end_date, strategy_setting,
ignore_manda)
# 日付のリストを取得
dates = self.simulate_dates(codes, stocks, start_date, end_date)
self.log("targets: %s" % list(simulators.keys()))
capacity = None
for step, date in enumerate(dates):
# 休日はスキップ
if not utils.is_weekday(utils.to_datetime(date)):
self.log("%s is not weekday" % date)
continue
self.log("\n=== [%s] ===" % date)
stats = self.stats.create_trade_data()
stats["date"] = date
binding = sum(
list(map(lambda x: x.order_binding(), simulators.values())))
for code in simulators.keys():
# 対象日までのデータの整形
self.log("[%s]" % code)
# M&A 適用
simulators = self.manda_by_date(date, code, simulators)
simulators[code].capacity = simulators[
code].capacity if capacity is None else capacity
simulators[code].binding = binding - simulators[
code].order_binding() # 自分の拘束分はsimulator側で加算するので引いておく
simulators[code].simulate_by_date(date, stocks[code], index)
capacity = simulators[code].capacity
binding += simulators[code].order_binding(
) - simulators[code].unbound
stats["unrealized_gain"] = self.sum_stats(
simulators, lambda x: x.stats.last_unrealized_gain())
stats["gain"] = self.sum_stats(simulators,
lambda x: x.stats.get("gain", 0))
self.stats.append(stats)
stats, simulators = self.closing(stats, simulators)
self.log(
"gain: %s, %s, %s" %
(stats["unrealized_gain"], stats["gain"], capacity + binding))
# 手仕舞い
if with_closing:
simulators = self.force_closing(dates, stocks, simulators)
return simulators
def job():
if utils.is_weekday():
#work_flow.process()
return TRUE
def job():
if utils.is_weekday():
work_flow.process()
def edit_timeline(self, bucket, intial_location_str, radius):
condition = True
tries = 0
while True:
location_type = np.random.choice(self.buckets[bucket])
print(location_type)
response = self.query(intial_location_str, radius, location_type)
tries += 1
if len(response['results']) == 0 and tries < 3:
continue
else:
break
if len(response['results']) == 0:
return {}
pruned_results = list(
np.random.choice(response['results'], self.places[bucket]))
if len(pruned_results) == 0:
return {}
if self.events[bucket] == 'everyday':
for key in self.timeline.keys():
location = np.random.choice(
pruned_results)['geometry']['location']
self.timeline[key].append(update_timestamp(location, key))
elif self.events[bucket] == 'weekday':
for key in self.timeline.keys():
if is_weekday(key):
location = np.random.choice(
pruned_results)['geometry']['location']
self.timeline[key].append(update_timestamp(location, key))
else:
continue
elif self.events[bucket] == 'regular':
random_number = np.random.randint(7, 10)
chosen_keys = np.random.choice(list(self.timeline.keys()),
random_number)
for key in chosen_keys:
location = np.random.choice(
pruned_results)['geometry']['location']
self.timeline[key].append(update_timestamp(location, key))
elif self.events[bucket] == 'occasional':
random_number = np.random.randint(4, 7)
chosen_keys = np.random.choice(list(self.timeline.keys()),
random_number)
for key in chosen_keys:
location = np.random.choice(
pruned_results)['geometry']['location']
self.timeline[key].append(update_timestamp(location, key))
elif self.events[bucket] == 'rare':
random_number = np.random.randint(0, 3)
chosen_keys = np.random.choice(list(self.timeline.keys()),
random_number)
for key in chosen_keys:
location = np.random.choice(
pruned_results)['geometry']['location']
self.timeline[key].append(update_timestamp(location, key))
return np.random.choice(pruned_results)['geometry']['location']
def apply_trace(figure, before, date, code, row, col, rows, cols, layout,
options):
args = create_args(code)
end = date
start = utils.to_format(
utils.to_datetime(end) - utils.relativeterm(int(before)))
simulator_data = strategy.load_simulator_data(
args.code,
start,
end,
args,
names=["average"] if options["use_multi"] else [])
df = simulator_data.middle
df = df[df["date"] >= start]
df = df.reset_index()
# 陽線-> candle.data[1], 陰線 -> candle.data[0]
candle = FF.create_candlestick(df["open"],
df["high"],
df["low"],
df["close"],
dates=df["date"])
stocks = list(candle.data)
figure = add_stats(figure, row, col, stocks, df, []) # ローソク足をグラフに適用
# 日付リスト
dates = list(map(lambda x: utils.to_datetime(x), df["date"].astype(str)))
rangebreaks = [{
"values":
list(
filter(lambda x: not utils.is_weekday(x),
utils.daterange(dates[0], dates[-1])))
}] # 休日を除外
daterange = [dates[0], dates[-1]]
layout_settings = create_layout_settings(options)
if options["use_multi"]:
setting = layout_settings[0]
setting["line"] = [setting["line"][0]] # candle with average
layout_settings = [setting]
# ===================================================================
# layout_settingをもとに各グラフにデータを入れる
domain_from = 0
for setting in sorted(layout_settings, key=lambda x: x["to"]):
i = row if options["use_multi"] else setting["id"]
label_i = (
(col - 1) +
(row - 1) * cols) + 1 if options["use_multi"] else setting["id"]
# multiの場合同じlegendがいくつも並ぶので最初のだけ有効に
showlegend = layout["showlegend"] and row == 1 and col == 1 if options[
"use_multi"] else layout["showlegend"]
figure = apply_fig_setting(figure,
i,
col,
df,
setting["bar"],
mode="bar",
showlegend=showlegend)
figure = apply_fig_setting(figure,
i,
col,
df,
setting["line"],
mode="lines",
showlegend=showlegend)
figure = apply_fig_setting(figure,
i,
col,
df,
setting["marker"],
mode="markers",
showlegend=showlegend)
xlabel = "xaxis%s" % label_i
layout[xlabel] = {
"range": daterange,
"rangebreaks": rangebreaks,
"scaleanchor": "x1"
}
if not options["use_multi"]:
ylabel = "yaxis%s" % label_i
layout[ylabel] = {"domain": [domain_from, setting["to"]]}
layout[xlabel]["domain"] = [0.0, 1.0]
domain_from = setting["to"]
return figure, layout
def simulates(self, strategy_setting, data, start_date, end_date, with_closing=True, ignore_manda=True):
self.log(lambda: "simulating %s %s" % (start_date, end_date))
self.stats = SimulatorStats()
args = data["args"]
stocks = data["data"]
index = data["index"]
codes = self.get_targets(args, [], start_date) # ファイル読込あり
# シミュレーター準備
combination, simulators = self.create_simulator(args, codes, stocks, start_date, end_date, strategy_setting, ignore_manda)
# 日付のリストを取得
dates = self.simulate_dates(codes, stocks, start_date, end_date)
self.log(lambda: "targets: %s" % list(simulators.keys()))
deposit = None
for step, date in enumerate(dates):
# 休日はスキップ
if not utils.is_weekday(utils.to_datetime(date)):
self.log(lambda: "%s is not weekday" % date)
continue
self.log(lambda: "\n=== [%s] ===" % date)
stats = self.stats.create_trade_data()
stats["date"] = date
binding = sum(list(map(lambda x: x.order_binding(), simulators.values())))
# atrを元にhard_limitを設定
atrs = list(map(lambda x: int(stocks[x].middle[stocks[x].middle["date"] <= date]["atr"].iloc[-1]), simulators.keys()))
hard_limit = max(atrs)
self.log(lambda : "allow_max_loss: %s, hard_limit: %s" % (hard_limit * self.combination_setting.max_position_size * self.simulator_setting.min_unit, hard_limit))
risk = 0
for code in simulators.keys():
# 対象日までのデータの整形
self.log(lambda: "[%s]" % code)
# M&A 適用
simulators = self.manda_by_date(date, code, simulators)
# hard_limit設定
simulators[code].setting.hard_limit = hard_limit if self.combination_setting.auto_limit else None
if self.simulator_setting.use_deposit:
simulators[code].update_deposit(simulators[code].deposit if deposit is None else deposit)
else:
simulators[code].capacity = simulators[code].capacity if deposit is None else deposit
simulators[code].binding = binding - simulators[code].order_binding() # 自分の拘束分はsimulator側で加算するので引いておく
simulators[code].simulate_by_date(date, stocks[code], index)
deposit = simulators[code].deposit if self.simulator_setting.use_deposit else simulators[code].capacity
binding += simulators[code].order_binding() - simulators[code].unbound
if risk > self.simulator_setting.assets * 0.1 and self.combination_setting.auto_limit:
self.log(lambda : " ! clear orders. risk: %s" % (risk))
simulators[code].clear_orders()
last_order = simulators[code].stats.last()["new_order"]
risk = risk + hard_limit * (0 if last_order is None else last_order.num) * self.simulator_setting.min_unit
stats["unrealized_gain"] = self.sum_stats(simulators, lambda x: x.stats.last_unrealized_gain())
stats["gain"] = self.sum_stats(simulators, lambda x: x.stats.get("gain", 0))
self.stats.append(stats)
stats, simulators = self.closing(args, stats, simulators)
self.log(lambda: "unrealized_gain: %s, gain: %s, total gain: %s, deposit: %s, binding: %s" % (stats["unrealized_gain"], stats["gain"], sum(self.stats.gain()), deposit, binding))
# 手仕舞い
if with_closing:
simulators = self.force_closing(dates, stocks, simulators)
return simulators