def pick(date_obj, **kwargs):
date_tw = RocDateConverter().get_roc_date_by_datetime(date_obj)
min_volume = kwargs.pop('min_volume', 1 * 1000)
max_volume = kwargs.pop('max_volume', 10 * 1000)
min_price = kwargs.pop('min_price', 12)
max_price = kwargs.pop('max_price', 1000)
min_change_percent = kwargs.pop('min_chagne_percent', 0.03)
consolidation_days = kwargs.pop('consolidation_days', 20)
retriever = Retriever()
data_path = retriever.data_dir
file_list = (f for f in listdir(data_path) if search_filename(f) is not None)
winners = []
for filename in file_list:
# system('clear')
# print('{} -- {}'.format(filename, ', '.join(winners)), end="\r")
search_stock_code = re.search('(\w+).csv$', filename)
stock_code = search_stock_code.group(1)
line_number = retriever.search_line_number_by_date(stock_code, date_tw)
if line_number is None:
continue
try:
check = retriever.check_model_1(stock_code, line_number,
min_volume=min_volume,
max_volume=max_volume,
min_price=min_price,
max_price=max_price,
min_change_percent=min_change_percent,
consolidation_days=consolidation_days)
except RetrieverException:
continue
if check:
winners.append(stock_code)
return winners
def main():
parser = argparse.ArgumentParser()
parser.add_argument('stock_codes', nargs='*', help="股票代號")
args = parser.parse_args()
stock_codes = args.stock_codes
#print(stock_codes)
retriever = Retriever(stock_codes)
retriever.put_mapping_by_stock_codes()
retriever.dump_to_es()
def main():
retriever = Retriever()
data_dir = retriever.data_dir
file_list = (f for f in listdir(data_dir) if search_filename(f) is not None
and int(search_filename(f).group(1)) > 3708)
for filename in file_list:
print(filename)
search_stock_code = re.search('(\w+).csv$', filename)
stock_code = search_stock_code.group(1)
stock_codes = [stock_code]
retriever.put_mapping_by_stock_codes()
retriever.dump_to_es()
def setUp(self):
self.retriever = Retriever()
def simulate(stock_codes, pick_date_obj, max_days, stop_loss_factor):
retriever = Retriever()
total_cost = 0
total_revenue = 0
total_roi = 0
buy_in_unit = 1
# summary_set = []
stop_loss_count = 0
# 開始買進時間
start_date_obj = None
start_date_tw = ''
end_date_obj = None
end_date_tw = ''
max_through_days = 0
pick_date_tw = RocDateConverter().get_roc_date_by_datetime(pick_date_obj)
for stock_code in stock_codes:
info = retriever.get_simulation_1_info(stock_code, pick_date_tw,
max_days, stop_loss_factor)
spend = info['buy_in_price'] * 1000 * buy_in_unit
buying_fee = max(spend * 0.001425 * 0.65, 20)
cost = spend + buying_fee
total_cost += cost
# print('股票編號: {}'.format(stock_code))
data_set = info['data_set']
if len(data_set) < max_days:
stop_loss_count += 1
closing_price = 0
for data in data_set:
# print(data)
date_tw = data[0]
date_obj = RocDateConverter().get_datetime_in_roc(date_tw)
if (start_date_obj is None) or (date_obj < start_date_obj):
start_date_obj = date_obj
start_date_tw = date_tw
if (end_date_obj is None) or (date_obj > end_date_obj):
end_date_obj = date_obj
end_date_tw = date_tw
closing_price = data[1]
income = closing_price * 1000 * buy_in_unit
selling_fee = max(income * 0.001425 * 0.65, 20)
tax = income * 0.003
revenue = income - selling_fee - tax
total_revenue += revenue
timedelta = end_date_obj - start_date_obj
through_days = timedelta.days + 1
if through_days > max_through_days:
max_through_days = through_days
# summary_set.append('股票編號: {}, 買進成本: {}, 賣出日期: {}, 賣出總價: {}'.format(stock_code, cost, end_date_tw, revenue))
# summary = '\n'.join(summary_set)
total_roi = (total_revenue - total_cost) / total_cost
formatted_roi = '{}%'.format(round(total_roi * 100, 2))
formatted_cost = '{:,.0f}'.format(total_cost)
net = total_revenue - total_cost
formatted_net = '{:,.0f}'.format(net)
pick_date = pick_date_obj.strftime("%Y/%m/%d")
print('選股日期 {}, 開始日期 {}, 結束日期 {}, 停損 {}/{}'
.format(pick_date, start_date_tw, end_date_tw, stop_loss_count, len(stock_codes)))
# print(summary)
print('總成本: {}, 利潤: {}, 投報率: {}\n'
.format(formatted_cost, formatted_net, formatted_roi))
result = {
'roi': total_roi,
'cost': total_cost,
'net': net,
'days': max_through_days,
'formatted_data_dict': {
'pick_date': pick_date,
'start_date_tw': start_date_tw,
'end_date_tw': end_date_tw,
'pick_count': len(stock_codes),
'stop_loss_count': stop_loss_count,
'cost': formatted_cost,
'net': formatted_net,
'roi': formatted_roi,
}
}
return result
def test_one(stock_code, date):
retriever = Retriever()
line_number = retriever.search_line_number_by_date(stock_code, date)
check = retriever.check_model_1(stock_code, line_number)
print(check)
#!/usr/bin/python
# -*- coding: utf-8 -*-
import sys
from classes.retriever import Retriever
stock_codes = ['1204']
retriever = Retriever()
read = retriever.readfiles_by_stock_codes(stock_codes)
for stock_code, line_number, line in read:
check = retriever.check_condition_1(stock_code, line_number)
if check:
print(line_number, check)