def get(self, section_name, key):
if os.path.exists(self.file_path):
try:
content = read_file_to_string(self.file_path)
json_data = json.loads(content)
return json_data[section_name][key]
except Exception as e:
return None
else:
return None
def read_portfolio_info(strategy_name):
file_path = PathMgr.get_strategies_portfolio_file(strategy_name)
if os.path.exists(file_path):
content = read_file_to_string(file_path)
dic = json.loads(content)
# for key in dic.keys():
# dic[key] = Portfolio.from_dict(dic[key])
return dic
else:
return {}
def load_log(self, symbol, date):
file_name = '%s%s.log' % (symbol, date.strftime('%Y%m%d'))
path = PathMgr.get_data_path('quantopian_daily_min/%s' % file_name)
content = read_file_to_string(path)
lines = content.split('\n')
filtered_lines = filter(lambda x: len(x) > 100, lines)
lines = map(lambda x: string_fetch(x, 'PRINT ', ''), filtered_lines)
close_list_str = ','.join(lines)
prices_list = map(float, close_list_str.split(','))
datetimes = TradeTime.generate_datetimes(date, date)
equities = map(lambda x, y: Equity(symbol, x, y, y, y, y), datetimes,
prices_list)
EquityMinDAO().insert(equities)
def set(self, section_name, key, value):
dic = {}
if os.path.exists(self.file_path):
try:
content = read_file_to_string(self.file_path)
dic = json.loads(content)
except Exception as e:
pass
if section_name in dic.keys():
dic[section_name][key] = value
else:
section_dic = {key: value}
dic[section_name] = section_dic
write_to_file(self.file_path, json.dumps(dic))
def parse_raw_file(raw_file):
content = read_file_to_string(raw_file)
underling_symbol = string_fetch(content, '<title>', ' Option')
sub_content = string_fetch(
content,
'"underlyingSymbol\":\"%s\"},\"contracts\":' % underling_symbol,
',\"displayed\"')
json_content = sub_content + '}'
json_obj = json.loads(json_content)
objs = json_obj['calls']
put_objs = json_obj['puts']
objs.extend(put_objs)
for obj in objs:
yield YahooOptionParser.json_obj_to_option(obj, underling_symbol)
def to_csv(self, symbol, date):
file_name = '%s%s.log' % (symbol, date.strftime('%Y%m%d'))
path = PathMgr.get_data_path('quantopian_daily_min/%s' % file_name)
content = read_file_to_string(path)
lines = content.split('\n')
filtered_lines = filter(lambda x: len(x) > 100, lines)
lines = map(lambda x: string_fetch(x, 'PRINT ', ''), filtered_lines)
close_list_str = ','.join(lines)
# print close_list_str
prices_list = map(float, close_list_str.split(','))
datetimes = TradeTime.generate_datetimes(date, date)
new_lines = map(lambda x, y: '%s,%s' % (x, y), datetimes, prices_list)
new_content = '\n'.join(new_lines)
write_path = PathMgr.get_data_path('quantopian_daily_min/%s%s.csv' %
(symbol, date.strftime('%Y%m%d')))
write_to_file(write_path, new_content)
def get_order_id():
order_file_path = PathMgr.get_data_file_path('orderid.txt')
order_id = int(read_file_to_string(order_file_path))
write_to_file(order_file_path, str(order_id + 1))
return order_id
def load_csv(self, symbol):
path = PathMgr.get_data_path('1mincsv/%s.txt' % symbol)
content = read_file_to_string(path)
lines = content.split('\n')
return map(lambda x: self.try_parse_line(x, symbol), lines)
def read_trade_trace(strategy_name):
file_path = PathMgr.get_strategies_tradetrace_file(strategy_name)
content = read_file_to_string(file_path)
lines = content.split('\r\n')[:-1]
return map(TradeRecord.read_from_line, lines)
def load_log(self, code):
path = PathMgr.get_data_path('joinquant_min/%s_2018.log'%code)
content = read_file_to_string(path)
lines = content.split('\n')
filtered_lines = filter(lambda x: 'INFO' not in x and x != '', lines)
return map(lambda x: self.parse_line(x, code), filtered_lines)