def _main():
basics = ts.get_stock_basics()
frame = DataFrame()
frame['name'] = np.nan
# frame['pe'] = basics['pe']
frame[COL_P_CHANGE_01] = np.nan
frame[COL_PASTAVERAGETURNOVER] = np.nan
frame[COL_STOPMARK] = ''
for i, code in enumerate(leading_shares):
frame.loc[code, 'name'] = basics.loc[code, 'name']
hist_data = ts.get_hist_data(code)
try:
frame.loc[code, COL_P_CHANGE_01] = hpc(hist_data,
begin=DAY_0,
end=DAY_1)
frame.loc[code, COL_PASTAVERAGETURNOVER] = pat(
hist_data, PAST_AVERAGE_TURNOVER_PERIOD)
if hist_data.index[0] != LAST_MARKET_DATE:
frame.loc[code, COL_STOPMARK] = 'stop'
except Exception:
continue
print('#####', i, '#####')
filtered_frame = frame[(frame[COL_STOPMARK] != 'stop')]
sorted_frame = filtered_frame.sort_values(by=COL_P_CHANGE_01)
print(sorted_frame)
file_name = '../logs/{date}@HeroSea.csv'.format(date=LAST_MARKET_DATE)
# print(fileName)
with open(file_name, 'w', encoding='utf8') as file:
sorted_frame.to_csv(file)
def _main():
basics = ts.get_stock_basics()
frame = DataFrame()
frame['name'] = basics['name']
frame[COL_PASTCHANGE] = np.nan
frame[COL_PASTPOSITIVE] = np.nan
frame['pe'] = basics['pe']
i = 0
for code in basics.index:
hist_data = ts.get_hist_data(code)
try:
frame.loc[code, COL_PASTCHANGE] = phpc(hist_data, PAST_DAY_PERIOD)
if phpc(hist_data, PAST_POSITIVE_PERIOD) > 0:
frame.loc[code, COL_PASTPOSITIVE] = '★'
frame.loc[code, COL_PASTAVERAGETURNOVER] = pat(
hist_data, PAST_AVERAGE_TURNOVER_PERIOD)
except Exception:
continue
i += 1
print('#####', i, '#####')
sorted_frame = frame.sort_values(by=COL_PASTCHANGE)
print(sorted_frame)
t = time.strftime('%Y-%m-%d', time.localtime())
file_name = '../logs/%s@rocket%s' % (t, '.csv')
# print(fileName)
with open(file_name, 'w', encoding='utf8') as file:
sorted_frame.to_csv(file)
def _main():
basics = ts.get_stock_basics()
frame = DataFrame()
frame['name'] = basics['name']
frame['pe'] = basics['pe']
frame[COL_P_CHANGE_01] = np.nan
frame[COL_P_CHANGE_12] = np.nan
frame[COL_PASTAVERAGETURNOVER] = np.nan
frame[COL_STOPMARK] = np.nan
frame[COL_SORT_KEY] = np.nan
for i, code in enumerate(basics.index):
hist_data = ts.get_hist_data(code)
try:
frame.loc[code, COL_P_CHANGE_01] = hpc(hist_data,
begin=DAY_0,
end=DAY_1)
frame.loc[code, COL_P_CHANGE_12] = hpc(hist_data,
begin=DAY_1,
end=DAY_2)
frame.loc[code, COL_SORT_KEY] = round(
frame.loc[code, COL_P_CHANGE_01] *
frame.loc[code, COL_P_CHANGE_12], 3)
frame.loc[code, COL_PASTAVERAGETURNOVER] = pat(
hist_data, PAST_AVERAGE_TURNOVER_PERIOD)
if hist_data.index[0] != LAST_MARKET_DATE:
frame.loc[code, COL_STOPMARK] = 'stop'
except Exception:
continue
print('#####', i, '#####')
filtered_frame = frame[(frame[COL_P_CHANGE_01] > 0)
& (frame[COL_P_CHANGE_12] < 0)
& (abs(frame[COL_P_CHANGE_12]) > abs(
frame[COL_P_CHANGE_01]))
& (frame[COL_PASTAVERAGETURNOVER] < 20) &
(frame[COL_PASTAVERAGETURNOVER] > 0.5)
& (frame['pe'] > 0)
& (frame[COL_STOPMARK] != 'stop')]
sorted_frame = filtered_frame.sort_values(by=COL_SORT_KEY)
print(sorted_frame)
file_name = '../logs/{date}@EnemyChaser.csv'.format(date=LAST_MARKET_DATE)
# print(fileName)
with open(file_name, 'w', encoding='utf8') as file:
sorted_frame.to_csv(file)
def _main():
basics = ts.get_stock_basics()
frame = DataFrame()
frame['name'] = basics['name']
frame['pe'] = basics['pe']
frame[COL_PASTFAR] = np.nan
frame[COL_PASTNEAR] = np.nan
frame[COL_PASTAVERAGETURNOVER] = np.nan
frame[COL_STOPMARK] = np.nan
i = 0
for code in basics.index:
hist_data = ts.get_hist_data(code)
try:
frame.loc[code, COL_PASTFAR] = hpc(hist_data, begin=DAY_NEAR, end=DAY_FAR)
frame.loc[code, COL_PASTNEAR] = hpc(hist_data, begin=0, end=DAY_NEAR)
frame.loc[code, COL_PASTAVERAGETURNOVER] = pat(hist_data, PAST_AVERAGE_TURNOVER_PERIOD)
if hist_data.index[0] != LAST_MARKET_DATE:
frame.loc[code, COL_STOPMARK] = 'stop'
except Exception:
continue
i += 1
print('#####', i, '#####')
filtered_frame = frame[(frame[COL_PASTFAR] < 0)
& (frame[COL_PASTNEAR] > 0)
& (frame[COL_PASTAVERAGETURNOVER] < 20) & (frame[COL_PASTAVERAGETURNOVER] > 0.5)
& (frame['pe'] < 100) & (frame['pe'] > 0)
& (frame[COL_STOPMARK] != 'stop')]
sorted_frame = filtered_frame.sort_values(by=COL_PASTFAR)
print(sorted_frame)
file_name = '../logs/%s@flash%s' % (LAST_MARKET_DATE, '.csv')
# print(fileName)
with open(file_name, 'w', encoding='utf8') as file:
sorted_frame.to_csv(file)