def get_price_above(df=None,
type="close above ma20",
period_of_days=1,
stock_list=None,
period_type='day'):
if df is None and stock_list is None:
stock_list_file = 'basic-no3.csv'
# stock_list_file = 'mystocklist-detail.csv'
df = myapi.read_csv(stock_list_file)
else:
if stock_list is not None:
df = myapi.read_csv(stock_list)
df_result = myapi.get_price_above(df, type, period_of_days, period_type)
return df_result
def get_maximum_price_sum_in_n(df=None,
p_change=(4, 10),
period_of_days=10,
stock_list=None,
period_type='day'):
if df is None and stock_list is None:
stock_list_file = 'basic-no3.csv'
# stock_list_file = 'mystocklist-detail.csv'
df = myapi.read_csv(stock_list_file)
else:
if stock_list is not None:
df = myapi.read_csv(stock_list)
df_result = myapi.get_maximum_price_sum_in_n(df, p_change, period_of_days,
period_type)
return df_result
def get_history_high_price(df=None,
event_to_now=1,
period_of_days=60,
stock_list=None,
period_type='day'):
if df is None and stock_list is None:
stock_list_file = 'basic-no3.csv'
#stock_list_file = 'mystocklist-detail.csv'
df = myapi.read_csv(stock_list_file)
else:
if stock_list is not None:
df = myapi.read_csv(stock_list)
df_result = myapi.get_history_high_price(df, event_to_now, period_of_days,
period_type)
return df_result
def get_maximum_period_break_high(df=None,
min_break_num=4,
period_of_days=10,
stock_list=None,
period_type='day'):
if df is None and stock_list is None:
stock_list_file = 'basic-no3.csv'
#stock_list_file = 'mystocklist-detail.csv'
df = myapi.read_csv(stock_list_file)
else:
if stock_list is not None:
df = myapi.read_csv(stock_list)
df_result = myapi.get_maximum_period_break_high(df, min_break_num,
period_of_days,
period_type)
return df_result
def get_a_across_b(df=None,
cross_above=True,
cross_type="ma5-ma10",
period_of_days=10,
stock_list=None,
period_type='day',
rank=False):
if df is None and stock_list is None:
stock_list_file = 'basic-no3.csv'
# stock_list_file = 'mystocklist-detail.csv'
df = myapi.read_csv(stock_list_file)
else:
if stock_list is not None:
df = myapi.read_csv(stock_list)
df_result = myapi.get_a_across_b(df, cross_above, cross_type,
period_of_days, period_type, rank)
return df_result
def get_minimum_price_sum_in_n(df=None,
is_price_up=True,
price_up_sum=0,
min_day_range=0,
period_of_days=10,
stock_list=None,
period_type='day'):
if df is None and stock_list is None:
stock_list_file = 'basic-no3.csv'
# stock_list_file = 'mystocklist-detail.csv'
df = myapi.read_csv(stock_list_file)
else:
if stock_list is not None:
df = myapi.read_csv(stock_list)
df_result = myapi.get_miminum_price_sum_in_n(df, is_price_up, price_up_sum,
min_day_range, period_of_days,
period_type)
return df_result
def get_first_history_high_volume_in_10_days():
stock_list_file = 'basic-no3.csv'
tmpfile = Path().joinpath('result', 'get_first_history_high_volume_in_10_days.csv')
df = myapi.read_csv(stock_list_file)
df = myapi.remove_unwanted_fields(df)
"""
in latest 10 days, find history high
"""
df_result = myapi.get_first_history_high_volume_in_n(df, 2)
df_result.to_csv(tmpfile)
def get_half_year_high_v2():
stock_list_file = 'basic-no3.csv'
tmpfile = Path().joinpath('result', 'get_half_year_high_v2.csv')
df = myapi.read_csv(stock_list_file)
df = myapi.remove_unwanted_fields(df)
"""
in latest 10 days, find history high
"""
df_result = myapi.get_history_high_v2(df, 3, 120)
df_result.to_csv(tmpfile)
def get_one_year_high():
stock_list_file = 'basic-no3.csv'
tmpfile = Path().joinpath('result', 'get_one_year_high.csv')
# stock_list_file = 'mystocklist-detail.csv'
df = myapi.read_csv(stock_list_file)
df = myapi.remove_unwanted_fields(df)
"""
in latest 10 days, find history high
"""
df_result = myapi.get_history_high(df, 10, 12)
df_result.to_csv(tmpfile)
def get_price_continuous_down_in_n(df=None,
price_down_sum=0,
num_of_days_down=4,
period_of_days=15,
period_type='day'):
if df is None:
stock_list_file = 'basic-no3.csv'
# stock_list_file = 'mystocklist-detail.csv'
df = myapi.read_csv(stock_list_file)
df_result = myapi.get_price_continuous_down_in_n(df, num_of_days_down,
price_down_sum,
period_of_days,
period_type)
return df_result
"""
first time in recent 5 days that close price stand above upper band
for binary-cmp, period_of_days specifies the period that the result of comparisons should all be true.
"""
def first_cross_above_upper(df, market='usa'):
myapi.market = market
df = dr5.get_a_across_b(df, period_of_days=1, cross_above=("close", "upper"), cross_type="binary-cmp",
period_type='day')
lib2.head_offset = 1
df1 = dr5.get_a_across_b(df, period_of_days=5, cross_above=("upper", "close"), cross_type="binary-cmp",
period_type='day')
df.to_csv("{}.csv".format(inspect.stack()[0][3]))
return df
df1 = myapi.read_csv(r"case\case-main-rise\usa-ma20-up-list.csv")
df1 = first_cross_above_upper(df1)
pdb.set_trace()
#create_ma20_up_list()
"""
df = myapi.read_csv("basic-no3.csv")
df1 = myapi.read_csv("ma20-up-list.csv", local=True)
df1 = lib2.filter_stock(df, df1, "outstanding", 5)
pdb.set_trace()
df1.to_csv("ma20-up-list.csv")
"""
def get_w_shape():
stock_list_file = 'basic-no3.csv'
# stock_list_file = 'mystocklist-detail.csv'
df = myapi.read_csv(stock_list_file)
df_result = myapi.get_w_shape(df, 40)
df_result.to_csv(Path().joinpath('result', 'w-shape.csv'))
def get_current_no_touch_ma5_periods():
stock_list_file = 'basic-no3.csv'
# stock_list_file = 'mystocklist-detail.csv'
df = myapi.read_csv(stock_list_file)
df_result = myapi.get_current_no_touch_ma5_periods(df)
df_result.to_csv(Path().joinpath('result', 'current_no_touch_ma5.csv'))
def get_no_toch_ma5():
stock_list_file = 'basic-no3.csv'
# stock_list_file = 'mystocklist-detail.csv'
df = myapi.read_csv(stock_list_file)
df_result = myapi.get_no_touch_ma5(df, 7)
df_result.to_csv(Path().joinpath('result', 'no_touch_ma5.csv'))
def test_read_csv(self):
name = "20190810"
filepath = r"C:"
columns = ["日期", "姓名", "ID"]
file = read_csv(name, filepath, columns)
self.assertTrue(file.name(), "20190810")
