def call_dd(self, other_args: List[str]):
"""Process DD command"""
due_diligence_view.due_diligence(other_args)
def screener(other_args: List[str], loaded_preset: str,
data_type: str) -> List[str]:
"""Screener
Parameters
----------
other_args : List[str]
Command line arguments to be processed with argparse
ticker : str
Loaded preset filter
data_type : str
Data type string between: overview, valuation, financial, ownership, performance, technical
Returns
-------
List[str]
List of stocks that meet preset criteria
"""
parser = argparse.ArgumentParser(
add_help=False,
prog="screener",
description="""
Prints screener data of the companies that meet the pre-set filtering.
The following information fields are expected: overview, valuation, financial,
ownership, performance, technical. Note that when the signal parameter (-s)
is specified, the preset is disregarded. [Source: Finviz]
""",
)
parser.add_argument(
"-p",
"--preset",
action="store",
dest="preset",
type=str,
default=loaded_preset,
help="Filter presets",
choices=[
preset.split(".")[0] for preset in os.listdir(presets_path)
if preset[-4:] == ".ini"
],
)
parser.add_argument(
"-s",
"--signal",
action="store",
dest="signal",
type=str,
default=None,
help="Signal",
choices=list(d_signals.keys()),
)
parser.add_argument(
"-l",
"--limit",
action="store",
dest="limit",
type=check_positive,
default=0,
help="Limit of stocks to print",
)
parser.add_argument(
"-a",
"--ascend",
action="store_true",
default=False,
dest="ascend",
help="Set order to Ascend, the default is Descend",
)
parser.add_argument(
"-e",
"--export",
action="store_true",
dest="exportFile",
help="Save list as a text file",
)
parser.add_argument(
"-m",
"--mill",
action="store_true",
dest="mill",
help="Run papermill on list",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return []
df_screen = get_screener_data(
ns_parser.preset,
data_type,
ns_parser.signal,
ns_parser.limit,
ns_parser.ascend,
)
if isinstance(df_screen, pd.DataFrame):
print(df_screen.to_string())
print("")
if ns_parser.exportFile:
now = datetime.now()
if not os.path.exists("reports/screener"):
os.makedirs("reports/screener")
with open(
f"reports/screener/{ns_parser.signal}-{now.strftime('%Y-%m-%d_%H:%M:%S')}",
"w",
) as file:
file.write(df_screen.to_string(index=False) + "\n")
if ns_parser.mill:
for i in range(len(df_screen)):
ticker = [df_screen.iat[i, 0]]
due_diligence_view.due_diligence(ticker, show=False)
return list(df_screen["Ticker"].values)
print("")
return []
except Exception as e:
print(e)
print("")
return []