def test_screener_overview():
foverview = Overview()
filters_dict = {'Exchange': 'AMEX', 'Sector': 'Basic Materials'}
foverview.set_filter(filters_dict=filters_dict)
df = foverview.screener_view()
assert (df is not None)
ticker = 'TSLA'
foverview.set_filter(signal='', filters_dict={}, ticker=ticker)
df = foverview.screener_view()
assert (df is not None)
def partition_days(self, mode="financial"):
"""Partition dataframe to separate dataframes according to the dates.
Args:
mode(str): choose an option of period(financial, overview, valuation, ownership,
performance, technical).
"""
check_list = [
"financial",
"overview",
"valuation",
"ownership",
"performance",
"technical",
]
if mode not in check_list:
raise ValueError("Invalid mode '{}'. Available mode: {}".format(
mode, check_list))
for earning_day in self.earning_days:
if mode == "financial":
self.df_days[earning_day] = self.df[
self.df["Earnings"] == earning_day].reset_index(drop=True)
else:
self.df_days[earning_day] = self.df[
self.df["Earnings"] == earning_day]["Ticker"].to_list()
fearnings = None
if mode == "financial":
return self.df_days
elif mode == "overview":
fearnings = Overview()
elif mode == "valuation":
fearnings = Valuation()
elif mode == "ownership":
fearnings = Ownership()
elif mode == "performance":
fearnings = Performance()
elif mode == "technical":
fearnings = Technical()
filters_dict = {"Earnings Date": self.period}
fearnings.set_filter(filters_dict=filters_dict)
df2 = fearnings.screener_view(order="Earnings Date", verbose=0)
df2_days = {}
for earning_day in self.earning_days:
tickers = self.df_days[earning_day]
df2_days[earning_day] = df2[df2["Ticker"].isin(
tickers)].reset_index(drop=True)
self.df_days = df2_days
return self.df_days
def partitionDays(self, mode='financial'):
"""Partition dataframe to separate dataframes according to the dates.
Args:
mode(str): choose an option of period(financial, overview, valuation, ownership,
performance, technical).
"""
check_list = [
'financial', 'overview', 'valuation', 'ownership', 'performance',
'technical'
]
if mode not in check_list:
print('Available mode: {}'.format(check_list))
raise ValueError()
for earning_day in self.earning_days:
if mode == 'financial':
self.df_days[earning_day] = self.df[
self.df['Earnings'] == earning_day].reset_index(drop=True)
else:
self.df_days[earning_day] = self.df[
self.df['Earnings'] == earning_day]['Ticker'].to_list()
fearnings = None
if mode == 'financial':
return self.df_days
elif mode == 'overview':
fearnings = Overview()
elif mode == 'valuation':
fearnings = Valuation()
elif mode == 'ownership':
fearnings = Ownership()
elif mode == 'performance':
fearnings = Performance()
elif mode == 'technical':
fearnings = Technical()
filters_dict = {'Earnings Date': self.period}
fearnings.set_filter(filters_dict=filters_dict)
df2 = fearnings.ScreenerView(order='Earnings Date', verbose=0)
df2_days = {}
for earning_day in self.earning_days:
tickers = self.df_days[earning_day]
df2_days[earning_day] = df2[df2['Ticker'].isin(
tickers)].reset_index(drop=True)
self.df_days = df2_days
return self.df_days