How to use the holidays.DE function in holidays
To help you get started, we’ve selected a few holidays examples, based on popular ways it is used in public projects.
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dr-prodigy / python-holidays / tests.py View on Github 
def setUp(self):
self.holidays = holidays.DE()
self.prov_hols = dict((prov, holidays.DE(prov=prov))
for prov in holidays.DE.PROVINCES)def setUp(self):
self.holidays = holidays.DE()
self.prov_hols = dict((prov, holidays.DE(prov=prov))
for prov in holidays.DE.PROVINCES)def test_no_data_before_1990(self):
de_1989 = sum(holidays.DE(years=[1989], prov=p)
for p in holidays.DE.PROVINCES)
self.assertTrue(len(de_1989) == 0)def test_all_holidays_present(self):
de_2015 = sum(holidays.DE(years=[2015], prov=p)
for p in holidays.DE.PROVINCES)
in_2015 = sum((de_2015.get_list(key) for key in de_2015), [])
all = ["Neujahr",
"Heilige Drei Könige",
"Karfreitag",
"Ostern",
"Ostermontag",
"Maifeiertag",
"Christi Himmelfahrt",
"Pfingsten",
"Pfingstmontag",
"Fronleichnam",
"Mariä Himmelfahrt",
"Tag der Deutschen Einheit",
"Reformationstag",
"Allerheiligen",# General first
ge_holidays = holidays.DE()
for year in list(years):
ge_holidays._populate(year)
ge_holidays.observed = False
hdays = [date for date, name in sorted(ge_holidays.items())]
holidays_df = pd.DataFrame(hdays, columns=[self.time_column], dtype='datetime64[ns]')
holidays_df['year'] = holidays_df[self.time_column].dt.year
holidays_df['doy'] = holidays_df[self.time_column].dt.dayofyear
holidays_df.sort_values(by=['year', 'doy']).drop_duplicates(subset=['year'], keep='first').reset_index(drop=True)
holidays_df.drop(self.time_column, axis=1, inplace=True)
self.memos['country'] = holidays_df
# Now do province in the same manner
for prov in ['BW', 'BY', 'BE', 'BB', 'HB', 'HH', 'HE', 'MV', 'NI', 'NW', 'RP', 'SL', 'SN', 'ST', 'SH', 'TH']:
ge_holidays = holidays.DE(prov=prov)
for year in list(years):
ge_holidays._populate(year)
ge_holidays.observed = False
hdays = [date for date, name in sorted(ge_holidays.items())]
holidays_df = pd.DataFrame(hdays, columns=[self.time_column], dtype='datetime64[ns]')
holidays_df['year'] = holidays_df[self.time_column].dt.year
holidays_df['doy'] = holidays_df[self.time_column].dt.dayofyear
holidays_df.sort_values(by=['year', 'doy']).drop_duplicates(subset=['year'], keep='first').reset_index(
drop=True)
holidays_df.drop(self.time_column, axis=1, inplace=True)
self.memos[prov] = holidays_dfmn_year = X[self.time_column].dt.year.min()
mx_year = X[self.time_column].dt.year.max()
if np.isnan(mn_year) or np.isnan(mx_year):
years = []
else:
# Start at min year and end at 2*max_year - min_year + 1
# If min year is 2016, max year 2018
# then we keep dates until 2021
# As a reminder np.arange(1, 3) returns [1, 2]
years = np.arange(int(mn_year), int(mx_year + mx_year - mn_year + 2))
# Germany general and province holidays
self.memos = {}
# General first
ge_holidays = holidays.DE()
for year in list(years):
ge_holidays._populate(year)
ge_holidays.observed = False
hdays = [date for date, name in sorted(ge_holidays.items())]
holidays_df = pd.DataFrame(hdays, columns=[self.time_column], dtype='datetime64[ns]')
holidays_df['year'] = holidays_df[self.time_column].dt.year
holidays_df['doy'] = holidays_df[self.time_column].dt.dayofyear
holidays_df.sort_values(by=['year', 'doy']).drop_duplicates(subset=['year'], keep='first').reset_index(drop=True)
holidays_df.drop(self.time_column, axis=1, inplace=True)
self.memos['country'] = holidays_df
# Now do province in the same manner
for prov in ['BW', 'BY', 'BE', 'BB', 'HB', 'HH', 'HE', 'MV', 'NI', 'NW', 'RP', 'SL', 'SN', 'ST', 'SH', 'TH']:
ge_holidays = holidays.DE(prov=prov)
for year in list(years):
ge_holidays._populate(year)holidays
Generate and work with holidays in Python
