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def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def __init__(self, key, child_proxy):
try:
self._key = int(key)
except ValueError:
self._key = key
self._child_proxy = child_proxy |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def log_row(self, row_category: str, row: List[int]):
"""Logs a confusion matrix row.
Args:
row_category: Category to which the row belongs.
row: List of integers specifying the values for the row.
Raises:
ValueError: If row_category is not in the list of categories set in
set_categories or size of the row does not match the size of
categories.
"""
if row_category not in self._categories:
raise ValueError('Invalid category: {} passed. Expected one of: {}'.\
format(row_category, self._categories))
if len(row) != len(self._categories):
raise ValueError('Invalid row. Expected size: {} got: {}'.\
format(len(self._categories), len(row)))
self._matrix[self._categories.index(row_category)] = row |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def get(self):
return self._child_proxy.get()[self._key] |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def log_cell(self, row_category: str, col_category: str, value: int):
"""Logs a cell in the confusion matrix.
Args:
row_category: String representing the name of the row category.
col_category: String representing the name of the column category.
value: Int value of the cell.
Raises:
ValueError: If row_category or col_category is not in the list of
categories set in set_categories.
"""
if row_category not in self._categories:
raise ValueError('Invalid category: {} passed. Expected one of: {}'.\
format(row_category, self._categories))
if col_category not in self._categories:
raise ValueError('Invalid category: {} passed. Expected one of: {}'.\
format(row_category, self._categories))
self._matrix[self._categories.index(row_category)][
self._categories.index(col_category)] = value |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def __init__(self):
self._cache = {}
self._bucket_client = None
self._param_client = None
self._secret_client = None |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def _get_or_create_cached_value(self, key, getter, ttl=None):
# happy path
try:
expiry, value = self._cache[key]
except KeyError:
pass
else:
if expiry is None or time.time() < expiry:
logger.debug("Key %s from cache", key)
return value
logger.debug("Cache for key %s has expired", key)
# get value
value = getter()
if ttl:
expiry = time.time() + ttl
else:
expiry = None
self._cache[key] = (expiry, value)
logger.debug("Set cache for key %s", key)
return value |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def getter():
with open(filepath, "r") as f:
return f.read() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def getter():
return self._secret_client.get(name) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def getter():
return self._bucket_client.download_to_tmpfile(key) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def getter():
return self._param_client.get(key) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def __init__(self, path=None, resolver=None):
self._path = path or ()
if not resolver:
resolver = Resolver()
self._resolver = resolver |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def _make_proxy(self, key, match):
proxy_type = match.group("type")
key = match.group("key").strip()
if proxy_type == "env":
proxy = EnvProxy(key)
else:
proxy = ResolverMethodProxy(self._resolver, proxy_type, key)
filters = [f for f in [rf.strip() for rf in match.group("filters").split("|")] if f]
for filter_name in filters:
if filter_name == "jsondecode":
proxy = JSONDecodeFilter(proxy)
elif filter_name == "base64decode":
proxy = Base64DecodeFilter(proxy)
elif filter_name.startswith("element:"):
key = filter_name.split(":", 1)[-1]
proxy = ElementFilter(key, proxy)
else:
raise ValueError("Unknown filter %s", filter_name)
return proxy |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def _from_python(self, key, value):
new_path = self._path + (key,)
if isinstance(value, dict):
value = self.custom_classes.get(new_path, ConfigDict)(value, new_path)
elif isinstance(value, list):
value = self.custom_classes.get(new_path, ConfigList)(value, new_path)
elif isinstance(value, str):
match = self.PROXY_VAR_RE.match(value)
if match:
value = self._make_proxy(key, match)
return value |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def _to_python(self, value):
if isinstance(value, Proxy):
return value.get()
else:
return value |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def __len__(self):
return len(self._collection) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def __delitem__(self, key):
del self._collection[key] |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def __setitem__(self, key, value):
self._collection[key] = self._from_python(key, value) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def pop(self, key, default=None):
value = self._collection.pop(key, default)
if isinstance(value, Proxy):
value = value.get()
return value |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def __init__(self, config_l, path=None, resolver=None):
super().__init__(path=path, resolver=resolver)
self._collection = []
for key, value in enumerate(config_l):
self._collection.append(self._from_python(str(key), value)) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def __getitem__(self, key):
value = self._collection[key]
if isinstance(key, slice):
slice_repr = ":".join(str("" if i is None else i) for i in (key.start, key.stop, key.step))
logger.debug("Get /%s[%s] config key", "/".join(self._path), slice_repr)
return [self._to_python(item) for item in value]
else:
logger.debug("Get /%s[%s] config key", "/".join(self._path), key)
return self._to_python(value) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def __iter__(self):
for element in self._collection:
yield self._to_python(element) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def serialize(self):
s = []
for v in self:
if isinstance(v, BaseConfig):
v = v.serialize()
s.append(v)
return s |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def __init__(self, config_d, path=None, resolver=None):
super().__init__(path=path, resolver=resolver)
self._collection = {}
for key, value in config_d.items():
self._collection[key] = self._from_python(key, value) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def __getitem__(self, key):
logger.debug("Get /%s config key", "/".join(self._path + (key,)))
value = self._collection[key]
return self._to_python(value) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def get(self, key, default=None):
try:
value = self[key]
except KeyError:
value = self._to_python(default)
return value |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def __iter__(self):
yield from self._collection |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def keys(self):
return self._collection.keys() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def values(self):
for value in self._collection.values():
yield self._to_python(value) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def items(self):
for key, value in self._collection.items():
yield key, self._to_python(value) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def clear(self):
return self._collection.clear() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def setdefault(self, key, default=None):
return self._collection.setdefault(key, self._from_python(key, default)) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def pop(self, key, default=None):
value = self._collection.pop(key, default)
return self._to_python(value) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def popitem(self):
key, value = self._collection.popitem()
return key, self._to_python(value) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def copy(self):
return ConfigDict(self._collection.copy(), path=self._path, resolver=self._resolver) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def update(self, *args, **kwargs):
chain = []
for arg in args:
if isinstance(arg, dict):
iterator = arg.items()
else:
iterator = arg
chain = itertools.chain(chain, iterator)
if kwargs:
chain = itertools.chain(chain, kwargs.items())
for key, value in iterator:
self._collection[key] = self._from_python(key, value) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def __init__(self, p_str):
TodoBase.__init__(self, p_str)
self.attributes = {} |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def get_organizations(self):
legis = Organization('Minnesota Legislature', classification='legislature')
upper = Organization('Minnesota Senate', classification='upper',
parent_id=legis._id)
lower = Organization('Minnesota House of Representatives',
classification='lower', parent_id=legis._id)
for n in range(1, 68):
upper.add_post(label=str(n), role='Senator',
division_id='ocd-division/country:us/state:mn/sldu:{}'.format(n))
lower.add_post(label=str(n) + 'A', role='Representative',
division_id='ocd-division/country:us/state:mn/sldl:{}a'.format(n))
lower.add_post(label=str(n) + 'B', role='Representative',
division_id='ocd-division/country:us/state:mn/sldl:{}b'.format(n))
yield legis
yield upper
yield lower |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def get_date(self, p_tag):
""" Given a date tag, return a date object. """
string = self.tag_value(p_tag)
result = None
try:
result = date_string_to_date(string) if string else None
except ValueError:
pass
return result |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def start_date(self):
""" Returns a date object of the todo's start date. """
return self.get_date(config().tag_start()) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def due_date(self):
""" Returns a date object of the todo's due date. """
return self.get_date(config().tag_due()) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def is_active(self):
"""
Returns True when the start date is today or in the past and the
task has not yet been completed.
"""
start = self.start_date()
return not self.is_completed() and (not start or start <= date.today()) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def is_overdue(self):
"""
Returns True when the due date is in the past and the task has not
yet been completed.
"""
return not self.is_completed() and self.days_till_due() < 0 |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def days_till_due(self):
"""
Returns the number of days till the due date. Returns a negative number
of days when the due date is in the past.
Returns 0 when the task has no due date.
"""
due = self.due_date()
if due:
diff = due - date.today()
return diff.days
return 0 |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def main(self):
UI.OpenDialog(
VBox(
Heading("This Is a Heading."),
Label("This is a Label."),
PushButton("&OK")
)
)
UI.UserInput()
UI.CloseDialog() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(df):
df2 = df[['A']]
df2['A'] += 10
return df2.A, df.A |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_scheme():
# does not raise NotImplementedError
UrlPath('/dev/null').touch() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
S1 = pd.Series(np.ones(n))
S2 = pd.Series(np.random.ranf(n))
df = pd.DataFrame({'A': S1, 'B': S2})
return df.A.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_scheme_not_supported():
with pytest.raises(NotImplementedError):
UrlPath('http:///tmp/test').touch() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(df):
return df['A'][df['B']].values |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_scheme_not_listed():
with pytest.raises(NotImplementedError):
UrlPath('test:///tmp/test').touch() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl():
A = np.array([1., 2., 3.])
A[0] = np.nan
df = pd.DataFrame({'A': A})
B = df.A.fillna(5.0)
return B.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_file_additional():
assert UrlPath('.').resolve() == UrlPath.cwd() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl():
A = np.array([1., 2., 3.])
A[0] = np.nan
df = pd.DataFrame({'A': A})
df.A.fillna(5.0, inplace=True)
return df.A.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl():
A = np.array([1., 2., 3.])
A[0] = np.nan
df = pd.DataFrame({'A': A})
return df.A.mean() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl():
A = np.array([1., 2., 3.])
A[0] = 4.0
df = pd.DataFrame({'A': A})
return df.A.var() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl():
A = np.array([1., 2., 3.])
A[0] = 4.0
df = pd.DataFrame({'A': A})
return df.A.std() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df = pd.DataFrame({'A': np.arange(n)})
df['B'] = df.A.map(lambda a: 2 * a)
return df.B.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(df):
df['B'] = df.A.map(lambda a: 2 * a)
return |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df = pd.DataFrame({'A': np.ones(n), 'B': np.random.ranf(n)})
Ac = df.A.cumsum()
return Ac.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df = pd.DataFrame({'A': np.ones(n), 'B': np.random.ranf(n)})
df.A.fillna(5.0, inplace=True)
DF = df.A.fillna(5.0)
s = DF.sum()
m = df.A.mean()
v = df.A.var()
t = df.A.std()
Ac = df.A.cumsum()
return Ac.sum() + s + m + v + t |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df = pd.DataFrame({'A': np.arange(0, n, 1, np.float64)})
return df.A.quantile(.25) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df = pd.DataFrame({'A': np.arange(0, n, 1, np.float32)})
df.A[0:100] = np.nan
df.A[200:331] = np.nan
return df.A.quantile(.25) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df = pd.DataFrame({'A': np.arange(0, n, 1, np.int32)})
return df.A.quantile(.25) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(A):
df = pd.DataFrame({'A': A})
return df.A.quantile(.25) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df = pd.DataFrame({'A': np.arange(n)})
df.A[2] = 0
return df.A.nunique() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl():
df = pq.read_table('example.parquet').to_pandas()
return df.four.nunique() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df = pd.DataFrame({'A': ['aa', 'bb', 'aa', 'cc', 'cc']})
return df.A.nunique() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl():
df = pq.read_table('example.parquet').to_pandas()
return df.two.nunique() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl():
df = pq.read_table('example.parquet').to_pandas()
return (df.four.unique() == 3.0).sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl():
df = pq.read_table('example.parquet').to_pandas()
return (df.two.unique() == 'foo').sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df = pd.DataFrame({'A': np.arange(0, n, 1, np.float64)})
return df.A.describe() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl():
A = StringArray(['ABC', 'BB', 'ADEF'])
df = pd.DataFrame({'A': A})
B = df.A.str.contains('AB*', regex=True)
return B.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl():
A = StringArray(['ABC', 'BB', 'ADEF'])
df = pd.DataFrame({'A': A})
B = df.A.str.contains('BB', regex=False)
return B.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(df):
return df.A.str.replace('AB*', 'EE', regex=True) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(df):
return df.A.str.replace('AB', 'EE', regex=False) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(df):
B = df.A.str.replace('AB*', 'EE', regex=True)
return B |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(df):
return df.A.str.split() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(df):
B = df.A.str.split(',')
df2 = pd.DataFrame({'B': B})
return df2[df2.B.str.len() > 1] |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(df):
return df.A.iloc[0] |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(df):
B = df.A.str.split(',')
C = pd.to_numeric(B.str.get(1), errors='coerce')
return C |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(df):
A = df.A.str.split(',')
return pd.Series(list(itertools.chain(*A))) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(df):
A = df.A.str.split(',')
B = pd.Series(list(itertools.chain(*A)))
return B |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(df):
B = pd.to_numeric(df.A, errors='coerce')
return B |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df = pd.DataFrame({'A': np.arange(n), 'B': np.arange(n) + 1.0})
df1 = df[df.A > 5]
return len(df1.B) |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df = pd.DataFrame({'A': np.arange(n), 'B': np.random.ranf(n)})
Ac = df.A.rolling(3).sum()
return Ac.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl_2(n):
df = pd.DataFrame({'A': np.arange(n) + 1.0, 'B': np.random.ranf(n)})
Ac = df.A.rolling(7).sum()
return Ac.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df = pd.DataFrame({'A': np.ones(n), 'B': np.random.ranf(n)})
df['moving average'] = df.A.rolling(window=5, center=True).mean()
return df['moving average'].sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df = pd.DataFrame({'A': np.ones(n), 'B': np.random.ranf(n)})
Ac = df.A.rolling(3, center=True).apply(lambda a: a[0] + 2 * a[1] + a[2])
return Ac.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df = pd.DataFrame({'A': np.arange(n) + 1.0, 'B': np.random.ranf(n)})
Ac = df.A.shift(1)
return Ac.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df = pd.DataFrame({'A': np.arange(n) + 1.0, 'B': np.random.ranf(n)})
Ac = df.A.pct_change(1)
return Ac.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(df):
return df.B.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(df):
C = df.B == 'two'
return C.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(df):
return df.B.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df1 = pd.DataFrame({'key1': np.arange(n), 'A': np.arange(n) + 1.0})
df2 = pd.DataFrame({'key2': n - np.arange(n), 'A': n + np.arange(n) + 1.0})
df3 = pd.concat([df1, df2])
return df3.A.sum() + df3.key2.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl():
df1 = pq.read_table('example.parquet').to_pandas()
df2 = pq.read_table('example.parquet').to_pandas()
A3 = pd.concat([df1, df2])
return (A3.two == 'foo').sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(n):
df1 = pd.DataFrame({'key1': np.arange(n), 'A': np.arange(n) + 1.0})
df2 = pd.DataFrame({'key2': n - np.arange(n), 'A': n + np.arange(n) + 1.0})
A3 = pd.concat([df1.A, df2.A])
return A3.sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl():
df1 = pq.read_table('example.parquet').to_pandas()
df2 = pq.read_table('example.parquet').to_pandas()
A3 = pd.concat([df1.two, df2.two])
return (A3 == 'foo').sum() |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(nsyms):
max_num_days = 100
all_res = 0.0
for i in sdc.prange(nsyms):
s_open = 20 * np.ones(max_num_days)
s_low = 28 * np.ones(max_num_days)
s_close = 19 * np.ones(max_num_days)
df = pd.DataFrame({'Open': s_open, 'Low': s_low, 'Close': s_close})
df['Stdev'] = df['Close'].rolling(window=90).std()
df['Moving Average'] = df['Close'].rolling(window=20).mean()
df['Criteria1'] = (df['Open'] - df['Low'].shift(1)) < -df['Stdev']
df['Criteria2'] = df['Open'] > df['Moving Average']
df['BUY'] = df['Criteria1'] & df['Criteria2']
df['Pct Change'] = (df['Close'] - df['Open']) / df['Open']
df['Rets'] = df['Pct Change'][df['BUY']]
all_res += df['Rets'].mean()
return all_res |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_impl(A, B):
df = pd.DataFrame({'A': A, 'B': B})
df2 = df.groupby('A', as_index=False)['B'].sum()
# TODO: fix handling of df setitem to force match of array dists
# probably with a new node that is appended to the end of basic block
# df2['C'] = np.full(len(df2.B), 3, np.int8)
# TODO: full_like for Series
df2['C'] = np.full_like(df2.B.values, 3, np.int8)
return df2 |
def emit(self, level, message):
raise NotImplementedError('Please implement an emit method') | def test_both():
"""Both f and g."""
p = are.above(2) & are.below(4)
ps = [p(x) for x in range(1, 6)]
assert ps == [False, False, True, False, False] |
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