4.4. Idiom All¶
Return True if all elements of the iterable are true (or if the iterable is empty).
Built-in (evaluated)
>>> DATA = [True, False, True]
>>>
>>> all(DATA)
False
4.4.1. Solution¶
>>> def all(iterable):
... if not iterable:
... return False
... for element in iterable:
... if not element:
... return False
... return True
4.4.2. Use Case - 0x01¶
>>> all(x for x in range(0,5))
False
4.4.3. Use Case - 0x02¶
>>> USERS = [
... {'is_admin': True, 'name': 'Mark Watney'},
... {'is_admin': True, 'name': 'Melisa Lewis'},
... {'is_admin': False, 'name': 'Rick Martinez'},
... {'is_admin': True, 'name': 'Alex Vogel'},
... {'is_admin': False, 'name': 'Beth Johanssen'},
... {'is_admin': False, 'name': 'Chris Beck'},
... ]
>>>
>>>
>>> if all(user['is_admin'] for user in USERS):
... print('Everyone is admin')
... else:
... print('Not everyone is admin')
Not everyone is admin
4.4.4. Use Case - 0x03¶
>>> DATA = [
... ('sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species'),
... (5.8, 2.7, 5.1, 1.9, 'virginica'),
... (5.1, 3.5, 1.4, 0.2, 'setosa'),
... (5.7, 2.8, 4.1, 1.3, 'versicolor'),
... (6.3, 2.9, 5.6, 1.8, 'virginica'),
... (6.4, 3.2, 4.5, 1.5, 'versicolor'),
... (4.7, 3.2, 1.3, 0.2, 'setosa'),
... (7.0, 3.2, 4.7, 1.4, 'versicolor'),
... ]
>>>
>>>
>>> all(value > 1.0
... for *values, species in DATA[1:]
... for value in values
... if isinstance(value, float))
False
4.4.5. Performance¶
Setup:
>>> DATA = [
... ('sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species'),
... (5.8, 2.7, 5.1, 1.9, 'virginica'),
... (5.1, 3.5, 1.4, 0.2, 'setosa'),
... (5.7, 2.8, 4.1, 1.3, 'versicolor'),
... (6.3, 2.9, 5.6, 1.8, 'virginica'),
... (6.4, 3.2, 4.5, 1.5, 'versicolor'),
... (4.7, 3.2, 1.3, 0.2, 'setosa'),
... (7.0, 3.2, 4.7, 1.4, 'versicolor'),
... ]
>>> %%timeit -n 1000 -r 1000
... result = []
... for row in DATA[1:]:
... for value in row:
... if isinstance(value, float):
... result.append(value >= 1.0)
... result = all(result)
5.24 µs ± 591 ns per loop (mean ± std. dev. of 1000 runs, 1,000 loops each)
>>> %%timeit -n 1000 -r 1000
... result = True
... for row in DATA[1:]:
... for value in row:
... if isinstance(value, float):
... if not value >= 1.0:
... result = False
... break
... if not result:
... break
1.49 µs ± 596 ns per loop (mean ± std. dev. of 1000 runs, 1,000 loops each)
>>> %%timeit -n 1000 -r 1000
... result = all(value >= 1.0
... for row in DATA[1:]
... for value in row
... if isinstance(value, float))
1.55 µs ± 436 ns per loop (mean ± std. dev. of 1000 runs, 1,000 loops each)
>>> %%timeit -n 1000 -r 1000
... result = all(value >= 1.0 for row in DATA[1:] for value in row if isinstance(value, float))
1.51 µs ± 396 ns per loop (mean ± std. dev. of 1000 runs, 1,000 loops each)
>>> %%timeit -n 1000 -r 1000
... result = all(y >= 1.0 for x in DATA[1:] for y in x if isinstance(y, float))
1.53 µs ± 433 ns per loop (mean ± std. dev. of 1000 runs, 1,000 loops each)
>>> %%timeit -n 1000 -r 1000
... result = all(x >= 1.0 for X in DATA[1:] for x in X if isinstance(x, float))
1.57 µs ± 437 ns per loop (mean ± std. dev. of 1000 runs, 1,000 loops each)