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‎.buildinfo

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# Sphinx build info version 1
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# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
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config: 47b693bb5cf37a4993f0ad3e8f17929d
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config: 4456476df0dbddf14fc886dd81ffe030
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tags: 645f666f9bcd5a90fca523b33c5a78b7

‎_sources/glossary.rst.txt

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Some named tuples are built-in types (such as the above examples).
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Alternatively, a named tuple can be created from a regular class
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definition that inherits from :class:`tuple` and that defines named
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fields. Such a class can be written by hand or it can be created with
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the factory function :func:`collections.namedtuple`. The latter
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technique also adds some extra methods that may not be found in
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hand-written or built-in named tuples.
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fields. Such a class can be written by hand, or it can be created by
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inheriting :class:`typing.NamedTuple`, or with the factory function
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:func:`collections.namedtuple`. The latter techniques also add some
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extra methods that may not be found in hand-written or built-in named
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tuples.
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namespace
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The place where a variable is stored. Namespaces are implemented as

‎_sources/library/itertools.rst.txt

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def sum_of_squares(it):
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"Add up the squares of the input values."
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# sum_of_squares([10, 20, 30]) -> 1400
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# sum_of_squares([10, 20, 30]) --> 1400
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return math.sumprod(*tee(it))
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def reshape(matrix, cols):
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def convolve(signal, kernel):
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"""Discrete linear convolution of two iterables.
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Equivalent to polynomial multiplication.
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The kernel is fully consumed before the calculations begin.
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The signal is consumed lazily and can be infinite.
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Convolutions are mathematically commutative.
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If the signal and kernel are swapped,
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the output will be the same.
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Convolutions are mathematically commutative; however, the inputs are
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evaluated differently. The signal is consumed lazily and can be
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infinite. The kernel is fully consumed before the calculations begin.
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Article: https://betterexplained.com/articles/intuitive-convolution/
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Video: https://www.youtube.com/watch?v=KuXjwB4LzSA
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"""
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# convolve([1, -1, -20], [1, -3]) --> 1 -4 -17 60
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# convolve(data, [0.25, 0.25, 0.25, 0.25]) --> Moving average (blur)
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# convolve(data, [1/2, 0, -1/2]) --> 1st derivative estimate
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# convolve(data, [1, -2, 1]) --> 2nd derivative estimate
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f(x) = x³ -4x² -17x + 60
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f'(x) = 3x² -8x -17
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"""
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# polynomial_derivative([1, -4, -17, 60]) -> [3, -8, -17]
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# polynomial_derivative([1, -4, -17, 60]) --> [3, -8, -17]
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n = len(coefficients)
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powers = reversed(range(1, n))
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return list(map(operator.mul, coefficients, powers))
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>>> take(10, count())
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[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
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>>> # Verify that the input is consumed lazily
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>>> it = iter('abcdef')
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>>> take(3, it)
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['a', 'b', 'c']
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>>> list(it)
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['d', 'e', 'f']
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>>> list(prepend(1, [2, 3, 4]))
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[1, 2, 3, 4]
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>>> list(tail(3, 'ABCDEFG'))
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['E', 'F', 'G']
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>>> # Verify the input is consumed greedily
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>>> input_iterator = iter('ABCDEFG')
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>>> output_iterator = tail(3, input_iterator)
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>>> list(input_iterator)
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[]
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>>> it = iter(range(10))
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>>> consume(it, 3)
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>>> # Verify the input is consumed lazily
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>>> next(it)
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3
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>>> # Verify the input is consumed completely
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>>> consume(it)
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>>> next(it, 'Done')
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'Done'
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>>> nth('abcde', 3)
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'd'
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>>> nth('abcde', 9) is None
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True
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>>> # Verify that the input is consumed lazily
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>>> it = iter('abcde')
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>>> nth(it, 2)
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'c'
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>>> list(it)
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['d', 'e']
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>>> [all_equal(s) for s in ('', 'A', 'AAAA', 'AAAB', 'AAABA')]
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[True, True, True, False, False]
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>>> [all_equal(s, key=str.casefold) for s in ('', 'A', 'AaAa', 'AAAB', 'AAABA')]
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[True, True, True, False, False]
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>>> # Verify that the input is consumed lazily and that only
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>>> # one element of a second equivalence class is used to disprove
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>>> # the assertion that all elements are equal.
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>>> it = iter('aaabbbccc')
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>>> all_equal(it)
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False
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>>> ''.join(it)
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'bbccc'
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>>> quantify(range(99), lambda x: x%2==0)
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>>> list(ncycles('abc', 3))
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['a', 'b', 'c', 'a', 'b', 'c', 'a', 'b', 'c']
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>>> # Verify greedy consumption of input iterator
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>>> input_iterator = iter('abc')
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>>> output_iterator = ncycles(input_iterator, 3)
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>>> list(input_iterator)
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[]
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>>> sum_of_squares([10, 20, 30])
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>>> list(transpose([(1, 2, 3), (11, 22, 33)]))
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[(1, 11), (2, 22), (3, 33)]
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>>> # Verify that the inputs are consumed lazily
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>>> input1 = iter([1, 2, 3])
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>>> input2 = iter([11, 22, 33])
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>>> output_iterator = transpose([input1, input2])
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>>> next(output_iterator)
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(1, 11)
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>>> list(zip(input1, input2))
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[(2, 22), (3, 33)]
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>>> list(matmul([(7, 5), (3, 5)], [[2, 5], [7, 9]]))
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[(49, 80), (41, 60)]
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>>> list(matmul([[2, 5], [7, 9], [3, 4]], [[7, 11, 5, 4, 9], [3, 5, 2, 6, 3]]))
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[(29, 47, 20, 38, 33), (76, 122, 53, 82, 90), (33, 53, 23, 36, 39)]
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>>> list(convolve([1, -1, -20], [1, -3])) == [1, -4, -17, 60]
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True
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>>> data = [20, 40, 24, 32, 20, 28, 16]
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>>> list(convolve(data, [0.25, 0.25, 0.25, 0.25]))
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[5.0, 15.0, 21.0, 29.0, 29.0, 26.0, 24.0, 16.0, 11.0, 4.0]
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>>> list(convolve(data, [1, -1]))
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[20, 20, -16, 8, -12, 8, -12, -16]
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>>> list(convolve(data, [1, -2, 1]))
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[20, 0, -36, 24, -20, 20, -20, -4, 16]
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>>> # Verify signal is consumed lazily and the kernel greedily
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>>> signal_iterator = iter([10, 20, 30, 40, 50])
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>>> kernel_iterator = iter([1, 2, 3])
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>>> output_iterator = convolve(signal_iterator, kernel_iterator)
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>>> list(kernel_iterator)
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[]
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>>> next(output_iterator)
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10
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>>> next(output_iterator)
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40
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>>> list(signal_iterator)
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[30, 40, 50]
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>>> from fractions import Fraction
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>>> from decimal import Decimal
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>>> # Test list input. Lists do not support None for the stop argument
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>>> list(iter_index(list('AABCADEAF'), 'A'))
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[0, 1, 4, 7]
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>>> # Verify that input is consumed lazily
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>>> input_iterator = iter('AABCADEAF')
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>>> output_iterator = iter_index(input_iterator, 'A')
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>>> next(output_iterator)
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0
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>>> next(output_iterator)
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1
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>>> next(output_iterator)
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4
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>>> ''.join(input_iterator)
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'DEAF'
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>>> list(sieve(30))
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[2, 3, 5, 7, 11, 13, 17, 19, 23, 29]
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[0, 2, 4, 6, 8]
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>>> list(odds)
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[1, 3, 5, 7, 9]
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>>> # Verify that the input is consumed lazily
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>>> input_iterator = iter(range(10))
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>>> evens, odds = partition(is_odd, input_iterator)
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>>> next(odds)
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1
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>>> next(odds)
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3
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>>> next(evens)
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0
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>>> list(input_iterator)
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[4, 5, 6, 7, 8, 9]
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>>> list(subslices('ABCD'))
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['A', 'AB', 'ABC', 'ABCD', 'B', 'BC', 'BCD', 'C', 'CD', 'D']
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['A', 'B', 'C', 'D']
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>>> list(unique_everseen('ABBcCAD', str.casefold))
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['A', 'B', 'c', 'D']
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>>> # Verify that the input is consumed lazily
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>>> input_iterator = iter('AAAABBBCCDAABBB')
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>>> output_iterator = unique_everseen(input_iterator)
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>>> next(output_iterator)
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'A'
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>>> ''.join(input_iterator)
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'AAABBBCCDAABBB'
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>>> list(unique_justseen('AAAABBBCCDAABBB'))
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['A', 'B', 'C', 'D', 'A', 'B']
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>>> list(unique_justseen('ABBCcAD', str.casefold))
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['A', 'B', 'C', 'A', 'D']
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>>> list(unique_justseen('ABBcCAD', str.casefold))
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['A', 'B', 'c', 'A', 'D']
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>>> # Verify that the input is consumed lazily
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>>> input_iterator = iter('AAAABBBCCDAABBB')
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>>> output_iterator = unique_justseen(input_iterator)
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>>> next(output_iterator)
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'A'
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>>> ''.join(input_iterator)
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'AAABBBCCDAABBB'
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>>> d = dict(a=1, b=2, c=3)
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>>> it = iter_except(d.popitem, KeyError)
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>>> first_true('ABC0DEF1', '9', str.isdigit)
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'0'
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>>> # Verify that inputs are consumed lazily
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>>> it = iter('ABC0DEF1')
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>>> first_true(it, predicate=str.isdigit)
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'0'
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>>> ''.join(it)
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'DEF1'
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.. testcode::

‎_sources/tutorial/errors.rst.txt

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>>> while True print('Hello world')
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^
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^^^^^
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SyntaxError: invalid syntax
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The parser repeats the offending line and displays a little 'arrow' pointing at
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the earliest point in the line where the error was detected. The error is
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caused by (or at least detected at) the token *preceding* the arrow: in the
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The parser repeats the offending line and displays little 'arrow's pointing
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at the token in the line where the error was detected. The error may be
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caused by the absence of a token *before* the indicated token. In the
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example, the error is detected at the function :func:`print`, since a colon
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(``':'``) is missing before it. File name and line number are printed so you
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‎_static/glossary.json

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‎about.html

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<br />
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<br />
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最後更新於 Mar 10, 2024 (09:05 UTC)。
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最後更新於 Mar 13, 2024 (02:41 UTC)。
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<a href="/bugs.html">Found a bug</a>?
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<br />
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‎bugs.html

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</section>
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<section id="getting-started-contributing-to-python-yourself">
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<span id="contributing-to-python"></span><h2>開始讓自己貢獻 Python<a class="headerlink" href="#getting-started-contributing-to-python-yourself" title="Link to this heading"></a></h2>
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<p>除了只是回報您所發現的錯誤之外，同樣也歡迎您提交修正它們的修補程式 (patch)。您可以在 <a class="reference external" href="https://devguide.python.org/">Python 開發者指南</a>中找到如何開始修補 Python 的更多資訊。如果您有任何問題，<a class="reference external" href="https://mail.python.org/mailman3/lists/core-mentorship.python.org/">核心導師郵寄清單</a>是一個友善的地方，您可以在那裡得到，關於 Python 修正錯誤的過程中，所有問題的答案。</p>
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<p>除了只是回報您所發現的錯誤之外，同樣也歡迎您提交修正它們的修補程式 (patch)。您可以在 <a class="reference external" href="https://mail.python.org/mailman3/lists/core-mentorship.python.org/">Python 開發者指南</a>中找到如何開始修補 Python 的更多資訊。如果您有任何問題，<a class="reference external" href="https://devguide.python.org/">核心導師郵寄清單</a>是一個友善的地方，您可以在那裡得到，關於 Python 修正錯誤的過程中，所有問題的答案。</p>
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</section>
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<br />
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<br />
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最後更新於 Mar 10, 2024 (09:05 UTC)。
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最後更新於 Mar 13, 2024 (02:41 UTC)。
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<a href="/bugs.html">Found a bug</a>?
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<br />
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‎c-api/abstract.html

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<br />
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最後更新於 Mar 10, 2024 (09:05 UTC)。
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最後更新於 Mar 13, 2024 (02:41 UTC)。
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<a href="/bugs.html">Found a bug</a>?
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<br />
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‎c-api/allocation.html

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<br />
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<br />
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最後更新於 Mar 10, 2024 (09:05 UTC)。
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最後更新於 Mar 13, 2024 (02:41 UTC)。
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<a href="/bugs.html">Found a bug</a>?
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<br />
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‎c-api/apiabiversion.html

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<br />
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最後更新於 Mar 10, 2024 (09:05 UTC)。
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最後更新於 Mar 13, 2024 (02:41 UTC)。
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<a href="/bugs.html">Found a bug</a>?
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<br />
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