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[3.12] Misc improvements to the itertools docs (GH-104916) (GH-104917)

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Miss Islington (bot) 2023-05-24 20:39:41 -07:00 • committed by GitHub
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Doc/library/itertools.rst
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@ -147,10 +147,10 @@ loops that truncate the stream.
>>> list(accumulate(data, max)) # running maximum >>> list(accumulate(data, max)) # running maximum
[3, 4, 6, 6, 6, 9, 9, 9, 9, 9] [3, 4, 6, 6, 6, 9, 9, 9, 9, 9]
# Amortize a 5% loan of 1000 with 4 annual payments of 90 # Amortize a 5% loan of 1000 with 10 annual payments of 90
>>> cashflows = [1000, -90, -90, -90, -90] >>> account_update = lambda bal, pmt: round(bal * 1.05) + pmt
>>> list(accumulate(cashflows, lambda bal, pmt: bal*1.05 + pmt)) >>> list(accumulate(repeat(-90, 10), account_update, initial=1_000))
[1000, 960.0, 918.0, 873.9000000000001, 827.5950000000001] [1000, 960, 918, 874, 828, 779, 728, 674, 618, 559, 497]
See :func:`functools.reduce` for a similar function that returns only the See :func:`functools.reduce` for a similar function that returns only the
final accumulated value. final accumulated value.
@ -951,7 +951,10 @@ which incur interpreter overhead.
nexts = cycle(islice(nexts, num_active)) nexts = cycle(islice(nexts, num_active))
def partition(pred, iterable): def partition(pred, iterable):
"Use a predicate to partition entries into false entries and true entries" """Partition entries into false entries and true entries.
If *pred* is slow, consider wrapping it with functools.lru_cache().
"""
# partition(is_odd, range(10)) --> 0 2 4 6 8 and 1 3 5 7 9 # partition(is_odd, range(10)) --> 0 2 4 6 8 and 1 3 5 7 9
t1, t2 = tee(iterable) t1, t2 = tee(iterable)
return filterfalse(pred, t1), filter(pred, t2) return filterfalse(pred, t1), filter(pred, t2)
@ -1031,7 +1034,7 @@ The following recipes have a more mathematical flavor:
return chain.from_iterable(combinations(s, r) for r in range(len(s)+1)) return chain.from_iterable(combinations(s, r) for r in range(len(s)+1))
def sieve(n): def sieve(n):
"Primes less than n" "Primes less than n."
# sieve(30) --> 2 3 5 7 11 13 17 19 23 29 # sieve(30) --> 2 3 5 7 11 13 17 19 23 29
data = bytearray((0, 1)) * (n // 2) data = bytearray((0, 1)) * (n // 2)
data[:3] = 0, 0, 0 data[:3] = 0, 0, 0
@ -1068,7 +1071,7 @@ The following recipes have a more mathematical flavor:
def matmul(m1, m2): def matmul(m1, m2):
"Multiply two matrices." "Multiply two matrices."
# matmul([(7, 5), (3, 5)], [[2, 5], [7, 9]]) --> (49, 80), (41, 60) # matmul([(7, 5), (3, 5)], [(2, 5), (7, 9)]) --> (49, 80), (41, 60)
n = len(m2[0]) n = len(m2[0])
return batched(starmap(math.sumprod, product(m1, transpose(m2))), n) return batched(starmap(math.sumprod, product(m1, transpose(m2))), n)
@ -1109,6 +1112,17 @@ The following recipes have a more mathematical flavor:
powers = map(pow, repeat(x), reversed(range(n))) powers = map(pow, repeat(x), reversed(range(n)))
return math.sumprod(coefficients, powers) return math.sumprod(coefficients, powers)
def polynomial_derivative(coefficients):
"""Compute the first derivative of a polynomial.
f(x) = x³ -4x² -17x + 60
f'(x) = 3x² -8x -17
"""
# polynomial_derivative([1, -4, -17, 60]) -> [3, -8, -17]
n = len(coefficients)
powers = reversed(range(1, n))
return list(map(operator.mul, coefficients, powers))
def nth_combination(iterable, r, index): def nth_combination(iterable, r, index):
"Equivalent to list(combinations(iterable, r))[index]" "Equivalent to list(combinations(iterable, r))[index]"
pool = tuple(iterable) pool = tuple(iterable)
@ -1297,6 +1311,9 @@ The following recipes have a more mathematical flavor:
>>> all(factored(x) == expanded(x) for x in range(-10, 11)) >>> all(factored(x) == expanded(x) for x in range(-10, 11))
True True
>>> polynomial_derivative([1, -4, -17, 60])
[3, -8, -17]
>>> list(iter_index('AABCADEAF', 'A')) >>> list(iter_index('AABCADEAF', 'A'))
[0, 1, 4, 7] [0, 1, 4, 7]
>>> list(iter_index('AABCADEAF', 'B')) >>> list(iter_index('AABCADEAF', 'B'))