Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

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

Merged
merged 1 commit into from
May 25, 2023
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
31 changes: 24 additions & 7 deletions Doc/library/itertools.rst
Original file line number Diff line number Diff line change
Expand Up @@ -147,10 +147,10 @@ loops that truncate the stream.
>>> list(accumulate(data, max)) # running maximum
[3, 4, 6, 6, 6, 9, 9, 9, 9, 9]

# Amortize a 5% loan of 1000 with 4 annual payments of 90
>>> cashflows = [1000, -90, -90, -90, -90]
>>> list(accumulate(cashflows, lambda bal, pmt: bal*1.05 + pmt))
[1000, 960.0, 918.0, 873.9000000000001, 827.5950000000001]
# Amortize a 5% loan of 1000 with 10 annual payments of 90
>>> account_update = lambda bal, pmt: round(bal * 1.05) + pmt
>>> list(accumulate(repeat(-90, 10), account_update, initial=1_000))
[1000, 960, 918, 874, 828, 779, 728, 674, 618, 559, 497]

See :func:`functools.reduce` for a similar function that returns only the
final accumulated value.
Expand Down Expand Up @@ -951,7 +951,10 @@ which incur interpreter overhead.
nexts = cycle(islice(nexts, num_active))

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
t1, t2 = tee(iterable)
return filterfalse(pred, t1), filter(pred, t2)
Expand Down Expand Up @@ -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))

def sieve(n):
"Primes less than n"
"Primes less than n."
# sieve(30) --> 2 3 5 7 11 13 17 19 23 29
data = bytearray((0, 1)) * (n // 2)
data[:3] = 0, 0, 0
Expand Down Expand Up @@ -1068,7 +1071,7 @@ The following recipes have a more mathematical flavor:

def matmul(m1, m2):
"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])
return batched(starmap(math.sumprod, product(m1, transpose(m2))), n)

Expand Down Expand Up @@ -1109,6 +1112,17 @@ The following recipes have a more mathematical flavor:
powers = map(pow, repeat(x), reversed(range(n)))
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):
"Equivalent to list(combinations(iterable, r))[index]"
pool = tuple(iterable)
Expand Down Expand Up @@ -1297,6 +1311,9 @@ The following recipes have a more mathematical flavor:
>>> all(factored(x) == expanded(x) for x in range(-10, 11))
True

>>> polynomial_derivative([1, -4, -17, 60])
[3, -8, -17]

>>> list(iter_index('AABCADEAF', 'A'))
[0, 1, 4, 7]
>>> list(iter_index('AABCADEAF', 'B'))
Expand Down