sync with cpython 89f44ac4

Author: github-actions[bot]

library/itertools.po

@@ -6,7 +6,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: Python 3.14\n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2026-04-09 00:20+0000\n"
+"POT-Creation-Date: 2026-04-25 00:26+0000\n"
 "PO-Revision-Date: 2024-08-16 15:01+0800\n"
 "Last-Translator: Adrian Liaw <adrianliaw2000@gmail.com>\n"
 "Language-Team: Chinese - TAIWAN (https://github.com/python/python-docs-zh-"
@@ -1808,13 +1808,15 @@ msgstr ""
 "term:`產生器 <generator>`，則能保持高速度。"
 
 #: ../../library/itertools.rst:831
+#, fuzzy
 msgid ""
 "from itertools import (accumulate, batched, chain, combinations, compress,\n"
 "     count, cycle, filterfalse, groupby, islice, permutations, product,\n"
 "     repeat, starmap, tee, zip_longest)\n"
 "from collections import Counter, deque\n"
 "from contextlib import suppress\n"
 "from functools import reduce\n"
+"from heapq import heappush, heappushpop, heappush_max, heappushpop_max\n"
 "from math import comb, isqrt, prod, sumprod\n"
 "from operator import getitem, is_not, itemgetter, mul, neg, truediv\n"
 "\n"
@@ -1830,11 +1832,6 @@ msgid ""
 "    # prepend(1, [2, 3, 4]) → 1 2 3 4\n"
 "    return chain([value], iterable)\n"
 "\n"
-"def running_mean(iterable):\n"
-"    \"Yield the average of all values seen so far.\"\n"
-"    # running_mean([8.5, 9.5, 7.5, 6.5]) → 8.5 9.0 8.5 8.0\n"
-"    return map(truediv, accumulate(iterable), count(1))\n"
-"\n"
 "def repeatfunc(function, times=None, *args):\n"
 "    \"Repeat calls to a function with specified arguments.\"\n"
 "    if times is None:\n"
@@ -2134,7 +2131,50 @@ msgid ""
 "    # totient(12) → 4 because len([1, 5, 7, 11]) == 4\n"
 "    for prime in set(factor(n)):\n"
 "        n -= n // prime\n"
-"    return n"
+"    return n\n"
+"\n"
+"\n"
+"# ==== Running statistics ====\n"
+"\n"
+"def running_mean(iterable):\n"
+"    \"Average of values seen so far.\"\n"
+"    # running_mean([37, 33, 38, 28]) → 37 35 36 34\n"
+"    return map(truediv, accumulate(iterable), count(1))\n"
+"\n"
+"def running_min(iterable):\n"
+"    \"Smallest of values seen so far.\"\n"
+"    # running_min([37, 33, 38, 28]) → 37 33 33 28\n"
+"    return accumulate(iterable, func=min)\n"
+"\n"
+"def running_max(iterable):\n"
+"    \"Largest of values seen so far.\"\n"
+"    # running_max([37, 33, 38, 28]) → 37 37 38 38\n"
+"    return accumulate(iterable, func=max)\n"
+"\n"
+"def running_median(iterable):\n"
+"    \"Median of values seen so far.\"\n"
+"    # running_median([37, 33, 38, 28]) → 37 35 37 35\n"
+"    read = iter(iterable).__next__\n"
+"    lo = []  # max-heap\n"
+"    hi = []  # min-heap the same size as or one smaller than lo\n"
+"    with suppress(StopIteration):\n"
+"        while True:\n"
+"            heappush_max(lo, heappushpop(hi, read()))\n"
+"            yield lo[0]\n"
+"            heappush(hi, heappushpop_max(lo, read()))\n"
+"            yield (lo[0] + hi[0]) / 2\n"
+"\n"
+"def running_statistics(iterable):\n"
+"    \"Aggregate statistics for values seen so far.\"\n"
+"    # Generate tuples:  (size, minimum, median, maximum, mean)\n"
+"    t0, t1, t2, t3 = tee(iterable, 4)\n"
+"    return zip(\n"
+"        count(1),\n"
+"        running_min(t0),\n"
+"        running_median(t1),\n"
+"        running_max(t2),\n"
+"        running_mean(t3),\n"
+"    )"
 msgstr ""
 "from itertools import (accumulate, batched, chain, combinations, compress,\n"
 "     count, cycle, filterfalse, groupby, islice, permutations, product,\n"