Move random selection recipes from itertools.rst to random.rst (GH-98369)

diff --git a/Doc/library/itertools.rst b/Doc/library/itertools.rst
index 88e1e5aa6ef7f33af5d1cd05b519ca481086afa9..9f7ec10729cd065cb8dba68474702ead2289bf7d 100644 (file)
--- a/Doc/library/itertools.rst
+++ b/Doc/library/itertools.rst
@@ -1000,31 +1000,6 @@ which incur interpreter overhead.
        # first_true([a,b], x, f) --> a if f(a) else b if f(b) else x
        return next(filter(pred, iterable), default)
 
-   def random_product(*args, repeat=1):
-       "Random selection from itertools.product(*args, **kwds)"
-       pools = [tuple(pool) for pool in args] * repeat
-       return tuple(map(random.choice, pools))
-
-   def random_permutation(iterable, r=None):
-       "Random selection from itertools.permutations(iterable, r)"
-       pool = tuple(iterable)
-       r = len(pool) if r is None else r
-       return tuple(random.sample(pool, r))
-
-   def random_combination(iterable, r):
-       "Random selection from itertools.combinations(iterable, r)"
-       pool = tuple(iterable)
-       n = len(pool)
-       indices = sorted(random.sample(range(n), r))
-       return tuple(pool[i] for i in indices)
-
-   def random_combination_with_replacement(iterable, r):
-       "Random selection from itertools.combinations_with_replacement(iterable, r)"
-       pool = tuple(iterable)
-       n = len(pool)
-       indices = sorted(random.choices(range(n), k=r))
-       return tuple(pool[i] for i in indices)
-
    def nth_combination(iterable, r, index):
        "Equivalent to list(combinations(iterable, r))[index]"
        pool = tuple(iterable)

diff --git a/Doc/library/random.rst b/Doc/library/random.rst
index 7e527a9b401ac6a33915b6fda3c41bec34a82fcc..669204ba65b77e17b32a33506439b7dbd504c34e 100644 (file)
--- a/Doc/library/random.rst
+++ b/Doc/library/random.rst
@@ -582,6 +582,37 @@ Simulation of arrival times and service deliveries for a multiserver queue::
 Recipes
 -------
 
+These recipes show how to efficiently make random selections
+from the combinatoric iterators in the :mod:`itertools` module:
+
+.. testcode::
+   import random
+
+   def random_product(*args, repeat=1):
+       "Random selection from itertools.product(*args, **kwds)"
+       pools = [tuple(pool) for pool in args] * repeat
+       return tuple(map(random.choice, pools))
+
+   def random_permutation(iterable, r=None):
+       "Random selection from itertools.permutations(iterable, r)"
+       pool = tuple(iterable)
+       r = len(pool) if r is None else r
+       return tuple(random.sample(pool, r))
+
+   def random_combination(iterable, r):
+       "Random selection from itertools.combinations(iterable, r)"
+       pool = tuple(iterable)
+       n = len(pool)
+       indices = sorted(random.sample(range(n), r))
+       return tuple(pool[i] for i in indices)
+
+   def random_combination_with_replacement(iterable, r):
+       "Random selection from itertools.combinations_with_replacement(iterable, r)"
+       pool = tuple(iterable)
+       n = len(pool)
+       indices = sorted(random.choices(range(n), k=r))
+       return tuple(pool[i] for i in indices)
+
 The default :func:`.random` returns multiples of 2⁻⁵³ in the range
 *0.0 ≤ x < 1.0*.  All such numbers are evenly spaced and are exactly
 representable as Python floats.  However, many other representable