Merge p3yk branch with the trunk up to revision 45595. This breaks a fair
number of tests, all because of the codecs/_multibytecodecs issue described
here (it's not a Py3K issue, just something Py3K discovers):
http://mail.python.org/pipermail/python-dev/2006-April/064051.html
Hye-Shik Chang promised to look for a fix, so no need to fix it here. The
tests that are expected to break are:
test_codecencodings_cn
test_codecencodings_hk
test_codecencodings_jp
test_codecencodings_kr
test_codecencodings_tw
test_codecs
test_multibytecodec
This merge fixes an actual test failure (test_weakref) in this branch,
though, so I believe merging is the right thing to do anyway.
diff --git a/Lib/random.py b/Lib/random.py
index b4ad2b3..465f477 100644
--- a/Lib/random.py
+++ b/Lib/random.py
@@ -285,6 +285,15 @@
large population: sample(xrange(10000000), 60)
"""
+ # XXX Although the documentation says `population` is "a sequence",
+ # XXX attempts are made to cater to any iterable with a __len__
+ # XXX method. This has had mixed success. Examples from both
+ # XXX sides: sets work fine, and should become officially supported;
+ # XXX dicts are much harder, and have failed in various subtle
+ # XXX ways across attempts. Support for mapping types should probably
+ # XXX be dropped (and users should pass mapping.keys() or .values()
+ # XXX explicitly).
+
# Sampling without replacement entails tracking either potential
# selections (the pool) in a list or previous selections in a set.
@@ -304,7 +313,9 @@
setsize = 21 # size of a small set minus size of an empty list
if k > 5:
setsize += 4 ** _ceil(_log(k * 3, 4)) # table size for big sets
- if n <= setsize: # is an n-length list smaller than a k-length set
+ if n <= setsize or hasattr(population, "keys"):
+ # An n-length list is smaller than a k-length set, or this is a
+ # mapping type so the other algorithm wouldn't work.
pool = list(population)
for i in xrange(k): # invariant: non-selected at [0,n-i)
j = _int(random() * (n-i))
@@ -312,17 +323,18 @@
pool[j] = pool[n-i-1] # move non-selected item into vacancy
else:
try:
- n > 0 and (population[0], population[n//2], population[n-1])
- except (TypeError, KeyError): # handle non-sequence iterables
- population = tuple(population)
- selected = set()
- selected_add = selected.add
- for i in xrange(k):
- j = _int(random() * n)
- while j in selected:
+ selected = set()
+ selected_add = selected.add
+ for i in xrange(k):
j = _int(random() * n)
- selected_add(j)
- result[i] = population[j]
+ while j in selected:
+ j = _int(random() * n)
+ selected_add(j)
+ result[i] = population[j]
+ except (TypeError, KeyError): # handle (at least) sets
+ if isinstance(population, list):
+ raise
+ return self.sample(tuple(population), k)
return result
## -------------------- real-valued distributions -------------------