mirror of https://github.com/python/cpython
In the case where only a user supplied random() method is available,
adopt a strategy that makes the fewest calls to random().
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@ -212,33 +212,33 @@ class Random(_random.Random):
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return self.randrange(a, b+1)
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def _randbelow(self, n, int=int, bpf=BPF, type=type,
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def _randbelow(self, n, int=int, maxsize=1<<BPF, type=type,
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Method=_MethodType, BuiltinMethod=_BuiltinMethodType):
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"""Return a random int in the range [0,n). Raises ValueError if n==0.
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"""
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"Return a random int in the range [0,n). Raises ValueError if n==0."
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k = n.bit_length() # don't use (n-1) here because n can be 1
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getrandbits = self.getrandbits
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# Only call self.getrandbits if the original random() builtin method
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# has not been overridden or if a new getrandbits() was supplied.
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if type(self.random) is BuiltinMethod or type(getrandbits) is Method:
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k = n.bit_length() # don't use (n-1) here because n can be 1
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r = getrandbits(k) # 0 <= r < 2**k
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while r >= n:
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r = getrandbits(k)
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return r
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# There's an overriden random() method but no new getrandbits() method,
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# so we can only use random() from here.
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if k > bpf:
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random = self.random
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if n >= maxsize:
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_warn("Underlying random() generator does not supply \n"
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"enough bits to choose from a population range this large.\n"
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"To remove the range limitation, add a getrandbits() method.")
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return int(self.random() * n)
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random = self.random
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N = 1 << k
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r = int(N * random()) # 0 <= r < 2**k
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while r >= n:
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r = int(N * random())
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return r
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return int(random() * n)
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rem = maxsize % n
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limit = (maxsize - rem) / maxsize # int(limit * maxsize) % n == 0
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r = random()
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while r >= limit:
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r = random()
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return int(r*maxsize) % n
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## -------------------- sequence methods -------------------
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