diff options
| -rw-r--r-- | Doc/library/random.rst | 6 | ||||
| -rw-r--r-- | Lib/random.py | 2 |
2 files changed, 4 insertions, 4 deletions
diff --git a/Doc/library/random.rst b/Doc/library/random.rst index d944518..4522f5a 100644 --- a/Doc/library/random.rst +++ b/Doc/library/random.rst @@ -21,8 +21,8 @@ lognormal, negative exponential, gamma, and beta distributions. For generating distributions of angles, the von Mises distribution is available. Almost all module functions depend on the basic function :func:`.random`, which -generates a random float uniformly in the semi-open range [0.0, 1.0). Python -uses the Mersenne Twister as the core generator. It produces 53-bit precision +generates a random float uniformly in the half-open range ``0.0 <= X < 1.0``. +Python uses the Mersenne Twister as the core generator. It produces 53-bit precision floats and has a period of 2\*\*19937-1. The underlying implementation in C is both fast and threadsafe. The Mersenne Twister is one of the most extensively tested random number generators in existence. However, being completely @@ -294,7 +294,7 @@ be found in any statistics text. .. function:: random() - Return the next random floating point number in the range [0.0, 1.0). + Return the next random floating point number in the range ``0.0 <= X < 1.0`` .. function:: uniform(a, b) diff --git a/Lib/random.py b/Lib/random.py index 1c9e1a4..3c4291f 100644 --- a/Lib/random.py +++ b/Lib/random.py @@ -849,7 +849,7 @@ class SystemRandom(Random): """ def random(self): - """Get the next random number in the range [0.0, 1.0).""" + """Get the next random number in the range 0.0 <= X < 1.0.""" return (int.from_bytes(_urandom(7)) >> 3) * RECIP_BPF def getrandbits(self, k): |