random --- Generate pseudo-random numbers — Functions for sequences
Return a random element from the non-empty sequence seq. If seq is empty, raises IndexError. Return a k sized list of elements chosen from the population with replacement. If the population is empty, raises IndexError. If a weights sequence is specified, selections are made according to the relative
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Return a random element from the non-empty sequence seq. If seq is empty, raises IndexError.
Return a k sized list of elements chosen from the population with replacement. If the population is empty, raises IndexError.
If a weights sequence is specified, selections are made according to the relative weights. Alternatively, if a cum_weights sequence is given, the selections are made according to the cumulative weights (perhaps computed using itertools.accumulate). For example, the relative weights [10, 5, 30, 5] are equivalent to the cumulative weights [10, 15, 45, 50]. Internally, the relative weights are converted to cumulative weights before making selections, so supplying the cumulative weights saves work.
If neither weights nor cum_weights are specified, selections are made with equal probability. If a weights sequence is supplied, it must be the same length as the population sequence. It is a TypeError to specify both weights and cum_weights.
The weights or cum_weights can use any numeric type that interoperates with the float values returned by random (that includes integers, floats, and fractions but excludes decimals). Weights are assumed to be non-negative and finite. A ValueError is raised if all weights are zero.
For a given seed, the choices function with equal weighting typically produces a different sequence than repeated calls to choice. The algorithm used by choices uses floating-point arithmetic for internal consistency and speed. The algorithm used by choice defaults to integer arithmetic with repeated selections to avoid small biases from round-off error.
Shuffle the sequence x in place.
To shuffle an immutable sequence and return a new shuffled list, use sample(x, k=len(x)) instead.
Note that even for small len(x), the total number of permutations of x can quickly grow larger than the period of most random number generators. This implies that most permutations of a long sequence can never be generated. For example, a sequence of length 2080 is the largest that can fit within the period of the Mersenne Twister random number generator.
Return a k length list of unique elements chosen from the population sequence. Used for random sampling without replacement. …
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Python Documentation — Doc/library/random.rst :: Functions for sequences ↗Revision f10166035d60 · PSF-2.0 and attribution