python常见库

python

os

chdir(path)
    Change the current working directory to the specified path.
    path may always be specified as a string.

random

sample(population, k) method of random.Random instance
    Chooses k unique random elements from a population sequence or set.
    从population随机选取k个不同的元素，以list返回

iter

iter(...)
    iter(iterable) -> iterator
    iter(callable, sentinel) -> iterator
    
    Get an iterator from an object.  In the first form, the argument must
    supply its own iterator, or be a sequence.
    In the second form, the callable is called until it returns the sentinel.

next

next(...)
    next(iterator[, default])
    
    Return the next item from the iterator. If default is given and the iterator
    is exhausted, it is returned instead of raising StopIteration.

zip

In: list(zip(*[[1,2,3],['1',2,3],[1,2,3],[1,2,3]]))
Out: [(1, '1', 1, 1), (2, 2, 2, 2), (3, 3, 3, 3)]

numpy

random

choice(...) method of mtrand.RandomState instance
    choice(a, size=None, replace=True, p=None)
    
    Generates a random sample from a given 1-D array
    
    Parameters
    -----------
    a : 1-D array-like or int
        If an ndarray, a random sample is generated from its elements.
        If an int, the random sample is generated as if a were np.arange(a)
    size : int or tuple of ints, optional
        Output shape.  If the given shape is, e.g., ``(m, n, k)``, then
        ``m * n * k`` samples are drawn.  Default is None, in which case a
        single value is returned.
    replace : boolean, optional
        Whether the sample is with or without replacement
    p : 1-D array-like, optional
        The probabilities associated with each entry in a.
        If not given the sample assumes a uniform distribution over all
        entries in a.
    
    Returns
    --------
    samples : single item or ndarray
        The generated random samples

    Examples
    ---------
    Generate a uniform random sample from np.arange(5) of size 3 without
    replacement:
    
    np.random.choice(5, 3, replace=False)
        array([3,1,0])
    #This is equivalent to np.random.permutation(np.arange(5))[:3]