More_itertools是一个第三方库，它实现了numeric_range工具:

import more_itertools as mit


for x in mit.numeric_range(0, 1, 0.1):
    print("{:.1f}".format(x))

输出

0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9

这个工具也适用于十进制和分数。

sign = lambda x: (1, -1)[x < 0]
def frange(start, stop, step):
    i = 0
    r=len(str(step).split('.')[-1])
    args=(start,stop,step)
    if not step :return []
    if all(int(i)==float(i) for i in args):
        start,stop,step=map(int,args)
    if sign(step)==1:
        while start + i * step < stop:
            yield round(start + i * step,r)
            i += 1
    else:
        while start + i * step > stop:
            yield round(start + i * step,r)
            i += 1

在步骤中添加可能出现错误符号的自动更正:

def frange(start,step,stop):
    step *= 2*((stop>start)^(step<0))-1
    return [start+i*step for i in range(int((stop-start)/step))]

最佳解决方案:没有舍入误差

>>> step = .1
>>> N = 10     # number of data points
>>> [ x / pow(step, -1) for x in range(0, N + 1) ]

[0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0]

或者，对于一组范围而不是一组数据点(例如，连续函数)，使用:

>>> step = .1
>>> rnge = 1     # NOTE range = 1, i.e. span of data points
>>> N = int(rnge / step
>>> [ x / pow(step,-1) for x in range(0, N + 1) ]

[0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0]

实现一个函数:将x / pow(step， -1)替换为f(x / pow(step， -1))，并定义f。 例如:

>>> import math
>>> def f(x):
        return math.sin(x)

>>> step = .1
>>> rnge = 1     # NOTE range = 1, i.e. span of data points
>>> N = int(rnge / step)
>>> [ f( x / pow(step,-1) ) for x in range(0, N + 1) ]

[0.0, 0.09983341664682815, 0.19866933079506122, 0.29552020666133955, 0.3894183423086505, 
 0.479425538604203, 0.5646424733950354, 0.644217687237691, 0.7173560908995228,
 0.7833269096274834, 0.8414709848078965]

在'xrange([start]， stop[， step])'基础上，你可以定义一个生成器，它接受并生成你选择的任何类型(坚持支持+和<的类型):

>>> def drange(start, stop, step):
...     r = start
...     while r < stop:
...         yield r
...         r += step
...         
>>> i0=drange(0.0, 1.0, 0.1)
>>> ["%g" % x for x in i0]
['0', '0.1', '0.2', '0.3', '0.4', '0.5', '0.6', '0.7', '0.8', '0.9', '1']
>>> 

法兰(开始、停止、精度)

def frange(a,b,i):
    p = 10**i
    sr = a*p
    er = (b*p) + 1
    p = float(p)
    return map(lambda x: x/p, xrange(sr,er))

In >frange(-1,1,1)

Out>[-1.0, -0.9, -0.8, -0.7, -0.6, -0.5, -0.4, -0.3, -0.2, -0.1, 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0]