“(5g)。”format (x)

我用这个来格式化浮点到尾零。

你可以使用%g来实现:

'%g'%(3.140)

或者，Python≥2.6:

'{0:g}'.format(3.140)

或者，Python≥3.6:

f'{3.140:g}'

格式:g cause (among other things)

不重要的后面的零[是] 从意义上移除，和 如果有，小数点也会被移除 后面没有剩余数字。

你可以像这样使用max():

打印(max (int (x), x)

以下是答案:

import numpy

num1 = 3.1400
num2 = 3.000
numpy.format_float_positional(num1, 3, trim='-')
numpy.format_float_positional(num2, 3, trim='-')

输出“3.14”和“3”

Trim ='-'删除后面的0和小数。

一个新的挑战者出现了。

def prettify_float(real: float, precision: int = 2) -> str:
    '''
    Prettify the passed floating-point number into a human-readable string,
    rounded and truncated to the passed number of decimal places.

    This converter prettifies floating-point numbers for human consumption,
    producing more readable results than the default :meth:`float.__str__`
    dunder method. Notably, this converter:

    * Strips all ignorable trailing zeroes and decimal points from this number
      (e.g., ``3`` rather than either ``3.`` or ``3.0``).
    * Rounds to the passed precision for perceptual uniformity.

    Parameters
    ----------
    real : float
        Arbitrary floating-point number to be prettified.
    precision : int, optional
        **Precision** (i.e., number of decimal places to round to). Defaults to
        a precision of 2 decimal places.

    Returns
    ----------
    str
        Human-readable string prettified from this floating-point number.

    Raises
    ----------
    ValueError
        If this precision is negative.
    '''

    # If this precision is negative, raise an exception.
    if precision < 0:
        raise ValueError(f'Negative precision {precision} unsupported.')
    # Else, this precision is non-negative.

    # String prettified from this floating-point number. In order:
    # * Coerce this number into a string rounded to this precision.
    # * Truncate all trailing zeroes from this string.
    # * Truncate any trailing decimal place if any from this string.
    result = f'{real:.{precision}f}'.rstrip('0').rstrip('.')

    # If rounding this string from a small negative number (e.g., "-0.001")
    # yielded the anomalous result of "-0", return "0" instead; else, return
    # this result as is.
    return '0' if result == '-0' else result

不要相信我的谎言

pytest风格的单元测试，否则就不会发生。

def test_prettify_float() -> None:
    '''
    Test usage of the :func:`prettify_float` prettifier.
    '''

    # Defer test-specific imports.
    from pytest import raises

    # Assert this function prettifies zero as expected.
    assert prettify_float(0.0) == '0'

    # Assert this function prettifies a negative integer as expected.
    assert prettify_float(-2.0) == '-2'

    # Assert this prettifier prettifies a small negative float as expected.
    assert prettify_float(-0.001) == '0'

    # Assert this prettifier prettifies a larger negative float as expected.
    assert prettify_float(-2.718281828) == '-2.72'
    assert prettify_float(-2.718281828, precision=4) == '-2.7183'

    # Assert this function prettifies a positive integer as expected.
    assert prettify_float(3.0) == '3'

    # Assert this function prettifies a positive float as expected.
    assert prettify_float(3.14159265359) == '3.14'
    assert prettify_float(3.14159265359, precision=4) == '3.1416'

    # Assert this prettifier raises the expected exception when passed a
    # negative precision.
    with raises(ValueError):
        prettify_float(2.718281828, precision=-2)

%100纯Python

忽略那些诱人的简单答案，比如:

琐碎的一行。它们在常见的边缘情况下都失败了，比如整数或小的负浮点数。 第三方包。NumPy, QuantiPhy和more_itertools?你肯定是在开玩笑。不要额外增加维护负担或代码债务。也就是说……

在prettify_float()上抛出@beartype，以增加运行时安全性，你就成功了!你的用户群会对你赞不绝口。那我也是，我很确定我的偏见在这里表现出来了。

另请参阅

这个答案站在巨大的猛犸象的肩膀上，包括:

亚历克斯·马尔泰利聪明的回答。 PolyMesh对Martelli答案的推广，以捕捉小负浮的边缘情况。 Kaushal Modi对PolyMesh的答案进行了概括，以强制实现小数点后两位的精度。

使用宽度足够大的%g，例如'%.99g'。 它将以定点符号打印任何相当大的数字。

编辑:它不起作用

>>> '%.99g' % 0.0000001
'9.99999999999999954748111825886258685613938723690807819366455078125e-08'