Удаление конечных нулей в Python

Мне нужно найти способ конвертировать следующие строки в Python:

0.000       => 0
0           => 0
123.45000   => 123.45
0000        => 0
123.4506780 => 123.450678

и так далее. Я пробовал.rstrip('0'). Rstrip('.'), Но это не работает, если ввод 0 или 00.

Есть идеи? Спасибо!

7 ответов

Решение

Обновлен Обобщенный для поддержания точности и обработки невидимых значений:

import decimal
import random

def format_number(num):
    try:
        dec = decimal.Decimal(num)
    except:
        return 'bad'
    tup = dec.as_tuple()
    delta = len(tup.digits) + tup.exponent
    digits = ''.join(str(d) for d in tup.digits)
    if delta <= 0:
        zeros = abs(tup.exponent) - len(tup.digits)
        val = '0.' + ('0'*zeros) + digits
    else:
        val = digits[:delta] + ('0'*tup.exponent) + '.' + digits[delta:]
    val = val.rstrip('0')
    if val[-1] == '.':
        val = val[:-1]
    if tup.sign:
        return '-' + val
    return val

# test data
NUMS = '''
    0.0000      0
    0           0
    123.45000   123.45
    0000        0
    123.4506780 123.450678
    0.1         0.1
    0.001       0.001
    0.005000    0.005
    .1234       0.1234
    1.23e1      12.3
    -123.456    -123.456
    4.98e10     49800000000
    4.9815135   4.9815135
    4e30        4000000000000000000000000000000
    -0.0000000000004 -0.0000000000004
    -.4e-12     -0.0000000000004
    -0.11112    -0.11112
    1.3.4.5     bad
    -1.2.3      bad
'''

for num, exp in [s.split() for s in NUMS.split('\n') if s]:
    res = format_number(num)
    print res
    assert exp == res

Выход:

0
0
123.45
0
123.450678
0.1
0.001
0.005
0.1234
12.3
-123.456
49800000000
4.9815135
4000000000000000000000000000000
-0.0000000000004
-0.0000000000004
-0.11112
bad
bad

Вы можете использовать строки форматирования, если хотите, но имейте в виду, что вам может потребоваться установить желаемую точность, так как строки форматирования имеют собственную логику для этого по умолчанию. Janneb предлагает точность 17 в другом ответе.

'{:g}'.format(float(your_string_goes_here))

Подумав об этом еще немного, я думаю, что самое простое и лучшее решение - просто бросить строку дважды (как предполагает джатанизм):

str(float(your_string_goes_here))

Редактировать: Добавлено пояснение из-за комментария.

Для чисел с плавающей запятой, вы можете просто привести строку к float:

>>> float('123.4506780')
123.450678

Для нулевых значений вы можете просто привести их к целому числу:

>>> int('0000')
0

При печати числовые значения автоматически преобразуются в строки. Если вам нужны эти строки, вы можете просто привести их обратно к строкам с str()Например:

>>> str(float('123.4506780'))
'123.450678'
'%.17g' % float(mystr)

в зависимости от того, что вы на самом деле хотите сделать..

ПЕРВЫЙ "РЕШЕНИЕ"

import re
regx=re.compile('(?<![\d.])'
                '(?!\d*\.\d*\.)'  # excludes certain string as not being numbers
                '((\d|\.\d)([\d.])*?)'  # the only matching  group
                '([0\.]*)'
                '(?![\d.])')
regx.sub('\\1',ch)

,

РЕДАКТИРОВАТЬ 1

Джон Мачин сказал, что 10000 и 10000.000 производят 1 вместо 10000

Я исправил функцию замены с помощью (?!(?<=0)\.)

import re
regx = re.compile('(?<![\d.])'       '(?![1-9]\d*(?![\d.])|\d*\.\d*\.)'
                  '0*(?!(?<=0)\.)'
                  '([\d.]+?)'      # the only group , which is kept
                  '\.?0*'
                  '(?![\d.])')    
regx.sub('\\1',ch)               

,

РЕДАКТИРОВАТЬ 2

Исправить оставшиеся недостатки [ '.0000' производит '.' На что указал Джон Мачин и "000078000", производящий "78" ], я переписал сборку регулярных выражений на основе новой идеи. Это проще Регулярное выражение обнаруживает все типы чисел.

Это решение обрезает не только конечные нули, но и нули заголовка. Вот сравнение этого решения с Джоном Мачином tidy_float() Самплебия number_format(), arussell84's '{:g}'.format(), Есть некоторые различия между результатами моей функции (все верно на этот раз) и другими:

import re
def number_shaver(ch,
                  regx = re.compile('(?<![\d.])0*(?:'
                                    '(\d+)\.?|\.(0)'
                                    '|(\.\d+?)|(\d+\.\d+?)'
                                    ')0*(?![\d.])')  ,
                  repl = lambda mat: mat.group(mat.lastindex)
                                     if mat.lastindex!=3
                                     else '0' + mat.group(3) ):
    return regx.sub(repl,ch)


def tidy_float(s):  # John Machin
    """Return tidied float representation.
    Remove superflous leading/trailing zero digits.
    Remove '.' if value is an integer.
    Return '****' if float(s) fails.
    """
    # float?
    try:
        f = float(s)
    except ValueError:
        return s
    # int?
    try:
        i = int(s)
        return str(i)
    except ValueError:
        pass
    # scientific notation?
    if 'e' in s or 'E' in s:
        t = s.lstrip('0')
        if t.startswith('.'): t = '0' + t
        return t
    # float with integral value (includes zero)?
    i = int(f)
    if i == f:
        return str(i)
    assert '.' in s
    t = s.strip('0')
    if t.startswith('.'): t = '0' + t
    if t.endswith('.'): t += '0'
    return t


def format_float(s):  # arrussell84
    return '{:g}'.format(float(s)) if s.count('.')<2 \
           else "Can't treat"


import decimal
def format_number(num):
    try:
        dec = decimal.Decimal(num)
    except:
        return 'bad'
    tup = dec.as_tuple()
    delta = len(tup.digits) + tup.exponent
    digits = ''.join(str(d) for d in tup.digits)
    if delta <= 0:
        zeros = abs(tup.exponent) - len(tup.digits)
        val = '0.' + ('0'*zeros) + digits
    else:
        val = digits[:delta] + ('0'*tup.exponent) + '.' + digits[delta:]
    val = val.rstrip('0')
    if val[-1] == '.':
        val = val[:-1]
    if tup.sign:
        return '-' + val
    return val


numbers = ['23456000', '23456000.', '23456000.000',
           '00023456000', '000023456000.', '000023456000.000',
           '10000', '10000.', '10000.000',
           '00010000', '00010000.', '00010000.000',
           '24', '24.', '24.000',
           '00024', '00024.', '00024.000',
           '8', '8.', '8.000',
           '0008', '0008.', '0008.000',
           '0', '00000', '0.', '000.',
           '\n',
           '0.0', '0.000', '000.0', '000.000', '.000000', '.0',
           '\n',
           '.00023456', '.00023456000', '.00503', '.00503000',
           '.068', '.0680000', '.8', '.8000',
           '.123456123456', '.123456123456000',
           '.657', '.657000', '.45', '.4500000', '.7', '.70000',
           '\n',
           '0.0000023230000', '000.0000023230000',
           '0.0081000', '0000.0081000',
           '0.059000', '0000.059000',
           '0.78987400000', '00000.78987400000',
           '0.4400000', '00000.4400000',
           '0.5000', '0000.5000',
           '0.90', '000.90', '0.7', '000.7',
           '\n',
           '2.6', '00002.6', '00002.60000',
           '4.71', '0004.71', '0004.7100',
           '23.49', '00023.49', '00023.490000',
           '103.45', '0000103.45', '0000103.45000',
           '10003.45067', '000010003.45067', '000010003.4506700',
           '15000.0012', '000015000.0012', '000015000.0012000',
           '78000.89', '000078000.89', '000078000.89000',
           '\n',
           '.0457e10', '.0457000e10','00000.0457000e10',
           '258e8', '2580000e4', '0000000002580000e4',
           # notice the difference of exponents
           '0.782e10', '0000.782e10', '0000.7820000e10',
           '1.23E2', '0001.23E2', '0001.2300000E2',
           '432e-102', '0000432e-102', '004320000e-106',
           # notice the difference of exponents
           '1.46e10', '0001.46e10', '0001.4600000e10',
           '1.077e-300', '0001.077e-300', '0001.077000e-300',
           '1.069e10', '0001.069e10', '0001.069000e10',
           '105040.03e10', '000105040.03e10', '105040.0300e10',
           '\n',
           '..18000', '25..00',  '36...77', '2..8',
           '3.8..9', '.12500.', '12.51.400' ]

pat = '% 18s% -15s% -15s% -15s% s' li = [pat% ('проверенное число','float_shaver', 'tidy_float', 'format_number()","'{:g}'.format()")] li.extend(pat % (n,number_shaver(n),tidy_float(n),format_number(n),format_float(n)), если n!='\n' else '\n' для n в цифрах)

print '\ n'.join (li)

Результат сравнения:

     tested number  float_shaver    tidy_float      format_number() '{:g}'.format()
          23456000  23456000        23456000        23456000        2.3456e+07
         23456000.  23456000        23456000        23456000        2.3456e+07
      23456000.000  23456000        23456000        23456000        2.3456e+07
       00023456000  23456000        23456000        23456000        2.3456e+07
     000023456000.  23456000        23456000        23456000        2.3456e+07
  000023456000.000  23456000        23456000        23456000        2.3456e+07
             10000  10000           10000           10000           10000
            10000.  10000           10000           10000           10000
         10000.000  10000           10000           10000           10000
          00010000  10000           10000           10000           10000
         00010000.  10000           10000           10000           10000
      00010000.000  10000           10000           10000           10000
                24  24              24              24              24
               24.  24              24              24              24
            24.000  24              24              24              24
             00024  24              24              24              24
            00024.  24              24              24              24
         00024.000  24              24              24              24
                 8  8               8               8               8
                8.  8               8               8               8
             8.000  8               8               8               8
              0008  8               8               8               8
             0008.  8               8               8               8
          0008.000  8               8               8               8
                 0  0               0               0               0
             00000  0               0               0               0
                0.  0               0               0               0
              000.  0               0               0               0


               0.0  0               0               0               0
             0.000  0               0               0               0
             000.0  0               0               0               0
           000.000  0               0               0               0
           .000000  0               0               0               0
                .0  0               0               0               0


         .00023456  0.00023456      0.00023456      0.00023456      0.00023456
      .00023456000  0.00023456      0.00023456      0.00023456      0.00023456
            .00503  0.00503         0.00503         0.00503         0.00503
         .00503000  0.00503         0.00503         0.00503         0.00503
              .068  0.068           0.068           0.068           0.068
          .0680000  0.068           0.068           0.068           0.068
                .8  0.8             0.8             0.8             0.8
             .8000  0.8             0.8             0.8             0.8
     .123456123456  0.123456123456  0.123456123456  0.123456123456  0.123456
  .123456123456000  0.123456123456  0.123456123456  0.123456123456  0.123456
              .657  0.657           0.657           0.657           0.657
           .657000  0.657           0.657           0.657           0.657
               .45  0.45            0.45            0.45            0.45
          .4500000  0.45            0.45            0.45            0.45
                .7  0.7             0.7             0.7             0.7
            .70000  0.7             0.7             0.7             0.7


   0.0000023230000  0.000002323     0.000002323     0.000002323     2.323e-06
 000.0000023230000  0.000002323     0.000002323     0.000002323     2.323e-06
         0.0081000  0.0081          0.0081          0.0081          0.0081
      0000.0081000  0.0081          0.0081          0.0081          0.0081
          0.059000  0.059           0.059           0.059           0.059
       0000.059000  0.059           0.059           0.059           0.059
     0.78987400000  0.789874        0.789874        0.789874        0.789874
 00000.78987400000  0.789874        0.789874        0.789874        0.789874
         0.4400000  0.44            0.44            0.44            0.44
     00000.4400000  0.44            0.44            0.44            0.44
            0.5000  0.5             0.5             0.5             0.5
         0000.5000  0.5             0.5             0.5             0.5
              0.90  0.9             0.9             0.9             0.9
            000.90  0.9             0.9             0.9             0.9
               0.7  0.7             0.7             0.7             0.7
             000.7  0.7             0.7             0.7             0.7


               2.6  2.6             2.6             2.6             2.6
           00002.6  2.6             2.6             2.6             2.6
       00002.60000  2.6             2.6             2.6             2.6
              4.71  4.71            4.71            4.71            4.71
           0004.71  4.71            4.71            4.71            4.71
         0004.7100  4.71            4.71            4.71            4.71
             23.49  23.49           23.49           23.49           23.49
          00023.49  23.49           23.49           23.49           23.49
      00023.490000  23.49           23.49           23.49           23.49
            103.45  103.45          103.45          103.45          103.45
        0000103.45  103.45          103.45          103.45          103.45
     0000103.45000  103.45          103.45          103.45          103.45
       10003.45067  10003.45067     10003.45067     10003.45067     10003.5
   000010003.45067  10003.45067     10003.45067     10003.45067     10003.5
 000010003.4506700  10003.45067     10003.45067     10003.45067     10003.5
        15000.0012  15000.0012      15000.0012      15000.0012      15000
    000015000.0012  15000.0012      15000.0012      15000.0012      15000
 000015000.0012000  15000.0012      15000.0012      15000.0012      15000
          78000.89  78000.89        78000.89        78000.89        78000.9
      000078000.89  78000.89        78000.89        78000.89        78000.9
   000078000.89000  78000.89        78000.89        78000.89        78000.9


          .0457e10  0.0457e10       0.0457e10       457000000       4.57e+08
       .0457000e10  0.0457e10       0.0457000e10    457000000       4.57e+08
  00000.0457000e10  0.0457e10       0.0457000e10    457000000       4.57e+08
             258e8  258e8           258e8           25800000000     2.58e+10
         2580000e4  2580000e4       2580000e4       25800000000     2.58e+10
0000000002580000e4  2580000e4       2580000e4       25800000000     2.58e+10
          0.782e10  0.782e10        0.782e10        7820000000      7.82e+09
       0000.782e10  0.782e10        0.782e10        7820000000      7.82e+09
   0000.7820000e10  0.782e10        0.7820000e10    7820000000      7.82e+09
            1.23E2  1.23E2          1.23E2          123             123
         0001.23E2  1.23E2          1.23E2          123             123
    0001.2300000E2  1.23E2          1.2300000E2     123             123
          432e-102  432e-102        432e-102        0.000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000432 4.32e-100
      0000432e-102  432e-102        432e-102        0.000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000432 4.32e-100
    004320000e-106  4320000e-106    4320000e-106    0.000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000432 4.32e-100
           1.46e10  1.46e10         1.46e10         14600000000     1.46e+10
        0001.46e10  1.46e10         1.46e10         14600000000     1.46e+10
   0001.4600000e10  1.46e10         1.4600000e10    14600000000     1.46e+10
        1.077e-300  1.077e-300      1.077e-300      0.000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001077 1.077e-300
     0001.077e-300  1.077e-300      1.077e-300      0.000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001077 1.077e-300
  0001.077000e-300  1.077e-300      1.077000e-300   0.000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001077 1.077e-300
          1.069e10  1.069e10        1.069e10        10690000000     1.069e+10
       0001.069e10  1.069e10        1.069e10        10690000000     1.069e+10
    0001.069000e10  1.069e10        1.069000e10     10690000000     1.069e+10
      105040.03e10  105040.03e10    105040.03e10    1050400300000000 1.0504e+15
   000105040.03e10  105040.03e10    105040.03e10    1050400300000000 1.0504e+15
    105040.0300e10  105040.03e10    105040.0300e10  1050400300000000 1.0504e+15


           ..18000  ..18000         ..18000         bad             Can't treat
            25..00  25..00          25..00          bad             Can't treat
           36...77  36...77         36...77         bad             Can't treat
              2..8  2..8            2..8            bad             Can't treat
            3.8..9  3.8..9          3.8..9          bad             Can't treat
           .12500.  .12500.         .12500.         bad             Can't treat
         12.51.400  12.51.400       12.51.400       bad             Can't treat

,

Я считаю, что у моего решения есть два преимущества:

  • регулярное выражение и функция number_shave() короткие

  • number_shave() не только обрабатывает одно число одновременно, но также обнаруживает и обрабатывает все числа в строке. Вот обработка, которую не могут сделать решения Джона Мачина и arrussel84:

код:

numbers = [['', '23456000', '23456000.', '23456000.000 \n',
            '00023456000', '000023456000.', '000023456000.000 \n',
            '10000', '10000.', '10000.000 \n',
            '00010000', '00010000.', '00010000.000 \n',
            '24', '24.', '24.000 \n',
            '00024', '00024.', '00024.000 \n',
            '8', '8.', '8.000 \n',
            '0008', '0008.', '0008.000 \n',
            '0', '00000', '0.', '000.' ],




            ['0.0', '0.000', '000.0', '000.000', '.000000', '.0'],

            ['.00023456', '.00023456000', '.00503', '.00503000 \n',
             '.068', '.0680000', '.8', '.8000 \n',
             '.123456123456', '.123456123456000 \n',
             '.657', '.657000', '.45', '.4500000', '.7', '.70000'],

            ['0.0000023230000', '000.0000023230000 \n',
             '0.0081000', '0000.0081000 \n',
             '0.059000', '0000.059000 \n',
             '0.78987400000', '00000.78987400000 \n',
             '0.4400000', '00000.4400000 \n',
             '0.5000', '0000.5000 \n',
             '0.90', '000.90', '0.7', '000.7 '],

            ['2.6', '00002.6', '00002.60000 \n',
             '4.71', '0004.71', '0004.7100 \n',
             '23.49', '00023.49', '00023.490000 \n',
             '103.45', '0000103.45', '0000103.45000 \n',
             '10003.45067', '000010003.45067', '000010003.4506700 \n',
             '15000.0012', '000015000.0012', '000015000.0012000 \n',
             '78000.89', '000078000.89', '000078000.89000'],

            ['.0457e10', '.0457000e10 \n',
             '0.782e10', '0000.782e10', '0000.7820000e10 \n',
             '1.23E2', '0001.23E2', '0001.2300000E2 \n',
             '1.46e10', '0001.46e10', '0001.4600000e10 \n',
             '1.077e-456', '0001.077e-456', '0001.077000e-456 \n',
             '1.069e10', '0001.069e10', '0001.069000e10 \n',
             '105040.03e10', '000105040.03e10', '105040.03e10'],

            ['..18000', '25..00',  '36...77', '2..8 \n',
             '3.8..9', '.12500.', '12.51.400' ]]


import re
def number_shaver(ch,
                 regx = re.compile('(?<![\d.])0*(?:'
                                   '(\d+)\.?|\.(0)'
                                   '|(\.\d+?)|(\d+\.\d+?)'
                                   ')0*(?![\d.])')  ,
                 repl = lambda mat: mat.group(mat.lastindex)
                                    if mat.lastindex!=3
                                    else '0' + mat.group(3) ):
    return regx.sub(repl,ch)




for li in numbers:
    one_string = ' --- '.join(li)
    print one_string + '\n\n' + number_shaver(one_string) + \
          '\n\n' + 3*'---------------------' + '\n'

Результаты обработки строк, содержащие несколько чисел:

 --- 23456000 --- 23456000. --- 23456000.000 
 --- 00023456000 --- 000023456000. --- 000023456000.000 
 --- 10000 --- 10000. --- 10000.000 
 --- 00010000 --- 00010000. --- 00010000.000 
 --- 24 --- 24. --- 24.000 
 --- 00024 --- 00024. --- 00024.000 
 --- 8 --- 8. --- 8.000 
 --- 0008 --- 0008. --- 0008.000 
 --- 0 --- 00000 --- 0. --- 000.

 --- 23456000 --- 23456000 --- 23456000 
 --- 23456000 --- 23456000 --- 23456000 
 --- 10000 --- 10000 --- 10000 
 --- 10000 --- 10000 --- 10000 
 --- 24 --- 24 --- 24 
 --- 24 --- 24 --- 24 
 --- 8 --- 8 --- 8 
 --- 8 --- 8 --- 8 
 --- 0 --- 0 --- 0 --- 0

---------------------------------------------------------------

0.0 --- 0.000 --- 000.0 --- 000.000 --- .000000 --- .0

0 --- 0 --- 0 --- 0 --- 0 --- 0

---------------------------------------------------------------

.00023456 --- .00023456000 --- .00503 --- .00503000 
 --- .068 --- .0680000 --- .8 --- .8000 
 --- .123456123456 --- .123456123456000 
 --- .657 --- .657000 --- .45 --- .4500000 --- .7 --- .70000

0.00023456 --- 0.00023456 --- 0.00503 --- 0.00503 
 --- 0.068 --- 0.068 --- 0.8 --- 0.8 
 --- 0.123456123456 --- 0.123456123456 
 --- 0.657 --- 0.657 --- 0.45 --- 0.45 --- 0.7 --- 0.7

---------------------------------------------------------------

0.0000023230000 --- 000.0000023230000 
 --- 0.0081000 --- 0000.0081000 
 --- 0.059000 --- 0000.059000 
 --- 0.78987400000 --- 00000.78987400000 
 --- 0.4400000 --- 00000.4400000 
 --- 0.5000 --- 0000.5000 
 --- 0.90 --- 000.90 --- 0.7 --- 000.7 

0.000002323 --- 0.000002323 
 --- 0.0081 --- 0.0081 
 --- 0.059 --- 0.059 
 --- 0.789874 --- 0.789874 
 --- 0.44 --- 0.44 
 --- 0.5 --- 0.5 
 --- 0.9 --- 0.9 --- 0.7 --- 0.7 

---------------------------------------------------------------

2.6 --- 00002.6 --- 00002.60000 
 --- 4.71 --- 0004.71 --- 0004.7100 
 --- 23.49 --- 00023.49 --- 00023.490000 
 --- 103.45 --- 0000103.45 --- 0000103.45000 
 --- 10003.45067 --- 000010003.45067 --- 000010003.4506700 
 --- 15000.0012 --- 000015000.0012 --- 000015000.0012000 
 --- 78000.89 --- 000078000.89 --- 000078000.89000

2.6 --- 2.6 --- 2.6 
 --- 4.71 --- 4.71 --- 4.71 
 --- 23.49 --- 23.49 --- 23.49 
 --- 103.45 --- 103.45 --- 103.45 
 --- 10003.45067 --- 10003.45067 --- 10003.45067 
 --- 15000.0012 --- 15000.0012 --- 15000.0012 
 --- 78000.89 --- 78000.89 --- 78000.89

---------------------------------------------------------------

.0457e10 --- .0457000e10 
 --- 0.782e10 --- 0000.782e10 --- 0000.7820000e10 
 --- 1.23E2 --- 0001.23E2 --- 0001.2300000E2 
 --- 1.46e10 --- 0001.46e10 --- 0001.4600000e10 
 --- 1.077e-456 --- 0001.077e-456 --- 0001.077000e-456 
 --- 1.069e10 --- 0001.069e10 --- 0001.069000e10 
 --- 105040.03e10 --- 000105040.03e10 --- 105040.03e10

0.0457e10 --- 0.0457e10 
 --- 0.782e10 --- 0.782e10 --- 0.782e10 
 --- 1.23E2 --- 1.23E2 --- 1.23E2 
 --- 1.46e10 --- 1.46e10 --- 1.46e10 
 --- 1.077e-456 --- 1.077e-456 --- 1.077e-456 
 --- 1.069e10 --- 1.069e10 --- 1.069e10 
 --- 105040.03e10 --- 105040.03e10 --- 105040.03e10

---------------------------------------------------------------

..18000 --- 25..00 --- 36...77 --- 2..8 
 --- 3.8..9 --- .12500. --- 12.51.400

..18000 --- 25..00 --- 36...77 --- 2..8 
 --- 3.8..9 --- .12500. --- 12.51.400

---------------------------------------------------------------

,

Следовательно, регулярное выражение может также использоваться, чтобы просто найти все числа в строке, не удаляя нули, если не желательно.

,

PS: смотрите больше в моем другом ответе, который объясняет регулярное выражение и его функционирование

Автор сценария:

def tidy_float(s):
    """Return tidied float representation.
    Remove superflous leading/trailing zero digits.
    Remove '.' if value is an integer.
    Return '****' if float(s) fails.
    """
    # float?
    try:
        f = float(s)
    except ValueError:
        return '****'
    # int?
    try:
        i = int(s)
        return str(i)
    except ValueError:
        pass
    # scientific notation?
    if 'e' in s or 'E' in s:
        t = s.lstrip('0')
        if t.startswith('.'): t = '0' + t
        return t
    # float with integral value (includes zero)?
    i = int(f)
    if i == f:
        return str(i)
    assert '.' in s
    t = s.strip('0')
    if t.startswith('.'): t = '0' + t
    if t.endswith('.'): t += '0'
    return t

if __name__ == "__main__":

    # Each line has test string followed by expected output
    tests = """
    0.000 0
    0 0
    0000 0
    0.4000 0.4
    0.0081000 0.0081
    103.45 103.45
    103.4506700 103.45067
    14500.0012 14500.0012
    478000.89 478000.89
    993.59.18 ****
    12.5831.400 ****
    .458 0.458
    .48587000 0.48587
    .0000 0
    10000 10000
    10000.000 10000
    -10000 -10000
    -10000.000 -10000
    1.23e2 1.23e2
    1.23e10 1.23e10
    .123e10 0.123e10
     """.splitlines()

    for test in tests:
        x = test.split()
        if not x: continue
        data, expected = x
        actual = tidy_float(data)
        print "data=%r exp=%r act=%r %s" % (
            data, expected, actual, ["**FAIL**", ""][actual == expected])

Выход (Python 2.7.1):

data='0.000' exp='0' act='0'
data='0' exp='0' act='0'
data='0000' exp='0' act='0'
data='0.4000' exp='0.4' act='0.4'
data='0.0081000' exp='0.0081' act='0.0081'
data='103.45' exp='103.45' act='103.45'
data='103.4506700' exp='103.45067' act='103.45067'
data='14500.0012' exp='14500.0012' act='14500.0012'
data='478000.89' exp='478000.89' act='478000.89'
data='993.59.18' exp='****' act='****'
data='12.5831.400' exp='****' act='****'
data='.458' exp='0.458' act='0.458'
data='.48587000' exp='0.48587' act='0.48587'
data='.0000' exp='0' act='0'
data='10000' exp='10000' act='10000'
data='10000.000' exp='10000' act='10000'
data='-10000' exp='-10000' act='-10000'
data='-10000.000' exp='-10000' act='-10000'
data='1.23e2' exp='1.23e2' act='1.23e2'
data='1.23e10' exp='1.23e10' act='1.23e10'
data='.123e10' exp='0.123e10' act='0.123e10'

ДОБАВЛЕНИЕ В РЕДАКТИРОВКУ 2 из моего другого ответа

(Все должно было быть долго только в одном посте)

Шаблон регулярного выражения определяет 4 подшаблонов, каждый из которых соответствует определенному типу чисел. Каждый раз, когда регулярное выражение совпадает с частью строки, есть только один из подшаблонов, который соответствует, следовательно, есть возможность использовать mat.lastindex в функции замены. Следующий код показывает совпадения подшаблона с различными числами:

import re
def float_show(ch,
               regx = re.compile(
                   '(?<![\d.])'
                   '0*' # potentiel heading zeros
                   '(?:'
                   '(\d+)\.?' # INTEGERS :
                              # ~ pure integers non-0 or 0
                              #   000450 , 136000 , 87 , 000 , 0
                              # ~ integer part non-0 + '.'
                              #   0044. , 4100.
                              # ~ integer part 0 + '.'
                              #   000. , 0. 
                              # ~ integer part non-0 + '.' + fractional part 0:
                              #   000570.00 , 193.0 , 3.000

                   '|\.(0)' # SPECIAL CASE, 0 WITH FRACTIONAL PART :
                            # ~ integer part 0 + compulsory fractional part 0:
                            #   000.0, 0.000 , .0 , .00000

                   '|(\.\d+?)' # FLOATING POINT NUMBER
                               # ~ with integer part 0:
                               #   000.0890 , 0.52 , 0.1 , .077000 , .1400 , .0006010

                   '|(\d+\.\d+?)' # FLOATING POINT NUMBER
                                  # ~ with integer part non-0:
                                  #   0024000.013000 , 145.0235 , 3.00058
                   ')'
                   '0*' # potential tailing zeros
                   '(?![\d.])'),
               repl = lambda mat: mat.group(mat.lastindex)
                                  if mat.lastindex!=3
                                  else '0' + mat.group(3)  ):
    mat = regx.search(ch)
    if mat:
        return (ch,regx.sub(repl,ch),repr(mat.groups()))
    else:
        return (ch,'No match','No groups')


numbers = ['23456000', '23456000.', '23456000.000',
           '00023456000', '000023456000.', '000023456000.000',
           '10000', '10000.', '10000.000',
           '00010000', '00010000.', '00010000.000',
           '24', '24.', '24.000',
           '00024', '00024.', '00024.000',
           '8', '8.', '8.000',
           '0008', '0008.', '0008.000',
           '0', '00000', '0.', '000.',
           '\n',
           '0.0', '0.000', '000.0', '000.000', '.000000', '.0',
           '\n',
           '.00023456', '.00023456000', '.00503', '.00503000',
           '.068', '.0680000', '.8', '.8000',
           '.123456123456', '.123456123456000',
           '.657', '.657000', '.45', '.4500000', '.7', '.70000',
           '\n',
           '0.0000023230000', '000.0000023230000',
           '0.0081000', '0000.0081000',
           '0.059000', '0000.059000',
           '0.78987400000', '00000.78987400000',
           '0.4400000', '00000.4400000',
           '0.5000', '0000.5000',
           '0.90', '000.90', '0.7', '000.7',
           '\n',
           '2.6', '00002.6', '00002.60000',
           '4.71', '0004.71', '0004.7100',
           '23.49', '00023.49', '00023.490000',
           '103.45', '0000103.45', '0000103.45000',
           '10003.45067', '000010003.45067', '000010003.4506700',
           '15000.0012', '000015000.0012', '000015000.0012000',
           '78000.89', '000078000.89', '000078000.89000',
           '\n',
           '.0457e10', '.0457000e10',
           '0.782e10', '0000.782e10', '0000.7820000e10',
           '1.23E2', '0001.23E2', '0001.2300000E2',
           '1.46e10', '0001.46e10', '0001.4600000e10',
           '1.077e-456', '0001.077e-456', '0001.077000e-456',
           '1.069e10', '0001.069e10', '0001.069000e10',
           '105040.03e10', '000105040.03e10', '105040.0300e10',
           '\n',
           '..18000', '25..00',  '36...77', '2..8',
           '3.8..9', '.12500.', '12.51.400' ]

pat = '%20s  %-16s %s'
li = [pat % ('tested number ',' shaved float',' regx.search(number).groups()')]
li.extend(pat % float_show(ch) if ch!='\n' else '\n' for ch in numbers)
print '\n'.join(li)

демонстрирует

      tested number    shaved float     regx.search(number).groups()
            23456000  23456000         ('23456000', None, None, None)
           23456000.  23456000         ('23456000', None, None, None)
        23456000.000  23456000         ('23456000', None, None, None)
         00023456000  23456000         ('23456000', None, None, None)
       000023456000.  23456000         ('23456000', None, None, None)
    000023456000.000  23456000         ('23456000', None, None, None)
               10000  10000            ('10000', None, None, None)
              10000.  10000            ('10000', None, None, None)
           10000.000  10000            ('10000', None, None, None)
            00010000  10000            ('10000', None, None, None)
           00010000.  10000            ('10000', None, None, None)
        00010000.000  10000            ('10000', None, None, None)
                  24  24               ('24', None, None, None)
                 24.  24               ('24', None, None, None)
              24.000  24               ('24', None, None, None)
               00024  24               ('24', None, None, None)
              00024.  24               ('24', None, None, None)
           00024.000  24               ('24', None, None, None)
                   8  8                ('8', None, None, None)
                  8.  8                ('8', None, None, None)
               8.000  8                ('8', None, None, None)
                0008  8                ('8', None, None, None)
               0008.  8                ('8', None, None, None)
            0008.000  8                ('8', None, None, None)
                   0  0                ('0', None, None, None)
               00000  0                ('0', None, None, None)
                  0.  0                ('0', None, None, None)
                000.  0                ('0', None, None, None)


                 0.0  0                (None, '0', None, None)
               0.000  0                (None, '0', None, None)
               000.0  0                (None, '0', None, None)
             000.000  0                (None, '0', None, None)
             .000000  0                (None, '0', None, None)
                  .0  0                (None, '0', None, None)


           .00023456  0.00023456       (None, None, '.00023456', None)
        .00023456000  0.00023456       (None, None, '.00023456', None)
              .00503  0.00503          (None, None, '.00503', None)
           .00503000  0.00503          (None, None, '.00503', None)
                .068  0.068            (None, None, '.068', None)
            .0680000  0.068            (None, None, '.068', None)
                  .8  0.8              (None, None, '.8', None)
               .8000  0.8              (None, None, '.8', None)
       .123456123456  0.123456123456   (None, None, '.123456123456', None)
    .123456123456000  0.123456123456   (None, None, '.123456123456', None)
                .657  0.657            (None, None, '.657', None)
             .657000  0.657            (None, None, '.657', None)
                 .45  0.45             (None, None, '.45', None)
            .4500000  0.45             (None, None, '.45', None)
                  .7  0.7              (None, None, '.7', None)
              .70000  0.7              (None, None, '.7', None)


     0.0000023230000  0.000002323      (None, None, '.000002323', None)
   000.0000023230000  0.000002323      (None, None, '.000002323', None)
           0.0081000  0.0081           (None, None, '.0081', None)
        0000.0081000  0.0081           (None, None, '.0081', None)
            0.059000  0.059            (None, None, '.059', None)
         0000.059000  0.059            (None, None, '.059', None)
       0.78987400000  0.789874         (None, None, '.789874', None)
   00000.78987400000  0.789874         (None, None, '.789874', None)
           0.4400000  0.44             (None, None, '.44', None)
       00000.4400000  0.44             (None, None, '.44', None)
              0.5000  0.5              (None, None, '.5', None)
           0000.5000  0.5              (None, None, '.5', None)
                0.90  0.9              (None, None, '.9', None)
              000.90  0.9              (None, None, '.9', None)
                 0.7  0.7              (None, None, '.7', None)
               000.7  0.7              (None, None, '.7', None)


                 2.6  2.6              (None, None, None, '2.6')
             00002.6  2.6              (None, None, None, '2.6')
         00002.60000  2.6              (None, None, None, '2.6')
                4.71  4.71             (None, None, None, '4.71')
             0004.71  4.71             (None, None, None, '4.71')
           0004.7100  4.71             (None, None, None, '4.71')
               23.49  23.49            (None, None, None, '23.49')
            00023.49  23.49            (None, None, None, '23.49')
        00023.490000  23.49            (None, None, None, '23.49')
              103.45  103.45           (None, None, None, '103.45')
          0000103.45  103.45           (None, None, None, '103.45')
       0000103.45000  103.45           (None, None, None, '103.45')
         10003.45067  10003.45067      (None, None, None, '10003.45067')
     000010003.45067  10003.45067      (None, None, None, '10003.45067')
   000010003.4506700  10003.45067      (None, None, None, '10003.45067')
          15000.0012  15000.0012       (None, None, None, '15000.0012')
      000015000.0012  15000.0012       (None, None, None, '15000.0012')
   000015000.0012000  15000.0012       (None, None, None, '15000.0012')
            78000.89  78000.89         (None, None, None, '78000.89')
        000078000.89  78000.89         (None, None, None, '78000.89')
     000078000.89000  78000.89         (None, None, None, '78000.89')


            .0457e10  0.0457e10        (None, None, '.0457', None)
         .0457000e10  0.0457e10        (None, None, '.0457', None)
            0.782e10  0.782e10         (None, None, '.782', None)
         0000.782e10  0.782e10         (None, None, '.782', None)
     0000.7820000e10  0.782e10         (None, None, '.782', None)
              1.23E2  1.23E2           (None, None, None, '1.23')
           0001.23E2  1.23E2           (None, None, None, '1.23')
      0001.2300000E2  1.23E2           (None, None, None, '1.23')
             1.46e10  1.46e10          (None, None, None, '1.46')
          0001.46e10  1.46e10          (None, None, None, '1.46')
     0001.4600000e10  1.46e10          (None, None, None, '1.46')
          1.077e-456  1.077e-456       (None, None, None, '1.077')
       0001.077e-456  1.077e-456       (None, None, None, '1.077')
    0001.077000e-456  1.077e-456       (None, None, None, '1.077')
            1.069e10  1.069e10         (None, None, None, '1.069')
         0001.069e10  1.069e10         (None, None, None, '1.069')
      0001.069000e10  1.069e10         (None, None, None, '1.069')
        105040.03e10  105040.03e10     (None, None, None, '105040.03')
     000105040.03e10  105040.03e10     (None, None, None, '105040.03')
      105040.0300e10  105040.03e10     (None, None, None, '105040.03')


             ..18000  No match         No groups
              25..00  No match         No groups
             36...77  No match         No groups
                2..8  No match         No groups
              3.8..9  No match         No groups
             .12500.  No match         No groups
           12.51.400  No match         No groups
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