Мне нужно найти способ преобразования следующих строк в python:
0.000 => 0
0 => 0
123.45000 => 123.45
0000 => 0
123.4506780 => 123.450678
и т.д. Я пробовал использовать .rstrip('0'). Rstrip ('.'), Но это не работает, если вход 0 или 00.
Любые идеи? Спасибо!
Обновлено Обобщены 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
Вывод:
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 форматировать строки, если хотите, но помните, что вам может потребоваться установить желаемую точность, поскольку строки формата имеют для этого по умолчанию установлена собственная логика. 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 набросить строку дважды (как предлагает jathanism):
str(float(your_string_goes_here))
Изменить: 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 передать их целому числу:
>>> int('0000')
0
При печати числовые значения автоматически преобразуются в строки. Если вам нужно, чтобы они действительно были строками, вы можете просто вернуть их к строкам с помощью str(), например:
>>> str(float('123.4506780'))
'123.450678'
'%.17g' % float(mystr)
в зависимости от того, что вы действительно хотите сделать.
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)
.
Джон Мачин сказал, что 10000 и 10000.000 производят 1 вместо 10000
Я скорректировал 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)
.
Чтобы исправить оставшиеся недостатки [ '.0000', создав '.', указал Джон Мачин и '000078000 '78 '], я переработал сборку регулярных выражений по новой идее. Это проще. Регулярное выражение обнаруживает все типы чисел.
Это решение не только сокращает конечные нули, но и нули заголовка.
Здесь сравнение этого решения с Джоном Макином tidy_float(), samplebias number_format(), arussell84 '{:g}'.format(). Существуют некоторые различия между результатами моей функции (все правильные 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()", "'{: г}' формат()." )] li.extend(pat% (n, number_shaver (n), tidy_float (n), format_number (n), format_float (n)) если n!= '\n' else '\n' для n в числах)
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 мое решение имеет два преимущества:
регулярное выражение и функция number_shave() короткие
number_shave() обрабатывает не только одно число за раз, но также обнаруживает и обрабатывает все числа в строке. Здесь лечение, которое 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, содержащих 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 также может использоваться, чтобы просто найти все числа в строке, не удаляя нули, если не пожелает.
.
PS: см. больше в моем другом ответе, в котором объясняется регулярное выражение и его функция
Script:
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'
(Все должно было длиться только в одном посте)
Образец регулярного выражения определяет 4 подматрицы, каждый из которых соответствует определенному типу чисел. Каждый раз, когда регулярное выражение совпадает с частью строки, существует только один из подматричек, который соответствует, следовательно, возможность использования mat.lastindex в функции замены. Следующий код показывает совпадения подматрицы с различными номерами:
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)
показывает
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