Rimozione gli zero finali in Python [duplicato]
https://stackoverflow.com/questions/5807952
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Questa domanda ha già una risposta qui:
Ho bisogno di trovare un modo per convertire le seguenti stringhe in Python:
0.000 => 0
0 => 0
123.45000 => 123.45
0000 => 0
123.4506780 => 123.450678
e così via. Ho provato .rstrip ( '0'). Rstrip ( ''), ma che non funziona se l'ingresso è 0 o 00.
Tutte le idee? Grazie!
Soluzione
Aggiornamento generalizzata per mantenere la precisione e gestire i valori invisibili:
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
Output:
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
Altri suggerimenti
È possibile utilizzare stringhe di formato se si vuole, ma essere consapevoli che potrebbe essere necessario impostare la precisione desiderata, come stringhe di formato hanno una loro logica per questo per impostazione predefinita. Janneb suggerisce una precisione di 17 in ??un'altra risposta .
'{:g}'.format(float(your_string_goes_here))
Dopo aver riflettuto su questo un po 'di più, però, credo che la soluzione più semplice e migliore è solo quello di lanciare la stringa due volte (come jathanism suggerisce ):
str(float(your_string_goes_here))
Modifica:. Inserito chiarimento a causa di commento
Per i numeri in virgola mobile, si può semplicemente lanciare la stringa in un float:
>>> float('123.4506780')
123.450678
Per i valori pari a zero, si può solo lanciare quelli ad un numero intero:
>>> int('0000')
0
Quando stampate, i valori numerici vengono convertiti automaticamente in stringhe. Se è necessario che questi siano in realtà le stringhe, si può semplicemente lanciare di nuovo a stringhe con str(), per esempio:.
>>> str(float('123.4506780'))
'123.450678'
'%.17g' % float(mystr)
a seconda di cosa si vuole realmente fare ..
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])
Output (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'
OLTRE AL EDIT 2 della mia altra risposta
(Tutto era a lungo per essere in un solo post)
Il modello del regex definisce 4 sub-modelli, ciascuno corrispondente con un certo tipo di numeri. Ogni volta che le partite regex con una parte di una stringa, c'è solo uno dei sotto-modelli che incontri, quindi la possibilità di impiego mat.lastindex nella funzione di sostituzione. Illustra il codice seguente gli abbinamenti della sub-pattern contro vari numeri:
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)
dimostra
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
FIRST "soluzione"
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)
.
EDIT 1
John Machin ha detto che 10000 e 10.000,000 produrre 1 invece di 10000
I corretto la funzione di sostituzione con l'aiuto di (?!(?<=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)
.
EDIT 2
Per correggere le carenze rimanenti ['. 0000 ' la produzione di ' ' , ha sottolineato John Machin, e ' 000.078.000' la produzione '78' ], ho riscritto un accumulo regex su una nuova idea. E 'più semplice. L'espressione regolare rileva tutti i tipi di numeri.
Questa soluzione non solo taglia gli zeri finali fuori, ma anche l'intestazione zeri.
Ecco il confronto di questa soluzione con tidy_float() di John Machin, number_format() di samplebias, '{:g}'.format() di arussell84. Ci sono alcune differenze tra i risultati della mia funzione (tutti corretti questa volta) e gli altri:
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' ]
'% 18s% -15s% -15s% -15s% s' Pat = Li = [pat% ( 'il numero testato', 'float_shaver', 'Tidy_float', "format_number ()", " '{: g}' format ().")] li.extend (pat% (n, number_shaver (n), tidy_float (n), format_number (n), format_float (n)) se n! = '\ n' altro '\ n' per n in numeri)
print '\ n'.join (LI)
risultato del confronto:
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
.
ritengo che la mia soluzione ha due vantaggi:
-
la regex e la funzione number_shave () sono brevi
-
number_shave () non solo numero trattare uno alla volta, ma rileva anche e tratta tutti i numeri in una stringa. Ecco un trattamento che le soluzioni di arrussel84 di John Machin e non possono fare:
codice:
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'
risultati dei trattamenti di stringhe contenente più numeri:
--- 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
---------------------------------------------------------------
.
Di conseguenza, l'espressione regolare può stato utilizzato anche per solo trovare tutti i numeri in una stringa, senza togliere gli zeri, se non voluto.
.
PS: vedere di più nella mia altra risposta che spiega la regex e la sua functionning
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