86

I'm looking for an equivalent to sscanf() in Python. I want to parse /proc/net/* files, in C I could do something like this:

int matches = sscanf(
        buffer,
        "%*d: %64[0-9A-Fa-f]:%X %64[0-9A-Fa-f]:%X %*X %*X:%*X %*X:%*X %*X %*d %*d %ld %*512s\n",
        local_addr, &local_port, rem_addr, &rem_port, &inode);

I thought at first to use str.split, however it doesn't split on the given characters, but the sep string as a whole:

>>> lines = open("/proc/net/dev").readlines()
>>> for l in lines[2:]:
>>>     cols = l.split(string.whitespace + ":")
>>>     print len(cols)
1

Which should be returning 17, as explained above.

Is there a Python equivalent to sscanf (not RE), or a string splitting function in the standard library that splits on any of a range of characters that I'm not aware of?

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8
  • Is there any reason you are insisting on "not RE"? Regexes are the perfect tool for this job. Commented Feb 1, 2010 at 6:46
  • 8
    If you want to program in C, why not program in C? If you want to program in python, use a regular expression. There's even a helpful hint in the documentation for the re module telling you how to convert scanf formats into regular expressions. docs.python.org/library/re.html#simulating-scanf Commented Feb 1, 2010 at 7:47
  • 9
    @Paul, the last bit would have made a great answer. Commented Feb 1, 2010 at 10:45
  • @MattJoiner, I think it would be better to request/disallow features than to request/disallow implementations. "I would like to have format strings that specify the type of the output variable, to have the types converted for me, and to assert specific formatting of the input string" rather than "not regex" explains why you have this preference. After all, if someone used regex to build what you wanted, you'd use it, wouldn't you? Commented Nov 13, 2015 at 14:43
  • @interestinglythere: wat Commented Nov 14, 2015 at 2:27

9 Answers 9

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103

There is also the parse module.

parse() is designed to be the opposite of format() (the newer string formatting function in Python 2.6 and higher).

>>> from parse import parse
>>> parse('{} fish', '1')
>>> parse('{} fish', '1 fish')
<Result ('1',) {}>
>>> parse('{} fish', '2 fish')
<Result ('2',) {}>
>>> parse('{} fish', 'red fish')
<Result ('red',) {}>
>>> parse('{} fish', 'blue fish')
<Result ('blue',) {}>
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2 Comments

This solution is clean and clear, but you need to install parse package.
If this functionality is not present out of the box, then that's obviously not the best answer. Python developers did not get the power of sprintf / sscanf ?
78

When I'm in a C mood, I usually use zip and list comprehensions for scanf-like behavior. Like this:

input = '1 3.0 false hello'
(a, b, c, d) = [t(s) for t,s in zip((int,float,strtobool,str),input.split())]
print (a, b, c, d)

Note that for more complex format strings, you do need to use regular expressions:

import re
input = '1:3.0 false,hello'
(a, b, c, d) = [t(s) for t,s in zip((int,float,strtobool,str),re.search('^(\d+):([\d.]+) (\w+),(\w+)$',input).groups())]
print (a, b, c, d)

Note also that you need conversion functions for all types you want to convert. For example, above I used something like:

strtobool = lambda s: {'true': True, 'false': False}[s]
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5 Comments

I really like this approach, especially as my problem was not just a need for scanf, but sscanf.
This appeared to be a good solution; sadly bool("false") returns True, because only empty strings evaluate to False. However, all is not lost, you could replace bool with a custom function which behaves the way you'd like.
@Aky Nice catch! I fixed my answer.
@rookiepig t(s) gets replaced by int(substring1), float(substring2), strtobool(substring3), and str(substring4), in order.
Thanks for actually addressing the type conversion and not just the string-splitting
38

Python doesn't have an sscanf equivalent built-in, and most of the time it actually makes a whole lot more sense to parse the input by working with the string directly, using regexps, or using a parsing tool.

Probably mostly useful for translating C, people have implemented sscanf, such as in this module: http://hkn.eecs.berkeley.edu/~dyoo/python/scanf/

In this particular case if you just want to split the data based on multiple split characters, re.split is really the right tool.

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4 Comments

i did say no re, but you justify it nicely
here's a py3k version of the linked implementation: gist.github.com/3875529
Its not built in, but there is a library for it here pypi.org/project/scanf
"most of the time it actually makes a whole lot more sense to parse the input by working with the string directly, using regexps, or using a parsing tool." This is a false statement. In most cases it makes sense to use (s-)scanf. I do not know about python2, but in python3 they have realized it already.
25

You can split on a range of characters using the re module.

>>> import re
>>> r = re.compile('[ \t\n\r:]+')
>>> r.split("abc:def  ghi")
['abc', 'def', 'ghi']
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4 Comments

it is not a funny to deal with regex on textual float representation
@ZAB: Nothing funny here. You use the regular expression to split fields, and then you use float() to parse it.
for this speciefic problem, to parse /proc/net/*, this ugly trick will work though
Or, even better, r = re.compile(r'[\s:]+'). (It's a good habit to put regular expressions in raw strings I think, even though it doesn't make any difference in this case.)
16

You can parse with module re using named groups. It won't parse the substrings to their actual datatypes (e.g. int) but it's very convenient when parsing strings.

Given this sample line from /proc/net/tcp:

line="   0: 00000000:0203 00000000:0000 0A 00000000:00000000 00:00000000 00000000     0        0 335 1 c1674320 300 0 0 0"

An example mimicking your sscanf example with the variable could be:

import re
hex_digit_pattern = r"[\dA-Fa-f]"
pat = r"\d+: " + \
      r"(?P<local_addr>HEX+):(?P<local_port>HEX+) " + \
      r"(?P<rem_addr>HEX+):(?P<rem_port>HEX+) " + \
      r"HEX+ HEX+:HEX+ HEX+:HEX+ HEX+ +\d+ +\d+ " + \
      r"(?P<inode>\d+)"
pat = pat.replace("HEX", hex_digit_pattern)

values = re.search(pat, line).groupdict()

import pprint; pprint values
# prints:
# {'inode': '335',
#  'local_addr': '00000000',
#  'local_port': '0203',
#  'rem_addr': '00000000',
#  'rem_port': '0000'}
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2

There is an example in the official python docs about how to use sscanf from libc:

# import libc
from ctypes import CDLL
if(os.name=="nt"):
    libc = cdll.msvcrt 
else:
    # assuming Unix-like environment
    libc = cdll.LoadLibrary("libc.so.6")
    libc = CDLL("libc.so.6")  # alternative

# allocate vars
i = c_int()
f = c_float()
s = create_string_buffer(b'\000' * 32)

# parse with sscanf
libc.sscanf(b"1 3.14 Hello", "%d %f %s", byref(i), byref(f), s)

# read the parsed values
i.value  # 1
f.value  # 3.14
s.value # b'Hello'
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1 Comment

replace from ctypes import CDLL with from ctypes import cdll, c_int, c_float, create_string_buffer, byref or from ctypes import *
1

you can turn the ":" to space, and do the split.eg

>>> f=open("/proc/net/dev")
>>> for line in f:
...     line=line.replace(":"," ").split()
...     print len(line)

no regex needed (for this case)

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1 Comment

You'd still have to verify that the original string was correct - for example, "abc def ghi" would parse the same as "abc:def:ghi". This distinction may matter.
1

You could install pandas and use pandas.read_fwf for fixed width format files. Example using /proc/net/arp:

In [230]: df = pandas.read_fwf("/proc/net/arp")

In [231]: print(df)
       IP address HW type Flags         HW address Mask Device
0   141.38.28.115     0x1   0x2  84:2b:2b:ad:e1:f4    *   eth0
1   141.38.28.203     0x1   0x2  c4:34:6b:5b:e4:7d    *   eth0
2   141.38.28.140     0x1   0x2  00:19:99:ce:00:19    *   eth0
3   141.38.28.202     0x1   0x2  90:1b:0e:14:a1:e3    *   eth0
4    141.38.28.17     0x1   0x2  90:1b:0e:1a:4b:41    *   eth0
5    141.38.28.60     0x1   0x2  00:19:99:cc:aa:58    *   eth0
6   141.38.28.233     0x1   0x2  90:1b:0e:8d:7a:c9    *   eth0
7    141.38.28.55     0x1   0x2  00:19:99:cc:ab:00    *   eth0
8   141.38.28.224     0x1   0x2  90:1b:0e:8d:7a:e2    *   eth0
9   141.38.28.148     0x1   0x0  4c:52:62:a8:08:2c    *   eth0
10  141.38.28.179     0x1   0x2  90:1b:0e:1a:4b:50    *   eth0

In [232]: df["HW address"]
Out[232]:
0     84:2b:2b:ad:e1:f4
1     c4:34:6b:5b:e4:7d
2     00:19:99:ce:00:19
3     90:1b:0e:14:a1:e3
4     90:1b:0e:1a:4b:41
5     00:19:99:cc:aa:58
6     90:1b:0e:8d:7a:c9
7     00:19:99:cc:ab:00
8     90:1b:0e:8d:7a:e2
9     4c:52:62:a8:08:2c
10    90:1b:0e:1a:4b:50

In [233]: df["HW address"][5]
Out[233]: '00:19:99:cc:aa:58'

By default it tries to figure out the format automagically, but there are options you can give for more explicit instructions (see documentation). There are also other IO routines in pandas that are powerful for other file formats.

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-2

If the separators are ':', you can split on ':', and then use x.strip() on the strings to get rid of any leading or trailing whitespace. int() will ignore the spaces.

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