py
natsort
If you want more detailed examples than given on this page, please see https://github.com/SethMMorton/natsort/tree/master/tests.
In the most basic use case, simply import ~natsorted
and use it as you would sorted
:
>>> a = ['2 ft 7 in', '1 ft 5 in', '10 ft 2 in', '2 ft 11 in', '7 ft 6 in']
>>> sorted(a)
['1 ft 5 in', '10 ft 2 in', '2 ft 11 in', '2 ft 7 in', '7 ft 6 in']
>>> from natsort import natsorted, ns
>>> natsorted(a)
['1 ft 5 in', '2 ft 7 in', '2 ft 11 in', '7 ft 6 in', '10 ft 2 in']
As of natsort
version >= 4.0.0, ~natsorted
will work for well-behaved version numbers, like MAJOR.MINOR.PATCH
.
By default, if you wish to sort versions that are not as simple as MAJOR.MINOR.PATCH
(or similar), you may not get the results you expect:
>>> a = ['1.2', '1.2rc1', '1.2beta2', '1.2beta1', '1.2alpha', '1.2.1', '1.1', '1.3']
>>> natsorted(a)
['1.1', '1.2', '1.2.1', '1.2alpha', '1.2beta1', '1.2beta2', '1.2rc1', '1.3']
To make the '1.2' pre-releases come before '1.2.1', you need to use the following recipe:
>>> natsorted(a, key=lambda x: x.replace('.', '~'))
['1.1', '1.2', '1.2alpha', '1.2beta1', '1.2beta2', '1.2rc1', '1.2.1', '1.3']
If you also want '1.2' after all the alpha, beta, and rc candidates, you can modify the above recipe:
>>> natsorted(a, key=lambda x: x.replace('.', '~')+'z')
['1.1', '1.2alpha', '1.2beta1', '1.2beta2', '1.2rc1', '1.2', '1.2.1', '1.3']
Please see this issue to see why this works.
If you know you are using a versioning scheme that follows a well-defined format for which there is third-party module support, you should use those modules to assist in sorting. Some examples might be PEP 440 or SemVer.
If we are being honest, using these methods to parse a version means you don't need to use natsort
- you should probably just use sorted
directly. Here's an example with SemVer:
>>> from semver import VersionInfo
>>> a = ['3.4.5-pre.1', '3.4.5', '3.4.5-pre.2+build.4']
>>> sorted(a, key=VersionInfo.parse)
['3.4.5-pre.1', '3.4.5-pre.2+build.4', '3.4.5']
In some cases when sorting file paths with OS-Generated names, the default ~natsorted
algorithm may not be sufficient. In cases like these, you may need to use the ns.PATH
option:
>>> a = ['./folder/file (1).txt',
... './folder/file.txt',
... './folder (1)/file.txt',
... './folder (10)/file.txt']
>>> natsorted(a)
['./folder (1)/file.txt', './folder (10)/file.txt', './folder/file (1).txt', './folder/file.txt']
>>> natsorted(a, alg=ns.PATH)
['./folder/file.txt', './folder/file (1).txt', './folder (1)/file.txt', './folder (10)/file.txt']
Note
Please read locale_issues
before using ns.LOCALE
, humansorted
, or index_humansorted
.
You can instruct natsort
to use locale-aware sorting with the ns.LOCALE
option. In addition to making this understand non-ASCII characters, it will also properly interpret non-'.' decimal separators and also properly order case. It may be more convenient to just use the humansorted
function:
>>> from natsort import humansorted
>>> import locale
>>> locale.setlocale(locale.LC_ALL, 'en_US.UTF-8')
'en_US.UTF-8'
>>> a = ['Apple', 'corn', 'Corn', 'Banana', 'apple', 'banana']
>>> natsorted(a, alg=ns.LOCALE)
['apple', 'Apple', 'banana', 'Banana', 'corn', 'Corn']
>>> humansorted(a)
['apple', 'Apple', 'banana', 'Banana', 'corn', 'Corn']
You may find that if you do not explicitly set the locale your results may not be as you expect... I have found that it depends on the system you are on. If you use PyICU (see below) then you should not need to do this.
For non-numbers, by default natsort
used ordinal sorting (i.e. it sorts by the character's value in the ASCII table). For example:
>>> a = ['Apple', 'corn', 'Corn', 'Banana', 'apple', 'banana']
>>> natsorted(a)
['Apple', 'Banana', 'Corn', 'apple', 'banana', 'corn']
There are times when you wish to ignore the case when sorting, you can easily do this with the ns.IGNORECASE
option:
>>> natsorted(a, alg=ns.IGNORECASE)
['Apple', 'apple', 'Banana', 'banana', 'corn', 'Corn']
Note thats since Python's sorting is stable, the order of equivalent elements after lowering the case is the same order they appear in the original list.
Upper-case letters appear first in the ASCII table, but many natural sorting methods place lower-case first. To do this, use ns.LOWERCASEFIRST
:
>>> natsorted(a, alg=ns.LOWERCASEFIRST)
['apple', 'banana', 'corn', 'Apple', 'Banana', 'Corn']
It may be undesirable to have the upper-case letters grouped together and the lower-case letters grouped together; most would expect all "a"s to bet together regardless of case, and all "b"s, and so on. To achieve this, use ns.GROUPLETTERS
:
>>> natsorted(a, alg=ns.GROUPLETTERS)
['Apple', 'apple', 'Banana', 'banana', 'Corn', 'corn']
You might combine this with ns.LOWERCASEFIRST
to get what most would expect to be "natural" sorting:
>>> natsorted(a, alg=ns.G | ns.LF)
['apple', 'Apple', 'banana', 'Banana', 'corn', 'Corn']
You can make ~natsorted
search for any float that would be a valid Python float literal, such as 5, 0.4, -4.78, +4.2E-34, etc. using the ns.FLOAT
key. You can disable the exponential component of the number with ns.NOEXP
.
>>> a = ['a50', 'a51.', 'a+50.4', 'a5.034e1', 'a+50.300']
>>> natsorted(a, alg=ns.FLOAT)
['a50', 'a5.034e1', 'a51.', 'a+50.300', 'a+50.4']
>>> natsorted(a, alg=ns.FLOAT | ns.SIGNED)
['a50', 'a+50.300', 'a5.034e1', 'a+50.4', 'a51.']
>>> natsorted(a, alg=ns.FLOAT | ns.SIGNED | ns.NOEXP)
['a5.034e1', 'a50', 'a+50.300', 'a+50.4', 'a51.']
For convenience, the ns.REAL
option is provided which is a shortcut for ns.FLOAT | ns.SIGNED
and can be used to sort on real numbers. This can be easily accessed with the ~realsorted
convenience function. Please note that the behavior of the ~realsorted
function was the default behavior of ~natsorted
for natsort
version < 4.0.0:
>>> natsorted(a, alg=ns.REAL)
['a50', 'a+50.300', 'a5.034e1', 'a+50.4', 'a51.']
>>> from natsort import realsorted
>>> realsorted(a)
['a50', 'a+50.300', 'a5.034e1', 'a+50.4', 'a51.']
Like the built-in sorted
function, natsorted
can accept a custom sort key so that:
>>> from operator import attrgetter, itemgetter
>>> a = [['a', 'num4'], ['b', 'num8'], ['c', 'num2']]
>>> natsorted(a, key=itemgetter(1))
[['c', 'num2'], ['a', 'num4'], ['b', 'num8']]
>>> class Foo:
... def __init__(self, bar):
... self.bar = bar
... def __repr__(self):
... return "Foo('{}')".format(self.bar)
>>> b = [Foo('num3'), Foo('num5'), Foo('num2')]
>>> natsorted(b, key=attrgetter('bar'))
[Foo('num2'), Foo('num3'), Foo('num5')]
natsort
does not come with any pre-built mechanism to sort units, but you can write your own key to do this. Below, I will demonstrate sorting imperial lengths (e.g. feet an inches), but of course you can extend this to any set of units you need. This example is based on code from this issue, and uses the function natsort.numeric_regex_chooser
to build a regular expression that will parse numbers in the same manner as natsort
itself.
>>> import re
>>> import natsort
>>>
>>> # Define how each unit will be transformed
>>> conversion_mapping = {
... "in": 1,
... "inch": 1,
... "inches": 1,
... "ft": 12,
... "feet": 12,
... "foot": 12,
... }
>>>
>>> # This regular expression searches for numbers and units
>>> all_units = "|".join(conversion_mapping.keys())
>>> float_re = natsort.numeric_regex_chooser(natsort.FLOAT | natsort.SIGNED)
>>> unit_finder = re.compile(r"({})\s*({})".format(float_re, all_units), re.IGNORECASE)
>>>
>>> def unit_replacer(matchobj):
... """
... Given a regex match object, return a replacement string where units are modified
... """
... number = matchobj.group(1)
... unit = matchobj.group(2)
... new_number = float(number) * conversion_mapping[unit]
... return "{} in".format(new_number)
...
>>> # Demo time!
>>> data = ['1 ft', '5 in', '10 ft', '2 in']
>>> [unit_finder.sub(unit_replacer, x) for x in data]
['12.0 in', '5.0 in', '120.0 in', '2.0 in']
>>>
>>> natsort.natsorted(data, key=lambda x: unit_finder.sub(unit_replacer, x))
['2 in', '5 in', '1 ft', '10 ft']
If you need to sort a list in-place, you cannot use ~natsorted
; you need to pass a key to the list.sort
method. The function ~natsort_keygen
is a convenient way to generate these keys for you:
>>> from natsort import natsort_keygen
>>> a = ['a50', 'a51.', 'a50.4', 'a5.034e1', 'a50.300']
>>> natsort_key = natsort_keygen(alg=ns.FLOAT)
>>> a.sort(key=natsort_key)
>>> a
['a50', 'a50.300', 'a5.034e1', 'a50.4', 'a51.']
~natsort_keygen
has the same API as ~natsorted
(minus the reverse option).
Sometimes you have multiple lists, and you want to sort one of those lists and reorder the other lists according to how the first was sorted. To achieve this you could use the ~index_natsorted
in combination with the convenience function ~order_by_index
:
>>> from natsort import index_natsorted, order_by_index
>>> a = ['a2', 'a9', 'a1', 'a4', 'a10']
>>> b = [4, 5, 6, 7, 8]
>>> c = ['hi', 'lo', 'ah', 'do', 'up']
>>> index = index_natsorted(a)
>>> order_by_index(a, index)
['a1', 'a2', 'a4', 'a9', 'a10']
>>> order_by_index(b, index)
[6, 4, 7, 5, 8]
>>> order_by_index(c, index)
['ah', 'hi', 'do', 'lo', 'up']
Just like the sorted
built-in function, you can supply the reverse
option to return the results in reverse order:
>>> a = ['a2', 'a9', 'a1', 'a4', 'a10']
>>> natsorted(a, reverse=True)
['a10', 'a9', 'a4', 'a2', 'a1']
Python 3 is rather strict about comparing strings and bytes, and this can make it difficult to deal with collections of both. Because of the challenge of guessing which encoding should be used to decode a bytes array to a string, natsort
does not try to guess and automatically convert for you; in fact, the official stance of natsort
is to not support sorting bytes. Instead, some decoding convenience functions have been provided to you (see bytes_help
) that allow you to provide a codec for decoding bytes through the key
argument that will allow natsort
to convert byte arrays to strings for sorting; these functions know not to raise an error if the input is not a byte array, so you can use the key on any arbitrary collection of data.
>>> from natsort import as_ascii
>>> a = [b'a', 14.0, 'b']
>>> # On Python 2, natsorted(a) would would work as expected.
>>> # On Python 3, natsorted(a) would raise a TypeError (bytes() < str())
>>> natsorted(a, key=as_ascii) == [14.0, b'a', 'b']
True
Additionally, regular expressions cannot be run on byte arrays, making it so that natsort
cannot parse them for numbers. As a result, if you run natsort
on a list of bytes, you will get results that are like Python's default sorting behavior. Of course, you can use the decoding functions to solve this:
>>> from natsort import as_utf8
>>> a = [b'a56', b'a5', b'a6', b'a40']
>>> natsorted(a) # doctest: +SKIP
[b'a40', b'a5', b'a56', b'a6']
>>> natsorted(a, key=as_utf8) == [b'a5', b'a6', b'a40', b'a56']
True
If you need a codec different from ASCII or UTF-8, you can use decoder
to generate a custom key:
>>> from natsort import decoder
>>> a = [b'a56', b'a5', b'a6', b'a40']
>>> natsorted(a, key=decoder('latin1')) == [b'a5', b'a6', b'a40', b'a56']
True
Starting from Pandas version 1.1.0, the sorting methods accept a "key" argument, so you can simply pass natsort_keygen
to the sorting methods and sort:
import pandas as pd
from natsort import natsort_keygen
s = pd.Series(['2 ft 7 in', '1 ft 5 in', '10 ft 2 in', '2 ft 11 in', '7 ft 6 in'])
s.sort_values(key=natsort_keygen())
# 1 1 ft 5 in
# 0 2 ft 7 in
# 3 2 ft 11 in
# 4 7 ft 6 in
# 2 10 ft 2 in
# dtype: object
Similarly, if you need to sort the index there is sort_index of a DataFrame.
If you are on an older version of Pandas, check out please check out this answer on StackOverflow for ways to do this without the key
argument to sort_values
.