2. Examples and Recipes¶
If you want more detailed examples than given on this page, please see https://github.com/SethMMorton/natsort/tree/master/tests.
- Basic Usage
- Sort Version Numbers
- Sort OS-Generated Paths
- Locale-Aware Sorting (Human Sorting)
- Controlling Case When Sorting
- Customizing Float Definition
- Using a Custom Sorting Key
- Generating a Natsort Key
- Sorting Multiple Lists According to a Single List
- Returning Results in Reverse Order
- Sorting Bytes on Python 3
- Sorting a Pandas DataFrame
2.1. Basic Usage¶
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']
2.2. Sort Version Numbers¶
As of natsort
version >= 4.0.0, natsorted()
will work for
well-behaved version numbers, like MAJOR.MINOR.PATCH
.
2.2.1. Sorting More Expressive Versioning Schemes¶
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.
2.2.1.1. Sorting Rigorously Defined Versioning Schemes (e.g. SemVer or PEP 440)¶
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']
2.3. Sort OS-Generated Paths¶
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']
2.4. Locale-Aware Sorting (Human Sorting)¶
Note
Please read Possible Issues with humansorted() or ns.LOCALE 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.
2.5. Controlling Case When Sorting¶
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']
2.6. Customizing Float Definition¶
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.']
2.7. Using a Custom Sorting Key¶
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')]
2.7.1. Accounting for Units When Sorting¶
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']
2.8. Generating a Natsort Key¶
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).
2.9. Sorting Multiple Lists According to a Single List¶
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']
2.10. Returning Results in Reverse Order¶
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']
2.11. Sorting Bytes on Python 3¶
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 Help With Bytes On Python 3) 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)
[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
2.12. Sorting a Pandas DataFrame¶
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
.