Simple yet flexible natural sorting in Python.
- Source Code: https://github.com/SethMMorton/natsort
- Downloads: https://pypi.org/project/natsort/
- Documentation: https://natsort.readthedocs.io/
- Quick Description
- Quick Examples
- FAQ
- Requirements
- Optional Dependencies
- Installation
- How to Run Tests
- How to Build Documentation
- Dropped Deprecated APIs
- History
NOTE: Please see the Dropped Deprecated APIs section for changes.
When you try to sort a list of strings that contain numbers, the normal python sort algorithm sorts lexicographically, so you might not get the results that you expect:
>>> 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']
Notice that it has the order ('1', '10', '2') - this is because the list is being sorted in lexicographical order, which sorts numbers like you would letters (i.e. 'b', 'ba', 'c').
natsort
provides a function natsorted
that helps sort lists
"naturally" ("naturally" is rather ill-defined, but in general it means
sorting based on meaning and not computer code point).
Using natsorted
is simple:
>>> from natsort import natsorted
>>> a = ['2 ft 7 in', '1 ft 5 in', '10 ft 2 in', '2 ft 11 in', '7 ft 6 in']
>>> natsorted(a)
['1 ft 5 in', '2 ft 7 in', '2 ft 11 in', '7 ft 6 in', '10 ft 2 in']
natsorted
identifies numbers anywhere in a string and sorts them
naturally. Below are some other things you can do with natsort
(also see the examples
for a quick start guide, or the
api for complete details).
Note: natsorted
is designed to be a drop-in replacement for the
built-in sorted
function. Like sorted
, natsorted
does not sort in-place. To sort a list and assign the output to the same
variable, you must explicitly assign the output to a variable:
>>> a = ['2 ft 7 in', '1 ft 5 in', '10 ft 2 in', '2 ft 11 in', '7 ft 6 in']
>>> natsorted(a)
['1 ft 5 in', '2 ft 7 in', '2 ft 11 in', '7 ft 6 in', '10 ft 2 in']
>>> print(a) # 'a' was not sorted; "natsorted" simply returned a sorted list
['2 ft 7 in', '1 ft 5 in', '10 ft 2 in', '2 ft 11 in', '7 ft 6 in']
>>> a = natsorted(a) # Now 'a' will be sorted because the sorted list was assigned to 'a'
>>> print(a)
['1 ft 5 in', '2 ft 7 in', '2 ft 11 in', '7 ft 6 in', '10 ft 2 in']
Please see Generating a Reusable Sorting Key and Sorting In-Place for an alternate way to sort in-place naturally.
- Sorting Versions
- Sort Paths Like My File Browser (e.g. Windows Explorer on Windows)
- Sorting by Real Numbers (i.e. Signed Floats)
- Locale-Aware Sorting (or "Human Sorting")
- Further Customizing Natsort
- Sorting Mixed Types
- Handling Bytes
- Generating a Reusable Sorting Key and Sorting In-Place
- Other Useful Things
natsort
does not actually comprehend version numbers.
It just so happens that the most common versioning schemes are designed to
work with standard natural sorting techniques; these schemes include
MAJOR.MINOR
, MAJOR.MINOR.PATCH
, YEAR.MONTH.DAY
. If your data
conforms to a scheme like this, then it will work out-of-the-box with
natsorted
(as of natsort
version >= 4.0.0):
>>> a = ['version-1.9', 'version-2.0', 'version-1.11', 'version-1.10']
>>> natsorted(a)
['version-1.9', 'version-1.10', 'version-1.11', 'version-2.0']
If you need to versions that use a more complicated scheme, please see these examples.
Prior to natsort
version 7.1.0, it was a common request to be able to
sort paths like Windows Explorer. As of natsort
7.1.0, the function
os_sorted
has been added to provide users the ability to sort
in the order that their file browser might sort (e.g Windows Explorer on
Windows, Finder on MacOS, Dolphin/Nautilus/Thunar/etc. on Linux).
import os
from natsort import os_sorted
print(os_sorted(os.listdir()))
# The directory sorted like your file browser might show
Output will be different depending on the operating system you are on.
For users not on Windows (e.g. MacOS/Linux) it is strongly recommended
to also install PyICU, which will help
natsort
give results that match most file browsers. If this is not installed,
it will fall back on Python's built-in locale
module and will give good
results for most input, but will give poor results for special characters.
This is useful in scientific data analysis (and was
the default behavior of natsorted
for natsort
version < 4.0.0). Use the realsorted
function:
>>> from natsort import realsorted, ns
>>> # Note that when interpreting as signed floats, the below numbers are
>>> # +5.10, -3.00, +5.30, +2.00
>>> a = ['position5.10.data', 'position-3.data', 'position5.3.data', 'position2.data']
>>> natsorted(a)
['position2.data', 'position5.3.data', 'position5.10.data', 'position-3.data']
>>> natsorted(a, alg=ns.REAL)
['position-3.data', 'position2.data', 'position5.10.data', 'position5.3.data']
>>> realsorted(a) # shortcut for natsorted with alg=ns.REAL
['position-3.data', 'position2.data', 'position5.10.data', 'position5.3.data']
This is where the non-numeric characters are also ordered based on their
meaning, not on their ordinal value, and a locale-dependent thousands
separator and decimal separator is accounted for in the number.
This can be achieved with the humansorted
function:
>>> a = ['Apple', 'apple15', 'Banana', 'apple14,689', 'banana']
>>> natsorted(a)
['Apple', 'Banana', 'apple14,689', 'apple15', 'banana']
>>> import locale
>>> locale.setlocale(locale.LC_ALL, 'en_US.UTF-8')
'en_US.UTF-8'
>>> natsorted(a, alg=ns.LOCALE)
['apple15', 'apple14,689', 'Apple', 'banana', 'Banana']
>>> from natsort import humansorted
>>> humansorted(a) # shortcut for natsorted with alg=ns.LOCALE
['apple15', 'apple14,689', 'Apple', 'banana', 'Banana']
You may find you need to explicitly set the locale to get this to work
(as shown in the example).
Please see locale issues and the
Optional Dependencies section below before using the humansorted
function.
If you need to combine multiple algorithm modifiers (such as ns.REAL
,
ns.LOCALE
, and ns.IGNORECASE
), you can combine the options using the
bitwise OR operator (|
). For example,
>>> a = ['Apple', 'apple15', 'Banana', 'apple14,689', 'banana']
>>> natsorted(a, alg=ns.REAL | ns.LOCALE | ns.IGNORECASE)
['Apple', 'apple15', 'apple14,689', 'Banana', 'banana']
>>> # The ns enum provides long and short forms for each option.
>>> ns.LOCALE == ns.L
True
>>> # You can also customize the convenience functions, too.
>>> natsorted(a, alg=ns.REAL | ns.LOCALE | ns.IGNORECASE) == realsorted(a, alg=ns.L | ns.IC)
True
>>> natsorted(a, alg=ns.REAL | ns.LOCALE | ns.IGNORECASE) == humansorted(a, alg=ns.R | ns.IC)
True
All of the available customizations can be found in the documentation for the ns enum.
You can also add your own custom transformation functions with the key
argument. These can be used with alg
if you wish.
>>> a = ['apple2.50', '2.3apple']
>>> natsorted(a, key=lambda x: x.replace('apple', ''), alg=ns.REAL)
['2.3apple', 'apple2.50']
You can mix and match int
, float
, and str
(or unicode
) types
when you sort:
>>> a = ['4.5', 6, 2.0, '5', 'a']
>>> natsorted(a)
[2.0, '4.5', '5', 6, 'a']
>>> # sorted(a) would raise an "unorderable types" TypeError
natsort
does not officially support the bytes type, but
convenience functions are provided that help you decode to str first:
>>> from natsort import as_utf8
>>> a = [b'a', 14.0, 'b']
>>> # natsorted(a) would raise a TypeError (bytes() < str())
>>> natsorted(a, key=as_utf8) == [14.0, b'a', 'b']
True
>>> a = [b'a56', b'a5', b'a6', b'a40']
>>> # natsorted(a) would return the same results as sorted(a)
>>> natsorted(a, key=as_utf8) == [b'a5', b'a6', b'a40', b'a56']
True
Under the hood, natsorted
works by generating a custom sorting
key using natsort_keygen
and then passes that to the built-in
sorted
. You can use the natsort_keygen
function yourself to
generate a custom sorting key to sort in-place using the list.sort
method.
>>> from natsort import natsort_keygen
>>> natsort_key = natsort_keygen()
>>> a = ['2 ft 7 in', '1 ft 5 in', '10 ft 2 in', '2 ft 11 in', '7 ft 6 in']
>>> natsorted(a) == sorted(a, key=natsort_key)
True
>>> a.sort(key=natsort_key)
>>> a
['1 ft 5 in', '2 ft 7 in', '2 ft 11 in', '7 ft 6 in', '10 ft 2 in']
All of the algorithm customizations mentioned in the
Further Customizing Natsort section can also be applied to
natsort_keygen
through the alg keyword option.
- recursively descend into lists of lists
- automatic unicode normalization of input data
- controlling the case-sensitivity
- sorting file paths correctly
- allow custom sorting keys
- accounting for units
- How do I debug
natsort.natsorted()
? The best way to debug
natsorted()
is to generate a key usingnatsort_keygen()
with the same options being passed tonatsorted
. One can take a look at exactly what is being done with their input using this key - it is highly recommended to look at this issue describing how to debug for how to debug, and also to review the How Does Natsort Work? page for whynatsort
is doing that to your data.If you are trying to sort custom classes and running into trouble, please take a look at SethMMorton#60. In short, custom classes are not likely to be sorted correctly if one relies on the behavior of
__lt__
and the other rich comparison operators in their custom class - it is better to use akey
function withnatsort
, or use thenatsort
key as part of your rich comparison operator definition.natsort
gave me results I didn't expect, and it's a terrible library!- Did you try to debug using the above advice? If so, and you still cannot figure out the error, then please file an issue.
- How does
natsort
work? If you don't want to read How Does Natsort Work?, here is a quick primer.
natsort
provides a key function that can be passed to list.sort() or sorted() in order to modify the default sorting behavior. This key is generated on-demand with the key generatornatsort.natsort_keygen()
.natsort.natsorted()
is essentially a wrapper for the following code:>>> from natsort import natsort_keygen >>> natsort_key = natsort_keygen() >>> sorted(['1', '10', '2'], key=natsort_key) ['1', '2', '10']
Users can further customize
natsort
sorting behavior with thekey
and/oralg
options (see details in the Further Customizing Natsort section).The key generated by
natsort_keygen
always returns atuple
. It does so in the following way (some details omitted for clarity):- Assume the input is a string, and attempt to split it into numbers and
non-numbers using regular expressions. Numbers are then converted into
either
int
orfloat
. - If the above fails because the input is not a string, assume the input
is some other sequence (e.g.
list
ortuple
), and recursively apply the key to each element of the sequence. - If the above fails because the input is not iterable, assume the input
is an
int
orfloat
, and just return the input in atuple
.
Because a
tuple
is always returned, aTypeError
should not be common unless one tries to do something odd like sort anint
against alist
.- Assume the input is a string, and attempt to split it into numbers and
non-numbers using regular expressions. Numbers are then converted into
either
natsort
comes with a shell script called natsort
, or can also be called
from the command line with python -m natsort
.
natsort
requires Python 3.6 or greater.
The most efficient sorting can occur if you install the
fastnumbers package
(version >=2.0.0); it helps with the string to number conversions.
natsort
will still run (efficiently) without the package, but if you need
to squeeze out that extra juice it is recommended you include this as a
dependency. natsort
will not require (or check) that
fastnumbers is installed
at installation.
It is recommended that you install PyICU if you wish to sort in a locale-dependent manner, see https://natsort.readthedocs.io/en/master/locale_issues.html for an explanation why.
Use pip
!
$ pip install natsort
If you want to install the Optional Dependencies, you can use the
"extras" notation
at installation time to install those dependencies as well - use fast
for
fastnumbers and icu
for
PyICU.
# Install both optional dependencies.
$ pip install natsort[fast,icu]
# Install just fastnumbers
$ pip install natsort[fast]
Please note that natsort
is NOT set-up to support python setup.py test
.
The recommended way to run tests is with tox.
After installing tox
, running tests is as simple as executing the following
in the natsort
directory:
$ tox
tox
will create virtual a virtual environment for your tests and install
all the needed testing requirements for you. You can specify a particular
python version with the -e
flag, e.g. tox -e py36
. Static analysis
is done with tox -e flake8
. You can see all available testing environments
with tox --listenvs
.
If you want to build the documentation for natsort
, it is recommended to
use tox
:
$ tox -e docs
This will place the documentation in build/sphinx/html
.
In natsort
version 6.0.0, the following APIs and functions were removed
number_type
keyword argument (deprecated since 3.4.0)signed
keyword argument (deprecated since 3.4.0)exp
keyword argument (deprecated since 3.4.0)as_path
keyword argument (deprecated since 3.4.0)py3_safe
keyword argument (deprecated since 3.4.0)ns.TYPESAFE
(deprecated since version 5.0.0)ns.DIGIT
(deprecated since version 5.0.0)ns.VERSION
(deprecated since version 5.0.0)versorted()
(discouraged since version 4.0.0, officially deprecated since version 5.5.0)index_versorted()
(discouraged since version 4.0.0, officially deprecated since version 5.5.0)
In general, if you want to determine if you are using deprecated APIs you can run your code with the following flag
$ python -Wdefault::DeprecationWarning my-code.py
By default DeprecationWarnings
are not shown, but this will cause them
to be shown. Alternatively, you can just set the environment variable
PYTHONWARNINGS
to "default::DeprecationWarning" and then run your code.
Seth M. Morton
Please visit the changelog on GitHub or in the documentation.