Plum: Multiple Dispatch in Python

Everybody likes multiple dispatch, just like everybody likes plums.

The design philosophy of Plum is to provide an implementation of multiple dispatch that is Pythonic, yet close to how Julia does it. See here for a comparison between Plum, multipledispatch, and multimethod.

Note: Plum 2 is now powered by Beartype! If you notice any issues with the new release, please open an issue.

Installation

Plum requires Python 3.8 or higher.

pip install plum-dispatch

Documentation

See here.

What's This?

Plum brings your type annotations to life:

from numbers import Number

from plum import dispatch


@dispatch
def f(x: str):
    return "This is a string!"


@dispatch
def f(x: int):
    return "This is an integer!"


@dispatch
def f(x: Number):
    return "This is a general number, but I don't know which type."

>>> f("1")
'This is a string!'

>>> f(1)
'This is an integer!'

>>> f(1.0)
'This is a number, but I don't know which type.'

>>> f(object())
NotFoundLookupError: `f(<object object at 0x7fd3b01cd330>)` could not be resolved.

Closest candidates are the following:
    f(x: str)
        <function f at 0x7fd400644ee0> @ /<ipython-input-2-c9f6cdbea9f3>:6
    f(x: int)
        <function f at 0x7fd3a0235ca0> @ /<ipython-input-2-c9f6cdbea9f3>:11
    f(x: numbers.Number)
        <function f at 0x7fd3a0235d30> @ /<ipython-input-2-c9f6cdbea9f3>:16

This also works for multiple arguments, enabling some neat design patterns:

from numbers import Number, Real, Rational

from plum import dispatch


@dispatch
def multiply(x: Number, y: Number):
    return "Performing fallback implementation of multiplication..."


@dispatch
def multiply(x: Real, y: Real):
    return "Performing specialised implementation for reals..."


@dispatch
def multiply(x: Rational, y: Rational):
    return "Performing specialised implementation for rationals..."

>>> multiply(1, 1)
'Performing specialised implementation for rationals...'

>>> multiply(1.0, 1.0)
'Performing specialised implementation for reals...'

>>> multiply(1j, 1j)
'Performing fallback implementation of multiplication...'

>>> multiply(1, 1.0)  # For mixed types, it automatically chooses the right optimisation!
'Performing specialised implementation for reals...'

Metadata

Release files for plum-dispatch 2.3.6

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for plum-dispatch 2.3.6
File	Size	Uploaded
plum_dispatch-2.3.6.tar.gz	31.7 kB	May 12, 2024	Details

Built distribution (wheel)

Table of built distributions (wheels) for plum-dispatch 2.3.6
File	Interpreter	ABI	Platform	Reset
plum_dispatch-2.3.6-py3-none-any.whl 38.6 kB May 12, 2024	Python 3	none	any	Details

Total release size: 70.4 kB

Release files / plum_dispatch-2.3.6.tar.gz

Download URL	plum_dispatch-2.3.6.tar.gz
Size	31.7 kB
Tags	Source
SHA-256 checksum How to use checksums	`664e79003076aac754127fe9d667f43cf22e448a179d46ddfe298f18c012551d`
BLAKE2b-256 checksum How to use checksums	`cfbc22150aa5e6e15e07f329f0437da8104d1b6b479d03b3f65b28ed90a611f2`
Upload date	May 12, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/5.0.0 CPython/3.12.3`

Release files / plum_dispatch-2.3.6-py3-none-any.whl

Download URL	plum_dispatch-2.3.6-py3-none-any.whl
Size	38.6 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`ad0e6f1aa40f6b0bd286e0c24bc5928545095e61dc7b07d19455a7f3b064c907`
BLAKE2b-256 checksum How to use checksums	`02f6cd88bc72fbe08a84f99d9eafe4d29926b2c3fd29dfa49a7ad5b1d093f50c`
Upload date	May 12, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/5.0.0 CPython/3.12.3`