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 3.10 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 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

[!IMPORTANT] Dispatch, as implemented by Plum, is based on the positional arguments to a function. Keyword arguments are not used in the decision making for which method to call. In particular, this means that positional arguments without a default value must always be given as positional arguments!

Example:
from plum import dispatch

@dispatch
def f(x: int):
   return x

>>> f(1)        # OK
1

>> try: f(x=1)  # Not OK
... except Exception as e: print(f"{type(e).__name__}: {e}")
NotFoundLookupError: `f()` could not be resolved...

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...'

Projects Using Plum

The following projects are using Plum to do multiple dispatch! Would you like to add your project here? Please feel free to open a PR to add it to the list!

Coordinax implements coordinates in JAX.
fasttransform provides the main building block of data pipelines in fastai.
GPAR is an implementation of the Gaussian Process Autoregressive Model.
GPCM is an implementation of various Gaussian Process Convolution Models.
Galax does galactic and gravitational dynamics.
Geometric Kernels implements kernels on non-Euclidean spaces, such as Riemannian manifolds, graphs, and meshes.
LAB uses Plum to provide backend-agnostic linear algebra (something that works with PyTorch/TF/JAX/etc).
MLKernels implements standard kernels.
MMEval is a unified evaluation library for multiple machine learning libraries.
Matrix extends LAB and implements structured matrix types, such as low-rank matrices and Kronecker products.
NetKet, a library for machine learning with JAX/Flax targeted at quantum physics, uses Plum extensively to pick the right, efficient implementation for a large combination of objects that interact.
NeuralProcesses is a framework for composing Neural Processes.
OILMM is an implementation of the Orthogonal Linear Mixing Model.
PySAGES is a suite for advanced general ensemble simulations.
Quax implements multiple dispatch over abstract array types in JAX.
Unxt implements unitful quantities in JAX.
Varz uses Plum to provide backend-agnostic tools for non-linear optimisation.

See the docs for a comparison of Plum to other implementations of multiple dispatch.

Development Status
- 5 - Production/Stable
License
- OSI Approved :: MIT License
Operating System
- OS Independent
Programming Language
- Python :: 3
Typing
- Typed

Metadata

Development Status
- 5 - Production/Stable
License
- OSI Approved :: MIT License
Operating System
- OS Independent
Programming Language
- Python :: 3
Typing
- Typed

Release files for plum-dispatch 2.10.1

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Source distribution (sdist)

Source distribution for plum-dispatch 2.10.1
File	Size	Uploaded
plum_dispatch-2.10.1.tar.gz	250.8 kB	Sep 7, 2026	Details

Built distributions (wheels)

Table of built distributions (wheels) for plum-dispatch 2.10.1
File	Interpreter	ABI	Platform	Reset
plum_dispatch-2.10.1-py3-none-any.whl 49.4 kB Sep 7, 2026	Python 3	none	any	Details
plum_dispatch-2.10.1-cp313-cp313-win_amd64.whl 246.6 kB Sep 7, 2026	CPython 3.13	CPython 3.13	Windows x86-64	Details
plum_dispatch-2.10.1-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl 332.9 kB Sep 7, 2026	CPython 3.13	CPython 3.13	Linux glibc 2.28+ x86-64, Linux glibc 2.17+ x86-64	Details
plum_dispatch-2.10.1-cp313-cp313-macosx_11_0_arm64.whl 265.6 kB Sep 7, 2026	CPython 3.13	CPython 3.13	macOS 11.0+ ARM64	Details
plum_dispatch-2.10.1-cp313-cp313-macosx_10_13_x86_64.whl 283.2 kB Sep 7, 2026	CPython 3.13	CPython 3.13	macOS 10.13+ x86-64	Details
plum_dispatch-2.10.1-cp312-cp312-win_amd64.whl 245.8 kB Sep 7, 2026	CPython 3.12	CPython 3.12	Windows x86-64	Details
plum_dispatch-2.10.1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl 334.6 kB Sep 7, 2026	CPython 3.12	CPython 3.12	Linux glibc 2.28+ x86-64, Linux glibc 2.17+ x86-64	Details
plum_dispatch-2.10.1-cp312-cp312-macosx_11_0_arm64.whl 267.4 kB Sep 7, 2026	CPython 3.12	CPython 3.12	macOS 11.0+ ARM64	Details
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plum_dispatch-2.10.1-cp311-cp311-win_amd64.whl 244.2 kB Sep 7, 2026	CPython 3.11	CPython 3.11	Windows x86-64	Details
plum_dispatch-2.10.1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl 328.4 kB Sep 7, 2026	CPython 3.11	CPython 3.11	Linux glibc 2.17+ x86-64, Linux glibc 2.28+ x86-64	Details
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plum_dispatch-2.10.1-cp310-cp310-win_amd64.whl 244.4 kB Sep 7, 2026	CPython 3.10	CPython 3.10	Windows x86-64	Details
plum_dispatch-2.10.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl 335.5 kB Sep 7, 2026	CPython 3.10	CPython 3.10	Linux glibc 2.17+ x86-64, Linux glibc 2.28+ x86-64	Details
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plum_dispatch-2.10.1-cp310-cp310-macosx_10_9_x86_64.whl 283.5 kB Sep 7, 2026	CPython 3.10	CPython 3.10	macOS 10.9+ x86-64	Details

Total release size: 4.8 MB

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Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/beartype/plum
Publishing commit: github.com/beartype/plum/tree/c835c8cf5ebea4f00ee304a647e026739034e63b

Workflow

Publishing configuration: github.com/beartype/plum/blob/c835c8cf5ebea4f00ee304a647e026739034e63b/.github/workflows/publish.yml
Publishing logs: github.com/beartype/plum/actions/runs/34147935638/attempts/1

Artifact

Subject: plum_dispatch-2.10.1-cp311-cp311-win_amd64.whl
SHA-256 checksum: 4adc9e9335bee9fffd24abd3be0aa6810e403129697ab767976d70cc3c88405c Verifying attestations

Release files / plum_dispatch-2.10.1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl

Download URL	plum_dispatch-2.10.1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Size	328.4 kB
Tags	CPython 3.11 Linux glibc 2.17+ x86-64 Linux glibc 2.28+ x86-64
SHA-256 checksum How to use checksums	`b8909bc8c3b776f116c50986718befeda1de17a3dc61e7ae93f5d3d71de5f98d`
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Upload date	Sep 7, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/beartype/plum
Publishing commit: github.com/beartype/plum/tree/c835c8cf5ebea4f00ee304a647e026739034e63b

Workflow

Publishing configuration: github.com/beartype/plum/blob/c835c8cf5ebea4f00ee304a647e026739034e63b/.github/workflows/publish.yml
Publishing logs: github.com/beartype/plum/actions/runs/34147935638/attempts/1

Artifact

Subject: plum_dispatch-2.10.1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
SHA-256 checksum: b8909bc8c3b776f116c50986718befeda1de17a3dc61e7ae93f5d3d71de5f98d Verifying attestations

Release files / plum_dispatch-2.10.1-cp311-cp311-macosx_11_0_arm64.whl

Download URL	plum_dispatch-2.10.1-cp311-cp311-macosx_11_0_arm64.whl
Size	264.0 kB
Tags	CPython 3.11 macOS 11.0+ ARM64
SHA-256 checksum How to use checksums	`193fa7d9809e6ccf38d0ec423b92c2ce88b1bb5dfa7c769ce7a3b216aeb61eb4`
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Upload date	Sep 7, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/beartype/plum
Publishing commit: github.com/beartype/plum/tree/c835c8cf5ebea4f00ee304a647e026739034e63b

Workflow

Publishing configuration: github.com/beartype/plum/blob/c835c8cf5ebea4f00ee304a647e026739034e63b/.github/workflows/publish.yml
Publishing logs: github.com/beartype/plum/actions/runs/34147935638/attempts/1

Artifact

Subject: plum_dispatch-2.10.1-cp311-cp311-macosx_11_0_arm64.whl
SHA-256 checksum: 193fa7d9809e6ccf38d0ec423b92c2ce88b1bb5dfa7c769ce7a3b216aeb61eb4 Verifying attestations

Release files / plum_dispatch-2.10.1-cp311-cp311-macosx_10_9_x86_64.whl

Download URL	plum_dispatch-2.10.1-cp311-cp311-macosx_10_9_x86_64.whl
Size	279.0 kB
Tags	CPython 3.11 macOS 10.9+ x86-64
SHA-256 checksum How to use checksums	`143b44537476fcfa644a7b3b00cdfce91cd94c501eb5d4a342d0b1dae6e00269`
BLAKE2b-256 checksum How to use checksums	`8a1a3736f28127e6aa0e87eaee3286c0f93bf8fd25382786d8409073fc1a9010`
Upload date	Sep 7, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/beartype/plum
Publishing commit: github.com/beartype/plum/tree/c835c8cf5ebea4f00ee304a647e026739034e63b

Workflow

Publishing configuration: github.com/beartype/plum/blob/c835c8cf5ebea4f00ee304a647e026739034e63b/.github/workflows/publish.yml
Publishing logs: github.com/beartype/plum/actions/runs/34147935638/attempts/1

Artifact

Subject: plum_dispatch-2.10.1-cp311-cp311-macosx_10_9_x86_64.whl
SHA-256 checksum: 143b44537476fcfa644a7b3b00cdfce91cd94c501eb5d4a342d0b1dae6e00269 Verifying attestations

Release files / plum_dispatch-2.10.1-cp310-cp310-win_amd64.whl

Download URL	plum_dispatch-2.10.1-cp310-cp310-win_amd64.whl
Size	244.4 kB
Tags	CPython 3.10 Windows x86-64
SHA-256 checksum How to use checksums	`c4fc7cd33ced7acdf29199a15eeee6158d193a8e50293068d7ca9b5acad33107`
BLAKE2b-256 checksum How to use checksums	`880406febfedf066a198cbffbf79c5381f298d4d5e2a1dd5d5170daa63af81e8`
Upload date	Sep 7, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/beartype/plum
Publishing commit: github.com/beartype/plum/tree/c835c8cf5ebea4f00ee304a647e026739034e63b

Workflow

Publishing configuration: github.com/beartype/plum/blob/c835c8cf5ebea4f00ee304a647e026739034e63b/.github/workflows/publish.yml
Publishing logs: github.com/beartype/plum/actions/runs/34147935638/attempts/1

Artifact

Subject: plum_dispatch-2.10.1-cp310-cp310-win_amd64.whl
SHA-256 checksum: c4fc7cd33ced7acdf29199a15eeee6158d193a8e50293068d7ca9b5acad33107 Verifying attestations

Release files / plum_dispatch-2.10.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl

Download URL	plum_dispatch-2.10.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
Size	335.5 kB
Tags	CPython 3.10 Linux glibc 2.17+ x86-64 Linux glibc 2.28+ x86-64
SHA-256 checksum How to use checksums	`fa44546ea07b44fd532e0eaf75450ee42d8a65c8d697fefcb39aa11a2c5a580b`
BLAKE2b-256 checksum How to use checksums	`4058b9dc2237adbb6e28a8816452bd29714de5d0ece3a92eadbecc581836ead4`
Upload date	Sep 7, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/beartype/plum
Publishing commit: github.com/beartype/plum/tree/c835c8cf5ebea4f00ee304a647e026739034e63b

Workflow

Publishing configuration: github.com/beartype/plum/blob/c835c8cf5ebea4f00ee304a647e026739034e63b/.github/workflows/publish.yml
Publishing logs: github.com/beartype/plum/actions/runs/34147935638/attempts/1

Artifact

Subject: plum_dispatch-2.10.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
SHA-256 checksum: fa44546ea07b44fd532e0eaf75450ee42d8a65c8d697fefcb39aa11a2c5a580b Verifying attestations

Release files / plum_dispatch-2.10.1-cp310-cp310-macosx_11_0_arm64.whl

Download URL	plum_dispatch-2.10.1-cp310-cp310-macosx_11_0_arm64.whl
Size	269.2 kB
Tags	CPython 3.10 macOS 11.0+ ARM64
SHA-256 checksum How to use checksums	`7a4fa486ca38577aea8abd462947b9e1d9209c7964d31e2ba09c4a0f32951536`
BLAKE2b-256 checksum How to use checksums	`9713baea9a6afacd7b4fc342e16bf6a2ce351063dd5b9c5f288baf793be246e3`
Upload date	Sep 7, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/beartype/plum
Publishing commit: github.com/beartype/plum/tree/c835c8cf5ebea4f00ee304a647e026739034e63b

Workflow

Publishing configuration: github.com/beartype/plum/blob/c835c8cf5ebea4f00ee304a647e026739034e63b/.github/workflows/publish.yml
Publishing logs: github.com/beartype/plum/actions/runs/34147935638/attempts/1

Artifact

Subject: plum_dispatch-2.10.1-cp310-cp310-macosx_11_0_arm64.whl
SHA-256 checksum: 7a4fa486ca38577aea8abd462947b9e1d9209c7964d31e2ba09c4a0f32951536 Verifying attestations

Release files / plum_dispatch-2.10.1-cp310-cp310-macosx_10_9_x86_64.whl

Download URL	plum_dispatch-2.10.1-cp310-cp310-macosx_10_9_x86_64.whl
Size	283.5 kB
Tags	CPython 3.10 macOS 10.9+ x86-64
SHA-256 checksum How to use checksums	`57ec3a0ad2fd8973595b56048bac7cffe5b7c0f4650bf7b95d8758c48d8fbaaf`
BLAKE2b-256 checksum How to use checksums	`d34667cd4414af3784b369468282653a9bd02928431f4864b35d40550c99f9d1`
Upload date	Sep 7, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/beartype/plum
Publishing commit: github.com/beartype/plum/tree/c835c8cf5ebea4f00ee304a647e026739034e63b

Workflow

Publishing configuration: github.com/beartype/plum/blob/c835c8cf5ebea4f00ee304a647e026739034e63b/.github/workflows/publish.yml
Publishing logs: github.com/beartype/plum/actions/runs/34147935638/attempts/1

Artifact

Subject: plum_dispatch-2.10.1-cp310-cp310-macosx_10_9_x86_64.whl
SHA-256 checksum: 57ec3a0ad2fd8973595b56048bac7cffe5b7c0f4650bf7b95d8758c48d8fbaaf Verifying attestations