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The Python toolkit for computing with string diagrams.

Project description

Snake equation


build readthedocs PyPI version DOI: 10.4204/EPTCS.333.13

DisCoPy is a Python toolkit for computing with string diagrams.

DisCoPy began as an implementation of DisCoCat and QNLP. This has now become its own library: lambeq.


Example: Cooking

This example is inspired from Pawel Sobocinski's blog post Crema di Mascarpone and Diagrammatic Reasoning.

from discopy.symmetric import Ty as Ingredient, Box as Step, Diagram as Recipe

egg, white, yolk = Ingredient("egg"), Ingredient("white"), Ingredient("yolk")
crack = Step("crack", egg, white @ yolk)
merge = lambda x: Step("merge", x @ x, x)

# DisCoPy allows string diagrams to be defined as Python functions

@Recipe.from_callable(egg @ egg, white @ yolk)
def crack_two_eggs(left_egg, right_egg):
    left_white, left_yolk = crack(left_egg)
    right_white, right_yolk = crack(right_egg)
    return (merge(white)(left_white, right_white),
            merge(yolk)(left_yolk, right_yolk))

# ... or in point-free style using parallel (@) and sequential (>>) composition

assert crack_two_eggs == crack @ crack\
  >> white @ Recipe.swap(yolk, white) @ yolk\
  >> merge(white) @ merge(yolk)




pip install discopy

If you want to see DisCoPy in action, check out the QNLP tutorial!


We're keen to welcome new contributors!

First, read the contributing guidelines. Then get in touch on Discord or open an issue.

How to cite

If you used DisCoPy in the context of an academic publication, we suggest you cite:

  • G. de Felice, A. Toumi & B. Coecke, DisCoPy: Monoidal Categories in Python, EPTCS 333, 2021, pp. 183-197, DOI: 10.4204/EPTCS.333.13

If furthermore your work is related to quantum computing, you can also cite:

  • A. Toumi, G. de Felice & R. Yeung, DisCoPy for the quantum computer scientist, arXiv:2205.05190

If you use any of the recent features (e.g. Hypergraph) you should also mention:

  • A. Toumi, R. Yeung, B. Poór & G. de Felice, DisCoPy: the Hierarchy of Graphical Languages in Python arXiv:2311.10608

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