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6399834
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Parent(s):
397edde
refactor(functors): `v0.1.5` of `functors.py`
Browse files
functional_programming/05_functors.py
CHANGED
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import marimo
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-
__generated_with = "0.12.
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app = marimo.App(
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@app.cell(hide_code=True)
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def _(mo):
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/// details | Notebook metadata
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type: info
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-
version: 0.1.
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reviewer: [Haleshot](https://github.com/Haleshot)
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///
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`fmap` for `Either` will ignore Left values, but will apply the supplied function to values contained in the Right.
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The implementation is:
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"""
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)
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return
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@classmethod
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@abstractmethod
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def fmap(cls, g: Callable[[A], B], fa: "Functor[A]") -> "Functor[B]":
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-
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@classmethod
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def const(cls, fa: "Functor[A]", b: B) -> "Functor[B]":
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Once again there are a few axioms that functors have to obey.
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1. Given an identity morphism $id_A$ on an object $A$, $F ( id_A )$ must be the identity morphism on $F ( A )
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-
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"""
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)
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return
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return
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@app.cell(hide_code=True)
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def _(mo):
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mo.md(
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@@ -1253,7 +1443,8 @@ def _(TypeVar):
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A = TypeVar("A")
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B = TypeVar("B")
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C = TypeVar("C")
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-
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if __name__ == "__main__":
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import marimo
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__generated_with = "0.12.8"
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app = marimo.App(
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app_title="Category Theory and Functors",
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css_file="/Users/chanhuizhihou/Library/Application Support/mtheme/themes/gruvbox.css",
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)
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@app.cell(hide_code=True)
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def _(mo):
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/// details | Notebook metadata
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type: info
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+
version: 0.1.5 | last modified: 2025-04-11 | author: [métaboulie](https://github.com/metaboulie)<br/>
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reviewer: [Haleshot](https://github.com/Haleshot)
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///
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`fmap` for `Either` will ignore Left values, but will apply the supplied function to values contained in the Right.
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The implementation is:
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"""
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)
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return
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@classmethod
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@abstractmethod
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def fmap(cls, g: Callable[[A], B], fa: "Functor[A]") -> "Functor[B]":
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raise NotImplementedError("Subclasses must implement fmap")
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@classmethod
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def const(cls, fa: "Functor[A]", b: B) -> "Functor[B]":
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Once again there are a few axioms that functors have to obey.
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1. Given an identity morphism $id_A$ on an object $A$, $F ( id_A )$ must be the identity morphism on $F ( A )$.:
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$$F({id} _{A})={id} _{F(A)}$$
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3. Functors must distribute over morphism composition.
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$$F(f\circ g)=F(f)\circ F(g)$$
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"""
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)
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return
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return
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@app.cell(hide_code=True)
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def _(mo):
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mo.md(
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r"""
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# Bifunctor
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A `Bifunctor` is a type constructor that takes two type arguments and **is a functor in both arguments.**
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For example, think about `Either`'s usual `Functor` instance. It only allows you to fmap over the second type parameter: `right` values get mapped, `left` values stay as they are.
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However, its `Bifunctor` instance allows you to map both halves of the sum.
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There are three core methods for `Bifunctor`:
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- `bimap` allows mapping over both type arguments at once.
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- `first` and `second` are also provided for mapping over only one type argument at a time.
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The abstraction of `Bifunctor` is:
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"""
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)
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return
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@app.cell
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def _(ABC, B, Callable, D, dataclass, f, id):
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@dataclass
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class Bifunctor[A, C](ABC):
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@classmethod
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def bimap(
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cls, g: Callable[[A], B], h: Callable[[C], D], fa: "Bifunctor[A, C]"
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) -> "Bifunctor[B, D]":
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return cls.first(f, cls.second(g, fa))
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@classmethod
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def first(
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cls, g: Callable[[A], B], fa: "Bifunctor[A, C]"
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) -> "Bifunctor[B, C]":
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return cls.bimap(g, id, fa)
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@classmethod
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def second(
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cls, g: Callable[[B], C], fa: "Bifunctor[A, B]"
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) -> "Bifunctor[A, C]":
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return cls.bimap(id, g, fa)
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return (Bifunctor,)
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@app.cell(hide_code=True)
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def _(mo):
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mo.md(
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r"""
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/// admonition | minimal implementation requirement
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- `bimap` or both `first` and `second`
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///
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"""
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)
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return
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@app.cell(hide_code=True)
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def _(mo):
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mo.md(r"""## Instances of Bifunctor""")
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return
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@app.cell(hide_code=True)
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def _(mo):
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mo.md(
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r"""
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### The Either Bifunctor
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For the `Either Bifunctor`, we allow it to map a function over the `left` value as well.
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Notice that, the `Either Bifunctor` still only contains the `left` value or the `right` value.
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"""
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)
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return
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@app.cell
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def _(B, Bifunctor, Callable, D, dataclass):
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@dataclass
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class BiEither[A, C](Bifunctor):
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left: A = None
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right: C = None
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def __post_init__(self):
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if (self.left is not None and self.right is not None) or (
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self.left is None and self.right is None
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):
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raise TypeError(
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"Provide either the value of the left or the value of the right."
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)
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@classmethod
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def bimap(
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cls, g: Callable[[A], B], h: Callable[[C], D], fa: "BiEither[A, C]"
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) -> "BiEither[B, D]":
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if fa.left is not None:
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return cls(left=g(fa.left))
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return cls(right=h(fa.right))
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def __repr__(self):
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if self.left is not None:
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return f"Left({self.left!r})"
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return f"Right({self.right!r})"
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return (BiEither,)
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@app.cell
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def _(BiEither):
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print(BiEither.bimap(lambda x: x + 1, lambda x: x * 2, BiEither(left=1)))
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print(BiEither.bimap(lambda x: x + 1, lambda x: x * 2, BiEither(right=2)))
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print(BiEither.first(lambda x: x + 1, BiEither(left=1)))
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print(BiEither.first(lambda x: x + 1, BiEither(right=2)))
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print(BiEither.second(lambda x: x + 1, BiEither(left=1)))
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print(BiEither.second(lambda x: x + 1, BiEither(right=2)))
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return
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@app.cell(hide_code=True)
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def _(mo):
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mo.md(
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r"""
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### The 2d Tuple Bifunctor
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For 2d tuples, we simply expect `bimap` to map 2 functions to the 2 elements in the tuple respectively.
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"""
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)
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return
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@app.cell
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def _(B, Bifunctor, Callable, D, dataclass):
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@dataclass
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class BiTuple[A, C](Bifunctor):
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value: tuple[A, C]
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@classmethod
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def bimap(
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cls, g: Callable[[A], B], h: Callable[[C], D], fa: "BiTuple[A, C]"
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) -> "BiTuple[B, D]":
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return cls((g(fa.value[0]), h(fa.value[1])))
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return (BiTuple,)
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@app.cell
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def _(BiTuple):
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print(BiTuple.bimap(lambda x: x + 1, lambda x: x * 2, BiTuple((1, 2))))
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print(BiTuple.first(lambda x: x + 1, BiTuple((1, 2))))
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print(BiTuple.second(lambda x: x + 1, BiTuple((1, 2))))
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return
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@app.cell(hide_code=True)
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def _(mo):
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mo.md(
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r"""
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## Bifunctor laws
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The only law we need to follow is
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```python
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bimap(id, id, fa) == id(fa)
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```
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and then other laws are followed automatically.
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"""
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)
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return
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@app.cell
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def _(BiEither, BiTuple, id):
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print(BiEither.bimap(id, id, BiEither(left=1)) == id(BiEither(left=1)))
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print(BiEither.bimap(id, id, BiEither(right=1)) == id(BiEither(right=1)))
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print(BiTuple.bimap(id, id, BiTuple((1, 2))) == id(BiTuple((1, 2))))
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return
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@app.cell(hide_code=True)
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def _(mo):
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mo.md(
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A = TypeVar("A")
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B = TypeVar("B")
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C = TypeVar("C")
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D = TypeVar("D")
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return A, B, C, D
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if __name__ == "__main__":
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functional_programming/CHANGELOG.md
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# Changelog of the functional-programming course
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## 2025-04-08
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**functors.py**
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# Changelog of the functional-programming course
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## 2025-04-11
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**functors.py**
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+ add `Bifunctor` section
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* replace `return NotImplementedError` with `raise NotImplementedError`
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## 2025-04-08
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**functors.py**
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functional_programming/README.md
CHANGED
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_🚧 This collection is a [work in progress](https://github.com/marimo-team/learn/issues/51)._
|
4 |
|
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This series of marimo notebooks introduces the powerful paradigm of functional
|
6 |
-
programming through Python. Taking inspiration from Haskell and Category
|
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-
we'll build a strong foundation in FP concepts that can transform how
|
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-
approach software development.
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## What You'll Learn
|
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**Using only Python's standard library**, we'll construct functional
|
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concepts from first principles.
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Topics include:
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-
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-
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-
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## Running Notebooks
|
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@@ -24,20 +24,21 @@ Topics include:
|
|
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|
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To run a notebook locally, use
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```bash
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uvx marimo edit <URL>
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```
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For example, run the `Functor` tutorial with
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```bash
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uvx marimo edit https://github.com/marimo-team/learn/blob/main/functional_programming/05_functors.py
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```
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### On Our Online Playground
|
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You can also open notebooks in our online playground by appending `marimo.app/` to a notebook's URL like:
|
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-
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### On Our Landing Page
|
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@@ -50,17 +51,19 @@ on Discord (@eugene.hs).
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# Description of notebooks
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Check [here](https://github.com/marimo-team/learn/issues/51) for current series
|
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-
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-
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-
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-
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**Authors.**
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Thanks to all our notebook authors!
|
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-
-
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|
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**Reviewers.**
|
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|
|
|
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_🚧 This collection is a [work in progress](https://github.com/marimo-team/learn/issues/51)._
|
4 |
|
5 |
This series of marimo notebooks introduces the powerful paradigm of functional
|
6 |
+
programming through Python. Taking inspiration from Haskell and Category
|
7 |
+
Theory, we'll build a strong foundation in FP concepts that can transform how
|
8 |
+
you approach software development.
|
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|
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## What You'll Learn
|
11 |
|
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+
**Using only Python's standard library**, we'll construct functional
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programming concepts from first principles.
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Topics include:
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+ Currying and higher-order functions
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+ Functors, Applicatives, and Monads
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+ Category theory fundamentals
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## Running Notebooks
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To run a notebook locally, use
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+
```bash
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uvx marimo edit <URL>
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```
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For example, run the `Functor` tutorial with
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+
```bash
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uvx marimo edit https://github.com/marimo-team/learn/blob/main/functional_programming/05_functors.py
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```
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### On Our Online Playground
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You can also open notebooks in our online playground by appending `marimo.app/` to a notebook's URL like:
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+
|
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+
https://marimo.app/https://github.com/marimo-team/learn/blob/main/functional_programming/05_functors.py
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### On Our Landing Page
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# Description of notebooks
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+
Check [here](https://github.com/marimo-team/learn/issues/51) for current series
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structure.
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+
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| Notebook | Title | Key Concepts | Prerequisites |
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+
|----------|-------|--------------|---------------|
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| [05. Functors](https://github.com/marimo-team/learn/blob/main/functional_programming/05_functors.py) | Category Theory and Functors | Category Theory, Functors, fmap | Basic Python, Functions |
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| [06. Applicatives](https://github.com/marimo-team/learn/blob/main/functional_programming/06_applicatives.py) | Applicative programming with effects | Applicative Functors, pure, apply, Effectful programming, Alternatives | Functors |
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**Authors.**
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Thanks to all our notebook authors!
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- [métaboulie](https://github.com/metaboulie)
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**Reviewers.**
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|