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refactor(applicatives): `v0.1.3` of applicatives.py
Browse files- functional_programming/06_applicatives.py +478 -126
- functional_programming/CHANGELOG.md +46 -25
functional_programming/06_applicatives.py
CHANGED
@@ -7,12 +7,12 @@
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import marimo
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-
__generated_with = "0.12.
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app = marimo.App(app_title="Applicative programming with effects")
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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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# Applicative programming with effects
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In this notebook, you will learn:
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1. How to view `
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2. How to use `lift` to simplify chaining application.
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3. How to bring *effects* to the functional pure world.
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4. How to view `
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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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"""
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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(
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r"""
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# The intuition: [Multifunctor](https://arxiv.org/pdf/2401.14286)
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And we have to declare a special version of the functor class for each case.
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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(
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r"""
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## Defining Multifunctor
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/// admonition
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-
we use prefix `f` rather than `ap` to indicate *Applicative Functor*
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///
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As a result, we may want to define a single `Multifunctor` such that:
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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(
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r"""
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## Pure, apply and lift
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# or if we have a regular function `g`
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g: Callable[[A], B]
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# then we can have `fg` as
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fg: Applicative[Callable[[A], B]] = pure(g)
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```
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2. `apply`: applies a function inside an applicative functor to a value inside an applicative functor
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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(
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r"""
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/// admonition | How to use *Applicative* in the manner of *Multifunctor*
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///
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/// attention | You can suppress the chaining application of `apply` and `pure` as:
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```python
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apply(pure(g), fa) -> lift(g, fa)
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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(
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r"""
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## Abstracting applicatives
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@classmethod
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@abstractmethod
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def pure(cls, a: A) -> "Applicative[A]":
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-
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@classmethod
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@abstractmethod
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def apply(
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cls, fg: "Applicative[Callable[[A], B]]", fa: "Applicative[A]"
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) -> "Applicative[B]":
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-
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@classmethod
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def lift(cls, f: Callable, *args: "Applicative") -> "Applicative":
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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, laws and utility functions""")
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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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## Applicative instances
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- apply a function inside the computation context to a value inside the computational context
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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(
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r"""
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### Wrapper
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- `pure` should simply *wrap* an object, in the sense that:
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```haskell
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Wrapper.pure(1) => Wrapper(value=1)
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The implementation is:
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"""
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)
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return
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@app.cell
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@app.cell(hide_code=True)
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def _(mo):
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mo.md(r"""> try with Wrapper below""")
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return
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@app.cell
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def _(Wrapper):
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Wrapper.lift(
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lambda a: lambda b: lambda c: a + b * c,
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Wrapper(1),
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Wrapper(2),
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Wrapper(3),
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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(
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r"""
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### List
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- `pure` should wrap the object in a list, in the sense that:
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The implementation is:
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"""
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)
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return
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@app.cell
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@app.cell(hide_code=True)
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def _(mo):
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mo.md(r"""> try with List below""")
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return
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@app.cell
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def _(List):
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List.apply(
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List([lambda a: a + 1, lambda a: a * 2]),
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List([1, 2]),
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)
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return
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@app.cell
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def _(List):
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List.lift(lambda a: lambda b: a + b, List([1, 2]), List([3, 4, 5]))
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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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### Maybe
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- `pure` should wrap the object in a Maybe, in the sense that:
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The implementation is:
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"""
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)
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return
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@app.cell
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@app.cell(hide_code=True)
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def _(mo):
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mo.md(r"""> try with Maybe below""")
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return
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@app.cell
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def _(Maybe):
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Maybe.lift(
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lambda a: lambda b: a + b,
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Maybe(1),
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Maybe(2),
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)
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return
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@app.cell
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def _(Maybe):
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Maybe.lift(
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lambda a: lambda b: None,
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Maybe(1),
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Maybe(2),
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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(
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r"""
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## Collect the list of response with sequenceL
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Let's try `sequenceL` with the instances.
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"""
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)
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return
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@app.cell
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def _(Wrapper):
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Wrapper.sequenceL([Wrapper(1), Wrapper(2), Wrapper(3)])
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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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/// attention
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///
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"""
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)
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return
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@app.cell
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def _(Maybe):
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Maybe.sequenceL([Maybe(1), Maybe(2), Maybe(None), Maybe(3)])
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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"""The result of `sequenceL` for `List Applicative` is the Cartesian product of the input lists, yielding all possible ordered combinations of elements from each list.""")
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return
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@app.cell
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def _(List):
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List.sequenceL([List([1, 2]), List([3]), List([5, 6, 7])])
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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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## Applicative laws
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```
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This one is the trickiest law to gain intuition for. In some sense it is expressing a sort of associativity property of `apply`.
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We can add 4 helper functions to `Applicative` to check whether an instance respects the laws or not:
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```python
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@dataclass
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> Try to validate applicative laws below
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"""
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)
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return
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@app.cell
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@app.cell
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def _(List, Wrapper):
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print("Checking Wrapper")
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print(Wrapper.check_identity(Wrapper.pure(1)))
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print(Wrapper.check_homomorphism(1, lambda x: x + 1))
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List.pure(lambda x: x * 2), List.pure(lambda x: x + 0.1), List.pure(1)
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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(
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r"""
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## Utility functions
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cls, fa: "Applicative[A]", fg: "Applicative[Callable[[A], [B]]]"
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) -> "Applicative[B]":
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'''
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The first computation produces values which are provided
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as input to the function(s) produced by the second computation.
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'''
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return cls.lift(lambda a: lambda f: f(a), fa, fg)
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```
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- `skip` sequences the effects of two Applicative computations, but **discards the result of the first**. For example, if `m1` and `m2` are instances of type `Maybe[Int]`, then `Maybe.skip(m1, m2)` is `Nothing` whenever either `m1` or `m2` is `Nothing`; but if not, it will have the same value as `m2`.
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- Likewise, `keep` sequences the effects of two computations, but **keeps only the result of the first**.
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- `revapp` is similar to `apply`, but where the first computation produces value(s) which are provided as input to the function(s) produced by the second computation.
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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(
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r"""
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/// admonition | exercise
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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(
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r"""
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# Formal implementation of Applicative
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Now, we can give the formal implementation of `Applicative`
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"""
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)
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-
return
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@app.cell
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@abstractmethod
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def pure(cls, a: A) -> "Applicative[A]":
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"""Lift a value into the Structure."""
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-
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@classmethod
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@abstractmethod
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cls, fg: "Applicative[Callable[[A], B]]", fa: "Applicative[A]"
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) -> "Applicative[B]":
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"""Sequential application."""
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-
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@classmethod
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def lift(cls, f: Callable, *args: "Applicative") -> "Applicative":
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return cls.pure([])
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return cls.apply(
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-
cls.fmap(lambda v: lambda vs: [v
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cls.sequenceL(fas[1:]),
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)
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return cls.lift(lambda a: lambda f: f(a), fa, fg)
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@classmethod
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-
def check_identity(cls, fa: "Applicative[A]"):
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if cls.lift(id, fa) != fa:
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-
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return True
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@classmethod
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-
def check_homomorphism(cls, a: A, f: Callable[[A], B]):
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if cls.lift(f, cls.pure(a)) != cls.pure(f(a)):
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-
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return True
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@classmethod
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-
def check_interchange(cls, a: A, fg: "Applicative[Callable[[A], B]]"):
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if cls.apply(fg, cls.pure(a)) != cls.lift(lambda g: g(a), fg):
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-
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return True
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@classmethod
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@@ -816,15 +878,16 @@ def _(
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fg: "Applicative[Callable[[B], C]]",
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fh: "Applicative[Callable[[A], B]]",
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fa: "Applicative[A]",
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-
):
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if cls.apply(fg, cls.apply(fh, fa)) != cls.lift(compose, fg, fh, fa):
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-
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return True
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return (Applicative,)
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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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# Effectful programming
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The arguments are no longer just plain values but may also have effects, such as the possibility of failure, having many ways to succeed, or performing input/output actions. In this manner, applicative functors can also be viewed as abstracting the idea of **applying pure functions to effectful arguments**, with the precise form of effects that are permitted depending on the nature of the underlying functor.
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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(
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r"""
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## The IO Applicative
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@@ -847,7 +909,7 @@ def _(mo):
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As before, we first abstract how `pure` and `apply` should function.
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-
- `pure` should wrap the object in an IO action, and make the object *callable* if it's not because we want to perform the action later:
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```haskell
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IO.pure(1) => IO(effect=lambda: 1)
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@@ -859,7 +921,6 @@ def _(mo):
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The implementation is:
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"""
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)
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-
return
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@app.cell
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@@ -882,34 +943,32 @@ def _(Applicative, Callable, dataclass):
|
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|
884 |
@app.cell(hide_code=True)
|
885 |
-
def _(mo):
|
886 |
mo.md(r"""For example, a function that reads a given number of lines from the keyboard can be defined in applicative style as follows:""")
|
887 |
-
return
|
888 |
|
889 |
|
890 |
@app.cell
|
891 |
def _(IO):
|
892 |
def get_chars(n: int = 3):
|
893 |
-
return IO.sequenceL(
|
894 |
-
|
895 |
-
)
|
896 |
return (get_chars,)
|
897 |
|
898 |
|
899 |
@app.cell
|
900 |
-
def _():
|
901 |
# get_chars()()
|
902 |
return
|
903 |
|
904 |
|
905 |
@app.cell(hide_code=True)
|
906 |
-
def _(mo):
|
907 |
mo.md(r"""# From the perspective of category theory""")
|
908 |
-
return
|
909 |
|
910 |
|
911 |
@app.cell(hide_code=True)
|
912 |
-
def _(mo):
|
913 |
mo.md(
|
914 |
r"""
|
915 |
## Lax Monoidal Functor
|
@@ -917,7 +976,6 @@ def _(mo):
|
|
917 |
An alternative, equivalent formulation of `Applicative` is given by
|
918 |
"""
|
919 |
)
|
920 |
-
return
|
921 |
|
922 |
|
923 |
@app.cell
|
@@ -939,10 +997,10 @@ def _(ABC, Functor, abstractmethod, dataclass):
|
|
939 |
|
940 |
|
941 |
@app.cell(hide_code=True)
|
942 |
-
def _(mo):
|
943 |
mo.md(
|
944 |
r"""
|
945 |
-
Intuitively, this states that a *monoidal functor* is one which has some sort of "default shape" and which supports some sort of "combining" operation.
|
946 |
|
947 |
- `unit` provides the identity element
|
948 |
- `tensor` combines two contexts into a product context
|
@@ -950,14 +1008,13 @@ def _(mo):
|
|
950 |
More technically, the idea is that `monoidal functor` preserves the "monoidal structure" given by the pairing constructor `(,)` and unit type `()`.
|
951 |
"""
|
952 |
)
|
953 |
-
return
|
954 |
|
955 |
|
956 |
@app.cell(hide_code=True)
|
957 |
-
def _(mo):
|
958 |
mo.md(
|
959 |
r"""
|
960 |
-
Furthermore, to deserve the name "monoidal", instances of Monoidal ought to satisfy the following laws, which seem much more straightforward than the traditional Applicative laws:
|
961 |
|
962 |
- Left identity
|
963 |
|
@@ -972,11 +1029,10 @@ def _(mo):
|
|
972 |
`tensor(u, tensor(v, w)) ≅ tensor(tensor(u, v), w)`
|
973 |
"""
|
974 |
)
|
975 |
-
return
|
976 |
|
977 |
|
978 |
@app.cell(hide_code=True)
|
979 |
-
def _(mo):
|
980 |
mo.md(
|
981 |
r"""
|
982 |
/// admonition | ≅ indicates isomorphism
|
@@ -988,11 +1044,10 @@ def _(mo):
|
|
988 |
///
|
989 |
"""
|
990 |
)
|
991 |
-
return
|
992 |
|
993 |
|
994 |
@app.cell(hide_code=True)
|
995 |
-
def _(mo):
|
996 |
mo.md(
|
997 |
r"""
|
998 |
## Mutual definability of Monoidal and Applicative
|
@@ -1010,11 +1065,10 @@ def _(mo):
|
|
1010 |
```
|
1011 |
"""
|
1012 |
)
|
1013 |
-
return
|
1014 |
|
1015 |
|
1016 |
@app.cell(hide_code=True)
|
1017 |
-
def _(mo):
|
1018 |
mo.md(
|
1019 |
r"""
|
1020 |
## Instance: ListMonoidal
|
@@ -1030,7 +1084,6 @@ def _(mo):
|
|
1030 |
The implementation is:
|
1031 |
"""
|
1032 |
)
|
1033 |
-
return
|
1034 |
|
1035 |
|
1036 |
@app.cell
|
@@ -1058,9 +1111,8 @@ def _(B, Callable, Monoidal, dataclass, product):
|
|
1058 |
|
1059 |
|
1060 |
@app.cell(hide_code=True)
|
1061 |
-
def _(mo):
|
1062 |
mo.md(r"""> try with `ListMonoidal` below""")
|
1063 |
-
return
|
1064 |
|
1065 |
|
1066 |
@app.cell
|
@@ -1072,15 +1124,13 @@ def _(ListMonoidal):
|
|
1072 |
|
1073 |
|
1074 |
@app.cell(hide_code=True)
|
1075 |
-
def _(mo):
|
1076 |
mo.md(r"""and we can prove that `tensor(fa, fb) = lift(lambda fa: lambda fb: (fa, fb), fa, fb)`:""")
|
1077 |
-
return
|
1078 |
|
1079 |
|
1080 |
@app.cell
|
1081 |
-
def _(List, xs, ys):
|
1082 |
List.lift(lambda fa: lambda fb: (fa, fb), List(xs.items), List(ys.items))
|
1083 |
-
return
|
1084 |
|
1085 |
|
1086 |
@app.cell(hide_code=True)
|
@@ -1090,7 +1140,8 @@ def _(ABC, B, Callable, abstractmethod, dataclass):
|
|
1090 |
@classmethod
|
1091 |
@abstractmethod
|
1092 |
def fmap(cls, f: Callable[[A], B], a: "Functor[A]") -> "Functor[B]":
|
1093 |
-
|
|
|
1094 |
|
1095 |
@classmethod
|
1096 |
def const(cls, a: "Functor[A]", b: B) -> "Functor[B]":
|
@@ -1110,10 +1161,10 @@ def _():
|
|
1110 |
|
1111 |
@app.cell(hide_code=True)
|
1112 |
def _():
|
1113 |
-
from dataclasses import dataclass
|
1114 |
from abc import ABC, abstractmethod
|
1115 |
-
from typing import TypeVar, Union
|
1116 |
from collections.abc import Callable
|
|
|
|
|
1117 |
return ABC, Callable, TypeVar, Union, abstractmethod, dataclass
|
1118 |
|
1119 |
|
@@ -1132,7 +1183,309 @@ def _(TypeVar):
|
|
1132 |
|
1133 |
|
1134 |
@app.cell(hide_code=True)
|
1135 |
-
def _(mo):
|
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|
1136 |
mo.md(
|
1137 |
r"""
|
1138 |
# Further reading
|
@@ -1155,7 +1508,6 @@ def _(mo):
|
|
1155 |
- [Applicative Functors](https://bartoszmilewski.com/2017/02/06/applicative-functors/)
|
1156 |
"""
|
1157 |
)
|
1158 |
-
return
|
1159 |
|
1160 |
|
1161 |
if __name__ == "__main__":
|
|
|
7 |
|
8 |
import marimo
|
9 |
|
10 |
+
__generated_with = "0.12.9"
|
11 |
app = marimo.App(app_title="Applicative programming with effects")
|
12 |
|
13 |
|
14 |
@app.cell(hide_code=True)
|
15 |
+
def _(mo) -> None:
|
16 |
mo.md(
|
17 |
r"""
|
18 |
# Applicative programming with effects
|
|
|
26 |
|
27 |
In this notebook, you will learn:
|
28 |
|
29 |
+
1. How to view `Applicative` as multi-functor intuitively.
|
30 |
2. How to use `lift` to simplify chaining application.
|
31 |
3. How to bring *effects* to the functional pure world.
|
32 |
+
4. How to view `Applicative` as a lax monoidal functor.
|
33 |
+
5. How to use `Alternative` to amalgamate multiple computations into a single computation.
|
34 |
|
35 |
/// details | Notebook metadata
|
36 |
type: info
|
37 |
|
38 |
+
version: 0.1.3 | last modified: 2025-04-16 | author: [métaboulie](https://github.com/metaboulie)<br/>
|
39 |
reviewer: [Haleshot](https://github.com/Haleshot)
|
40 |
|
41 |
///
|
42 |
"""
|
43 |
)
|
|
|
44 |
|
45 |
|
46 |
@app.cell(hide_code=True)
|
47 |
+
def _(mo) -> None:
|
48 |
mo.md(
|
49 |
r"""
|
50 |
# The intuition: [Multifunctor](https://arxiv.org/pdf/2401.14286)
|
|
|
68 |
And we have to declare a special version of the functor class for each case.
|
69 |
"""
|
70 |
)
|
|
|
71 |
|
72 |
|
73 |
@app.cell(hide_code=True)
|
74 |
+
def _(mo) -> None:
|
75 |
mo.md(
|
76 |
r"""
|
77 |
## Defining Multifunctor
|
78 |
|
79 |
/// admonition
|
80 |
+
we use prefix `f` rather than `ap` to indicate *Applicative Functor*
|
81 |
///
|
82 |
|
83 |
As a result, we may want to define a single `Multifunctor` such that:
|
|
|
111 |
```
|
112 |
"""
|
113 |
)
|
|
|
114 |
|
115 |
|
116 |
@app.cell(hide_code=True)
|
117 |
+
def _(mo) -> None:
|
118 |
mo.md(
|
119 |
r"""
|
120 |
## Pure, apply and lift
|
|
|
133 |
# or if we have a regular function `g`
|
134 |
g: Callable[[A], B]
|
135 |
# then we can have `fg` as
|
136 |
+
fg: Applicative[Callable[[A], B]] = pure(g)
|
137 |
```
|
138 |
|
139 |
2. `apply`: applies a function inside an applicative functor to a value inside an applicative functor
|
|
|
153 |
```
|
154 |
"""
|
155 |
)
|
|
|
156 |
|
157 |
|
158 |
@app.cell(hide_code=True)
|
159 |
+
def _(mo) -> None:
|
160 |
mo.md(
|
161 |
r"""
|
162 |
/// admonition | How to use *Applicative* in the manner of *Multifunctor*
|
|
|
172 |
|
173 |
///
|
174 |
|
175 |
+
/// attention | You can suppress the chaining application of `apply` and `pure` as:
|
176 |
|
177 |
```python
|
178 |
apply(pure(g), fa) -> lift(g, fa)
|
|
|
183 |
///
|
184 |
"""
|
185 |
)
|
|
|
186 |
|
187 |
|
188 |
@app.cell(hide_code=True)
|
189 |
+
def _(mo) -> None:
|
190 |
mo.md(
|
191 |
r"""
|
192 |
## Abstracting applicatives
|
|
|
199 |
@classmethod
|
200 |
@abstractmethod
|
201 |
def pure(cls, a: A) -> "Applicative[A]":
|
202 |
+
raise NotImplementedError("Subclasses must implement pure")
|
203 |
|
204 |
@classmethod
|
205 |
@abstractmethod
|
206 |
def apply(
|
207 |
cls, fg: "Applicative[Callable[[A], B]]", fa: "Applicative[A]"
|
208 |
) -> "Applicative[B]":
|
209 |
+
raise NotImplementedError("Subclasses must implement apply")
|
210 |
|
211 |
@classmethod
|
212 |
def lift(cls, f: Callable, *args: "Applicative") -> "Applicative":
|
|
|
225 |
///
|
226 |
"""
|
227 |
)
|
|
|
228 |
|
229 |
|
230 |
@app.cell(hide_code=True)
|
231 |
+
def _(mo) -> None:
|
232 |
mo.md(r"""# Instances, laws and utility functions""")
|
|
|
233 |
|
234 |
|
235 |
@app.cell(hide_code=True)
|
236 |
+
def _(mo) -> None:
|
237 |
mo.md(
|
238 |
r"""
|
239 |
## Applicative instances
|
|
|
244 |
- apply a function inside the computation context to a value inside the computational context
|
245 |
"""
|
246 |
)
|
|
|
247 |
|
248 |
|
249 |
@app.cell(hide_code=True)
|
250 |
+
def _(mo) -> None:
|
251 |
mo.md(
|
252 |
r"""
|
253 |
+
### The Wrapper Applicative
|
254 |
|
255 |
+
- `pure` should simply *wrap* an object, in the sense that:
|
256 |
|
257 |
```haskell
|
258 |
Wrapper.pure(1) => Wrapper(value=1)
|
|
|
263 |
The implementation is:
|
264 |
"""
|
265 |
)
|
|
|
266 |
|
267 |
|
268 |
@app.cell
|
|
|
284 |
|
285 |
|
286 |
@app.cell(hide_code=True)
|
287 |
+
def _(mo) -> None:
|
288 |
mo.md(r"""> try with Wrapper below""")
|
|
|
289 |
|
290 |
|
291 |
@app.cell
|
292 |
+
def _(Wrapper) -> None:
|
293 |
Wrapper.lift(
|
294 |
lambda a: lambda b: lambda c: a + b * c,
|
295 |
Wrapper(1),
|
296 |
Wrapper(2),
|
297 |
Wrapper(3),
|
298 |
)
|
|
|
299 |
|
300 |
|
301 |
@app.cell(hide_code=True)
|
302 |
+
def _(mo) -> None:
|
303 |
mo.md(
|
304 |
r"""
|
305 |
+
### The List Applicative
|
306 |
|
307 |
- `pure` should wrap the object in a list, in the sense that:
|
308 |
|
|
|
316 |
The implementation is:
|
317 |
"""
|
318 |
)
|
|
|
319 |
|
320 |
|
321 |
@app.cell
|
|
|
335 |
|
336 |
|
337 |
@app.cell(hide_code=True)
|
338 |
+
def _(mo) -> None:
|
339 |
mo.md(r"""> try with List below""")
|
|
|
340 |
|
341 |
|
342 |
@app.cell
|
343 |
+
def _(List) -> None:
|
344 |
List.apply(
|
345 |
List([lambda a: a + 1, lambda a: a * 2]),
|
346 |
List([1, 2]),
|
347 |
)
|
|
|
348 |
|
349 |
|
350 |
@app.cell
|
351 |
+
def _(List) -> None:
|
352 |
List.lift(lambda a: lambda b: a + b, List([1, 2]), List([3, 4, 5]))
|
|
|
353 |
|
354 |
|
355 |
@app.cell(hide_code=True)
|
356 |
+
def _(mo) -> None:
|
357 |
mo.md(
|
358 |
r"""
|
359 |
+
### The Maybe Applicative
|
360 |
|
361 |
- `pure` should wrap the object in a Maybe, in the sense that:
|
362 |
|
|
|
372 |
The implementation is:
|
373 |
"""
|
374 |
)
|
|
|
375 |
|
376 |
|
377 |
@app.cell
|
|
|
399 |
|
400 |
|
401 |
@app.cell(hide_code=True)
|
402 |
+
def _(mo) -> None:
|
403 |
mo.md(r"""> try with Maybe below""")
|
|
|
404 |
|
405 |
|
406 |
@app.cell
|
407 |
+
def _(Maybe) -> None:
|
408 |
Maybe.lift(
|
409 |
lambda a: lambda b: a + b,
|
410 |
Maybe(1),
|
411 |
Maybe(2),
|
412 |
)
|
|
|
413 |
|
414 |
|
415 |
@app.cell
|
416 |
+
def _(Maybe) -> None:
|
417 |
Maybe.lift(
|
418 |
lambda a: lambda b: None,
|
419 |
Maybe(1),
|
420 |
Maybe(2),
|
421 |
)
|
|
|
422 |
|
423 |
|
424 |
@app.cell(hide_code=True)
|
425 |
+
def _(mo) -> None:
|
426 |
+
mo.md(
|
427 |
+
r"""
|
428 |
+
### The Either Applicative
|
429 |
+
|
430 |
+
- `pure` should wrap the object in `Right`, in the sense that:
|
431 |
+
|
432 |
+
```haskell
|
433 |
+
Either.pure(1) => Right(1)
|
434 |
+
```
|
435 |
+
|
436 |
+
- `apply` should apply a function that is either on Left or Right to a value that is either on Left or Right
|
437 |
+
- if the function is `Left`, simply returns the `Left` of the function
|
438 |
+
- else `fmap` the `Right` of the function to the value
|
439 |
+
|
440 |
+
The implementation is:
|
441 |
+
"""
|
442 |
+
)
|
443 |
+
|
444 |
+
|
445 |
+
@app.cell
|
446 |
+
def _(Applicative, B, Callable, Union, dataclass):
|
447 |
+
@dataclass
|
448 |
+
class Either[A](Applicative):
|
449 |
+
left: A = None
|
450 |
+
right: A = None
|
451 |
+
|
452 |
+
def __post_init__(self):
|
453 |
+
if (self.left is not None and self.right is not None) or (
|
454 |
+
self.left is None and self.right is None
|
455 |
+
):
|
456 |
+
msg = "Provide either the value of the left or the value of the right."
|
457 |
+
raise TypeError(
|
458 |
+
msg
|
459 |
+
)
|
460 |
+
|
461 |
+
@classmethod
|
462 |
+
def pure(cls, a: A) -> "Either[A]":
|
463 |
+
return cls(right=a)
|
464 |
+
|
465 |
+
@classmethod
|
466 |
+
def apply(
|
467 |
+
cls, fg: "Either[Callable[[A], B]]", fa: "Either[A]"
|
468 |
+
) -> "Either[B]":
|
469 |
+
if fg.left is not None:
|
470 |
+
return cls(left=fg.left)
|
471 |
+
return cls.fmap(fg.right, fa)
|
472 |
+
|
473 |
+
@classmethod
|
474 |
+
def fmap(
|
475 |
+
cls, g: Callable[[A], B], fa: "Either[A]"
|
476 |
+
) -> Union["Either[A]", "Either[B]"]:
|
477 |
+
if fa.left is not None:
|
478 |
+
return cls(left=fa.left)
|
479 |
+
return cls(right=g(fa.right))
|
480 |
+
|
481 |
+
def __repr__(self):
|
482 |
+
if self.left is not None:
|
483 |
+
return f"Left({self.left!r})"
|
484 |
+
return f"Right({self.right!r})"
|
485 |
+
return (Either,)
|
486 |
+
|
487 |
+
|
488 |
+
@app.cell(hide_code=True)
|
489 |
+
def _(mo) -> None:
|
490 |
+
mo.md(r"""> try with `Either` below""")
|
491 |
+
|
492 |
+
|
493 |
+
@app.cell
|
494 |
+
def _(Either) -> None:
|
495 |
+
Either.apply(Either(left=TypeError("Parse Error")), Either(right=2))
|
496 |
+
|
497 |
+
|
498 |
+
@app.cell
|
499 |
+
def _(Either) -> None:
|
500 |
+
Either.apply(
|
501 |
+
Either(right=lambda x: x + 1), Either(left=TypeError("Parse Error"))
|
502 |
+
)
|
503 |
+
|
504 |
+
|
505 |
+
@app.cell
|
506 |
+
def _(Either) -> None:
|
507 |
+
Either.apply(Either(right=lambda x: x + 1), Either(right=1))
|
508 |
+
|
509 |
+
|
510 |
+
@app.cell(hide_code=True)
|
511 |
+
def _(mo) -> None:
|
512 |
mo.md(
|
513 |
r"""
|
514 |
## Collect the list of response with sequenceL
|
|
|
534 |
Let's try `sequenceL` with the instances.
|
535 |
"""
|
536 |
)
|
|
|
537 |
|
538 |
|
539 |
@app.cell
|
540 |
+
def _(Wrapper) -> None:
|
541 |
Wrapper.sequenceL([Wrapper(1), Wrapper(2), Wrapper(3)])
|
|
|
542 |
|
543 |
|
544 |
@app.cell(hide_code=True)
|
545 |
+
def _(mo) -> None:
|
546 |
mo.md(
|
547 |
r"""
|
548 |
/// attention
|
|
|
550 |
///
|
551 |
"""
|
552 |
)
|
|
|
553 |
|
554 |
|
555 |
@app.cell
|
556 |
+
def _(Maybe) -> None:
|
557 |
Maybe.sequenceL([Maybe(1), Maybe(2), Maybe(None), Maybe(3)])
|
|
|
558 |
|
559 |
|
560 |
@app.cell(hide_code=True)
|
561 |
+
def _(mo) -> None:
|
562 |
mo.md(r"""The result of `sequenceL` for `List Applicative` is the Cartesian product of the input lists, yielding all possible ordered combinations of elements from each list.""")
|
|
|
563 |
|
564 |
|
565 |
@app.cell
|
566 |
+
def _(List) -> None:
|
567 |
List.sequenceL([List([1, 2]), List([3]), List([5, 6, 7])])
|
|
|
568 |
|
569 |
|
570 |
@app.cell(hide_code=True)
|
571 |
+
def _(mo) -> None:
|
572 |
mo.md(
|
573 |
r"""
|
574 |
## Applicative laws
|
|
|
612 |
```
|
613 |
This one is the trickiest law to gain intuition for. In some sense it is expressing a sort of associativity property of `apply`.
|
614 |
|
615 |
+
We can add 4 helper functions to `Applicative` to check whether an instance respects the laws or not:
|
616 |
|
617 |
```python
|
618 |
@dataclass
|
|
|
651 |
> Try to validate applicative laws below
|
652 |
"""
|
653 |
)
|
|
|
654 |
|
655 |
|
656 |
@app.cell
|
|
|
662 |
|
663 |
|
664 |
@app.cell
|
665 |
+
def _(List, Wrapper) -> None:
|
666 |
print("Checking Wrapper")
|
667 |
print(Wrapper.check_identity(Wrapper.pure(1)))
|
668 |
print(Wrapper.check_homomorphism(1, lambda x: x + 1))
|
|
|
684 |
List.pure(lambda x: x * 2), List.pure(lambda x: x + 0.1), List.pure(1)
|
685 |
)
|
686 |
)
|
|
|
687 |
|
688 |
|
689 |
@app.cell(hide_code=True)
|
690 |
+
def _(mo) -> None:
|
691 |
mo.md(
|
692 |
r"""
|
693 |
## Utility functions
|
|
|
724 |
cls, fa: "Applicative[A]", fg: "Applicative[Callable[[A], [B]]]"
|
725 |
) -> "Applicative[B]":
|
726 |
'''
|
727 |
+
The first computation produces values which are provided
|
728 |
+
as input to the function(s) produced by the second computation.
|
729 |
'''
|
730 |
return cls.lift(lambda a: lambda f: f(a), fa, fg)
|
731 |
```
|
732 |
|
733 |
- `skip` sequences the effects of two Applicative computations, but **discards the result of the first**. For example, if `m1` and `m2` are instances of type `Maybe[Int]`, then `Maybe.skip(m1, m2)` is `Nothing` whenever either `m1` or `m2` is `Nothing`; but if not, it will have the same value as `m2`.
|
734 |
- Likewise, `keep` sequences the effects of two computations, but **keeps only the result of the first**.
|
735 |
+
- `revapp` is similar to `apply`, but where the first computation produces value(s) which are provided as input to the function(s) produced by the second computation.
|
736 |
"""
|
737 |
)
|
|
|
738 |
|
739 |
|
740 |
@app.cell(hide_code=True)
|
741 |
+
def _(mo) -> None:
|
742 |
mo.md(
|
743 |
r"""
|
744 |
/// admonition | exercise
|
|
|
746 |
///
|
747 |
"""
|
748 |
)
|
|
|
749 |
|
750 |
|
751 |
@app.cell(hide_code=True)
|
752 |
+
def _(mo) -> None:
|
753 |
mo.md(
|
754 |
r"""
|
755 |
# Formal implementation of Applicative
|
|
|
757 |
Now, we can give the formal implementation of `Applicative`
|
758 |
"""
|
759 |
)
|
|
|
760 |
|
761 |
|
762 |
@app.cell
|
|
|
777 |
@abstractmethod
|
778 |
def pure(cls, a: A) -> "Applicative[A]":
|
779 |
"""Lift a value into the Structure."""
|
780 |
+
msg = "Subclasses must implement pure"
|
781 |
+
raise NotImplementedError(msg)
|
782 |
|
783 |
@classmethod
|
784 |
@abstractmethod
|
|
|
786 |
cls, fg: "Applicative[Callable[[A], B]]", fa: "Applicative[A]"
|
787 |
) -> "Applicative[B]":
|
788 |
"""Sequential application."""
|
789 |
+
msg = "Subclasses must implement apply"
|
790 |
+
raise NotImplementedError(msg)
|
791 |
|
792 |
@classmethod
|
793 |
def lift(cls, f: Callable, *args: "Applicative") -> "Applicative":
|
|
|
817 |
return cls.pure([])
|
818 |
|
819 |
return cls.apply(
|
820 |
+
cls.fmap(lambda v: lambda vs: [v, *vs], fas[0]),
|
821 |
cls.sequenceL(fas[1:]),
|
822 |
)
|
823 |
|
|
|
852 |
return cls.lift(lambda a: lambda f: f(a), fa, fg)
|
853 |
|
854 |
@classmethod
|
855 |
+
def check_identity(cls, fa: "Applicative[A]") -> bool:
|
856 |
if cls.lift(id, fa) != fa:
|
857 |
+
msg = "Instance violates identity law"
|
858 |
+
raise ValueError(msg)
|
859 |
return True
|
860 |
|
861 |
@classmethod
|
862 |
+
def check_homomorphism(cls, a: A, f: Callable[[A], B]) -> bool:
|
863 |
if cls.lift(f, cls.pure(a)) != cls.pure(f(a)):
|
864 |
+
msg = "Instance violates homomorphism law"
|
865 |
+
raise ValueError(msg)
|
866 |
return True
|
867 |
|
868 |
@classmethod
|
869 |
+
def check_interchange(cls, a: A, fg: "Applicative[Callable[[A], B]]") -> bool:
|
870 |
if cls.apply(fg, cls.pure(a)) != cls.lift(lambda g: g(a), fg):
|
871 |
+
msg = "Instance violates interchange law"
|
872 |
+
raise ValueError(msg)
|
873 |
return True
|
874 |
|
875 |
@classmethod
|
|
|
878 |
fg: "Applicative[Callable[[B], C]]",
|
879 |
fh: "Applicative[Callable[[A], B]]",
|
880 |
fa: "Applicative[A]",
|
881 |
+
) -> bool:
|
882 |
if cls.apply(fg, cls.apply(fh, fa)) != cls.lift(compose, fg, fh, fa):
|
883 |
+
msg = "Instance violates composition law"
|
884 |
+
raise ValueError(msg)
|
885 |
return True
|
886 |
return (Applicative,)
|
887 |
|
888 |
|
889 |
@app.cell(hide_code=True)
|
890 |
+
def _(mo) -> None:
|
891 |
mo.md(
|
892 |
r"""
|
893 |
# Effectful programming
|
|
|
897 |
The arguments are no longer just plain values but may also have effects, such as the possibility of failure, having many ways to succeed, or performing input/output actions. In this manner, applicative functors can also be viewed as abstracting the idea of **applying pure functions to effectful arguments**, with the precise form of effects that are permitted depending on the nature of the underlying functor.
|
898 |
"""
|
899 |
)
|
|
|
900 |
|
901 |
|
902 |
@app.cell(hide_code=True)
|
903 |
+
def _(mo) -> None:
|
904 |
mo.md(
|
905 |
r"""
|
906 |
## The IO Applicative
|
|
|
909 |
|
910 |
As before, we first abstract how `pure` and `apply` should function.
|
911 |
|
912 |
+
- `pure` should wrap the object in an IO action, and make the object *callable* if it's not because we want to perform the action later:
|
913 |
|
914 |
```haskell
|
915 |
IO.pure(1) => IO(effect=lambda: 1)
|
|
|
921 |
The implementation is:
|
922 |
"""
|
923 |
)
|
|
|
924 |
|
925 |
|
926 |
@app.cell
|
|
|
943 |
|
944 |
|
945 |
@app.cell(hide_code=True)
|
946 |
+
def _(mo) -> None:
|
947 |
mo.md(r"""For example, a function that reads a given number of lines from the keyboard can be defined in applicative style as follows:""")
|
|
|
948 |
|
949 |
|
950 |
@app.cell
|
951 |
def _(IO):
|
952 |
def get_chars(n: int = 3):
|
953 |
+
return IO.sequenceL([
|
954 |
+
IO.pure(input(f"input the {i}th str")) for i in range(1, n + 1)
|
955 |
+
])
|
956 |
return (get_chars,)
|
957 |
|
958 |
|
959 |
@app.cell
|
960 |
+
def _() -> None:
|
961 |
# get_chars()()
|
962 |
return
|
963 |
|
964 |
|
965 |
@app.cell(hide_code=True)
|
966 |
+
def _(mo) -> None:
|
967 |
mo.md(r"""# From the perspective of category theory""")
|
|
|
968 |
|
969 |
|
970 |
@app.cell(hide_code=True)
|
971 |
+
def _(mo) -> None:
|
972 |
mo.md(
|
973 |
r"""
|
974 |
## Lax Monoidal Functor
|
|
|
976 |
An alternative, equivalent formulation of `Applicative` is given by
|
977 |
"""
|
978 |
)
|
|
|
979 |
|
980 |
|
981 |
@app.cell
|
|
|
997 |
|
998 |
|
999 |
@app.cell(hide_code=True)
|
1000 |
+
def _(mo) -> None:
|
1001 |
mo.md(
|
1002 |
r"""
|
1003 |
+
Intuitively, this states that a *monoidal functor* is one which has some sort of "default shape" and which supports some sort of "combining" operation.
|
1004 |
|
1005 |
- `unit` provides the identity element
|
1006 |
- `tensor` combines two contexts into a product context
|
|
|
1008 |
More technically, the idea is that `monoidal functor` preserves the "monoidal structure" given by the pairing constructor `(,)` and unit type `()`.
|
1009 |
"""
|
1010 |
)
|
|
|
1011 |
|
1012 |
|
1013 |
@app.cell(hide_code=True)
|
1014 |
+
def _(mo) -> None:
|
1015 |
mo.md(
|
1016 |
r"""
|
1017 |
+
Furthermore, to deserve the name "monoidal", instances of Monoidal ought to satisfy the following laws, which seem much more straightforward than the traditional Applicative laws:
|
1018 |
|
1019 |
- Left identity
|
1020 |
|
|
|
1029 |
`tensor(u, tensor(v, w)) ≅ tensor(tensor(u, v), w)`
|
1030 |
"""
|
1031 |
)
|
|
|
1032 |
|
1033 |
|
1034 |
@app.cell(hide_code=True)
|
1035 |
+
def _(mo) -> None:
|
1036 |
mo.md(
|
1037 |
r"""
|
1038 |
/// admonition | ≅ indicates isomorphism
|
|
|
1044 |
///
|
1045 |
"""
|
1046 |
)
|
|
|
1047 |
|
1048 |
|
1049 |
@app.cell(hide_code=True)
|
1050 |
+
def _(mo) -> None:
|
1051 |
mo.md(
|
1052 |
r"""
|
1053 |
## Mutual definability of Monoidal and Applicative
|
|
|
1065 |
```
|
1066 |
"""
|
1067 |
)
|
|
|
1068 |
|
1069 |
|
1070 |
@app.cell(hide_code=True)
|
1071 |
+
def _(mo) -> None:
|
1072 |
mo.md(
|
1073 |
r"""
|
1074 |
## Instance: ListMonoidal
|
|
|
1084 |
The implementation is:
|
1085 |
"""
|
1086 |
)
|
|
|
1087 |
|
1088 |
|
1089 |
@app.cell
|
|
|
1111 |
|
1112 |
|
1113 |
@app.cell(hide_code=True)
|
1114 |
+
def _(mo) -> None:
|
1115 |
mo.md(r"""> try with `ListMonoidal` below""")
|
|
|
1116 |
|
1117 |
|
1118 |
@app.cell
|
|
|
1124 |
|
1125 |
|
1126 |
@app.cell(hide_code=True)
|
1127 |
+
def _(mo) -> None:
|
1128 |
mo.md(r"""and we can prove that `tensor(fa, fb) = lift(lambda fa: lambda fb: (fa, fb), fa, fb)`:""")
|
|
|
1129 |
|
1130 |
|
1131 |
@app.cell
|
1132 |
+
def _(List, xs, ys) -> None:
|
1133 |
List.lift(lambda fa: lambda fb: (fa, fb), List(xs.items), List(ys.items))
|
|
|
1134 |
|
1135 |
|
1136 |
@app.cell(hide_code=True)
|
|
|
1140 |
@classmethod
|
1141 |
@abstractmethod
|
1142 |
def fmap(cls, f: Callable[[A], B], a: "Functor[A]") -> "Functor[B]":
|
1143 |
+
msg = "Subclasses must implement fmap"
|
1144 |
+
raise NotImplementedError(msg)
|
1145 |
|
1146 |
@classmethod
|
1147 |
def const(cls, a: "Functor[A]", b: B) -> "Functor[B]":
|
|
|
1161 |
|
1162 |
@app.cell(hide_code=True)
|
1163 |
def _():
|
|
|
1164 |
from abc import ABC, abstractmethod
|
|
|
1165 |
from collections.abc import Callable
|
1166 |
+
from dataclasses import dataclass
|
1167 |
+
from typing import TypeVar, Union
|
1168 |
return ABC, Callable, TypeVar, Union, abstractmethod, dataclass
|
1169 |
|
1170 |
|
|
|
1183 |
|
1184 |
|
1185 |
@app.cell(hide_code=True)
|
1186 |
+
def _(mo) -> None:
|
1187 |
+
mo.md(
|
1188 |
+
r"""
|
1189 |
+
# From Applicative to Alternative
|
1190 |
+
|
1191 |
+
## Abstracting Alternative
|
1192 |
+
|
1193 |
+
In our studies so far, we saw that both `Maybe` and `List` can represent computations with a varying number of results.
|
1194 |
+
|
1195 |
+
We use `Maybe` to indicate a computation can fail somehow and `List` for computations that can have many possible results. In both of these cases, one useful operation is amalgamating all possible results from multiple computations into a single computation.
|
1196 |
+
|
1197 |
+
`Alternative` formalizes computations that support:
|
1198 |
+
|
1199 |
+
- **Failure** (empty result)
|
1200 |
+
- **Choice** (combination of results)
|
1201 |
+
- **Repetition** (multiple results)
|
1202 |
+
|
1203 |
+
It extends `Applicative` with monoidal structure, where:
|
1204 |
+
|
1205 |
+
```python
|
1206 |
+
@dataclass
|
1207 |
+
class Alternative[A](Applicative, ABC):
|
1208 |
+
@classmethod
|
1209 |
+
@abstractmethod
|
1210 |
+
def empty(cls) -> "Alternative[A]":
|
1211 |
+
'''Identity element for alternative computations'''
|
1212 |
+
|
1213 |
+
@classmethod
|
1214 |
+
@abstractmethod
|
1215 |
+
def alt(
|
1216 |
+
cls, fa: "Alternative[A]", fb: "Alternative[A]"
|
1217 |
+
) -> "Alternative[A]":
|
1218 |
+
'''Binary operation combining computations'''
|
1219 |
+
```
|
1220 |
+
|
1221 |
+
- `empty` is the identity element (e.g., `Maybe(None)`, `List([])`)
|
1222 |
+
- `alt` is a combination operator (e.g., `Maybe` fallback, list concatenation)
|
1223 |
+
|
1224 |
+
`empty` and `alt` should satisfy the following **laws**:
|
1225 |
+
|
1226 |
+
```python
|
1227 |
+
# Left identity
|
1228 |
+
alt(empty, fa) == fa
|
1229 |
+
# Right identity
|
1230 |
+
alt(fa, empty) == fa
|
1231 |
+
# Associativity
|
1232 |
+
alt(fa, alt(fb, fc)) == alt(alt(fa, fb), fc)
|
1233 |
+
```
|
1234 |
+
|
1235 |
+
/// admonition
|
1236 |
+
Actually, `Alternative` is a *monoid* on `Applicative Functors`. We will talk about *monoid* and review these laws in the next notebook about `Monads`.
|
1237 |
+
///
|
1238 |
+
|
1239 |
+
/// attention | minimal implementation requirement
|
1240 |
+
- `empty`
|
1241 |
+
- `alt`
|
1242 |
+
///
|
1243 |
+
"""
|
1244 |
+
)
|
1245 |
+
|
1246 |
+
|
1247 |
+
@app.cell(hide_code=True)
|
1248 |
+
def _(mo) -> None:
|
1249 |
+
mo.md(
|
1250 |
+
r"""
|
1251 |
+
## Instances of Alternative
|
1252 |
+
|
1253 |
+
### The Maybe Alternative
|
1254 |
+
|
1255 |
+
- `empty`: the identity element of `Maybe` is `Maybe(None)`
|
1256 |
+
- `alt`: return the first element if it's not `None`, else return the second element
|
1257 |
+
"""
|
1258 |
+
)
|
1259 |
+
|
1260 |
+
|
1261 |
+
@app.cell
|
1262 |
+
def _(Alternative, Maybe, dataclass):
|
1263 |
+
@dataclass
|
1264 |
+
class AltMaybe[A](Maybe, Alternative):
|
1265 |
+
@classmethod
|
1266 |
+
def empty(cls) -> "AltMaybe[A]":
|
1267 |
+
return cls(None)
|
1268 |
+
|
1269 |
+
@classmethod
|
1270 |
+
def alt(cls, fa: "AltMaybe[A]", fb: "AltMaybe[A]") -> "AltMaybe[A]":
|
1271 |
+
if fa.value is not None:
|
1272 |
+
return cls(fa.value)
|
1273 |
+
return cls(fb.value)
|
1274 |
+
|
1275 |
+
def __repr__(self):
|
1276 |
+
return "Nothing" if self.value is None else f"Just({self.value!r})"
|
1277 |
+
return (AltMaybe,)
|
1278 |
+
|
1279 |
+
|
1280 |
+
@app.cell
|
1281 |
+
def _(AltMaybe) -> None:
|
1282 |
+
print(AltMaybe.empty())
|
1283 |
+
print(AltMaybe.alt(AltMaybe(None), AltMaybe(1)))
|
1284 |
+
print(AltMaybe.alt(AltMaybe(None), AltMaybe(None)))
|
1285 |
+
print(AltMaybe.alt(AltMaybe(1), AltMaybe(None)))
|
1286 |
+
print(AltMaybe.alt(AltMaybe(1), AltMaybe(2)))
|
1287 |
+
|
1288 |
+
|
1289 |
+
@app.cell
|
1290 |
+
def _(AltMaybe) -> None:
|
1291 |
+
print(AltMaybe.check_left_identity(AltMaybe(1)))
|
1292 |
+
print(AltMaybe.check_right_identity(AltMaybe(1)))
|
1293 |
+
print(AltMaybe.check_associativity(AltMaybe(1), AltMaybe(2), AltMaybe(None)))
|
1294 |
+
|
1295 |
+
|
1296 |
+
@app.cell(hide_code=True)
|
1297 |
+
def _(mo) -> None:
|
1298 |
+
mo.md(
|
1299 |
+
r"""
|
1300 |
+
### The List Alternative
|
1301 |
+
|
1302 |
+
- `empty`: the identity element of `List` is `List([])`
|
1303 |
+
- `alt`: return the concatenation of 2 input lists
|
1304 |
+
"""
|
1305 |
+
)
|
1306 |
+
|
1307 |
+
|
1308 |
+
@app.cell
|
1309 |
+
def _(Alternative, List, dataclass):
|
1310 |
+
@dataclass
|
1311 |
+
class AltList[A](List, Alternative):
|
1312 |
+
@classmethod
|
1313 |
+
def empty(cls) -> "AltList[A]":
|
1314 |
+
return cls([])
|
1315 |
+
|
1316 |
+
@classmethod
|
1317 |
+
def alt(cls, fa: "AltList[A]", fb: "AltList[A]") -> "AltList[A]":
|
1318 |
+
return cls(fa.value + fb.value)
|
1319 |
+
return (AltList,)
|
1320 |
+
|
1321 |
+
|
1322 |
+
@app.cell
|
1323 |
+
def _(AltList) -> None:
|
1324 |
+
print(AltList.empty())
|
1325 |
+
print(AltList.alt(AltList([1, 2, 3]), AltList([4, 5])))
|
1326 |
+
|
1327 |
+
|
1328 |
+
@app.cell
|
1329 |
+
def _(AltList) -> None:
|
1330 |
+
AltList([1])
|
1331 |
+
|
1332 |
+
|
1333 |
+
@app.cell
|
1334 |
+
def _(AltList) -> None:
|
1335 |
+
AltList([1])
|
1336 |
+
|
1337 |
+
|
1338 |
+
@app.cell
|
1339 |
+
def _(AltList) -> None:
|
1340 |
+
print(AltList.check_left_identity(AltList([1, 2, 3])))
|
1341 |
+
print(AltList.check_right_identity(AltList([1, 2, 3])))
|
1342 |
+
print(
|
1343 |
+
AltList.check_associativity(
|
1344 |
+
AltList([1, 2]), AltList([3, 4, 5]), AltList([6])
|
1345 |
+
)
|
1346 |
+
)
|
1347 |
+
|
1348 |
+
|
1349 |
+
@app.cell(hide_code=True)
|
1350 |
+
def _(mo) -> None:
|
1351 |
+
mo.md(
|
1352 |
+
r"""
|
1353 |
+
## some and many
|
1354 |
+
|
1355 |
+
|
1356 |
+
/// admonition | This section mainly refers to
|
1357 |
+
|
1358 |
+
- https://stackoverflow.com/questions/7671009/some-and-many-functions-from-the-alternative-type-class/7681283#7681283
|
1359 |
+
|
1360 |
+
///
|
1361 |
+
|
1362 |
+
First let's have a look at the implementation of `some` and `many`:
|
1363 |
+
|
1364 |
+
```python
|
1365 |
+
@classmethod
|
1366 |
+
def some(cls, fa: "Alternative[A]") -> "Alternative[list[A]]":
|
1367 |
+
# Short-circuit if input is empty
|
1368 |
+
if fa == cls.empty():
|
1369 |
+
return cls.empty()
|
1370 |
+
|
1371 |
+
return cls.apply(
|
1372 |
+
cls.fmap(lambda a: lambda b: [a] + b, fa), cls.many(fa)
|
1373 |
+
)
|
1374 |
+
|
1375 |
+
@classmethod
|
1376 |
+
def many(cls, fa: "Alternative[A]") -> "Alternative[list[A]]":
|
1377 |
+
# Directly return empty list if input is empty
|
1378 |
+
if fa == cls.empty():
|
1379 |
+
return cls.pure([])
|
1380 |
+
|
1381 |
+
return cls.alt(cls.some(fa), cls.pure([]))
|
1382 |
+
```
|
1383 |
+
|
1384 |
+
So `some f` runs `f` once, then *many* times, and conses the results. `many f` runs f *some* times, or *alternatively* just returns the empty list.
|
1385 |
+
|
1386 |
+
The idea is that they both run `f` as often as possible until it **fails**, collecting the results in a list. The difference is that `some f` immediately fails if `f` fails, while `many f` will still succeed and *return* the empty list in such a case. But what all this exactly means depends on how `alt` is defined.
|
1387 |
+
|
1388 |
+
Let's see what it does for the instances `AltMaybe` and `AltList`.
|
1389 |
+
"""
|
1390 |
+
)
|
1391 |
+
|
1392 |
+
|
1393 |
+
@app.cell(hide_code=True)
|
1394 |
+
def _(mo) -> None:
|
1395 |
+
mo.md(r"""For `AltMaybe`. `None` means failure, so some `None` fails as well and evaluates to `None` while many `None` succeeds and evaluates to `Just []`. Both `some (Just ())` and `many (Just ())` never return, because `Just ()` never fails.""")
|
1396 |
+
|
1397 |
+
|
1398 |
+
@app.cell
|
1399 |
+
def _(AltMaybe) -> None:
|
1400 |
+
print(AltMaybe.some(AltMaybe.empty()))
|
1401 |
+
print(AltMaybe.many(AltMaybe.empty()))
|
1402 |
+
|
1403 |
+
|
1404 |
+
@app.cell(hide_code=True)
|
1405 |
+
def _(mo) -> None:
|
1406 |
+
mo.md(r"""For `AltList`, `[]` means failure, so `some []` evaluates to `[]` (no answers) while `many []` evaluates to `[[]]` (there's one answer and it is the empty list). Again `some [()]` and `many [()]` don't return.""")
|
1407 |
+
|
1408 |
+
|
1409 |
+
@app.cell
|
1410 |
+
def _(AltList) -> None:
|
1411 |
+
print(AltList.some(AltList.empty()))
|
1412 |
+
print(AltList.many(AltList.empty()))
|
1413 |
+
|
1414 |
+
|
1415 |
+
@app.cell(hide_code=True)
|
1416 |
+
def _(mo) -> None:
|
1417 |
+
mo.md(r"""## Formal implementation of Alternative""")
|
1418 |
+
|
1419 |
+
|
1420 |
+
@app.cell
|
1421 |
+
def _(ABC, Applicative, abstractmethod, dataclass):
|
1422 |
+
@dataclass
|
1423 |
+
class Alternative[A](Applicative, ABC):
|
1424 |
+
"""A monoid on applicative functors."""
|
1425 |
+
|
1426 |
+
@classmethod
|
1427 |
+
@abstractmethod
|
1428 |
+
def empty(cls) -> "Alternative[A]":
|
1429 |
+
msg = "Subclasses must implement empty"
|
1430 |
+
raise NotImplementedError(msg)
|
1431 |
+
|
1432 |
+
@classmethod
|
1433 |
+
@abstractmethod
|
1434 |
+
def alt(
|
1435 |
+
cls, fa: "Alternative[A]", fb: "Alternative[A]"
|
1436 |
+
) -> "Alternative[A]":
|
1437 |
+
msg = "Subclasses must implement alt"
|
1438 |
+
raise NotImplementedError(msg)
|
1439 |
+
|
1440 |
+
@classmethod
|
1441 |
+
def some(cls, fa: "Alternative[A]") -> "Alternative[list[A]]":
|
1442 |
+
# Short-circuit if input is empty
|
1443 |
+
if fa == cls.empty():
|
1444 |
+
return cls.empty()
|
1445 |
+
|
1446 |
+
return cls.apply(
|
1447 |
+
cls.fmap(lambda a: lambda b: [a, *b], fa), cls.many(fa)
|
1448 |
+
)
|
1449 |
+
|
1450 |
+
@classmethod
|
1451 |
+
def many(cls, fa: "Alternative[A]") -> "Alternative[list[A]]":
|
1452 |
+
# Directly return empty list if input is empty
|
1453 |
+
if fa == cls.empty():
|
1454 |
+
return cls.pure([])
|
1455 |
+
|
1456 |
+
return cls.alt(cls.some(fa), cls.pure([]))
|
1457 |
+
|
1458 |
+
@classmethod
|
1459 |
+
def check_left_identity(cls, fa: "Alternative[A]") -> bool:
|
1460 |
+
return cls.alt(cls.empty(), fa) == fa
|
1461 |
+
|
1462 |
+
@classmethod
|
1463 |
+
def check_right_identity(cls, fa: "Alternative[A]") -> bool:
|
1464 |
+
return cls.alt(fa, cls.empty()) == fa
|
1465 |
+
|
1466 |
+
@classmethod
|
1467 |
+
def check_associativity(
|
1468 |
+
cls, fa: "Alternative[A]", fb: "Alternative[A]", fc: "Alternative[A]"
|
1469 |
+
) -> bool:
|
1470 |
+
return cls.alt(fa, cls.alt(fb, fc)) == cls.alt(cls.alt(fa, fb), fc)
|
1471 |
+
return (Alternative,)
|
1472 |
+
|
1473 |
+
|
1474 |
+
@app.cell(hide_code=True)
|
1475 |
+
def _(mo) -> None:
|
1476 |
+
mo.md(
|
1477 |
+
r"""
|
1478 |
+
/// admonition
|
1479 |
+
|
1480 |
+
We will explore more about `Alternative` in a future notebooks about [Monadic Parsing](https://www.cambridge.org/core/journals/journal-of-functional-programming/article/monadic-parsing-in-haskell/E557DFCCE00E0D4B6ED02F3FB0466093)
|
1481 |
+
|
1482 |
+
///
|
1483 |
+
"""
|
1484 |
+
)
|
1485 |
+
|
1486 |
+
|
1487 |
+
@app.cell(hide_code=True)
|
1488 |
+
def _(mo) -> None:
|
1489 |
mo.md(
|
1490 |
r"""
|
1491 |
# Further reading
|
|
|
1508 |
- [Applicative Functors](https://bartoszmilewski.com/2017/02/06/applicative-functors/)
|
1509 |
"""
|
1510 |
)
|
|
|
1511 |
|
1512 |
|
1513 |
if __name__ == "__main__":
|
functional_programming/CHANGELOG.md
CHANGED
@@ -1,47 +1,65 @@
|
|
1 |
# Changelog of the functional-programming course
|
2 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
3 |
## 2025-04-11
|
4 |
|
5 |
**functors.py**
|
6 |
|
7 |
-
|
8 |
-
|
|
|
9 |
|
10 |
## 2025-04-08
|
11 |
|
12 |
**functors.py**
|
13 |
|
14 |
-
|
15 |
-
|
16 |
-
|
17 |
-
|
18 |
-
+ add `unzip` utility function for functors
|
19 |
|
|
|
|
|
|
|
20 |
|
21 |
## 2025-04-07
|
22 |
|
23 |
**applicatives.py**
|
24 |
|
25 |
-
|
26 |
-
|
27 |
-
|
28 |
-
|
29 |
-
|
30 |
-
|
|
|
|
|
|
|
|
|
|
|
31 |
|
32 |
## 2025-04-06
|
33 |
|
34 |
**applicatives.py**
|
35 |
|
36 |
-
- remove `sequenceL` from `Applicative` because it should be a classmethod but can't be
|
|
|
37 |
|
38 |
## 2025-04-02
|
39 |
|
40 |
**functors.py**
|
41 |
|
42 |
-
|
43 |
|
44 |
-
|
45 |
|
46 |
```python
|
47 |
class Functor(Generic[A])
|
@@ -55,18 +73,18 @@
|
|
55 |
|
56 |
for conciseness
|
57 |
|
58 |
-
|
59 |
|
60 |
**applicatives.py**
|
61 |
|
62 |
-
|
63 |
|
64 |
## 2025-03-16
|
65 |
|
66 |
**functors.py**
|
67 |
|
68 |
-
|
69 |
-
|
70 |
|
71 |
For example:
|
72 |
|
@@ -83,21 +101,24 @@
|
|
83 |
Wrapper(value=2)
|
84 |
```
|
85 |
|
86 |
-
|
|
|
87 |
- Rename `ListWrapper` to `List` for simplicity
|
88 |
- Remove the `Just` class
|
89 |
-
|
|
|
90 |
|
91 |
## 2025-03-13
|
92 |
|
93 |
**functors.py**
|
94 |
|
95 |
-
|
96 |
|
97 |
-
Thank [Akshay](https://github.com/akshayka) and [Haleshot](https://github.com/Haleshot)
|
|
|
98 |
|
99 |
## 2025-03-11
|
100 |
|
101 |
**functors.py**
|
102 |
|
103 |
-
|
|
|
1 |
# Changelog of the functional-programming course
|
2 |
|
3 |
+
## 2025-04-16
|
4 |
+
|
5 |
+
**applicatives.py**
|
6 |
+
|
7 |
+
- replace `return NotImplementedError` with `raise NotImplementedError`
|
8 |
+
|
9 |
+
- add `Either` applicative
|
10 |
+
- Add `Alternative`
|
11 |
+
|
12 |
## 2025-04-11
|
13 |
|
14 |
**functors.py**
|
15 |
|
16 |
+
- add `Bifunctor` section
|
17 |
+
|
18 |
+
- replace `return NotImplementedError` with `raise NotImplementedError`
|
19 |
|
20 |
## 2025-04-08
|
21 |
|
22 |
**functors.py**
|
23 |
|
24 |
+
- restructure the notebook
|
25 |
+
- replace `f` in the function signatures with `g` to indicate regular functions and
|
26 |
+
distinguish from functors
|
27 |
+
- move `Maybe` funtor to section `More Functor instances`
|
|
|
28 |
|
29 |
+
- add `Either` functor
|
30 |
+
|
31 |
+
- add `unzip` utility function for functors
|
32 |
|
33 |
## 2025-04-07
|
34 |
|
35 |
**applicatives.py**
|
36 |
|
37 |
+
- the `apply` method of `Maybe` _Applicative_ should return `None` when `fg` or `fa` is
|
38 |
+
`None`
|
39 |
+
|
40 |
+
- add `sequenceL` as a classmethod for `Applicative` and add examples for `Wrapper`,
|
41 |
+
`Maybe`, `List`
|
42 |
+
- add description for utility functions of `Applicative`
|
43 |
+
|
44 |
+
- refine the implementation of `IO` _Applicative_
|
45 |
+
- reimplement `get_chars` with `IO.sequenceL`
|
46 |
+
|
47 |
+
- add an example to show that `ListMonoidal` is equivalent to `List` _Applicative_
|
48 |
|
49 |
## 2025-04-06
|
50 |
|
51 |
**applicatives.py**
|
52 |
|
53 |
+
- remove `sequenceL` from `Applicative` because it should be a classmethod but can't be
|
54 |
+
generically implemented
|
55 |
|
56 |
## 2025-04-02
|
57 |
|
58 |
**functors.py**
|
59 |
|
60 |
+
- Migrate to `python3.13`
|
61 |
|
62 |
+
- Replace all occurrences of
|
63 |
|
64 |
```python
|
65 |
class Functor(Generic[A])
|
|
|
73 |
|
74 |
for conciseness
|
75 |
|
76 |
+
- Use `fa` in function signatures instead of `a` when `fa` is a _Functor_
|
77 |
|
78 |
**applicatives.py**
|
79 |
|
80 |
+
- `0.1.0` version of notebook `06_applicatives.py`
|
81 |
|
82 |
## 2025-03-16
|
83 |
|
84 |
**functors.py**
|
85 |
|
86 |
+
- Use uppercased letters for `Generic` types, e.g. `A = TypeVar("A")`
|
87 |
+
- Refactor the `Functor` class, changing `fmap` and utility methods to `classmethod`
|
88 |
|
89 |
For example:
|
90 |
|
|
|
101 |
Wrapper(value=2)
|
102 |
```
|
103 |
|
104 |
+
- Move the `check_functor_law` method from `Functor` class to a standard function
|
105 |
+
|
106 |
- Rename `ListWrapper` to `List` for simplicity
|
107 |
- Remove the `Just` class
|
108 |
+
|
109 |
+
- Rewrite proofs
|
110 |
|
111 |
## 2025-03-13
|
112 |
|
113 |
**functors.py**
|
114 |
|
115 |
+
- `0.1.0` version of notebook `05_functors`
|
116 |
|
117 |
+
Thank [Akshay](https://github.com/akshayka) and [Haleshot](https://github.com/Haleshot)
|
118 |
+
for reviewing
|
119 |
|
120 |
## 2025-03-11
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**functors.py**
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- Demo version of notebook `05_functors.py`
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