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https://github.com/higherkindness/droste
recursion schemes for cats; to iterate is human, to recurse, divine
https://github.com/higherkindness/droste
functional-programming recursion-schemes scala
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recursion schemes for cats; to iterate is human, to recurse, divine
- Host: GitHub
- URL: https://github.com/higherkindness/droste
- Owner: higherkindness
- License: apache-2.0
- Created: 2018-01-12T08:17:00.000Z (almost 7 years ago)
- Default Branch: main
- Last Pushed: 2024-05-06T05:21:34.000Z (6 months ago)
- Last Synced: 2024-05-19T05:53:10.356Z (6 months ago)
- Topics: functional-programming, recursion-schemes, scala
- Language: Scala
- Homepage:
- Size: 1.43 MB
- Stars: 384
- Watchers: 24
- Forks: 51
- Open Issues: 27
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.md
- Code of conduct: CODE_OF_CONDUCT.md
- Authors: AUTHORS.md
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README
# Droste
[](https://gitter.im/higherkindness/droste?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
Droste is a recursion library for Scala.
**SBT installation**
Select a tagged release version (`x.y.z`) and then add the following
to your SBT build:
```scala
libraryDependencies += "io.higherkindness" %% "droste-core" % "x.y.z"
```
# Usage
Droste makes it easy to assemble morphisms. For example, calculating
Fibonacci values can be done with a histomorphism if we model natural
numbers as a chain of `Option`. We can easily unfold with an
anamorphism and then fold to our result with a histomorphism.
```scala
import higherkindness.droste._
import higherkindness.droste.data._
val natCoalgebra: Coalgebra[Option, BigDecimal] =
Coalgebra(n => if (n > 0) Some(n - 1) else None)
val fibAlgebra: CVAlgebra[Option, BigDecimal] = CVAlgebra {
case Some(r1 :< Some(r2 :< _)) => r1 + r2
case Some(_ :< None) => 1
case None => 0
}
val fib: BigDecimal => BigDecimal = scheme.ghylo(
fibAlgebra.gather(Gather.histo),
natCoalgebra.scatter(Scatter.ana))
```
```scala
fib(0)
// res0: BigDecimal = 0
fib(1)
// res1: BigDecimal = 1
fib(2)
// res2: BigDecimal = 1
fib(10)
// res3: BigDecimal = 55
fib(100)
// res4: BigDecimal = 354224848179261915075
```
An anamorphism followed by a histomorphism is also known as a
dynamorphism. Recursion scheme animals like dyna are available
in the zoo:
```scala
val fibAlt: BigDecimal => BigDecimal =
scheme.zoo.dyna(fibAlgebra, natCoalgebra)
```
```scala
fibAlt(0)
// res5: BigDecimal = 0
fibAlt(1)
// res6: BigDecimal = 1
fibAlt(2)
// res7: BigDecimal = 1
fibAlt(10)
// res8: BigDecimal = 55
fibAlt(100)
// res9: BigDecimal = 354224848179261915075
```
What if we want to do two things at once? Let's calculate a
Fibonacci value and the sum of all squares.
```scala
val fromNatAlgebra: Algebra[Option, BigDecimal] = Algebra {
case Some(n) => n + 1
case None => 0
}
// note: n is the fromNatAlgebra helper value from the previous level of recursion
val sumSquaresAlgebra: RAlgebra[BigDecimal, Option, BigDecimal] = RAlgebra {
case Some((n, value)) => value + (n + 1) * (n + 1)
case None => 0
}
val sumSquares: BigDecimal => BigDecimal = scheme.ghylo(
sumSquaresAlgebra.gather(Gather.zygo(fromNatAlgebra)),
natCoalgebra.scatter(Scatter.ana))
```
```scala
sumSquares(0)
// res10: BigDecimal = 0
sumSquares(1)
// res11: BigDecimal = 1
sumSquares(2)
// res12: BigDecimal = 5
sumSquares(10)
// res13: BigDecimal = 385
sumSquares(100)
// res14: BigDecimal = 338350
```
Now we can zip the two algebras into one so that we calculate
both results in one pass.
```scala
val fused: BigDecimal => (BigDecimal, BigDecimal) =
scheme.ghylo(
fibAlgebra.gather(Gather.histo) zip
sumSquaresAlgebra.gather(Gather.zygo(fromNatAlgebra)),
natCoalgebra.scatter(Scatter.ana))
```
```scala
fused(0)
// res15: (BigDecimal, BigDecimal) = (0, 0)
fused(1)
// res16: (BigDecimal, BigDecimal) = (1, 1)
fused(2)
// res17: (BigDecimal, BigDecimal) = (1, 5)
fused(10)
// res18: (BigDecimal, BigDecimal) = (55, 385)
fused(100)
// res19: (BigDecimal, BigDecimal) = (354224848179261915075, 338350)
```
Droste includes [athema](athema), a math expression parser/processor,
as a more extensive example of recursion schemes.
# Credits
A substantial amount of Droste's code is a derivation-- or an
alternative encoding-- of patterns pioneered by others. Droste has
benefited from the excellent work in many other recursion libraries,
blog posts, academic papers, etc. Notably, Droste has benefited from:
- [recursion-schemes](https://github.com/ekmett/recursion-schemes)
- [Matryoshka](https://github.com/slamdata/matryoshka)
Thank you to everyone involved. Additionally, thanks to Greg Pfeil
(@sellout) for answering my random questions over the last few years
while I've been slowly learning (and using recursion) schemes.
# Copyright and License
Copyright the maintainers, 2018-present.
All code is available to you under the Apache License, Version 2.0,
available at http://www.apache.org/licenses/LICENSE-2.0.
Logos provided by the very excellent [@impurepics](https://twitter.com/impurepics).
# Disclamer
Please be advised that I have no idea what I am doing.
Nevertheless, this project is already being used for real
work with real data in real life.