Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Try Cats
Search
fuzyco
January 11, 2018
Technology
0
550
Try Cats
Scalaの関数型ライブラリCatsをやってみた話です。
fuzyco
January 11, 2018
Tweet
Share
More Decks by fuzyco
See All by fuzyco
Functional Error&Retry Handling
hiroki6
2
520
Extensible Effects: beyond the Monad Transformers
hiroki6
1
760
High Performance Scala/high_performance_scala
hiroki6
4
4k
並行四方山話/tales_of_concurrency
hiroki6
0
91
Scalaでの並行・並列処理戦略/strategy-for-concurrency-and-parallel-by-scala
hiroki6
9
2.9k
Monad Error with Cats/monad-error-with-cats
hiroki6
0
580
scala_multi_thread.pdf
hiroki6
0
310
GAEを用いたBQ Load戦略/gae_bq_load_strategy
hiroki6
2
1.8k
Extensible Effects with Scala/eff-with-scala
hiroki6
0
990
Other Decks in Technology
See All in Technology
IAMのマニアックな話 2025 ~40分バージョン ~
nrinetcom
PRO
8
920
Explainable Software Engineering in the Public Sector
avandeursen
0
360
頻繁リリース × 高品質 = 無理ゲー? いや、できます!/20250306 Shoki Hyo
shift_evolve
0
150
AIエージェントキャッチアップと論文リサーチ
os1ma
6
1.2k
セマンティックレイヤー入門
ikkimiyazaki
8
3.2k
お問い合わせ対応の改善取り組みとその進め方
masartz
1
370
DevinはクラウドエンジニアAIになれるのか!? 実践的なガードレール設計/devin-can-become-a-cloud-engineer-ai-practical-guardrail-design
tomoki10
3
1.3k
Symfony in 2025: Scaling to 0
fabpot
2
190
非エンジニアにも伝えるメールセキュリティ / Email security for non-engineers
ykanoh
13
3.9k
AI・LLM事業部のSREとタスクの自動運転
shinyorke
PRO
0
300
チームの性質によって変わる ADR との向き合い方と、生成 AI 時代のこれから / How to deal with ADR depends on the characteristics of the team
mh4gf
4
330
Cline、めっちゃ便利、お金が飛ぶ💸
iwamot
19
18k
Featured
See All Featured
The Illustrated Children's Guide to Kubernetes
chrisshort
48
49k
Building Your Own Lightsaber
phodgson
104
6.3k
How to train your dragon (web standard)
notwaldorf
91
5.9k
Faster Mobile Websites
deanohume
306
31k
The Cost Of JavaScript in 2023
addyosmani
48
7.6k
Fireside Chat
paigeccino
37
3.3k
Designing Dashboards & Data Visualisations in Web Apps
destraynor
231
53k
ピンチをチャンスに:未来をつくるプロダクトロードマップ #pmconf2020
aki_iinuma
118
51k
Building an army of robots
kneath
304
45k
Helping Users Find Their Own Way: Creating Modern Search Experiences
danielanewman
29
2.5k
Code Reviewing Like a Champion
maltzj
522
39k
Understanding Cognitive Biases in Performance Measurement
bluesmoon
28
1.6k
Transcript
5SZ$BUT
ΞδΣϯμ w $BUTͱ w $BUTಠࣗͷϞφυ w $BUTΛ௨ֶͯ͠Μͩ͜ͱ
$BUTͱ 4DBMB[ͷ෦྾ʹΑͬͯੜ·Εͨ ؔܕϓϩάϥϛϯά༻ͷ4DBMBϥΠϒϥϦ ɾࠒੜ ɾʹWϦϦʔε ɾݍ DBUFHPSZ ʹ༝དྷ ಡΜͩจݙ ɾೣ൪IUUQFFETJODPNIFSEJOHDBUTKB
ɾ4DBMB8JUI$BUT
$BUTͷಛ ɾؔܕϓϩάϥϛϯάΛ࣮ݱ͢ΔͨΊͷ ๛ͳܕΫϥεͷఏڙ ɾIBTLFMMʹ͍࣮ۙ &Rɺ4IPXͳͲ
$BUTWT4DBMB[ $BUT ɾ৽͍͠σʔλܕ ɾ࣮༻্ඞཁͳશͯͷ൚༻ؔͷ࣮ ΞυϗοΫଟ૬ੑɺUSBJU JNQMJDJU ೣ൪ΑΓҾ༻ 4DBMB[ ɾ৽͍͠σʔλܕ
ɾඪ४Ϋϥεͷ֦ு 0QUJPO0QT -JTU0QT ɾ࣮༻্ඞཁͳશͯͷ൚༻ؔͷ࣮ ΞυϗοΫଟ૬ੑɺUSBJU JNQMJDJU ಠश4DBMB[ΑΓҾ༻
$BUTWT4DBMB[ &JUIFSa 7BMJEBUFE7BMJEBUJPO 3FBEFS3FBEFS 4UBUF4UBUF 8SJUFS8SJUFS ɾ༻ҙ͞Ε͍ͯΔϝιου͕Ұ෦ҟͳΔ͕ɺ ಉ͡Α͏ͳσʔλܕ͕͋Δ
$BUTಠࣗͷϞφυ ɾ&WBM
&WBMϞφυ ධՁΛ੍ޚ͢Δσʔλܕ import cats.Eval // valͷΑ͏ʹఆٛ࣌ʹධՁ val x = Eval.now
{ println("Computing X") math.random } // Computing X // x: cats.Eval[Double] = Now(0.8724950064732552) // defͷΑ͏ʹৗʹධՁ val y = Eval.always { println("Computing Y") math.random } // y: cats.Eval[Double] = cats.Always@5212e1f5 // lazy valͷΑ͏ʹԆධՁ val z = Eval.later { println("Computing Z") math.random } // z: cats.Eval[Double] = cats.Later@33eda11
&WBMϞφυ ධՁΛ੍ޚ͢Δσʔλܕ x.value // first access // res9: Double =
0.8724950064732552 x.value // second access // res10: Double = 0.8724950064732552 y.value // first access // Computing Y // res11: Double = 0.8795680260041828 y.value // second access // Computing Y // res12: Double = 0.5640213059400854 z.value // first access // Computing Z // res13: Double = 0.5813583535421343 z.value // second access // res14: Double = 0.5813583535421343 import cats.Eval // valͷΑ͏ʹఆٛ࣌ʹධՁ val x = Eval.now { println("Computing X") math.random } // Computing X // x: cats.Eval[Double] = Now(0.8724950064732552) // defͷΑ͏ʹৗʹධՁ val y = Eval.always { println("Computing Y") math.random } // y: cats.Eval[Double] = cats.Always@5212e1f5 // lazy valͷΑ͏ʹԆධՁ val z = Eval.later { println("Computing Z") math.random } // z: cats.Eval[Double] = cats.Later@33eda11
&WBMʹΑΔ࠶ؼॲཧ def factorial(n: BigInt): BigInt = if(n == 1) n
else n * factorial(n - 1) factorial(50000) // ࣮ߦ ඌ࠶ؼͰͳ͍࠶ؼؔ
&WBMʹΑΔ࠶ؼॲཧ def factorial(n: BigInt): BigInt = if(n == 1) n
else n * factorial(n - 1) factorial(50000) // ࣮ߦ ඌ࠶ؼͰͳ͍࠶ؼؔ ελοΫΦʔόʔϑϩʔ͕ى͖Δ factorial(50000) // java.lang.StackOverflowError // ...
&WBMʹΑΔ࠶ؼॲཧ def factorial(n: BigInt): Eval[BigInt] = if(n == 1) {
Eval.now(n) } else { factorial(n - 1).map(_ * n) } factorial(50000).value // ࣮ߦ &WBMΛ༻͍ͨίʔυʹมߋ
&WBMʹΑΔ࠶ؼॲཧ def factorial(n: BigInt): Eval[BigInt] = if(n == 1) {
Eval.now(n) } else { factorial(n - 1).map(_ * n) } factorial(50000).value // ࣮ߦ &WBMΛ༻͍ͨίʔυʹมߋ factorial(50000).value // java.lang.StackOverflowError // ... ελοΫΦʔόʔϑϩʔ͕ى͖Δ
&WBMʹΑΔ࠶ؼॲཧ def factorial(n: BigInt): Eval[BigInt] = if(n == 1) {
Eval.now(n) } else { Eval.defer(factorial(n - 1).map(_ * n)) } factorial(50000).value // ࣮ߦ // res20: BigInt = //33473205095971448369154760940714864779127732…… &WBMEFGFSϝιουΛͬͯ͞ΒʹϦϑΝΫλϦϯά
&WBMʹΑΔ࠶ؼॲཧ def factorial(n: BigInt): Eval[BigInt] = if(n == 1) {
Eval.now(n) } else { Eval.defer(factorial(n - 1).map(_ * n)) } factorial(50000).value // ࣮ߦ // res20: BigInt = //33473205095971448369154760940714864779127732…… factorial(50000).value // res20: BigInt = //33473205095971448369154760940714864779127732…… &WBMEFGFSϝιουΛͬͯ͞ΒʹϦϑΝΫλϦϯά ਖ਼ৗऴྃ
&WBMʹΑΔ࠶ؼॲཧ &WBMEFGFSϝιουԿΛ͍ͯ͠Δͷ͔ʁ def defer[A](a: => Eval[A]): Eval[A] = new Eval.Defer[A](a
_) {} sealed abstract class Defer[A](val thunk: () => Eval[A]) extends Eval[A] { def memoize: Eval[A] = Memoize(this) def value: A = evaluate(this) } &WBM<">Λฦ͢ܭࢉΛԆ͍ͯ͠Δ τϥϯϙϦϯԽ͕ߦΘΕɺ͕ؔचͭͳ͗ ͰݺΕͳ͘ͳΔ
$BUTΛษڧֶͯͯ͠Μͩ͜ͱ ಡΜͩจݙ ɾೣ൪IUUQFFETJODPNIFSEJOHDBUTKB ɾ4DBMB8JUI$BUT ֶͼ ɾϞφυͬͯԿͳͷ͔ ɾ,MFJTMJɺ3FBEFSϞφυ ɾϞφυมࢠ
ϞφυͬͯԿͳͷ͔ Ϟφυͱɺ݁߹ͱಉҰΛຬͨ͢࠷খݶͷ ϞφυίϯϏωʔλͷू·Γͷ͍ͣΕ͔Λ࣮ͨ͠ͷͰ͋Δɻ ΧϥʔίοϓຊΑΓҾ༻
ϞφυͬͯԿͳͷ͔ Ϟφυͱɺ݁߹ͱಉҰΛຬͨ͢࠷খݶͷ ϞφυίϯϏωʔλͷू·Γͷ͍ͣΕ͔Λ࣮ͨ͠ͷͰ͋Δɻ ʁ ΧϥʔίοϓຊΑΓҾ༻
ϞφυͬͯԿͳͷ͔ ϞφυΛඥղ͘Ωʔϫʔυ ɾϑΝϯΫλʔ 'VODUPS ɾΞϓϦΧςΟϒϑΝϯΫλʔ "QQMJDBUJWF'VODUPS ͜ͷೋͭඞͣग़ͯ͘Δ Ϟφυͱɺ݁߹ͱಉҰΛຬͨ͢࠷খݶͷ ϞφυίϯϏωʔλͷू·Γͷ͍ͣΕ͔Λ࣮ͨ͠ͷͰ͋Δɻ
ʁ ΧϥʔίοϓຊΑΓҾ༻
Ϟφυ 'VODUPS"QQMZ "QQMJDBUJWF'VODUPS.POBE DBUTʹ͓͍ͯɺ࣍ͷॱͰਐԽ͍ͯ͘͠
'VODUPS -JTU 0QUJPOͳͲʹରͯ͠ɺ แ·Εͨʹରͯ͠ҾؔΛద༻͢ΔॲཧΛఏڙ͢ΔܕΫϥε List(1, 2, 3).map(_ * 2) //
List(2, 4, 6) Some(1).map(_ * 2) // Some(2) @typeclass trait Functor[F[_]] extends functor.Invariant[F] { self => def map[A, B](fa: F[A])(f: A => B): F[B] .... }
"QQMZ 'VODUPSΛ֦ுͯ͠ɺ/ݸͷ'VODUPSʹ/ҾؔΛ ద༻͢ΔॲཧΛఏڙ͢ΔܕΫϥε import cats.implicits._ // implicit defͰ҉తʹmap2, map3͕ద༻͞ΕΔ (Some(1),
Some(2)).mapN(_ + ) // Some(3) (Some(1), Some(2), Some(3)).mapN(_ * _ * _) // Some(6) (List("ha", "heh", "hmm"), List("?", "!", ".")) mapN {_ + _} // List(ha?, ha!, ha., heh?, heh!, heh., hmm?, hmm!, hmm.)
"QQMJDBUJWF'VODUPS "QQMJDBUJWF"QQMZʹ QVSFϝιου "'<"> ΛՃ͍ͯ͠ΔܕΫϥε ϓϦϛςΟϒΛ"QQMJDBUJWFܕʹมͯ͠ɺ ଞͷ"QQMJDBUJWFͱ߹Ͱ͖Δɹ DBUTͷ7BMJEBUFEBQQMJDBUJWFGVODUPSΛܗ͢Δ 1.pure[Option] //
Some(1) // શͯͷΠϕϯτΛݕূ্ͨ͠Ͱɺ߹Λߦ͏ val result = (valid[String, String]("event 1 ok") |@| invalid[String, String]("event 2 failed!") |@| invalid[String, String]("event 3 failed!")) map {_ + _ + _} // result: cats.data.Validated[String,String] = Invalid(event 2 failed!event 3 failed!) DPNQPTF G QVSF G DPNQPTF QVSF G G QVSFಉҰΛຬͨ͢
.POBE "QQMJDBUJWF'VODUPSෳͷ'VODUPSΛѻ͏͜ͱ͕Ͱ͖͕ͨɺ લͷ'VODUPSʹґଘ͢ΔॲཧΛॻ͚ͳ͍ɻ def hogeOption(a: Int): Option[Int] = Some(a) hogeOption(1).flatMap(a
=> hogeOption(a).map(b => a+b)) // Some(2) for { a <- hogeOption(1) b <- hogeOption(a) } yield (a + b) // Some(2) .POBEલͷʹґଘ͢ΔॲཧΛఏڙ͢ΔܕΫϥε /POFqBU.BQ G qBU.BQ H /POFqBU.BQ BG B qBU.BQ H qBU.BQ݁߹Λຬͨ͢
Ϟφυ·ͱΊ Ϟφυͱɺ݁߹ͱಉҰΛຬͨ͢࠷খݶͷ ϞφυίϯϏωʔλͷू·Γͷ͍ͣΕ͔Λ࣮ͨ͠ͷͰ͋Δɻ DPNQPTF G QVSF G DPNQPTF QVSF G
G ಉҰ /POFqBU.BQ G qBU.BQ H /POFqBU.BQ BG B qBU.BQ H ݁߹ ʹแ·Εͨͷʹରͯ͠ɺؔͷ࿈Λ࣮ߦͰ͖Δ