Upgrade to Pro — share decks privately, control downloads, hide ads and more …

scala introduction 2018.06.12

82852d7c64083861d2472602e654a0fd?s=47 matsutomu
June 12, 2018
Programming
0
140

scala introduction 2018.06.12

scala introduction

82852d7c64083861d2472602e654a0fd?s=128

matsutomu

June 12, 2018
Tweet

More Decks by matsutomu

See All by matsutomu
scala recommend learning materials
82852d7c64083861d2472602e654a0fd?s=48 matsutomu
0
120

Other Decks in Programming

See All in Programming
Airflow1=>Airflow2へのupgrade 事例紹介
A3ae651ab614249880dd9fad4fd0cee7?s=48 reizist
0
110
Monadic Java
9eafc29df96e6aaf4a3eb4c0209086ae?s=48 mariofusco
4
260
質とスピード（2022春版、質疑応答用資料付き） / Quality and Speed 2022 Spring Edition
9f3a83db74bee75a64b5e6ed106a775c?s=48 twada
PRO
29
18k
dbtとBigQueryで始めるData Vault入門
F2bd408c57c20505bd4202c9e28ecd59?s=48 kazk1018
0
190
未経験QAの私が、よきQA（Question Asker） になっていく物語
F0a8d07597a19192791bf663504d2a17?s=48 atamaplus
0
270
SPA/MPA 議論の俯瞰と 現代における設計のポイント - #tfcon 2022 フロントエンド設計
1644fba8a219c89987390ef4f23d06bf?s=48 ahomu
3
1.8k
Named Document って何？
4cda705b5eecbba889fb97ce9f374efe?s=48 harunakano
0
430
職場にPythonistaを増やす方法
86b349524dfba1c635e944f2a9c92e91?s=48 soogie
0
320
GraphQL+KMM開発でわかったこと / What we learned from GraphQL+KMM development
E505897a79eede1a676f92740261e8f8?s=48 kubode
0
130
You CANt teach an old dog new tricks
Bd5b8981a308c94b642befb656d8cf8f?s=48 michaelbukachi
0
110
Update from the Elixir team - 2022
Faafc04d9e69b73b9f49995fd4c94d4d?s=48 whatyouhide
0
190
WindowsコンテナDojo : 第1回 Visual StudioでWindowsコンテナアプリ作成
E5eb221d34d4ffbe973f8542b4c3a00e?s=48 oniak3ibm
PRO
0
330

Featured

See All Featured
Typedesign – Prime Four
A0517b08532aec8ab2aae3f65d40ad86?s=48 hannesfritz
33
1.3k
The MySQL Ecosystem @ GitHub 2015
Be9caeb9d4ef9944d151af909063ed6e?s=48 samlambert
238
11k
Debugging Ruby Performance
D47656e20ff5e42f125fc5ea0fd636c6?s=48 tmm1
65
10k
Scaling GitHub
78b475797a14c84799063c7cd073962f?s=48 holman
451
140k
Principles of Awesome APIs and How to Build Them.
B47b288784fda77a94aeb234ca743c24?s=48 keavy
113
15k
Helping Users Find Their Own Way: Creating Modern Search Experiences
3d4519fd34b76fb265fc0237f3792bd4?s=48 danielanewman
7
1k
ParisWeb 2013: Learning to Love: Crash Course in Emotional UX Design
651dcfe41723207fbb0aa044a4f7c07f?s=48 dotmariusz
100
5.9k
Atom: Resistance is Futile
7fa6101cd43067653cf4ac6c7ca54305?s=48 akmur
255
20k
CSS Pre-Processors: Stylus, Less & Sass
7559f6cff1f5efc2d210965febd4d71c?s=48 bermonpainter
349
27k
Embracing the Ebb and Flow
C9b18d9dff88a9dd2393364c2b3b21bd?s=48 colly
73
3.3k
Facilitating Awesome Meetings
245cee81a9c424266e5e401d844ea881?s=48 lara
29
3.9k
Creatively Recalculating Your Daily Design Routine
48c098b6579220a67a6ba949be6e4b5a?s=48 revolveconf
205
10k

Transcript

  1. 4DBMB*OUSPEVDUJPO .BUTVNPUP5TVUPNV !NBUTVUPPN 

  2. ͸͡Ίʹ ࣗݾ঺հ ɹɹদຊɹ຿ ɹɹձࣾһʢ౦ژຊࣾͷاۀۈ຿ʣ ɹɹόϦόϦ։ൃʂͯ͠·ͤΜ ɹɹ͕ɺݸਓతʹ4DBMBʹڵຯΛ࣋ͬͯ೥͕ͨͪ·ͨ͠ ɹɹ΋ͬͱ4DBMBͷྗΛ਎ʹ෇͚͍ͨத೥உͰ͢

  3. ͸͡Ίʹ 4DBMBʢεΧϥʣͱ͸ʁ

  4. ͸͡Ίʹ εΠε࿈๜޻Պେֶ &1'-  ϚʔςΟϯɾΦʔμεΩʔڭत ൚༻ݴޠ͸εέʔϥϒϧͰͳͯ͘͸ͳΒͳ͍ɻ ಉ֓͡೦Ͱɺখ͍͞ϓϩάϥϜ΋େ͖ͳϓϩάϥϜ΋هड़Ͱ͖Δ΂͖Ͱ͋Δɻ εέʔϥϏϦςΟ͸ؔ਺ܕݴޠͱΦϒδΣΫτࢦ޲ݴޠͷ ͭͷϓϩάϥϛϯάͷ֓೦Λ౷߹͠ɺҰൠԽ͢Δ͜ͱʹΑΓ࣮ݱͰ͖Δɻ #Z8JLJQFEJB

  5. ͸͡Ίʹ ྺ࢙ ೥ࠒʹ͸طʹઃܭ͕ਐΊΒΕ͓ͯΓ ೥ʹ͸ެ։͞Ε͍ͯΔɻ ೥ࠒʹ͸UXJUUFSͷόοΫΤϯυʹ࠾༻ ೥ʹେ෯ͳมߋͷ4DBMB͕ϦϦʔε ݱࡏͷόʔδϣϯ͸ IUUQTXXXTDBMBMBOHPSH

  6. ͸͡Ίʹ ΦϒδΣΫτࢦ޲ɹͱɹؔ਺ܕݴޠͷಛ௃Λ ߹Θͤ࣋ͭϓϩάϥϛϯάݴޠ +7.Ͱಈ࡞͠·͢

  7. ͸͡Ίʹ ͱݴ͍ग़͢ͱɺएׯখ೉͍͠ͷͰ

  8. ͸͡Ίʹ ֶͼॳΊ͙ͯ͢ʹಈ͔ͤΔ ߏจͷޡΓ΋ίϯύΠϧ࣌ʹ ͔ͬ͠ΓνΣοΫͯ͘͠ΕΔ ༏͍͠ϓϩάϥϛϯάݴޠ

  9. ͸͡Ίʹ ͱݴ͏ࣄͰ ·ͣಈ͔ͯ͠Έ·͠ΐ͏

  10. 4DBTUJF IUUQTTDBTUJFTDBMBMBOHPSH

  11. 4DBTUJF )FMMP4DBMB

  12. 4DBTUJF ม਺એݴར༻

  13. 3&1- ଞʹ΋

  14. 3&1- ؆୯ʹ4DBMBͷίʔυยΛ࣮ߦՄೳ

  15. 3&1- ৭ʑͳߏจ͕ࢼͤ·͢

  16. 3&1- ৭ʑͳߏจ͕ࢼͤ·͢ WBMOBNFl!NBUTVUPNVz WBSNPOFZ

  17. 3&1- ৭ʑͳߏจ͕ࢼͤ·͢ GPS YUP \ QSJOUMO Y  ^

  18. 3&1- WBMDPOEJUJPOlѱ͍ DPOEJUJPONBUDI\ DBTFྑ͍QSJOUMO ໷஗͘·Ͱ࢓ࣄ͢Δ  DBTFѱ͍QSJOUMO ̎̍࣌͝Ζʹ͸ؼ୐͢Δ  ^

  19. 3&1- WBM BHF DPOEJUJPO  த೥ ѱ͍  BHF DPOEJUJPO

    NBUDI\ DBTF த೥ ྑ͍ QSJOUMO ૣ৸ૣى͖ʹͳΔ  DBTF த೥ ѱ͍ QSJOUMO ૣ৸ૣى͖ʹͳΔ  DBTF த೥ @ QSJOUMO ૣ৸ૣى͖ʹͳΔ  DBTF @ ྑ͍ QSJOUMO ૣ৸ૣى͖ʹͳΔ  DBTF @ ѱ͍ QSJOUMO ૣ৸ૣى͖ʹͳΔ  DBTF @ @ QSJOUMO ૣ৸ૣى͖ʹͳΔ  ^

  20. 4VSQSJTF ಥવͰ͕͢ɾɾɾ

  21. 4VSQSJTF ͜͜ͰΫΠζͰ͢

  22. 4VSQSJTF ϕΫτϧ a, b ͕௚ߦ͢Δ͔Λ൑ఆ͢Δ਺ࣜ͸ʁ (ax1, ay1 ) (ax0 ,

    ay0 ) (bx0 , by0 ) (bx1 , by1 ) a b ʢࢀߟʣʰϓϩάϥϛϯάίϯςετ߈ུͷͨΊͷΞϧΰϦζϜͱσʔλߏ଄ʱɹ *4#/

  23. 4VSQSJTF

  24. 4VSQSJTF ϕΫτϧ a, b ͕௚ߦ͢Δ͔Λ൑ఆ͢Δ਺ࣜ͸ʁ (ax1, ay1 ) (ax0 ,

    ay0 ) (bx0 , by0 ) (bx1 , by1 ) a b ౴͑ ϕΫτϧͷ಺ੵ͕̌ͷ৔߹ʹ௚ߦ͢Δɻ aɾb = |a||b|cosθ = ax * bx + ay * by

  25. 4VSQSJTF PCKFDU$HM4BNQMF\ DBTFDMBTT1PJOU Y%PVCMF Z%PVCMF \ EFG Q1PJOU 1PJOU1PJOU UIJTY

    QY UIJTZ QZ  ^ UZQF(FP7FDUPS1PJOU ಺ੵ EFGEPU B1PJOU C1PJOU %PVCMFBY CY BZ CZ EFGJT0SUIPHPOBM B(FP7FDUPS C(FP7FDUPS #PPMFBOEPU B C  ^

  26. ࣮༻ྫ Ͳ͏Ͱ͠ΐ͏͔ʁ ༏͍͠ϓϩάϥϛϯάݴޠ ͷΠϝʔδΛ࣋ͯ·͔ͨ͠ʁ

  27. ࣮༻ྫ ࣮ࡍͷͱ͜Ζ͸ʁ اۀɾ044

  28. ࣮༻ྫ ɹɹɹɹɹɹɹɹɹɹɹɹɹɹɹʢࢀߟʣʲ4DBMBΛ࠾༻͍ͯ͠Δاۀ ϓϩμΫτ Ұཡʳɹɹɹ IUUQTRJJUBDPNPVCBLJPVJUFNTGEDBEBF ւ֎ 5XJUUFS -JOLFE*O 'PVS4RVBSF 1BZ1BM

    $PVSTFSB 5IF(VBSEJBO UVNCMS

  29. ࣮༻ྫ ɹɹɹɹɹɹɹɹɹɹɹɹɹɹɹʢࢀߟʣʲ4DBMBΛ࠾༻͍ͯ͠Δاۀ ϓϩμΫτ Ұཡʳɹɹɹ IUUQTRJJUBDPNPVCBLJPVJUFNTGEDBEBF ࠃ಺ υϫϯΰ ͸ͯͳ ηϓςʔχɾΦϦδφϧ ϏζϦʔν

    $IBU8PSL ΤϜεϦʔ /VMBC αΠόʔΤʔδΣϯτ

  30. ࣮༻ྫ اۀ͚ͩͰͳ͘ 044΋݁ߏ͋Γ·͢

  31. ࣮༻ྫ 4DBMBͷ044Ұཡ ʢࢀߟʣʲ5IJTJTBNPTUQPQVMBSSFQPTJUPSZMJTUGPS4DBMBTPSUFECZOVNCFSPGTUBSTʳɹɹɹ IUUQTHJUIVCDPNLBYBQBSMCMPCNBTUFS3&"%.&4DBMBNE

  32. ࣮༻ྫ 1MBZ'SBNFXPSL 8FCΞϓϦέʔγϣϯ ϑϨʔϜϫʔΫ

  33. ࣮༻ྫ σʔλϕʔεΞΫηε༻ ʢؔ਺ܕʣ

  34. ࣮༻ྫ TDBMBUSB 8FCϚΠΫϩϑϨʔϜϫʔΫ

  35. ࣮༻ྫ 4LJOOZ'SBNFXPSL 8FCΞϓϦέʔγϣϯ ϑϨʔϜϫʔΫ

  36. ࣮༻ྫ 4DBMJLF+%#$ σʔλϕʔεΞΫηε༻

  37. ࣮༻ྫ ෛՙࢼݧπʔϧʢ8FCʣ

  38. ࣮༻ྫ ϝοηʔδϕʔεͷඇಉظॲཧΛ࣮ݱ

  39. ࣮༻ྫ ετϦʔϛϯάॲཧ༻

  40. ࣮༻ྫ େྔσʔλΛฒྻ෼ࢄॲཧ

  41. ࣮༻ྫ ػցֶश༻ΞϓϦέʔγϣϯͷ։ൃࢧԉ

  42. ࣮༻ྫ 4DBMB੡ͷ(JUϓϥοτϗʔϜ

  43. ·ͱΊ ͪΐͬͱͨ͠εΫϦϓτ 8FCΞϓϦέʔγϣϯ σʔλϕʔεΞΫηε ฒྻॲཧ େྔσʔλॲཧ ։ൃࢧԉʢ(JU 6OJU5FTU ίʔυॻࣜʣ ͳͲͳͲ

    4DBMB͸৭ʑͳιϑτ΢ΣΞ͕ଘࡏ

  44. ·ͱΊ ͦͷഎܠʹ͸ ΦϒδΣΫτࢦ޲ ͱ ؔ਺ܕݴޠ ͱݴͬͨߟ͑ํ͚ͩͰͳ͘ ৭ʑͳར఺͕͋Δͷͩͱࢥ͍·͢

  45. ·ͱΊ ͜Ε͔ΒҰॹʹ4DBMBΛֶͼ·ͤΜ͔ʁ ͦͯ͠044ͷੈքʹೖ໳͠·ͤΜ͔ʁ