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
learning-cleanarchitecture-in-go
Search
Sponsored
·
SiteGround - Reliable hosting with speed, security, and support you can count on.
→
Takashi Matsuyuki
February 28, 2019
Programming
0
220
learning-cleanarchitecture-in-go
Takashi Matsuyuki
February 28, 2019
Tweet
Share
More Decks by Takashi Matsuyuki
See All by Takashi Matsuyuki
新規事業立ち上げ、グロースで きちんと”デリバリー”も"ディスカバリー"も し続けられるアジャイル組織の作り方
applepine1125
2
2.5k
最後に勝つ負け方を知っておく
applepine1125
1
500
評価者を孤独にしない
applepine1125
15
6k
"OKR"と"野望"で、 メンバーと組織をアラインメントする
applepine1125
5
1.2k
君たちはどうユーザーと向き合うか
applepine1125
0
450
Self-Organizing Product Development Team: Empowered Output Cycle and Collaborative Culture
applepine1125
0
1.2k
オーナーシップを持ち自己組織化するチームに必要な Engineering Program Managerという役割
applepine1125
2
2.3k
Settlement simulation testing to ensure correct settlement processing
applepine1125
2
3.2k
goはwireでDIする
applepine1125
0
350
Other Decks in Programming
See All in Programming
Amazon Bedrockを活用したRAGの品質管理パイプライン構築
tosuri13
4
670
The Past, Present, and Future of Enterprise Java
ivargrimstad
0
570
組織で育むオブザーバビリティ
ryota_hnk
0
170
20260127_試行錯誤の結晶を1冊に。著者が解説 先輩データサイエンティストからの指南書 / author's_commentary_ds_instructions_guide
nash_efp
1
970
生成AIを使ったコードレビューで定性的に品質カバー
chiilog
1
270
【卒業研究】会話ログ分析によるユーザーごとの関心に応じた話題提案手法
momok47
0
200
並行開発のためのコードレビュー
miyukiw
0
120
AI前提で考えるiOSアプリのモダナイズ設計
yuukiw00w
0
230
QAフローを最適化し、品質水準を満たしながらリリースまでの期間を最短化する #RSGT2026
shibayu36
2
4.4k
LLM Observabilityによる 対話型音声AIアプリケーションの安定運用
gekko0114
2
430
Patterns of Patterns
denyspoltorak
0
1.4k
副作用をどこに置くか問題:オブジェクト指向で整理する設計判断ツリー
koxya
1
610
Featured
See All Featured
StorybookのUI Testing Handbookを読んだ
zakiyama
31
6.6k
Noah Learner - AI + Me: how we built a GSC Bulk Export data pipeline
techseoconnect
PRO
0
110
Public Speaking Without Barfing On Your Shoes - THAT 2023
reverentgeek
1
310
Building Experiences: Design Systems, User Experience, and Full Site Editing
marktimemedia
0
410
Raft: Consensus for Rubyists
vanstee
141
7.3k
Helping Users Find Their Own Way: Creating Modern Search Experiences
danielanewman
31
3.1k
Lessons Learnt from Crawling 1000+ Websites
charlesmeaden
PRO
1
1.1k
Scaling GitHub
holman
464
140k
Hiding What from Whom? A Critical Review of the History of Programming languages for Music
tomoyanonymous
2
420
Code Reviewing Like a Champion
maltzj
527
40k
A better future with KSS
kneath
240
18k
Technical Leadership for Architectural Decision Making
baasie
1
240
Transcript
Go ͰֶͿClean Architecture ͓·͚: GoΛֶͿͨΊͷ͓͢͢ΊυΩϡϝϯτ
झࢫ(࠷ॳͷఆ) Go 㲗 CA GoΛ௨ͯ͠CAͷཧղΛਂΊΔ CAΛ௨ͯ͠GoͷཧղΛਂΊΔ
झࢫ(ࢿྉ࡞ͬͨ݁Ռ) Go → CA GoΛ௨ͯ͠CAͷཧղΛਂΊΔ CAΛ௨ͯ͠GoͷཧղΛਂΊΔ ޙΖʹ͓·͚Λ͚ͭ·ͨ͠
ΞδΣϯμ • Clean Architectureͱʁ • SOLIDݪଇ • CAͷϨΠϠʔߏ • ϨΠϠʔͷڥքɺӽڥ
• GoͰCA࠾༻͢ΔͱͲ͏ʁ • GoΛษڧ͢ΔͳΒ͜ΕಡΜͲ͚
αϯϓϧΞϓϦέʔγϣϯ TODOΞϓϦΛఆ UserใͱTaskใΛฦ͢APIαʔό ϦϙδτϦ: https://github.com/applepine1125/learning- cleanarchitecture-in-go ઈࢍվળத 13डத
෮श ΞʔΩςΫνϟͱʁ
ΞʔΩςΫνϟͷత ॏཁͳํʹྗ͠ɺৄࡉͷܾఆΛΒͤΔ →มߋʹॊೈͳΞϓϦέʔγϣϯΛ࡞Δ ϏδωεϩδοΫ ํ ϑϨʔϜϫʔΫɺυϥΠό ৄࡉ ॏཁ େখ ଐਓੑ
େখ
෮श Clean Architectureͱʁ
ͳΜ͔͜Μͳਤͷͭ
CAͷతɺಛੑ • ϑϨʔϜϫʔΫඇґଘ • ςετՄೳ • UIඇґଘ • σʔλϕʔεඇґଘ •
֎෦ΤʔδΣϯτඇґଘ →ͭ·ΓৄࡉͱํΛΓ͍͢͠
CAΛߏ͢Δཁૉ • Ϟδϡʔϧείʔϓʹ͓͚Δ5ݪଇ • ίϯϙʔωϯτείʔϓʹ͓͚Δ6ݪଇ • ϨΠϠʔ • ֤ϨΠϠʔͷҙຯɺ •
ϨΠϠʔͷڥքͷҾ͖͔ͨɺӽڥͷ͔ͨ͠
CAΛߏ͢Δݪଇ • Ϟδϡʔϧείʔϓ (SOLIDݪଇ) • ୯Ұͷݪଇ (SRP) • ΦʔϓϯɾΫϩʔζυͷݪଇ (OCP)
• Ϧείϑͷஔݪଇ (LSP) • ΠϯλʔϑΣʔεͷݪଇ (ISP) • ґଘؔٯసͷݪଇ (DIP) ← Ұ൪ॏཁ
CAΛߏ͢Δݪଇ • ίϯϙʔωϯτείʔϓ (ڽूੑ) • ࠶ར༻ɾϦϦʔεՁͷݪଇ (REP) • ดੑڞ௨ͷݪଇ (CCP)
• શ࠶ར༻ͷݪଇ (CRP)
CAΛߏ͢Δݪଇ • ίϯϙʔωϯτείʔϓ (ؔ࿈ੑ) • ඇ॥ґଘؔͷݪଇ (ADP) • ҆ఆґଘͷݪଇ (SDP)
• ҆ఆɾநՁͷݪଇ (SAP)
CAΛߏ͢Δݪଇ • Ϟδϡʔϧείʔϓ • DIP ←Ұ൪ॏཁ • Ϟδϡʔϧείʔϓ • SRP,
OCP, LSP, ISP • ίϯϙʔωϯτείʔϓ(ڽूੑ) • REP, CCP, CRP • ίϯϙʔωϯτείʔϓ(ؔੑ) • ADP, SDP, SAP આ໌͠·͢ ࣗश
SOLIDݪଇ
୯Ұͷݪଇ “ϞδϡʔϧͨͬͨҰͭͷΞΫλʔʹରͯ͠ Λෛ͏͖Ͱ͋Δ”
୯Ұͷݪଇ ϙΠϯτ • มߋ͢Δཧ༝͕ඞͣڞ௨Ͱ͋Εɺ ڞ௨Ϟδϡʔϧͱͯ͠Γग़ͯ͠ྑ͍ ٯʹݴ͏ͱͲ͏ͳΔʁ
ΦʔϓϯɾΫϩʔζυͷݪଇ “ߏཁૉ֦ுʹରͯ͠։͍͍ͯͯɺमਖ਼ʹ ରͯ͠ด͍ͯ͡ͳ͚ΕͳΒͳ͍”
ΦʔϓϯɾΫϩʔζυͷݪଇ ϙΠϯτ • interfaceʹΑͬͯ৽͍͠ػೳΛ؆୯ʹ औΓೖΕΔ͜ͱ͕Ͱ͖Δ • ͋ΔϞδϡʔϧͷมߋͷӨڹ͕ଞͷ ϞδϡʔϧӨڹ͠ͳ͍
Ϧείϑͷஔݪଇ “SܕͷΦϒδΣΫτͷo1ͷ֤ʑʹɺରԠ͢ΔTܕͷΦϒδΣΫτo2͕̍ͭ ଘࡏ͠ɺTΛͬͯఆٛ͞ΕͨϓϩάϥϜPʹରͯ͠o2ͷΘΓʹo1Λ ͬͯPͷৼΔ͍͕มΘΒͳ͍߹STͷੜܕͰ͋Δͱݴ͑Δ”
Ϧείϑͷஔݪଇ ϙΠϯτ • ϞδϡʔϧΛஔՄೳͳঢ়ଶʹ͢Δ ΦʔϓϯɾΫϩʔζυͷݪଇͷ֦ுੑͷ༰ͱҰॹ
ΠϯλʔϑΣʔεͷݪଇ ϙΠϯτ • ຊདྷඞཁͱ͠ͳ͍ͷʹ·Ͱґଘ͠ͳ͍Α͏ ʹɺΠϯλʔϑΣʔεΛڬΜͰૄ݁߹ʹ͢Δ
ґଘؔٯసͷݪଇ • interfaceΛ༻͍ͯґଘؔΛٯసͤ͞Δ 6TFDBTF 3FQPTJUPSZ 42-)BOEMFS %*1ద༻લ %*1ద༻ޙ 6TFDBTF 3FQPTJUPSZ
42-)BOEMFS 3FQPTJUPSZ *OUFSGBDF 42-)BOEMFS *OUFSGBDF
ґଘؔٯసͷݪଇ ϙΠϯτ • มԽ͍͢͠ϞδϡʔϧΛࢀরɺܧঝɺ ΦʔόʔϥΠυɺ໊ࢦ͠Ͱࢀর͠ͳ͍ →CAͰϨΠϠʔΛ·͍ͨͰϞδϡʔϧΛ ࢀর͢Δͱ͖ʹॏཁʂ
CAͷతɺಛੑ • ϑϨʔϜϫʔΫඇґଘ • ςετՄೳ • UIඇґଘ • σʔλϕʔεඇґଘ •
֎෦ΤʔδΣϯτඇґଘ →ݪଇΛར༻͢Ε࣮ݱͰ͖ͦ͏ʁ վΊͯɾɾɾ
CAͷϨΠϠʔߏ
CAͷ֤ϨΠϠʔ • ΤϯςΟςΟ • Ϣʔεέʔε • ΠϯλʔϑΣʔεΞμϓλ • ϑϨʔϜϫʔΫɺυϥΠό
• ΤϯςΟςΟ • Ϣʔεέʔε • ΠϯλʔϑΣʔεΞμϓλ • ϑϨʔϜϫʔΫɺυϥΠό ϙΠϯτ ୯ํґଘͰ͋Δ
CAͷ֤ϨΠϠʔ ґଘ͞Ε͍ͯΔ ԁͷத ԁͷ֎ ґଘ͍ͯ͠Δ
ΤϯςΟςΟ • Ϗδωεࣗମͷ࠷ॏཁϧʔϧΛ·ͱΊͨͷ • γεςϜ͕webΞϓϦέʔγϣϯͱ͍͏ܗଶ Ͱͳ͔ͬͨͱͯ͠ଘࡏ͢Δใ
ΤϯςΟςΟ w ۀʹඞཁͳใ͕ೖͬͨߏମ w ඞཁͳใΛੜ͢ΔͨΊͷϝιου ྫTSDQLHEPNBJOVTFSHP
Ϣʔεέʔε • ΞϓϦέʔγϣϯݻ༗ͷϏδωεϧʔϧ ΛؚΉ • ΤϯςΟςΟͷϏδωεϩδοΫΛΈ߹Θ ͤͯ༻ɺ੍ޚ͢Δ
Ϣʔεέʔε ྫTSDQLHVTFDBTFUBTLJOUFSBDUPSHP w σʔλͷऔಘ SFQPTJUPSZ JOUFSGBDFΛૠ͢ w ӬଓԽ͢ΔͨΊʹUBTLͷใΛͬͯΞϓϦέʔγϣϯݻ༗ͷ σʔλͷܗʹม
ΠϯλʔϑΣʔεΞμϓλ • ϢʔεέʔεɺΤϯςΟςΟ͔ΒDBϑϨʔ ϜϫʔΫͳͲ͕͏ϑΥʔϚοτσʔλΛ ม͢Δ(ͦͷٯવΓ) • ೖྗɺग़ྗɺӬଓԽʹؔ͢ΔϞδϡʔϧ͕ॴ ଐ͢Δ
ΠϯλʔϑΣʔεΞμϓλ ྫTSDQLHJOUFSGBDFUBTLSFQPTJUPSZHP w ӬଓԽͷͨΊʹΫΤϦΛൃߦ͍ͯ͠Δ
ϑϨʔϜϫʔΫɺυϥΠό • ϑϨʔϜϫʔΫπʔϧͳͲͷίʔυͰ ߏ͞Ε͍ͯΔ • WebͷUIͳͲ͜͜
ϑϨʔϜϫʔΫɺυϥΠό ྫTSDQLHJOGSBTRMIBOEMFSHP w EBUBCBTFTRMϥΠϒϥϦΛ༻ w ԼҐͱଓ͍͢͠Α͏ʹXSBQ͢Δ
ϨΠϠʔͷڥքɺӽڥ
ϨΠϠʔͷڥքɺӽڥ ڥքͷҾ͖͔ͨ • γεςϜΛίϯϙʔωϯτʹׂ͢Δ • ݪଇɺϧʔϧΛݩʹ֤ϨΠϠʔʹྨ͢Δ • ґଘؔͷઢΛҾ͍ͯΈΔ
ϨΠϠʔͷڥքɺӽڥ ӽڥͷ͔ͨ͠ • DIPΛͬͯґଘͷ͖Λίϯτϩʔϧ͢Δ 3FQPTJUPSZ 6TFDBTF 6TFDBTF 3FQPTJUPSZ JOUFSGBDF 3FQPTJUPSZ
*OUFSGBDF"EBQUFS 6TFDBTF %*1ద༻લ %*1ద༻ޙ
ϨΠϠʔͷڥքɺӽڥ ӽڥͷ͔ͨ͠ TSDQLHVTFDBTFVTFSJOUFSBDUPSHP TSDQLHJOUFSGBDFVTFSDPOUSPMMFSHP ܕVTFDBTF6TFS3FQPTJUPSZ ࣮ࡍʹೖΕͯΔͷEBUBCBTF6TFS3FQPTJUPSZ
GoͰCA࠾༻͢ΔͱͲ͏ʁ
GoͰCA࠾༻͢ΔͱͲ͏ʁ ϥΠϒϥϦʹґଘ͗͢͠ͳ͍ • αʔυύʔςΟͷϥΠϒϥϦ͍͗ͣ͢ɺ͋͘ ·Ͱwrapperͱͯ͠͏ఔʹཹΊΔจԽ͕ ͋Δ • infraҎԼͷ֎෦ίϯϙʔωϯτͷӨڹ͕ গͳ͍ →֎෦ίϯϙʔωϯτͷมߋʹͭΑ͍
GoͰCA࠾༻͢ΔͱͲ͏ʁ MockͭΒ͍ • CAΛ࠾༻͢Δͱinterface͍ͬͺ͍ੜ͑Δ • ࣗ࡞interfacegoMockͳͲͰMockੜ HPMBOHNPDL IUUQTHJUIVCDPNHPMBOHNPDL
GoͰCA࠾༻͢ΔͱͲ͏ʁ ඪ४ύοέʔδΛMock͢Δʹɾɾɾʁ • ςετ͍ͨ͠ϥΠϒϥϦͷinterface, ߏମͱ ϝιου͕Ұக͢ΔinterfaceΛखݩͰ࡞Γ goMockͰMockੜ ͩΔ͍
CAͷ·ͱΊ
CA·ͱΊ ”ਤͷԁɺ֓ཁΛࣔͨ͠ͷͰ͋Δɻ͕ͨͬͯ͠ɺ͜ͷ̐ͭ Ҏ֎ʹඞཁͳͷ͋ΔͩΖ͏ɻͨͩ͠ɺґଘੑͷϧʔϧ ৗʹద༻͞ΕΔ” ”νʔϜͷنϝϯόʔͷεΩϧιϦϡʔγϣϯͷෳࡶ ͞ɺͦͯ࣌ؒ͠ͱ༧ࢉͷ੍ͳͲΛߟྀ͠Α͏” 3PCFSU$.BSUJO
CA·ͱΊ • νʔϜͰ߹ҙ͕औΕ͍ͯΕਖ਼ͳΜͰ ͍͍ͱࢥ͍ͬͯΔ • ԿΛୡ͍͔ͨ͠Λݟਾ͑ɺઌਓ͕ͨ͠ ݪཧݪଇνʔϜͷܦݧɺγεςϜͷಛੑɺ υϝΠϯࣝͳͲΛϑϧʹ׆༻ͯ͠ৗʹద ͳߏʹͳΔΑ͏ྗ͢Δ
CA͓͢͢ΊυΩϡϝϯτ w $MFBO"SDIJUFDUVSFɹୡਓʹֶͿιϑτΣΞͷߏͱઃܭ IUUQTXXXBNB[PODPKQEQ#'4#)47SFGEQLJOEMFSFEJSFDU @FODPEJOH65'CULS w ࣮ફΫϦʔϯΞʔΩςΫνϟ IUUQTOSTMJCDPNDMFBOBSDIJUFDUVSF w $MFBO"SDIJUFDUVSFͰ"1*4FSWFSΛߏஙͯ͠ΈΔ
IUUQTRJJUBDPNIJSPUBLBOJUFNTDGBDDBF
GoΛษڧ͢ΔͳΒ͜ΕಡΜͲ͚
GoΛษڧ͢ΔͳΒ͜ΕಡΜͲ͚ • ॳ৺ऀ w "5PVSPG(P IUUQTHPUPVSKQBQQTQPUDPNXFMDPNF w 1SPHBUF IUUQTQSPHDPNMBOHVBHFTHP
GoΛษڧ͢ΔͳΒ͜ΕಡΜͲ͚ • ॳ৺ऀ~தڃऀ w (PݴޠʹΑΔ8FCΞϓϦέʔγϣϯ։ൃ w (PͰଞͷษڧΛ͢Δ (PͳΒΘ͔ΔγεςϜϓϩάϥϛϯά (PݴޠͰͭ͘ΔΠϯλϓϦλ 3FBM8PSME)551
8SJUJOHdJO(Pܥ
GoΛษڧ͢ΔͳΒ͜ΕಡΜͲ͚ • தڃऀ~্ڃऀ w (PݴޠʹΑΔฒߦॲཧ w ϓϩάϥϛϯάݴޠ(P w ΈΜͳͷ(PݴޠʲݱͰ͑Δ࣮ફςΫχοΫʳ w
&⒎FDUJWF(P ӳޠ൛ɿIUUQTHPMBOHPSHEPDF⒎FDUJWF@HPIUNM ຊޠ൛IUUQHPMBOHKQF⒎FDUJWF@HP
GoΛษڧ͢ΔͳΒ͜ΕಡΜͲ͚ GoDocಡΊ
͓ΘΓ