AI Dev Tools Zoomcamp 2026

Homework 2: Build and Ship an AI-Assisted Full-Stack App Statistics

Distribution of scores and reported study time for this homework.

Submissions

260

Median total score

6

Average total score

7

Score distribution

All values are points.

Questions score

Min
6
Median
6.0
Max
6
Q1
6.0
Avg
6.0
Q3
6.0

Learning in public score

Min
-
Median
0.0
Max
7
Q1
0.0
Avg
0.6
Q3
1.0

Total score

Min
6
Median
6.0
Max
14
Q1
6.0
Avg
6.7
Q3
7.0

Time distribution

All values are hours reported by students.

Lectures

Min
0.0
Median
2.0
Max
80.0
Q1
2.0
Avg
4.1
Q3
3.0

Homework

Min
0.0
Median
3.0
Max
40.0
Q1
2.0
Avg
4.5
Q3
4.0

Question breakdown

Correctness and answer distribution per question.

1. Which project did you choose for this homework?

250 / 260 correct (96.2%)

1 Expense splitter 53 (20.4%)
2 Restaurant waitlist manager 48 (18.5%)
3 Mini Kanban board 114 (43.8%)
4 Sports-league scoreboard 35 (13.5%)

2. What is the name you chose?

260 / 260 correct (100.0%)

Answer Count
Flowboard 5
Mini Kanban Board 5
SplitEasy 4
TableTurn 4
Tasklane 3
TaskLane 3
KanbanFlow 3
Waitlist 3
TaskFlow 3
Snake Arena 3
FlowBoard 3
mini-kanban 3
LeagueBoard 2
NextTable 2
Waitly 2
SplitFair 2
Seatly 2
FairShare 2
Kanbanana 2
KanFlow 2
Expense Splitter 2
Mini Kanban board 2
Restaurant waitlist manager 2
WaitWise 2
CareSplit 2
restaurant-waitlist-manager 2
Boardly 2
Tennis Tournament Manager 1
Delivery Flow Board 1
MyKanban 1
VividFlow 1
Mini-Kanban Board 1
Viloq 1
Evenly 1
MaitreQ 1
mini-kanban-board 1
Kanbloom 1
ShareTrip 1
Interview Canvas 1
Kanvas 1
shared-household-chore-manager 1
Splitwise Lite 1
Kanbits 1
EntreNos 1
Mini Kanban 1
mamban 1
Sprintlane 1
Expenses4All 1
Laneway 1
Card Catalog 1
None of them, I create a simple CRM app that I´ll try to use in my family business. 1
Juniper Table 1
Waitlist Manager - Olive & Ember 1
SplitWeave 1
LeagueScore 1
basketball-scoreboard 1
MINI_KANBAN (I couldn't find the homework.md so I just followed the post and the MINI KANBAN topic) 1
Kano 1
flowdeck 1
Atlas Premier League 1
Tavli 1
Leagueboard 1
QueueBite — AI-Powered Restaurant Waitlist Manager 1
board buddy 1
Nexus 1
Table Ready 1
ScoreBoard 1
LaneDeck 1
Nookan 1
M_Kanban 1
Flux 1
ScoreFeed 1
Cardstock 1
tedious-chores 1
expense-tracker 1
Family Kanban 1
Interactive Restaurant Table Reservation System 1
ai-task-decomposer 1
CodeInterview Live 1
kanban-mini 1
GrabTab 1
System Design Interview Canvas since I used to experimenting and training. I selected Expense splitter but I ran into limitation with those tools and I could not finish within the available usage. 1
SplitEase 1
FastKanban 1
ai-dev-zoomcamp-week2-kanbanite 1
ChopTheBill 1
QueueIQ 1
SeatFlow 1
MiniFlow 1
Kickboard 1
TableHop 1
Ledger 1
mini-kabnab-board 1
piano-lessons-booking (I thought it was more fun to do a project I can relate to and it is similar to the restaurant booking system) 1
kevin-hm2 1
Korda 1
weekslot 1
sports-league-dashboard 1
Splitzy — Expense Splitter 1
HostBoard 1
ApitaCerto 1
Flowlane 1
MatchTracker Pro 1
LeagueLens Scoreboard 1
sports-league scoreboard 1
TableOK 1
queueside 1
Pocket Flow 1
Mini Kanban API (kanban-app) 1
'Tennis Prediction Game' is the repo and project name. The app's in-product brand is 'Deuce'. 1
Kinuflow 1
SplitTheDiff 1
EvenSplit 1
Quits 1
sports-league-scoreboard 1
Servd 1
VacaSplit 1
WeSplit 1
EntryStock 1
project board 1
WorkPulse 1
Divide Expenses 1
TaskLance 1
Splitly 1
TeamFlow 1
board-buddy 1
Sports-League-Scoreboard 1
kanbunny-board 1
Homework 2 Restaurant Waitlist Manager 1
QuickQueue 1
FocusBoard 1
https://github.com/Nalyvaiko/kanban-board 1
TableFlow 1
hex-tracker 1
Prem League Scoreboard 1
home_finance 1
Boardlet 1
WaitFlow 1
TableQ 1
Kanbanit 1
Even Split 1
pocketflow-app 1
restaurant-waitlist-management-system 1
TableReady 1
Head of the Class 1
Project Board 1
SplitLedger 1
SparkBoard 1
Owesome 1
tidyboard 1
Kanvia 1
Cardly 1
AI-Powered Expense Splitter 1
Stacked 1
Nextable 1
CuentaClara 1
WaitEase 1
FairShare — AI-Assisted Expense Splitter 1
Tally 1
Expense splitter 1
coding-interview 1
Share Settle 1
Taskmate 1
pairpad 1
cadence 1
Splitmate 1
Cardinal 1
TopTable 1
Premier League Scoreboard (`pl_scoreboard`) 1
real-time-design/ 1
KickPulse 1
NextLane 1
KanbanBro 1
quick-flow-board 1
Petri — a small, contained space to run an experiment and watch it grow. 1
SeatCute 1
LeagueLedger 1
Scoreline 1
Balancio 1
waitlist 1
TableQueue 1
Little League Leaderboard 1
karate-scoreboard 1
TableScore 1
CloseTab 1
Coperto 1
sports-scoreboard-ai 1
TaskTide 1
KanbanLite 1
foxglove 1
Flowly 1
FocusTree Planner 1
wait-o-rest 1
IceNow 1
ai_system_design_canvas 1
L'Étoile 1
DoneGaBang 1
Next in dining 1
Sharebucks 1
LeagueHub 1
ProRata 1
Saldo 1
littleboard 1
LeagueTable 1
Bitácora 1
Punchlist 1
Trip Ledger 1
Chip In 1
Herding Cats 1
expenser 1
team-task-board 1
mini-kanban-board_lab_IA 1
Sharable Private Kanban Boards 1
Splitit 1

3. What is the sha1 hash for this commit?

260 / 260 correct (100.0%)

Answer Count
8ae5ac612324496474ea656ccc6dbbf26f1a02b2 2
a1a3307033d7104e734bdd56f3ed378448240ced 1
d00cbeb 1
856efd9eabe5af42a69549497700cabcf937ae5d 1
e5ba0655fc3eab17ba1a3a908030269318107adc 1
ec2904354f545f6b685c55951517f850a031caf4 1
93e604a 1
58ba80f71f2e075cfaf8938e8901e5e08bf982fa 1
c20918610b4776ab2c774eb702f6c4569baacc8b 1
cae121d 1
dc8bad2093562731f46c59ef5f7113df1483a989 1
b5ae4cd 1
e2d85ef935991de3e6424b6f5ba06525fa95e2cc 1
a3f5b8c1d4e7092f6a8b3c5d1e7f9a0b2c4d6e8f 1
ed93f11bc1fbeced0638b487b18209920e644d7a 1
1fab7e2b582afa07acd1c7fadaf7de0ffcfaab61 1
d47f82a3e535278fd17f3c132573d1054cd3a81d 1
d50cdd52cab0f8fdbb3562174ad2da63f3b7d049 1
102e618da0e119add600459342340079b0eae2d8 1
e7fce0c5a9d988880a7a4eb33cef0c59193c7e48 1
62285a64ecbe902649b6d03d4805ec11100302ee 1
0d6905d7d2b902623423ebfa97865bb00a515544 1
ebe6182d7fcb078f580277abcab0c2237f4f196e 1
f02246fe17c2f5f16d26d87043478f730b5317bc 1
d4202a0eac1f5ab603ac72b7e275892b40374768 1
97e7eecab9e0c0953ad5d7ea72cc5e56723e067f 1
6a49d2b57507568fe31eac53784898cfe1fb35a5 1
"Initial commit: Simple CRM MVP scaffolding" is: d57d9791220fdc7030270eb592e35bbb4744f203 1
f66c669cb19f7248f8dec92c273cb9c5e9312681 1
8cc4333f76351e09bd27ef0f96bb68367e4fb944 1
3b21e00d1bb25a4a58bd3b2c1b697ee8b7379935 1
686f22dc23051aaf090e7878eba9ddf195e09674 1
d1645d6 1
f452488 1
SHA-1 command: git rev-parse HEAD Full SHA-1: 44ea39842a272190c3110e38458746acf276b8bf 1
0d6dfe143745be20c84789681caa140117104ed4 1
e82f16329eaacaa5ada78070cbce2bd4aa4f2db6 1
34e2cb6 1
58a5227a08a26687fb4f38154a68677bb6e5cfea 1
a791d98d636e188ff34a2349d6303e99a53abfbe 1
61cb133c2429c3bcec6e20f4709cf9378645af3d 1
a4ba271f73e667c43db907d6a4c82f6dd39a3966 1
baebec66988f4d26e7ca557e3a040ef79f75877b 1
2650658 1
8b9d7805b8cdb924691e40477f8c8ec77cb12a66 1
48530e46519efa22e138aeaa60300a0d60c00549 1
f93738a3f90a63e6ee4edaa022fd7d344712429d 1
6137937ef908a35858ce1f89cf8a6850619aa251 1
fb9e519 1
688407b21d91b5d41b2e3a3b05fd493b33c78cc1 1
262333eae5cd5cc904a4661216e6ab65c805ac52 1
1d1d9c5 1
dedb262 1
cf878545446c6ab67ee7a4ccbfe61edcccaa6579 1
fb32f6b033d2f4c70a6b343c493b50804d605167 1
eb0cd55 1
2511679 Start Homework 2 Flux 1
d35a91b 1
cc5dd5a 1
013b87f5d99e7fd0a58a7a877e0205ee3fd8a3a8 1
7ad5a24ca4fa05e0f4f7f46c5780de5d92b1b656 1
d36de123ca0e511c6e73c93c6b635ebf4cfd842b 1
da69112 1
9b7878afe7559a03d47c4c7abcc2bc737d7af2a1 1
1432ffc8493998f8573c09561e4edf49dc53448a 1
d742b8c02f4efd73f3a95557d0a7541922b485db 1
3f58c8c8fdcacf5dd336c157dd1dbc832106820c 1
1b57a75f4f101c9c995e58b9d680d813b08a67bb 1
6a6ff3739e54b1381759bd6551868b3811bbaa4c 1
git rev-parse HEAD 1
b735907836d3f4f60e062a6b437f71b8a4825511 1
a28ecc1e3364382d92efb1bb896f70a4ba467698 1
c5403af27d9f06a725b9f7982606b38e295b841b 1
0e3bd09801eda07bd6f6972478b99672f001b2f4 1
1511eebaee085c418ed021fb99f49a7cf90ac781 1
5ba74ae4fbe9844f13267a7aba73e44fda81d895 1
f016987 1
a5ac0bc9d52d7ef03b3f0a099ee7e1e485f1d7e8 1
926bc90 1
313b857 1
e9bdf8a0dc188c4dd7f25ffdd10efa1403167208 1
57e6a0f0ae1078ea34bf3b0342f6a71b678876f8 1
e15545d10c080251c1333ca051702314f7a09924 1
55e50463b9dfb4909252705e6dec85e38977fbf0 1
f23be746428e39f6e3ba36d71f9ef4f0015bbe18 1
0c9494c2a8a913dea4b4804d66149ba9ea42950b 1
d5fe28024d556685b660c8ea0e6ba4e373028954 1
4c5273494b067ac370f15d27f51485bdecdfbb40 1
a77b7e65fc5e164834baf8b6f4a9eba5599ccefd 1
4c94176dd154cfbe7463e38c0662b48ad7d53035 1
ff07360 1
ce7ae1e 1
1d8ee91a07ff733feb9c191ffb54978d879c806f 1
Commit sha1: b869261 1
4744c72b6452977f55a994530a67ea16d36edba8 1
85a6dab3032237b4d57594ae08f866ebfff62e63 1
95fed8503f3a6165db6d4fb225e0da2f84bbdd12 1
718aecd6f4e627b0d0fbbe5bcd2e6dce15004768 - the specifications commit 1
4456845ce996a1310d33573d3014d188bdb6812c 1
4acf474312e6ee37ae38c233e27768a7daf73bf6 1
57dda2d41d1706a420ec2b06ad1920eeb6f91ed4 1
72bcfa8 1
514de3953015992e08766f4687385a135f630c83 1
56a3ece55177bda53865e75a1dc393e7c1bdd3df 1
commit 2e46b1c2a2ed7e40416cc5bc6b70d58f3ca64c17 (HEAD -> main, origin/main) 1
9e52f18 1
87e223477ab4f4651da5cc4efe4e4c7eb4fc7167 1
51179816bb5a959b1b6fa5a98c5a6126e6970ae2 1
70504a154a9d5153a6a04ea449ad93d98bb14ca0 1
4b2124927b45ae73bb6a9edeac01848a74bf8dad 1
git commit -m "Initial TABLEOK full-stack implementation" 1
fb519f35d7a78bc3d48249a2a2c378c4eb57bfc6 1
a6d52a6 1
d73571258e905a75296630576afa70b53ae294cc 1
8cd0a8c4ef0b58f09f2218b0c1f22170985c650d 1
318ecba2024047610630c60af1062ea3baa5d925 1
1a010a8030aae5fdd980c918c07b12d0ccd1a470 1
3b308af 1
35ba871e6a5f737ac16c4d3d561c1c44576cfba1 1
e925ce4fe844dbfafb36e9e6a212e46968d4337e 1
a2cc0f074930c08d3142d1f42efb587565dba64d 1
c36a34342200649a8775a17a638ccdccb4b5062b 1
968834643cef6327c533ddc682f648e0fb98dea3 1
5b59e5163ccbdf17a15baa08ce6b76780fd72ba9 (o 5b59e51) 1
3d6cd1d42ac4478a466e36ea41d681aa03e1bd35 1
532733beda172c14f3aa9294bac1ca81f96289db 1
9ce400c1f0656865c80a8a9a0c683e2d30ed5263 1
6afaf35 1
16466a76f117ae97a0843b48c2d80c1d8823834b 1
f428a7e 1
09860006c55a4a938984ed0ab610579e9428316e 1
067c809834981fcb7cccea3969e151005de354c5 (short form: 067c809) 1
a71b13fbd9d3d7a79c1be8196647de32c23c3f5a 1
c07a388d15454b310738f3f1508ae4e87ac4c3b0 1
443a50456539dbe0de0229ed1116bee9648154a5 1
6eee7cecae39d95bf0bf2b4aea1c23869b6bd6dd 1
8fa2e2d499dcb8c9515fe5cf2b8a2ea759e5fa38 1
e3b303ea040d553750568d580b462275fbdae24d 1
6c9517eb99ac0d591b99bfcd42fe91c5734520e6 1
2662fda9a3fa71dc88668e5a9555d0afd41df214 1
8971501c418146e5a9ee9cca686dd48642dfd5aa 1
db9201e24647248ba72952f7dd78ff1b188019ac 1
6036f72c745ebeb5a6f31cf5155f5a00303ee871 1
2cf19c0582199e28949fbbbaa4429e71b0649a06 1
8d0fe9e13f4b8a42e589df7b5ebdc9e8182d8665 1
3ba68a70802c7e7df182eb9a9eb5392e7a792373 1
d12cbbc 1
8a73b51d9cbbcd670272067faec92cc9e4250486 1
2489d8d21b8ab9dfde5876e7586faf52baaaefa5 1
79bf04b0c54568e1dd9a6ac21ac57fbd0751c292 1
cad9dc9a3cac4f4fd074ba7d8553bdedde791718 1
45bb9ba9159b8a3490bb62aa9522d0e261dc728f 1
2bb8eec4df441009f6627e0e9ac4c598700abefb 1
a42a5bb452daf6a4e4624e3dc67095a388bb271e 1
986c155 1
c25af81692f1f5940c4ca21a57201fd649a07365 1
12699a0 1
aae68870d863c15dcdd8ccd731c22b035d66bc6f 1
95459e3a909346712999c10a98b4bdf00f1ff7b0 1
19e51e14c8b23c8301e34d8ab240b7b15e1c0201 1
499b32fea4e4d91516f6f142f61c93a9bed57ef2 1
15f77a6ac460efa43f2bf1bff4839826b081cce7 1
067c809834981fcb7cccea3969e151005de354c5 (short form: 067c809) 1
a5e9026e52a33e13ae9b99fce69ad07bd63e5eea 1
4339441502603adbd01537d22027c074f69c81e5 1
804fabcc54604f6e6c0efea3bde7a5a92416402b 1
5b2daa2e7d7bf9296e8bf5347094103061abe6a3 1
c294d1c 1
f9e4f5a9d48bf024a0fc433c71d0e5c83dd881a6 1
1a11b3d 1
4b53500600502eadbf3038dd5247bbf9007200fa 1
a61b5b9063c8b4cd4f0361224458fc71b5f9acaf 1
cf7d8293b0655bdfb7ee647c95d299468fe2363b 1
2420c88 1
https://github.com/davidacodes/table-tango-assist/commit/f9e3c5c22600f71635c16cedbdfe0b453bac686c 1
3eb67bb 1
1829b771b0dd2e795411837106eb26b1be890cd6 1
f820dc160517ef2ced9f4b9e6fa820ee1261d041 1
36671f7ac9f2230704217b4d69a1c3a6dcf24769 1
61d065ab329fb7df8bf70246cfd0518b020daa44 1
afe115dac1459a9ecd08d3ab5f45c2539d7fb78e 1
6594dde5ca66b071a7e342843b9a3ee0a0609f65 1
git log --oneline -1 1
832e6629bb858455a2bb2609868a65f6d2b53e8a 1
5e47bd4a85b4d1475e7a186c5f54244930ecf75e 1
be95414 1
b3f1b73c8941c55731959bdbe1d1a77989f05f6c 1
7dafa66 1
02547477af0e6a144f20640603c6f465afc98902 1
7a8c3de23e0066e06c39b892e2bd9783f4ec0b84 1
b84936746c9e6b8bd477ded6cb92c0584c318bc2 1
342402a49fc329c55fb53534eba9fff5ff709f0c 1
3a26ad3ec464f1b4991c08c03c87f03757aef3f9 1
43afc5780d8781273997dacf90347473de8618a9 1
7915c36f169ec3bcf150ea60683fa9c7f18098f8 1
de56aeb5d0660400430280cdca2dc5a0a9b06c55 1
d365012a3b5388e426046bbbe6ea8a55f382db23 1
e04baf6 1
84b70b9 1
d7b2c5c244ab8355e1908fa29b5c1d5dd0767e35 1
81a3eb7d65107194e586e160d18ca1286b753da8 1
b7844feff5781dc6c67b22b14b0328bf15a00e52 1
4d1598a497de67f67e8a9f6aefeb424ca90d20ac 1
324ee4e67fd2c5a5ffe9013cbc342ee6d2f01657 1
bf3a240d61d23ce7dcef02664abbec0911614402 1
995e5f8371d75642a0a0a261ae1c91c82648bdb4 1
0f40ed0 1
056edeaa119a222a6991008ea87b06c5a2144e1a 1
38dd0286e4f9cc56af14d7624b5ce21bda68063f 1
8e32ca74bb2ddaba9b9db8b7e1de373aab37be58 1
102da9ba89495c08a63644b018376e9f6ac97716 1
482af1c378e30c8e71ed8443b05a02cafb31eba8 1
1b59302bc8ea3dc182e30f926e903df13dd42b8c 1
b087763b68681eff466853e81a9b04cf0ba78bba 1
c05c01bbfdf32a9f57d7a15e0d39545aa6367a95 1
e48cb6ddf077528896a8a0685168e32b63f7f9d2 1
552242e1ba3f21581ad8f5219c1c7b228f66fdf9 1
4243fbccb66b14cf23e6485d89ad0adccaad7b3f 1
e4c69899d817db71ee439605e68af3da694cbff2 1
add8792 1
e111c6f2f051af0d9a607cb34f9d2ca178f4859a 1
d57e0f6db212eb49eb403fb50a986b64aa50797e 1
e1b705c2a1f844db2c3128bc3f1e8b67c6fcb3c2 1
b13a7ed2cefc60953a965d4b3735dfe4e67d4918 1
99c63f6f6095349558f6cff787d9e03ca55da08e 1
1d7aefdb5450e119e6d9d1a7ac6535898ab2dda4 1
• 7b137e8343150a561f8b48bd447e415a974a7ea7 1
cecd39f 1
f6191af8cb8d206fbfaab504e2e08fa39ce4299c 1
9f876543c904ad1aafefbc5490a3212934f34c04 1
c7afa9586dc31f0fc5cd552ca4cb83e26aab6827 1
f3e60795b8596586626c8f63f841fa06d1b1d973 1
For the frontend 2dc9ed6e15d48b69820ef37e048aeeb4f4611d4b 1
528a2592637d9d5bdf298a7b6940b446e7a9f993 1
6eea722d5ccd0bcdd4652d83fab258a44119dfba 1
d183e4d 1
5caf77d57c211a77e5ee30fa7e9ecf321ed87123 1
git rev-parse --short HEAD 1
HEAD is 8fe5433fc315d693d8e9cf174c5be775fcfab28a. 1
7aa187d 1
60ebd81219c3b55660da4eb52caa42e2fd2b8703 1
95c6c5446b01873595dccd268d0a83faa72456de 1
6ca8892a633856fbc4cb876feffd834e1064c9e1 1
9ecec1ecdbea50d6f9f3e3c0976f492c17d4633c 1
SHA1: 58f2ad1dc1f7fae9b683057d0deea3096bc70b5d 1
63381447553b2235d1f439517add5a2db067ad11 1
9ba8e39aec0272577dd491e39f91ed1321b5787a 1
38f3ee353da43a2ab723ea4caa7f015d48c67436 1
b1f281a3a63e7960396dba8af98c886997e3d4dc 1
f432853c68bbd3aeb39517e39a42b7594fefb981 1
20b3277 1
0000000000000000000000000000000000000000 1
d64a054 1
89150466aee0a40c5d7c3965f1fb09a7a7340af9 1
3a04a0e3d05f62da2415e28722c583c8c46e87d7 1
73cb224f3e18b8c3f28ca9cb216b3e23911b7aad 1
eccaecef24025912ac758d1642b8f59ca5578468 1

4. Which command do you use to start the frontend?

260 / 260 correct (100.0%)

Answer Count
npm run dev 125
cd frontend && npm run dev 16
make frontend 7
cd frontend && npm install && npm run dev 5
make run-frontend 4
cd frontend npm run dev 4
npm install && npm run dev 2
npm.cmd run dev 2
docker compose up --build -d frontend 2
uv run python manage.py runserver 2
cd frontend && python3 -m http.server 5500 2
npm run dev (from frontend/) 2
npm --prefix frontend run dev 2
pnpm dev 2
streamlit run frontend/Home.py 1
cd Homework2/frontend && npm install && npm run dev 1
pnpm --filter frontend dev 1
python -m http.server 5173 --directory frontend 1
python3 -m http.server 8123 -d frontend 1
uv run npm run dev 1
$make frontend (`$npm run dev` inside a folder with nvm) 1
make frontend (or cd frontend && npm run dev) 1
npm run dev from frontend/ 1
make run-frontend / npm i 1
make dev-frontend 1
npm run dev (after npm install, from frontend/) 1
python -m http.server 8000 1
cd frontend → npm install → npm run dev 1
make dev 1
uv run python -m http.server 8000 --directory frontend 1
python3 -m http.server 5500 1
npm run build 1
npm run dev (after npm run install) 1
npm start/ng serve 1
.make.ps1 frontend 1
cd frontend py -m http.server 5173 1
npm run dev after cd frontend 1
cd Homework2/frontent npm install npm run dev 1
cd frontend && npm run dev -- --host 0.0.0.0 --port 5173 1
python3 -m http.server 8000 1
python3 -m http.server 3000 --directory frontend 1
cd frontent && npm run dev 1
npm run dev (run in frontend/; or `make frontend` from the repository root) 1
npm run start 1
.\make.ps1 frontend (or from frontend/: npm run dev) 1
npx --yes serve . 1
cd frontend -> npm install -> npm run dev 1
make a system named will be Tableok and Tagline will be Table worth to wait. Common components will be queue, database, LLMs, rectangles, I mean like services. The app should be for both parties, i mean the person or restaurant or staffs of the hotels or pubs, cafes. Also for the clients and customers who are waiting for the table to be reserved by him/her or anyone. You can also ask me questions and make it interactive. Also keep it in my mind many people can join at the same time. 1
could you suggest me couple different style of it could go from and i will pick one from it and give me pics of it to compare with like maybe 3 versions of it 1
make run-mock 1
React + Vite in evensplit/frontend/, all backend calls centralized in src/api.js (mocked initially with a USE_MOCK flag). Start command: npm run dev. 1
VITE_API_BASE_URL=http://localhost:8000 npm run dev 1
python3 -m http.server 8080 1
cd frontend -> python3 -m http.server 5173 1
Run from the frontend/ directory: `npm run dev` 1
cd ../Lesson_2_SimpleKanban/frontend python -m http.server 8020 1
npm install # first time only npm run dev 1
wslview frontend/index.html (or explorer.exe frontend/index.html 1
npm run dev --prefix frontend 1
npx serve frontend 1
npm start 1
python3 -m http.server 4173 1
cd frontend then npm run dev 1
npm run dev Q5 1
Start frontend — from repo root: PORT=22152 BASE_PATH=/ pnpm --filter @workspace/kanban-board run dev (or make dev-frontend; make dev / make run starts both) 1
cd frontend, npm run dev 1
cd 02-development/src/frontend && npm install && npm run dev 1
npm run dev:frontend 1
npm run dev (in frontend/) 1
python3 -m http.server [port] 1
make dev-frontend (or cd frontend && npm run dev) 1
cd frontend && python -m http.server 8000 1
npm i && npm run dev 1
cd frontent ; npm run dev 1
py -m http.server 8765 1
cd /home/user/karate-scoreboard/frontend && nohup npx vite --port 5183 --strictPort > /tmp/vite.log 2>&1 & disown 1
make frontend (or cd frontend && npm run dev) — serves at http://localhost:5173 1
npx http-server frontend 1
python3 -m http.server 8080 --directory frontend 1
python3 -m http.server 4173 --directory frontent 1
cd "02 - development/frontend" npm run dev 1
npm run dev -- --host 127.0.0.1 1
npm run dev -- --host 0.0.0.0 1
pnpm run dev 1
1. First go to frontend folder. 2. Run `npm install` 3. Run `npm run dev` 1
docker compose up --build 1
cd frontend; npm install; npm run dev -- --host 0.0.0.0 1
cd homework_2/frontend npm.cmd start 1
make dev-frontend (cd frontend && npm run dev) 1
bun run dev -- --port 5173 1
python -m http.server 3000 1
npm run dev — from frontend/ 1
python3 -m http.server --directory frontend 8000 1
make frontend; cd frontend & npm run dev 1

5. Which command do you use to start the backend?

260 / 260 correct (100.0%)

Answer Count
uv run uvicorn app.main:app --reload 31
uv run uvicorn app.main:app --reload --port 8000 19
make run 12
uv run uvicorn main:app --reload 10
uv run fastapi dev app/main.py 6
make backend 6
uv run uvicorn backend.main:app --reload 5
cd backend && uv run uvicorn app.main:app --reload 5
uv run uvicorn app.main:app --reload --host 127.0.0.1 --port 8000 4
uv run uvicorn app.main:app --reload --port 8091 4
uvicorn app.main:app --reload --port 8000 4
cd backend && uv run uvicorn app.main:app --reload --port 8000 3
make run-backend 3
npm start 3
npm run dev 3
uvicorn app.main:app --reload 3
uvicorn backend.main:app --reload 2
python -m uvicorn app.main:app --reload 2
uv run uvicorn backend.app.main:app --reload --port 8000 2
docker compose up --build 2
uv run fastapi dev 2
uv run uvicorn app.main:app --host 0.0.0.0 --port 8000 2
docker compose up --build -d backend 2
npm run dev:backend 2
uv run uvicorn app.main:app --host 127.0.0.1 --port 8000 2
uvicorn main:app --reload 2
cd backend && uv sync && uv run uvicorn app.main:app --reload --port 8000 2
cd backend && uv run uvicorn app.main:app --reload --host 0.0.0.0 2
KANBAN_SECURE_COOKIES=false uv run uvicorn kanban.main:app --reload --port 8000 1
py -m uvicorn backend.main:app --reload --port 8000 1
python manage.py runserver 1
uv run uvicorn waitly.app:app --reload --port 8000 --host 0.0.0.0 1
uv run --directory backend uvicorn expense_splitter.main:app --reload 1
cd backend && uv run fastapi dev src/app/main.py 1
uv run uvicorn app.main:app --host 127.0.0.1 --port 8000 --reload 1
uv run mamban-backend 1
uv run uvicorn waitlist.main:app --reload 1
uv run uvicorn backend.app:app --reload --port 4000 1
uv run seatly-backend 1
make dev-backend 1
uv sync && uv run uvicorn app.main:app --reload 1
uv run uvicorn app.main:create_app --factory --port 8000 (after uv sync, from backend/) 1
uv run kanban-backend 1
uv run python manage.py runserver 1
cd backend → uv sync → uv run nexus 1
uv run uvicorn seatcute_backend.main:app --reload --app-dir src 1
uv run uvicorn backend.main:create_app --factory --reload --port 8000 1
uv run uvicorn lanedeck_backend.main:create_app --factory --reload --host 127.0.0.1 --port 8000 1
cd backend && uv run uvicorn nookan_backend.main:app --reload 1
uv run uvicorn app.main:app --port 8000 1
uv run uvicorn scoreboard_api.main:app --reload --port 8001 1
uv run uvicorn app.main:app --host 0.0.0.0 --port 43131 1
.make.ps1 backend 1
uv run waitly-api 1
uv run uvicorn backend.app:app --reload --port 8000 1
poetry run uvicorn backend.main:app --reload --port 8091 after cd backend (note I use poetry not uv) 1
cd Homework2/backend uv run uvicorn app.main:app --reload 1
uv run python -m backend.app 1
uv run uvicorn app.main:app --reload --port 8001 1
cd backend && uvicorn app.main:app --reload --port 8000 1
cd backend && uv run uvicorn --app-dir src tasklane.app:app --reload 1
cd backend && uv sync && uv run fastapi dev app/main.py 1
uvicorn backend.main:app --reload --port 8000 or .\backend\venv\Scripts\python.exe -m uvicorn backend.main:app --reload --port 8000 1
\make.ps1 backend (or from backend/: uv run uvicorn app.main:app --reload --port 8000) 1
uv run uvicorn backend.main:app --reload --port 8000 1
uv run fastapi dev app/main.py --port 8000 1
uv run uvicorn backend.app:app --reload 1
cd backend -> uv sync -> uv run uvicorn app.main:app --reload 1
uv --directory server run fastapi dev src/flowlane_api/main.py 1
uv run uvicorn src.main:app --reload 1
cd backend && uv run uvicorn app.main:app --port 8000 1
Now we move from API design → backend implementation. 1
Based on openapi.yaml, create a FastAPI backend. Use uv for package management. Use a mock database, we will replace it with a real one later. Write tests for the endpoints first, then implement them. 1
uvicorn main:app 1
Question 5: uv run uvicorn app.main:app --reload 1
FastAPI in evensplit/backend/, managed with uv. Tests written first (tests/test_api.py), then endpoints, first against a mock in-memory store. Start command: uv run uvicorn app.main:app --reload 1
uv run uvicorn quits.app:app --reload 1
uv run uvicorn app.main:app --reload --port 8009 1
To start the backend: `uv run uvicorn app.main:app --reload --port 8000`. The API will be available at http://localhost:8000 with auto-generated docs at http://localhost:8000/docs 1
python app.py 1
cd backend-> uv sync -> uv run uvicorn backend.main:app --reload --port 8091 1
make install install backend dependencies (uv sync) make run run the backend dev server on http://localhost:8020 make test run the backend test suite 1
uv run uvicorn backend.main:app --reload --port 8001 1
cd backend uv run uvicorn app.main:app --reload --port 8000 1
uv run uvicorn quickqueue_backend.main:app --reload 1
cd backend && uvicorn main:app --reload --port 8000 1
cd backend && uv run uvicorn app.main:app --app-dir src --reload --port 8000 1
uv run uvicorn tableready_backend.main:app --reload 1
uv run uvicorn app.main:create_app --factory --reload 1
uv sync | uv run uvicorn app.main:app --reload 1
cd Homework2/backend && uv sync && uv run uvicorn app.main:app --reload 1
uv run --locked uvicorn kanbloom.api:app --host 127.0.0.1 --port 8000 1
python -m uv run uvicorn app.main:app --reload 1
uv run uvicorn app.main:app --reload --port 5000 1
$uv run --directory $(BACKEND_DIR) uvicorn app.main:app --reload 1
make run (or cd backend && uv run uvicorn main:app --reload --port 8091) 1
make run-backend / uv run uvicorn app.main:app --reload -p 8000 1
cd backend -> uv sync -> uv run uvicorn backend.main:app --reload --port 8001 1
Start backend — from backend/api-server/: uv run uvicorn app.main:app --host 0.0.0.0 --port 5000 (or make dev-backend) 1
uvicorn app.main:app --reload --app-dir backend 1
cd 02-development/src/backend && uv run uvicorn app.main:app --reload --host 0.0.0.0 --port 8000 1
uv run fastapi dev main.py 1
uv run uvicorn app.app:app --reload --port 8000 1
uv run backend/manage.py runserver 1
uv run uvicorn app.main:app --reload --port 8000 from backend/ 1
cd backend && uv run uvicorn app.main:app --reload --port 8091 1
uv run uvicorn app.main:app --reload (in backend/) 1
uv sync --group dev && uv run uvicorn backend.main:app --reload --port [port] 1
make dev-backend (or cd backend && uv run uvicorn app.main:app --reload --port 8000) 1
cd backend && uv run uvicorn app.main:app --reload --port 8001 1
uv run uvicorn app.main:app --port 8000 --reload 1
uv sync && uv run unicorn app.main:app --reload --port 8091 1
uv run uvicorn app.main:app --reload (run in backend/; or `make backend` from the repository root) 1
cd backend; uv run uvicorn app.main:app --host 127.0.0.1 --port 8001 --no-access-log 1
vicorn backend.app.main:app --reload --port 8000 1
cd /home/user/karate-scoreboard/backend && nohup uv run uvicorn app.main:app --port 8000 > /tmp/uvicorn.log 2>&1 & disown 1
make backend (or cd backend && uv run uvicorn backend.main:app --reload --port 8091) 1
uv run uvicorn app.main:app --reload --port 3000 1
cd backend && uv run uvicorn app.main:app --reload --host 127.0.0.1 --port 8000 1
cd backend uv run uvicorn backend.main:app --reload --port 8000 --app-dir src 1
cd "02 - development/backend" uv run uvicorn app.main:app --reload 1
make sync (if no dependencies Yet)/ make run 1
uvicorn backend.main:app --host 0.0.0.0 --port 8000 --reload 1
uv run fastapi run app/main.py (from backend/) 1
node dist/server.cjs 1
uv run --project backend uvicorn backend.main:app --reload --port 8000 1
uv run uvicorn entrystock.analytics_api.main:app --reload --port 8001 1
make run (first time: make install) 1
uv run uvicorn app.main:app --reload --host 0.0.0.0 --port 8000 1
cd backend; .\.venv\Scripts\python.exe -m uvicorn app.main:app --host 127.0.0.1 --port 8000 1
uv run fastapi dev src/boardly_backend/main.py 1
uv run uvicorn littleboard.main:app --reload --port 8000 1
make dev-backend (cd backend && uv run uvicorn app.main:app --reload --port 8000) 1
uv run uvicorn taskflow_backend.app:create_app --factory --reload --host localhost --port 8000 1
cd backend make dev 1
pocketflow-app 1
uv run uvicorn splitledger_backend.main:app --reload — from backend/ 1
cd backend && uv run python app.py 1
uv run uvicorn app.main:app --reload --port 8000 (from backend/) 1
make backend; cd backend & uv run uvicorn splitit_backend.main:app --reload --port 8000 1

6. Which URL does the frontend use to talk to the backend?

260 / 260 correct (100.0%)

Answer Count
http://localhost:8000 93
http://127.0.0.1:8000 31
http://localhost:8000/api 20
http://localhost:8091 10
http://127.0.0.1:8000/api 8
http://localhost:8000/api/v1 7
http://127.0.0.1:8001 4
http://127.0.0.1:8000/api/tasks 3
http://localhost:8001 3
http://localhost:5173 2
http://localhost:5173/api/ 2
ws://localhost:8000/ws 2
http://127.0.0.1:8080/ 2
http://localhost:8091/api 2
http://127.0.0.1:8000/api/v1/ 1
http://localhost:8091/api/v1, 1
The URL is /api (configurable via VITE_API_BASE); in development it's served from the same origin as the frontend, and Vite's proxy redirects it to the backend at http://127.0.0.1:8090. 1
http://127.0.0.1:8787 1
http://localhost:8000/api/ 1
http://localhost:4000/api/v1 1
http://127.0.0.1:5173/api, which calls http://127.0.0.1:8000 via proxy server 1
http://127.0.0.1:8000/api/ 1
http://localhost:8000/api/state 1
http://127.0.0.1:8000/api/v1 1
http://localhost:8000/api/matches/ 1
The frontend calls relative paths like /api/scoreboard and /api/favorites 1
http://localhost:43131/api/board 1
http://localhost:5000 1
8000 1
http://localhost:8000/api for local development .the deployed version, this is build-time-configurable via the VITE_API_BASE env var (currently pointed at restaurant-backend-9ce6.onrender.com). 1
http://localhost:8001/v1 1
http://127.0.0.1:8091 1
http://51.68.121.19:8000/api 1
/api/v1 1
http://localhost:8000 (set by VITE_API_BASE_URL in frontend/.env) 1
http://localhost:5173/api — the frontend calls relative /api/... paths on its own origin, and the Vite dev server proxies them to the backend at http://localhost:8000. 1
default is http://127.0.0.1:8000 1
localhost:8000/api/* 1
http://localhost:8080/api/v1/ 1
sqlite:///kanban-app/kanban.db 1
/api 1
http://localhost:3000/ 1
http://localhost:8123 1
http://localhost:8000/api/trips/<token> 1
http://localhost:8009 1
http://localhost:5001/api 1
http://localhost:9127/api 1
via vite proxy --> /api, literal http://localhost:8000 1
API will run at http://localhost:8000 (Swagger documentation at http://localhost:8000/docs). 1
http://localhost:8020/api — defined as BASE_URL in frontend/js/api.js, the one place all backend calls go through. 1
http://localhost:8000/ 1
The frontend uses the relative URL /api, o 1
http://localhost:8001/api/v1 1
http://localhost:8000/api or http://localhost:8000 1
The frontend calls the backend at the same-origin relative path /api (e.g. GET /api/projects). In dev, Vite proxies /api → http://localhost:5000 (frontend/kanban-board/vite.config.ts:50-55), so you access the app through the frontend URL at http://localhost:22152. 1
https://coding-interviews.onrender.com 1
http://localhost:8001/api 1
localhost:8000/api 1
http://localhost:8091/api/v1 1
localhost/api/scoreboard and localhost/api/matches/{id} 1
http://localhost:3001 1
http://127.0.0.1:8000/api/.... 1
http://localhost:8000/api/v1\* 1
http://localhost:8091 (see VITE_API_BASE_URL in frontend/src/services/index.ts) 1
http://localhost:3000 1
http://localhost:8000/api/v1/matches 1
http://localhost:8081/ 1
http://localhost:3001/api/tasks 1
http://127.0.0.1:8000/api/scoreboard/{dateKey} 1
http://3.22.100.241:8000 1
http://localhost:3000/api 1
The frontend uses relative URLs (e.g. /api/people) with no hardcoded host. The Vite dev server proxy at vite.config.ts:9 forwards all /api requests to http://localhost:8000. 1
http://localhost:8000/v1 (VITE_API_BASE_URL in frontend/.env.example, consumed by src/services/restWaitlistService.ts) 1
http://127.0.0.1:8000/api/task 1
uv run uvicorn app.main:app --reload 1
/api (proxied by the Vite dev server to http://127.0.0.1:8000) 1
http://localhost:8000 (since we are still in local development) 1
http://localhost:8000 (from VITE_API_URL) 1
http://localhost:3000/api/tasks 1
http://localhost:5173/api 1
http://127.0.0.1:5000/api/... 1
the frontend calls the backend at  http://localhost:8000/api/v1  by default, configured via the  VITE_API_BASE_URL  env var (read in  frontend/src/lib/mock-api.ts , falls back to that same default if unset). To change it, copy  frontend/.env.example  to  frontend/.env.local  and edit the value. 1

7. Which command do you use for running tests?

260 / 260 correct (100.0%)

Answer Count
uv run pytest 81
make test 26
cd backend && uv run pytest 18
npm test 14
uv run pytest -q 11
pytest 10
uv run pytest -v 5
uv run --directory backend pytest 3
python -m pytest 2
uv run pytest tests/test_api.py 2
docker run --rm -v "$(pwd)/backend":/app -w /app python:3.12-slim \ sh -c "pip install -r requirements.txt && PYTHONPATH=. pytest tests -q" 2
pytest backend/tests -q 1
cd Homework2/backend && uv run pytest 1
Backend tests run with uv run pytest -q from backend/; frontend tests run with npm test from frontent/ 1
cd backend uv run python -m unittest discover -s tests -v cd frontend npm test Browser checks: npm run test:browser 1
uv run pytest (and npm test for the frontend jsdom suite) 1
python manage.py test 1
For the backend: `cd backend && uv run pytest`. For the frontend: `cd frontend && npm test`. For the end-to-end tests: `cd e2e && npx playwright test` 1
uv run --project backend pytest backend/tests -q, and npm --prefix frontend test 1
from backend/: uv run pytest 1
Frontend: npx --yes pnpm@10.34.3 run test Backend: uv run pytest 1
python -m pytest tests/ -v 1
uv run python -m pytest 1
npx playwright test --project=end-to-end 1
uv run pytest (in backend/) 1
uv run python -m unittest discover -s tests -v 1
python -m pytest tests/ -q 1
cd backend uv run pytest || cd waitlist-app npm.cmd test 1
uv run pytest ../tests -v 1
uv run pytest -q / npm run test(in frontend dir) 1
.make.ps1 test 1
uv run --directory backend pytest -v 1
Backend: make test, Frontend: npx vitest --run 1
cd Homework2/backend python -m pytest -q 1
cd backend && pytest -v 1
Backend - uv run pytest. Frontend - npm test 1
Backend + OpenAPI contract tests (from the repo root): ``` uv run pytest ``` Frontend tests: ``` cd frontend && npm run test ``` Both at once: ``` make test ``` 1
.\make.ps1 test (or cd backend; uv run pytest and cd frontend; npm test) 1
http://localhost:8000/api/tasks 1
uv run --extra dev pytest 1
cd backend -> uv run pytest 1
uv run pytest tests/ 1
npm run build 1
python -m unittest 1
cd backend -> uv run pytest 1
To run tests: `uv run pytest` 1
make test (from Lesson_2_SimpleKanban/), which runs cd backend && uv run pytest. 1
npm run test:frontend or npm run test:backend 1
uv run pytest backend/test_api.py -v 1
uv run pytest and npm test 1
cd backend; .\.venv\Scripts\python.exe -m pytest -q 1
- Backend: cd backend && uv run pytest - Frontend: cd frontend && npm run test 1
cd backend && pytest 1
pytest ../tests/test_scores.py -v 1
uv run pytest ../tests 1
npm tests 1
uv run pytest -v; npm run test 1
cd backend → uv run pytest 1
uv run --locked pytest -q 1
python -m uv run pytest 1
backend: uv run pytest. frontend: npm exec vitest run 1
uv run --directory $(BACKEND_DIR) pytest 1
cd backend && uv run pytest 1
backend: uv run pytest (from backend/api-server/); frontend: pnpm --filter @workspace/kanban-board run test; both at once: make test. 1
cd 02-development/src/backend && uv run pytest 1
uv run --project backend pytest | npm test 1
from backend/, run uv run pytest 1
(cd backend && uv run pytest) && (cd frontend && npm test) 1
uv run pytest from backend/ 1
make test (or cd backend && uv run pytest -v) 1
uv run pytest (run in backend/; or `make test` from the repository root for backend and frontend) 1
python -m pytest backend/tests -q 1
poetry run pytest 1
uv run pytest (from backend/) 1
make test (or make test-backend / make test-frontend individually) 1
make test (backend), npm run test (frontend) 1
npm run test 1
cd "02 - development/backend" uv run pytest 1
make test(For the backend test suite) , make frontend-test (For frontend unit tests) 1
uv run --project backend pytest 1
uv run pytest tests/test_valuation.py 1
Backend: cd backend && make test Frontend: npm test 1
backend: uv run pytest frontend: npm run test 1
uv run --locked --group integration pytest -q 1
test: test-backend test-frontend ## Run all tests test-backend: ## Run backend tests (pytest) cd backend && uv run pytest test-frontend: ## Run frontend tests (vitest) cd frontend && npx vitest run 1
npm test for frontend / uv run pytest for backend 1
backend "uv run pytest -q tests" and frontend "bun run test" 1
python -m pytest && pnpm test 1
cd backend make test 1
cd backend uv run pytest 1
uv run pytest (from hw2/backend/) 1
uv run pytest — from backend/ 1
backend tests run via  make test  (or manually  cd backend && uv run pytest ) — 42 tests via pytest + FastAPI TestClient. There's no frontend test suite yet, only  make lint  (eslint); noted this as a gap and offered to add one if wanted. 1

Calculated: 30 September 2026, 09:25