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AI에게 주면 좋은 사항들

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AI에게 주면 좋은 사항들

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## 앱 목표

- 대상 사이트:

- 목적(무엇을, 어디서, 어떤 형태로 저장):

- 실행 환경(Windows/macOS, 로컬 전용 여부):

## 대상 페이지/흐름

- 시작 URL:

- 로그인 필요 여부:

- 스크롤 방식: (무한스크롤/더보기/페이지네이션)

- 종료 조건(몇 건/몇 페이지/더 이상 로딩 없음):

## 수집 데이터(엑셀 컬럼)

- 컬럼 목록:

- 각 컬럼 파싱 규칙(단위/포맷/없을 때 처리):

- 중복 기준(유니크 키):

## 사용자 입력(필터/검색)

- 입력 항목:

- 기본값:

- 정렬/기간/카테고리 규칙:

## 엑셀 출력 규격

- 파일명 규칙:

- 시트 구성:

- 컬럼 순서/헤더명:

- 서식(필터/굵게/열너비 등):

## UX/화면(UI)

- UI 형태(CLI/GUI/웹):

- 주요 버튼/기능:

- 진행률/로그 표시 방식:

## 기술/제약

- 선호 언어/라이브러리:

- API 수집 가능 여부(Network 확인 결과):

- 배포(exe 필요 여부):

## 예외/오류 처리

- 재시도 규칙:

- 차단/캡차 발생 시 처리:

- 속도 제한:

## 테스트/성공 기준

- 목표 수집량:

- 검증 방법:

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Request URL (엔드포인트)

Method (GET/POST)

Query Params / Payload (page, cursor, offset, size 등)

Response 샘플(일부): 리스트가 들어있는 key가 뭔지 (items, data, resultList 등)

필요한 Headers / Cookies 여부

Authorization 토큰 필요?

세션쿠키 필요?

페이지 넘김 방식 힌트

page=2 형태인지

cursor/nextToken 형태인지

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https://streamlit.io/

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Streamlit turns data scripts into shareable web apps in minutes.
All in pure Python. No front‑end experience required.

Get started in under a minute

Streamlit's open-source app framework is a breeze to get started with. It's just a matter of:

← Copy to clipboard Copied!

← Copy to clipboard Copied!

And you're done! Now check out our documentation and forums for next steps.

Streamlit builds upon three simple principles

Embrace scripting

Build an app in a few lines of code with our magically simple API. Then see it automatically update as you iteratively save the source file.

Weave in interaction

Adding a widget is the same as declaring a variable. No need to write a backend, define routes, handle HTTP requests, connect a frontend, write HTML, CSS, JavaScript, ...

Deploy instantly

Effortlessly share, manage and deploy your apps, directly from Streamlit. All for free!

Used in the world's top data science groups

and...

Compatible with

Basically everything!

And even more, with Streamlit Components! Build your own, share with the community, bask in the glory.

See why developers
Streamlit

Really really pleased with @streamlit so far. Used it to build a clickable prototype for a complex piece of a web application. It turned out faster and more flexible than everything else I could find. Highly recommended! #python #streamlit #prototyping

I spent the day playing with Streamlit, which is like Shiny for python, and here's my initial review:
It is very good.

Streamlit

This one is just impressive. Create and deploy data-driven web apps in the simplest way possible. These apps look great, are easy to update, and can even be interactive. Check it out: https://streamlit.io/

I just discovered the most beautiful thing ever created.@streamlit I friggin love you

No hassle,no complications,no drama
Just straight up works like a dream
Ugh.....I could cry

Machine learning just got a whole lot fun-er

Productionizing your machine learning model is a mandatory part of your ML project lifecycle.

In that context, I have found Streamlit to be very effective and practical, not to mention how fun it is.

Really really pleased with @streamlit so far. Used it to build a clickable prototype for a complex piece of a web application. It turned out faster and more flexible than everything else I could find. Highly recommended! #python #streamlit #prototyping

I spent the day playing with Streamlit, which is like Shiny for python, and here's my initial review:
It is very good.

Streamlit

This one is just impressive. Create and deploy data-driven web apps in the simplest way possible. These apps look great, are easy to update, and can even be interactive. Check it out: https://streamlit.io/

I just discovered the most beautiful thing ever created.@streamlit I friggin love you

No hassle,no complications,no drama
Just straight up works like a dream
Ugh.....I could cry

Machine learning just got a whole lot fun-er

Productionizing your machine learning model is a mandatory part of your ML project lifecycle.

In that context, I have found Streamlit to be very effective and practical, not to mention how fun it is.

Really really pleased with @streamlit so far. Used it to build a clickable prototype for a complex piece of a web application. It turned out faster and more flexible than everything else I could find. Highly recommended! #python #streamlit #prototyping

I spent the day playing with Streamlit, which is like Shiny for python, and here's my initial review:
It is very good.

Streamlit

This one is just impressive. Create and deploy data-driven web apps in the simplest way possible. These apps look great, are easy to update, and can even be interactive. Check it out: https://streamlit.io/

I just discovered the most beautiful thing ever created.@streamlit I friggin love you

No hassle,no complications,no drama
Just straight up works like a dream
Ugh.....I could cry

Machine learning just got a whole lot fun-er

Productionizing your machine learning model is a mandatory part of your ML project lifecycle.

In that context, I have found Streamlit to be very effective and practical, not to mention how fun it is.

Try Community Cloud

Deploy, manage, and share your apps with the world.

Copyright © 2023 Snowflake Inc. All Rights Reserved.

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Streamlit * A faster way to build and share data apps

# data[].attributes.attachment_link.description
Streamlit is an open-source app framework for Machine Learning and Data Science teams. Create beautiful web apps in minutes.

# data[].attributes.headline
프롬프트_거리측정 웹앱

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프롬프트_거리측정 웹앱

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1. Openstreetmap의 nominatim API로 거리측정앱을 만들고 싶다.

2. 웹앱으로 서비스 하고 싶다. 깃헙에 레포지토리 하고 나서 streamlit 으로 서비스 할거야.

3. 출발지를 입력할수 있고, 도착지를 입력할 수 있게 해줘.

4. 출발지와 도착지가 실제 있는 명칭이어야 하니까 조회가 되면 좋겠다.

5. 총거리가 나오게 해줘.

6. 총거리 하단에 "지도에서 보기"라는 메뉴가 나오게 해줘. 그리고 그 링크를 누르면 해당 지도맵으로 연결되게 해줘.

7. GUI를 tailwind css로 구성

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웹앱을 테스트 해줘

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완성된 웹앱을 테스트 하고 깃헙에 올리기

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요청 URL https://crawl-target-server.vercel.app/api/products?category=digital&page=1&pageSize=12 응답 json 샘플 "products": [ { "id": "3", "name": "스마트 워치 S2", "price": 168000, "originalPrice": 199000, "image": "https://images.unsplash.com/photo-1516574187841-cb9cc2ca948b?auto=format&fit=crop&w=400&q=80", "description": "건강 모니터링과 알림 기능을 제공하는 스마트 워치입니다.", "rating": 4.6, "reviewCount": 210, "specialOffer": "Y", "category": "digital", "sellerName": "이민준", "sellerEmail": "genstore_0003@genstore.com" 이다. 이 웹사이트를 스크롤링해서 상품정보와 내용, 가격, 판매자, 가격변동, 각 항목당 고유 URL을 스크롤해서 엑셀 파일로 만드는 PYQT5 기반의 exe 파일을 개발하는 requirements.md 파일 작성