INTL
Freelancer
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외주
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Python Data Scraping Automation
예산
$12,500~$37,500 INR
예상 기간
1~2주
난이도
보통
기술 스택
Python
Web Scraping
Data Scraping
requests
BeautifulSoup
pandas
Selenium
Playwright
Software Architecture
Automation
AI 분석 요약
재사용 가능한 Python 스크립트를 개발하여 공개 웹 페이지에서 데이터를 자동으로 스크래핑하고, 페이지네이션 처리 및 CSV/JSON 저장을 구현해야 합니다. 중급 Python 실력과 requests, BeautifulSoup, Selenium 등 웹 스크래핑 라이브러리 활용 능력이 필수적이며, 깔끔한 코드 구조와 유지보수성이 중요합니다.
프로젝트 원문 설명
A reusable Python script is required to automate data scraping from a series of publicly accessible web pages. The script should accept a list of URLs, navigate through any paginated content, extract the specified fields, and save the results to CSV and JSON.
The task suits someone with an intermediate grasp of Python who is comfortable working with libraries such as requests, BeautifulSoup, pandas, or, when a site relies on JavaScript, Selenium or Playwright. Clear, well-commented code and concise setup instructions are essential so the script can be dropped into an existing workflow without modification.
Acceptance criteria and deliverables:
• Fully functional .py script that runs from the command line.
• Configuration section (or .env file) for URL list and field selectors.
• Output in both CSV and JSON, written to an /output directory created by the script if missing.
• A brief README explaining prerequisites, setup, and sample usage.
• Confirmation the scraper respects robots.txt and rate limits to avoid blocking.
The project is straightforward but demands attention to clean structure, error handling, and maintainability consistent with intermediate-level best practices.
The task suits someone with an intermediate grasp of Python who is comfortable working with libraries such as requests, BeautifulSoup, pandas, or, when a site relies on JavaScript, Selenium or Playwright. Clear, well-commented code and concise setup instructions are essential so the script can be dropped into an existing workflow without modification.
Acceptance criteria and deliverables:
• Fully functional .py script that runs from the command line.
• Configuration section (or .env file) for URL list and field selectors.
• Output in both CSV and JSON, written to an /output directory created by the script if missing.
• A brief README explaining prerequisites, setup, and sample usage.
• Confirmation the scraper respects robots.txt and rate limits to avoid blocking.
The project is straightforward but demands attention to clean structure, error handling, and maintainability consistent with intermediate-level best practices.
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