Python Scraper for Google Scholar Profile

We need a Python-based scraper to fetch publication details from a given Google Scholar profile: titles, abstracts, citation counts (total and yearly), publication year/date. Optionally package it as an AWS Lambda function with a Lambda Layer for use as a serverless tool. Key Responsibilities: • Scrape all research papers from a specified Google Scholar profile. • Collect metadata: title, description/abstract, citation counts, year, publication date. • (Optional) Retrieve citation trends by year from the paper’s detailed citation breakdown. • Handle pagination to ensure complete data capture. • Write clean, well-tested Python code with error handling and rate-limit compliance. • (Optional) Package as AWS Lambda with dependencies in a Lambda Layer. Requirements: • Strong Python skills; familiarity with BeautifulSoup, requests, or APIs like scholarly • Understand scraping best practices to avoid IP blocks (e.g., delays, headers, proxies)   . • (Optional) AWS Lambda experience and layering dependencies. Deliverables: 1. Fully functional and documented Python script. 2. README with setup and execution instructions. 3. (Optional) AWS Lambda deployment guide + deployment scripts. 4. Sample output (CSV/JSON) based on your test run. Timeline & Compensation: • Expected completion: 3 days

Project ID: 39730865