Node.js Scholarship Data Scraper

@malkesh3m

⭐ Hello there, My availability is immediate. I read your project post on Python Developer for Node.js Scholarship Data Scraper. We are experienced full-stack Python developers with skill sets in - Python, Django, Flask, FastAPI, Jupyter Notebook, Selenium, Data Visualization, ETL - React, JavaScript, jQuery, TypeScript, NextJS, React Native - NodeJS, ExpressJS - Web App Development, Data Science, Web/API Scrapping - API Development, Authentication, Authorization - SQLAlchemy, PostegresDB, MySQL, SQLite, SQLServer, Datasets - Web hosting, Docker, Azure, AWS, GPC, Digital Ocean, GoDaddy, Web Hosting - Python Libraries: NumPy, pandas, scikit-learn, tensorflow, etc. Please send a message So we can quickly discuss your project and proceed further. I am looking forward to hearing from you. Thanks

@monicasynthesis

Hello, I’ve gone through your job description and understand that you’re looking for a reliable Node.js script to automatically collect scholarship information from government, university, and private portals. With 5+ years of experience in Node.js development and web scraping, I’ve built clean, modular scripts using Puppeteer, Cheerio, and other tools that reliably capture structured data. What I can help you with: • Crawl all specified sources on a repeatable schedule and extract key fields like scholarship name, provider, eligibility, award, dates, and URLs. • Insert results into PostgreSQL or MongoDB, while preventing duplicates and logging failed pages. • Deliver clean, well-commented code designed for easy addition of new sources and future feature expansion. Warm regards, Monica Bhatia

@abhisheks039

Hello I can build a reliable Node.js scraping script that automatically collects fresh scholarship data from your specified sources and stores it cleanly in your database. I’ll use a combination of tools like Axios + Cheerio for fast static scraping and Puppeteer for dynamic pages when needed. To ensure data quality, I’ll implement duplicate detection (based on unique keys like URL/title), structured logging for failed parses, and a modular architecture so you can easily add or modify sources later. The code will be clean, well-documented, and built with scalability in mind for future features like filtering or automation. I’m comfortable working with both PostgreSQL and MongoDB and can adapt to your preferred setup. I can deliver an initial working version quickly and iterate based on your feedback. **I am willing to have a quick call to discuss all the requirements in details to be on the same page So I can provide you with an effective solution from my side** I’m ready to get started and can deliver a solid first version quickly. Best regards, Abhishek

@ukokab

I am an experienced Node.js developer with 10+ years building reliable web scrapers and automation pipelines. I will build your scholarship data collection system – extracting key fields from government, university, and private portals, storing them in PostgreSQL/MongoDB, and handling duplicates and parsing errors gracefully. ✅ **Tech Stack:** Node.js with **Cheerio** for static pages, **Puppeteer** for dynamic content, **node-cron** for scheduling, and **PostgreSQL/Mongoose** for storage – clean, modular code ready for future expansion. ✅ **Data Integrity:** Duplicate detection, field normalization, and logging of failed pages for manual review. Extensible source configuration. ✅ **Delivery:** First working version in 3–5 days, with clear documentation for adding new sources. Let’s build a foundation you can scale. Best, Usman Kokab Automation Specialist

@shailender18

As an experienced full-stack developer specialized in MERN and MEAN stack, I am confident that I can deliver a high-quality solution tailored to your needs. In terms of web scraping, I have a comprehensive understanding of technologies like Cheerio and Puppeteer -- this experience will be invaluable in building a resilient, efficient scholarship data scraper for you. Moreover, my proven proficiency in MongoDB and Node.js will ensure a smooth integration of the script with your preferred database, be it PostgreSQL or MongoDB. Rest assured, I will design a clean and well-documented code that allows easy addition of new sources in the future. What sets me apart from competitors is my ability to think ahead. While you mentioned only needing data collection initially, I am always considering what future functionalities could enhance the project. My focus is always on building robust, scalable systems with clean architecture that lays the perfect foundation for future expansion. Choose me for this project and together we can optimize the way you collect scholarship information. Let's get started!

@bhavishayak

I’d be glad to help you build a clean, reliable scraping system for collecting scholarship data. With experience in Node.js and working with tools like Puppeteer and Cheerio, I can design a structured crawler that pulls fresh data from your listed sources on a scheduled basis, captures all key fields, and inserts them directly into your preferred database (PostgreSQL or MongoDB). I’ll make sure the system includes proper duplicate detection, logging for failed parses, and a modular architecture so you can easily add or modify sources as needed. My focus will be on stability, readability, and scalability—so this can later evolve into filtering or automation features without requiring a rewrite. I’ll also handle rate-limiting and respectful scraping practices to avoid blocks or interruptions. You can expect a well-documented first working version quickly, along with clear guidance on how to manage and extend the system going forward.

@mubashir021

Hello, I see you need a reliable Node.js script for scholarship information. I am Mubashir Ahmed, a Full-Stack Developer, Engineer, and UI/UX Specialist with 6+ years of web scraping experience. You want a script to crawl sources on a repeatable schedule to collect scholarship data. - I will set up a Node.js environment using Cheerio or Puppeteer to scrape government and university sites, capturing core fields like scholarship name, provider, and award amount. - I will implement a scheduling mechanism to ensure the script runs regularly, checking for new listings and logging failed pages. - I will design the data insertion process to input collected information into your chosen database, either PostgreSQL or MongoDB, with a duplicate flagging system. - I will ensure the code is clean, well-commented, and structured for easy expansion. My Portfolio: https://www.freelancer.com/u/mubashir021 Mubashir Ahmed

@jamesscr

Hello, I can build your crawler quickly and reliably. I’ll deliver a clean Node.js script that: • Crawls multiple scholarship sources on a schedule • Extracts all required fields • Prevents duplicates • Stores everything in PostgreSQL or MongoDB • Logs failed pages for review I focus on clean architecture, so you can easily add new sources later.

@Dhananjayan6

Hi, My name is Dhananjayan and I am a senior software engineer currently working in One of the top MNC in India. I saw your project and would like to express my interest. I already worked on a project regarding scraping the data from public api which is very similar to current one and I think I can do this work. Feel free to contact me, we will discuss regarding this. Regards Dhananjayan

@amanagarwal2

Hi, I can build a clean, reliable Node.js crawler to fetch scholarship data from multiple sources and store it directly in your database. I’ve worked on similar scraping and data pipeline systems with scheduling, deduplication, and structured storage. Why I’m a good fit * 5+ years with Node.js and backend automation scripts * Experience using Puppeteer and Cheerio for dynamic and static scraping * Built data pipelines with MongoDB/PostgreSQL and deduplication logic * Focus on clean, modular code for easy extension How I’ll approach * Use Puppeteer for dynamic sites and Cheerio for faster static parsing * Schedule crawlers using cron-based jobs * Extract key fields (name, provider, eligibility, amount, dates, URL) * Implement duplicate detection using unique keys/URL hashing * Log failed parses and edge cases for review * Structure code to easily plug in new sources Stack * Node.js + Puppeteer/Cheerio * MongoDB or PostgreSQL (your preference) Timeline * First working version in 3–5 days Happy to discuss sources and rate limits before starting. Best regards, Aman

@ralozano33

Hi, I can build a reliable Node.js scraper for this, and I’ve worked on similar data collection systems before. To keep things efficient and aligned with the budget, I suggest starting with a focused MVP: • Integration of 2–3 scholarship sources • Extraction of core fields (title, provider, amount, dates, URL) • Data storage in PostgreSQL or MongoDB • Basic deduplication (based on URL/hash) • Simple logging for failed pages • Clean and modular structure to easily add more sources later This approach ensures you get a stable and working foundation quickly, and we can expand it step by step (more sources, advanced parsing, filtering, etc.). Technical approach: - Node.js - Cheerio (Puppeteer only if needed) - Cron-based scheduling - Clean, extendable code I can deliver a first working version within a few days. Let me know which sources you’d like to prioritize. Best regards, Ricardo Lozano

@Antonio1228

You need a reliable Node.js crawler that collects scholarship data from government, university, and private-scholarship portals and stores it cleanly in a database — I'll deliver exactly that. Here's my delivery plan: - Stack: Node.js with Cheerio (static pages) + Puppeteer (JS-rendered sites), PostgreSQL for storage with indexed schema - Fields captured: scholarship name, provider, eligibility summary, award amount, key dates, source URL - Scheduler: node-cron for configurable repeatable crawl runs - Duplicate detection: SHA-256 hash of name + provider + URL to prevent double-entry - Error logging: failed-parse URLs written to error_logs table with timestamps and HTTP status - Extensibility: each source as a standalone config object — adding new sites needs only a new config entry, no core changes - Deliverables: working crawler script, PostgreSQL migration file, .env config template, README with setup and run instructions I'll use PostgreSQL as the primary store with a clean migration script. Rate limits handled via per-domain configurable delays. Architecture is modular so expanding into filtering or auto-apply later is straightforward. Ready to start immediately — no back-and-forth needed.