BeautifulSoup Jobs

I need investment performance data scraped from a research website and organized into an Excel file. It needs to be set up for scraping on a regular basis. Requirements: - Experience with web scraping tools and techniques - Ability to extract and format data accurately - Proficiency in Excel - Attention to detail and reliability Ideal Skills: - Familiarity with Python, BeautifulSoup, or similar scraping libraries - Prior experience with financial data - Strong data handling and manipulation skills Please provide a sample of your previous work related to web scraping.

I need a small utility that sits in the background, pings a single public web page every second, and alerts me the moment it detects any difference in either the visible text or the images. The page updates unpredictably, so true real-time tracking is essential; a one-minute polling interval is already too slow for my use-case. A lightweight approach that respects the site’s bandwidth and avoids triggering blocks or captchas will be valued. I am open to whatever stack you favour—Python with BeautifulSoup or Selenium, Node.js with Puppeteer, or a compiled solution—so long as it is stable on a Windows environment and easy for me to tweak the target URL later. Notification method is flexible: an email is fine, but if you have a smarter suggestion (desktop toast, webhoo...

I need an end-to-end AI agent that automatically scouts freelancing websites, general job boards, and specialised training platforms for roles or courses that involve artificial-intelligence work. The agent must: • Crawl and scrape the relevant pages in real time or on a frequent schedule. • Apply NLP or other classification techniques to decide whether a posting is truly AI-related, then tag it by sub-domain (e.g. vision, NLP, MLOps, prompt-engineering). • Deliver concise, deduplicated listings to me through an in-app notification feed—no email or SMS required. For the deployment side I’m open to Python (Scrapy, BeautifulSoup, Selenium), Node, or any stack you are comfortable with so long as it is containerised and can run unattended on a small cloud insta...

Hey! I’m looking to hire an experienced developer to build a universal product-detail scraping pipeline that takes a product URL (any website) and returns a complete structured product record. This is not a “simple HTML parse.” Many target sites are React/Next/Vue, load content via XHR/GraphQL, hide details behind tabs/accordions/modals, and lazy-load images/PDFs. The solution needs to reliably extract everything a human can see on the page, plus the underlying data used to render it. What the scraper must do (high level) Given a product URL, the pipeline should: Load the page like a real user (handle cookies/overlays). Capture all content from multiple sources (DOM + network + interactions). Use GPT API strategically to increase accuracy (field mapping, variant ext...

I need every product on copied into my existing WooCommerce shop so the catalog mirrors theirs one-to-one. That means grabbing each item’s title, plain-text description and all associated images, then pushing them into WordPress with the correct categories, colour swatches and size variations exactly as they appear on Furnx. Only product details are required right now—reviews and live stock counts can wait for a later phase—so the job is focused on clean data capture and a flawless import workflow. Descriptions must remain in plain text; no extra HTML markup. Images should arrive attached to the right variation, including separate gallery shots where available, and the colour options need to show as clickable swatches in WooCommerce, not just text labels. I’m...

I have two source spreadsheets that I need merged and enriched through automated scraping: • “File 1” – 170 k Spanish local businesses with emails • “File 2” – 65 k additional businesses with websites only Phase 1 – Email extraction Using a Python script and well-known libraries (requests, BeautifulSoup, Scrapy or similar), scan every site listed in File 2, capture all working email addresses you can locate, then append them to the corresponding rows so I can produce a unified “File 3”. Phase 2 – Offer harvesting Next, visit each live site in File 3. Where an offer, deal or promotion is publicly displayed, record the details in a fresh Excel sheet with these exact columns: Business ID | Business Name | Offer...

Project Description: Find school districts and charter schools who use a specific vendor for a large list of domains. I am seeking an experienced web scraping specialist to improve our Python script to analyze a large list of school district websites (approximately 4000+ URLs) and identify the ones who show a specific link on any page found in their sitemap. The primary method of identification must be to scan the website's for specific, known vendor links. Deliverables Required 1. A Production-Ready Python Script (.py file): The script must be commented, easily configurable, and capable of reading the provided CSV list, performing the scan, and generating the output CSV. It should handle timeouts and basic error handling gracefully. 2. The Final Results (CSV/Excel File): A c...

We are building a full internal marketplace analytics web system, not just a reporting script. The system is designed to combine competitive intelligence with internal sales and stock analytics in a single interface. Functional Requirements The system must provide the following capabilities: 1. Product and SKU structure - Each product must be split into individual SKUs based on flavor and volume. - All analytics and reports are built at the SKU level. 2. Our product analytics (primary focus) - Current stock levels (total and per SKU). - Sales volume for selected periods (daily / weekly / monthly). - Reorder recommendations based on stock thresholds and sales dynamics. - Revenue calculations per product and per SKU with period filtering. 3. Competitive analytics - Automated collection o...

I need a small automation script that periodically checks item availability on the Bigbasket website and pings me on Telegram the moment any of the tracked products come back in stock. You are free to choose the underlying tech stack (Python + Requests/BeautifulSoup, Selenium, Playwright, or a headless browser of your choice) as long as it works reliably with Bigbasket’s current site layout and protects my account from rate-limit blocks or captchas. The flow I have in mind is straightforward: I feed the bot a list of product URLs (or SKUs). It runs on a schedule I can change—every few minutes during peak shortages, maybe every hour otherwise—grabs the stock status, and fires a concise Telegram message whenever the status flips from “Out of Stock” to “Av...

I’m expanding our Florida outreach list and need a reliable web-scraped data set of school, college, and university administrators who oversee Nursing or other Healthcare programs. You’ll pull the information directly from two source types only—official institution websites and reputable educational directories—so every entry must be traceable back to one of those pages. Here’s exactly what must land in the spreadsheet: • Institution name • Contact’s first and last name • Job title (Administrator, Director of Nursing, CTE Healthcare lead, etc.) • Verified email address • State (always Florida) Format & delivery – Send the file in Excel (.xlsx). – First progress drop: within 5 days so I can spot-c...

I want a clean, well-commented Python 3 script that I can run locally whenever I need fresh information. The program should visit the target site (I’ll share the URL once we start) and pull Product Details exactly as they appear online. That means every time I point the script at a category or search page it should work through all pagination, capture the data, and save it to CSV or Excel so I can sort and analyse it later. Key points to cover • Use reliable, open-source libraries such as requests, BeautifulSoup, or Selenium—whichever gives the most stable results for the site once you see it. • Build in simple settings (URL, output file name, optional delay between requests) near the top of the file so I can tweak them without touching the core logic. • H...

I’m looking for a well-structured Python solution, built around BeautifulSoup (BS4) and any supportive libraries you deem essential, that reliably pulls both product details and customer reviews from Lazada on a daily schedule. The data will fuel ongoing competitor research, so consistency and clarity of the output are critical. I looking specifically to get data using bs4 by bypassing the captcha Here’s how I picture the flow: • Input: category URL(s) or product list I supply in a CSV/JSON. • Scrape: title, price, promos, specs, images, ratings, full review texts, review dates, and reviewer scores. • Output: clean CSV or JSON dropped into a dated folder after each run. Make the script easy to tweak if Lazada changes its markup. Acceptance criteria 1. S...

I need a seasoned Python developer to build a robust scraper that collects the required data and writes it straight to JSON—no additional cleaning or processing necessary. Once we begin I’ll provide the target URL(s) and any access details; for now, assume a standard public site with pagination and occasional anti-bot checks. Core expectations • Written in Python 3 using requests/BeautifulSoup or Scrapy; resort to Selenium only if there’s no lighter workaround. • Handles pagination, retries, and polite delays gracefully so the run can complete unattended. • Config file or clear constants for headers, cookies, and start URLs, letting me tweak targets without editing core logic. • Produces a single JSON file (or one file per page if that’s...

I need to build a reliable, well-structured lead list and I already know exactly what it should contain. The task is to extract contact information—email addresses, phone numbers and full mailing addresses—from three sources: company and organisation websites, their public social-media profiles, and well-known online directories. I expect the data to be gathered with a solid scraping workflow (Python, Scrapy, BeautifulSoup, Selenium or an equivalent stack is fine) and then verified so that bounced emails and dead numbers are kept to an absolute minimum. Deliverables • One CSV or Excel file with separate columns for name, company, job title, email, phone, street address, city, state, ZIP/postcode, country, source URL and date collected. • No duplicates; every...