BeautifulSoup Jobs

I have three specific school-website links that list all current teachers and administrators. From each page I need a clean scrape of every staff member’s name, role, email address, plus the city/town and the school name, compiled into a single Excel workbook. Alongside that, I already hold an Excel sheet that contains a roster of Tow and roadside drivers. The sheet has their names and the URLs of the companies they work for, but no contact details. Please crawl those company sites, locate each driver’s email address, and append the results to the same workbook, using matching columns so everything stays consistent. Key points to keep in mind: • Final deliverable: one Excel file ready for copy-and-paste outreach. • Source material: my three school websites and...

I need the entire contents of a specific website captured in a single pass. That means every piece of on-page text, all publicly visible image files, and every internal or external hyperlink. Once scraped, the information should be organised into a clean CSV file—one row per page—with columns for page URL, full body text, image file names, and link destinations. Please download the images themselves as well and bundle them in a separate folder (a simple ZIP is fine); the CSV should reference the exact filenames so everything lines up. I’m happy for you to use Python with BeautifulSoup, Scrapy, Selenium or whichever stack you prefer, as long as the final output meets these acceptance criteria: • Complete CSV containing text, image names, and link URLs for each ...

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’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...

I need a reliable way to pull data from Facebook Marketplace seller pages at scale. The target platform is Facebook; other marketplaces such as eBay, Amazon or Etsy are irrelevant for this job. Here’s what I’m after: when I paste one or many seller profile URLs into your script or small desktop app, it should crawl every public listing on those pages and export the results to CSV or Google Sheets. I mainly care about item title, price, description, photos (image URLs are fine), posting date, item location and the seller’s profile link so I can trace each record back to its source. If you can collect additional fields that Facebook exposes, even better—just keep everything neatly labelled. No hard requirement on the stack: Python with BeautifulSoup / Selenium, ...

I need a developer to collect data from multiple public websites and deliver it in a clean, structured format. This is for legitimate data extraction from publicly available pages. I will share the target URLs and exact data fields with shortlisted candidates. Scope of work Scrape data from multiple public websites (details shared after shortlisting) Extract specific fields consistently and handle pagination/filtering where needed Normalize/clean the data (remove duplicates, consistent formatting) Export results to CSV/Excel/JSON (format to be confirmed) Provide a repeatable solution (script or small app) that I can run on demand Basic documentation: how to run it, how to adjust settings, where outputs go Quality requirements Reliable scraping with error handling and retries Resp...

I have an urgent need for a clean, well-structured dataset containing the listing agent’s first name, last name, mailing address, and phone number for well over 500 active Zillow listings. Speed is critical, but accuracy matters just as much; the final file should be ready for immediate import into my CRM. You are free to use whichever stack you prefer—Python with BeautifulSoup or Scrapy, Selenium, residential proxies, even the unofficial Zillow API—so long as rate-limits are respected and the data is complete. I don’t need property details or price history; the focus is strictly on the agent contact fields. Deliverables • CSV or XLSX with a separate column for each required field • A short read-me explaining the script or method so I can rerun it la...

I want a Telegram bot that can reliably extract the client’s phone number, the property owner’s number, and the unit number from listings on Bayut, Propertyfinder, and similar real-estate sites—even though these fields aren’t shown in the public UI and no official API is used. Here’s the flow I’m after: I drop a listing URL (or several) into the chat, the bot quietly scrapes the page, jumps through whatever loophole is needed to reveal the hidden contact and unit details, then replies with a single, structured template that looks something like: Property: <Title> Unit No.: <unit_number> Client: <client_phone> Owner: <owner_phone> Source: <URL> Key points • No reliance on the Bayut or Propertyfinder APIs&m...

Ich betreibe eine Vinyldatenbank und erhalte regelmäßig Neuheitenlisten per E-Mail. Damit ich die Informationen nicht mehr manuell übernehmen muss, suche ich eine Lösung, die die Nachrichten automatisch einliest, die relevanten Felder erkennt und direkt in meine Datenbank schreibt. Was verarbeitet werden soll • Künstlername & Albumtitel • Veröffentlichungsdatum & Label • Musikgenre & komplette Trackliste mit MMP3 und Covern * Preisermittlung Wie es ablaufen soll 1. Automatische Filterung der Eingangspostfächer (z. B. nach Absender oder Betreff). 2. Keyword-basierte Extraktion der oben genannten Felder. 3. Option zur manuellen Überprüfung, bevor die Datensätze endgültig gespeichert w...