BeautifulSoup Jobs

I need a clean one-off scrape of tabular data that sits openly on a public website and have that entire dataset placed into a Google Spreadsheet. Because it is only a single extraction, I am not looking for a recurring script or scheduler—just an accurate pull of everything that appears in the table on the page today. Feel free to use your preferred stack—Python with BeautifulSoup/Requests, Apps Script, or any reliable web-scraping tool—as long as the final result lands neatly in the sheet, keeping the same column order and row count that appears online. Before we wrap up, I’ll quickly check row totals and a handful of random cells against the site to confirm accuracy; once those spot checks pass, the job is done.

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 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 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...

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...