Every CV-Library ad carries two identifiers, the advertiser's own Job Reference and CV-Library's Job ID. Our CV-Library scraper keeps both, so reposts can be traced.
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Tell us which part of CV-Library you need - an industry such as IT or Warehouse, towns with a radius in miles, a list of employers or agencies, or every live ad - and the cadence. We write the crawler, run it and fix it when CV-Library redesigns its two-pane results view. Rendering, proxy rotation, pacing and CAPTCHA handling come with the service.
You receive one row per ad with CV-Library's own labels intact and parsed columns beside them: the salary band split into figures and period, Posted yesterday turned into a date, the distance stripped from the location. Field documentation ships with the first file, and a sample can be ordered before any plan.
A CV-Library ad address is /job/ plus the Job ID and a slug, and the details box at the foot of the ad repeats that ID beside the advertiser's Job Reference. The fields below come from the result card, the ad page and that box:
The details box also lists a contact name and telephone that CV-Library shows only after login or registration. Those belong to individual recruiters, so they stay out of the dataset by default.
CV-Library builds search pages from a keyword and a place - data analyst jobs in London, warehouse jobs in Manchester - and lets a visitor set a radius from one mile to several hundred, a posted-within window, salary bands by year, day or hour, job type, industry and a remote-only switch. Results sort by relevance, most recent, salary either way or distance, with a choice of page sizes. We slice large categories by industry, region and posting window and merge on Job ID.
The Employer A-Z is a business directory split into employers and recruitment agencies, browsable by letter, industry and county. Each company page shows its count of live jobs, a business address, a website and an About us section, followed by the current ads - an advertiser table ready to join.
Run on a schedule, the same scope becomes a time series: new ads per day, how long ads stay live, which agencies repost, how salary bands move for one title. Search pages also carry an FAQ block on pay and skills for the title and town, which can be captured alongside.
CV-Library is an independent UK job board led by its founder and CEO, Lee Biggins. It describes itself as one of the UK's first job boards and as the largest independent job site, and its listings cover every industry from cleaning and warehouse work to IT, engineering and the NHS.
Advertisers are a mix of direct employers and recruitment agencies, and the site keeps the two apart: its directory has separate searches for each, and a direct employer's company page says so in its breadcrumb. In the results, the Posted by line names whoever placed the ad, which on agency ads is the agency rather than the hiring company.
CV-Library also owns a network of specialist sector and location job sites that send candidates to the ads on its main board. We collect from cv-library.co.uk, where every ad has its full page and details box. The jobseeker side adds a salary guide, a salary tax calculator and career advice, and a search box that accepts a job reference as well as a keyword.
Despite the name, the dataset is the job side only. The CV database that recruiters pay to search is candidate data and is never part of what we collect or deliver.
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Delivery: CSV, JSON or XLSX files, our API or a JSON feed. MCP server on request.
Full plan details →When clients scrape CV-Library salaries, the period matters as much as the figure: a band can be per annum, per day or per hour, and CV-Library's own filter offers bands for each. Read that way, the board supports several kinds of analysis.
Learn how to use web scraping to solve data problems for your organization
Leveraging advances in technology, the AI-powered web scraper has skyrocketed in demand and is helping to expand capabilities by automating tedious daily tasks and speeding up data collection from thousands of websites several times over.
Web scraping is a method of obtaining web data by extracting it from pages of web resources with the help of a program, that is, in automatic mode. It is used to syntactically convert web pages into more usable forms.
If you specialize in machine learning, you need to feed large amounts of data to the algorithms. Web scraping is the easiest and the most efficient method of collecting the data from all over the Internet.
ScrapeIt is a managed scraping service: our team builds the crawlers, keeps them running and answers for the data they return. For a UK board like CV-Library that means salary bands in three periods, repeated ads from agencies and locations given as postcode districts. We deliver Excel, CSV, JSONLines or a load into your database, daily or weekly, with recruiters' names left out and anything personal handled under GDPR. An MCP server is available on request.
Yes. The ScrapeIt CV-Library API returns Job ID, Job Reference, title, advertiser, salary band and job type for each ad as JSON from an endpoint we host, refreshed on the schedule you set. Prefer files? The same rows come as Excel or CSV by e-mail, SFTP or Google Drive, or as a JSON feed.
Yes. Result cards, ad pages with their details box, company pages and the Employer A-Z are open to any visitor. We collect only publicly available data - everything a visitor can see on CV-Library - and we collect it legally. Contact names and phone numbers that appear only after login stay out.
No. We collect job ads and advertiser pages only. The CV database is candidate data that recruiters buy access to, and it is never part of a ScrapeIt project, whatever the brand name suggests.
When an advertiser posts one vacancy in many towns, the results show one card marked Also in other locations, and behind it every town has its own copy with its own Job ID. We keep each copy as a row and add a group key from title, advertiser and salary band, so the vacancy can be counted once or per town.
Cards say Posted just now, today or yesterday on fresh ads, and the posted filter starts at the last 24 hours, so a daily run catches new ads on the day they appear. Ads leave the board when filled or expired, which a daily run also records; weekly is enough for salary studies.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
CV-Library data from €169/month. Free project assessment, reply within 1 business day.
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