You will get a custom PDF parser that extracts data into Excel
Rising Talent
Rising Talent
Project details
Most PDF exports break in Excel because the text layer has no concept of columns. Tools like ChatGPT or online converters guess at the structure and drop rows without warning. This parser reads the coordinate layout directly. Each word in the PDF has an x/y position, and the script uses those coordinates to figure out which column it belongs to.
I tested this on a 28-page IKEA product catalog: 141 line items extracted, article numbers and prices matched exactly. A subset of highlighted items was automatically separated into a second sheet.
You get a Python script that runs locally, a sample Excel file built from your own PDF, and a short usage note. Drop in a new PDF of the same format and run the script.
I tested this on a 28-page IKEA product catalog: 141 line items extracted, article numbers and prices matched exactly. A subset of highlighted items was automatically separated into a second sheet.
You get a Python script that runs locally, a sample Excel file built from your own PDF, and a short usage note. Drop in a new PDF of the same format and run the script.
Programming Languages
PythonWhat's included $45
These options are included with the project scope.
$45
- Delivery Time 4 days
- Number of Revisions 2
- Number of Pages Mined/Scraped 200
- Number of Sources Mined/Scraped 1
- Install Script
- Test Script
Optional add-ons
You can add these on the next page.
Fast 2 Days Delivery
+$15
Additional Revision
+$10
Additional Source Mined/Scraped
(+ 1 Day)
+$20
Scheduled automation
+$25Frequently asked questions
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Mary Jane B.
Jun 29, 2026
Typeform Logic Expert
Excellent!
CB
Catherine B.
Jun 18, 2026
Chrome Extension for Grok to Blogger
I'm very satisfied. Adam created a user friendly Chrome Extension saving me countless hours of work.
About Adam
Web Scraping | Chrome Extensions | WordPress Speed | Web Design
100%
Job Success
Lodz, Poland - 12:01 am local time
Recent work: three live business sites, hand-coded with no page builder, scoring 97 to 100 on Google PageSpeed on mobile, a multi-page salon site, a service landing page with a live price calculator, and a SaaS product landing. A public WordPress speed case study too: the same landscaping page built three ways, 63 on a bloated Elementor build, 71 optimized in place, 99 on a lean rebuild, every trade-off measured. Excel-driven scrapers for a client where targets are read from a spreadsheet and results written back, across LinkedIn, USPTO, WIPO, and G2. A Chrome extension that moves AI-generated content straight into Blogger posts, delivered and in use. A price monitor where you paste a product photo, Google Vision turns it into the search query, and prices from five marketplaces come back side by side, running 24/7 in Docker.
A typical build for me: a scraper watches a site, Claude decides what matters, a bot sends the result to your phone. For social platforms I stick to official APIs (Telegram Bot API, Discord, WhatsApp via Twilio, Instagram and Facebook via Meta Graph API). If a job needs mass DMs or fake engagement, I pass. That gets accounts banned.
What I take on:
- Web scraping and price monitoring (httpx, Playwright, BeautifulSoup4)
- Chrome extensions (Manifest V3, OAuth2)
- Fast websites and landing pages (hand-coded HTML/CSS/JS, no page-builder bloat, green on mobile PageSpeed, per-page technical SEO)
- WordPress speed optimization: measure the site, fix what a free pass can fix (images, render-blocking CSS, lazy-load, plugin and font cleanup), and say when a lean rebuild beats paying for more plugins
- PDF-to-Excel pipelines (pdfplumber, openpyxl)
- Telegram and Discord bots: alerts, lead capture, group admin, content posting
- n8n workflows with LLM steps (Claude, GPT)
- API integrations: Gmail, Google Sheets, Google Vision, Twilio, Anthropic
Background: 10 years as an embedded C++ developer. Firmware work teaches you to plan for what breaks at 3am: timeouts, retries, malformed input, flaky networks. Scrapers, bots, and websites fail the same ways, so mine ship with those cases already handled.
Everything ships with source code you own, a short setup doc, and tests. My code is public on GitHub: async parallel scraping with a web UI and image search (price-aggregator), Gmail API + OAuth2 extensions (keeptouch), Manifest V3 service workers with reconnect logic (sse-notifier-extension), n8n + LLM pipelines (upwork-job-alert), plus three hand-coded sites live at 97 to 100 on mobile PageSpeed (salon.helban.dev, kalkulator.helban.dev, dropwatch.helban.dev) and a WordPress speed case study (wp-speed.helban.dev). That price scraper runs 24/7 as a Docker container on my own server. Writing a scraper is one thing, keeping it running is another, and I do both.
I work async: written updates and fast replies, no calls needed. Send a link or a sample file with your message. On most jobs I run a smoke test on your actual data first, so you see real output before committing to full scope.
Steps for completing your project
After purchasing the project, send requirements so Adam can start the project.
Delivery time starts when Adam receives requirements from you.
Adam works on your project following the steps below.
Revisions may occur after the delivery date.
Review your PDF
I open your file, map the layout, and confirm which fields are extractable. I'll flag anything unusual before writing any code.
Build the parser
Python script reads your PDF page by page, clusters words into rows, and maps each field to the correct column.