Szybki start
This guide covers every ScrapeGraphAI feature:
- Rozpoczęcie pracy — Create an account and add your API key
- How to Use Smart Scraper — pull structured data from any single page using a plain natural language prompt
- How to Use Search Scraper — gather web data straight from live search results without opening each link yourself
- How to Use Markdownify — transform web content into clean Markdown that AI models read without extra noise
- How to Use Spidy Agent — crawl multiple pages as a multi page scraper for larger scraping projects
- How to Use Universal Data Extraction — handle many data extraction tasks across product data, news articles, and more
- How to Use Easy Integrations — connect extracted data to your data science and machine learning models in minutes
- How to Use Smart Agentic Scraper — read dynamic content on JavaScript heavy sites that break traditional scrapers
- How to Use Job Scheduler — run scraping operations on a schedule so the data extraction repeats on its own
- How to Use Simple Interface — use ScrapeGraphAI effectively from a no-code dashboard without deep technical expertise
Czas potrzebny: 5 minut na każdy film
Również w tym przewodniku: Profesjonalne porady | Typowe błędy | Rozwiązywanie problemów | Wycena | Alternatywy
Dlaczego warto zaufać temu przewodnikowi
I have used ScrapeGraphAI and tested every feature in this How to Use ScrapeGraph AI tutorial myself.
This walkthrough on how to use ScrapeGraphAI comes from real scraping projects, not vendor screenshots.
ScrapeGraphAI is an AI powered tool that turns messy web dane into structured data fast.
It uses large language models to read pages the way a person would.
This intelligent web scraping approach helps you simplify web scraping across many web scraping tasks.
Below I cover each of the key features step by step, with screenshots and pro tips.
ScrapeGraphAI Tutorial
This how to use ScrapeGraph AI tutorial walks you through the full scraping process, from setup to advanced data extraction.
ScrapeGraph AI
Turn any website into clean, structured data with natural language prompts. ScrapeGraphAI pairs large language models with direct graph logic to extract data fast. Start free, no credit card required.
Getting Started with ScrapeGraphAI
Before any feature, finish this one-time setup process.
Obejrzyj najpierw ten krótki przegląd:
Przyjrzyjmy się teraz każdemu krokowi.
Step 1: Create Your Account and API Key
Sign up on the ScrapeGraphAI dashboard and open the keys tab.
Copy your ScrapeGraphAI API key, since every request needs that API key.
✓ Punkt kontrolny: Your dashboard shows an active API key.
Step 2: Install ScrapeGraphAI
Create a clean virtual environment, then install ScrapeGraphAI with pip.
In your script add import os I import client to load the API key safely.
Oto jak wygląda pulpit nawigacyjny:
✓ Punkt kontrolny: The library imports with no errors.
Step 3: Pick Your Language Model
Choose a language model such as GPT 4o for your first run.
ScrapeGraphAI supports multiple LLM providers, so you can swap AI models anytime.
✅ Zrobione: You can now use ScrapeGraphAI for any feature below.
How to Use ScrapeGraphAI Smart Scraper
Smart Scraper lets you pull structured data from any single page using a plain natural language prompt.
Oto jak z niego korzystać krok po kroku.
Step 1: Open the Single Page Scraper
Pick the single page scraper and paste one target URL.
Step 2: Write a Natural Language Prompt
Describe the fields you want to extract from the web page.
Oto jak to wygląda:
✓ Punkt kontrolny: Your output matches the fields you asked for.
Step 3: Run and Read the JSON
Run it and read clean JSON data in a structured format.
✅ Wynik: You scraped one page into structured data in seconds.
💡 Wskazówka: Write a detailed prompt with the exact JSON keys you want for sharper extraction.
How to Use ScrapeGraphAI Search Scraper
Search Scraper lets you gather web data straight from live search results without opening each link yourself.
Oto jak z niego korzystać krok po kroku.
Krok 1: Wprowadź swoje zapytanie
Type a query and let it pull live search results.
Step 2: Set What to Collect
Tell it which web data to extract from each result.
Oto jak to wygląda:
✓ Punkt kontrolny: Your output matches the fields you asked for.
Step 3: Export the Output
Get meaningful data back as ready-to-use JSON.
✅ Wynik: You turned search results into usable web data.
💡 Wskazówka: Narrow your query first so the results stay focused and clean.
How to Use ScrapeGraphAI Markdownify
Markdownify lets you transform web content into clean Markdown that AI models read without extra noise.
Oto jak z niego korzystać krok po kroku.
Step 1: Paste the Page URL
Drop in any URL with heavy HTML structure.
Step 2: Convert to Markdown
Markdownify will transform web content into clean Markdown.
Oto jak to wygląda:
✓ Punkt kontrolny: Your output matches the fields you asked for.
Step 3: Reuse the Clean Data
Feed the clean data to your model or notes.
✅ Wynik: You converted a page into clean, model-ready tekst.
💡 Wskazówka: Markdown output works great as input for any AI powered summary.
How to Use ScrapeGraphAI Spidy Agent
Spidy Agent lets you crawl multiple pages as a multi page scraper for larger scraping projects.
Oto jak z niego korzystać krok po kroku.
Step 1: Add Your Start Page
Give Spidy Agent a starting link for the crawl.
Step 2: Set Crawl Depth
Choose whether to scrape a few pages or many pages.
Oto jak to wygląda:
✓ Punkt kontrolny: Your output matches the fields you asked for.
Step 3: Collect at Scale
Let this multi page scraper handle large scale scraping jobs.
✅ Wynik: You crawled multiple pages in a single run.
💡 Wskazówka: Start with a few pages to test before any large scale scraping run.
How to Use ScrapeGraphAI Universal Data Extraction
Universal Data Extraction lets you handle many data extraction tasks across product data, news articles, and more.
Oto jak z niego korzystać krok po kroku.
Step 1: Choose Your Source
Point it at product data, news articles, or any web pages.
Step 2: Define the Schema
Set the structured format you want the extracted data to follow.
Oto jak to wygląda:
✓ Punkt kontrolny: Your output matches the fields you asked for.
Step 3: Pull the Data
Run the data extraction tasks and review the output.
✅ Wynik: You handled mixed data extraction tasks at once.
💡 Wskazówka: Define a Pydantic schema to lock the structure of every record.
How to Use ScrapeGraphAI Easy Integrations
Łatwe integracje lets you connect extracted data to your data science and machine learning models in minutes.
Oto jak z niego korzystać krok po kroku.
Step 1: Open the API
Connect through the API for your scripts and apps.
Step 2: Send Data Downstream
Route extracted data into your data pipelines.
Oto jak to wygląda:
✓ Punkt kontrolny: Your output matches the fields you asked for.
Step 3: Feed Your Models
Hand the data to machine learning models and AI agents.
✅ Wynik: Your extracted data now flows into your stack.
💡 Wskazówka: Connect it to Make.com or n8n to extend your data pipelines.
How to Use ScrapeGraphAI Smart Agentic Scraper
Smart Agentic Scraper lets you read dynamic content on JavaScript heavy sites that break traditional skrobaki.
Oto jak z niego korzystać krok po kroku.
Step 1: Load a Tricky Site
Paste a JavaScript heavy site that hides its content.
Step 2: Let the Agent Render
The agent loads dynamic content before reading it.
Oto jak to wygląda:
✓ Punkt kontrolny: Your output matches the fields you asked for.
Step 3: Get Stable Results
It adapts when websites change, unlike traditional scrapers.
✅ Wynik: You read a JavaScript heavy site cleanly.
💡 Wskazówka: Pair it with rotating proxies on sites that block bots hard.
How to Use ScrapeGraphAI Job Scheduler
Job Harmonogram lets you run scraping operations on a schedule so the data extraction repeats on its own.
Oto jak z niego korzystać krok po kroku.
Step 1: Create a Job
Save a scrape as a repeatable job.
Step 2: Set the Cadence
Pick how often the scraping operations should run.
Oto jak to wygląda:
✓ Punkt kontrolny: Your output matches the fields you asked for.
Step 3: Let It Run
The scraping process repeats and stores fresh data.
✅ Wynik: Your scraping data now refreshes on autopilot.
💡 Wskazówka: Stagger jobs so you never trigger too many requests at once.
How to Use ScrapeGraphAI Simple Interface
Prosty interfejs lets you use ScrapeGraphAI effectively from a no-code dashboard without deep technical expertise.
Oto jak z niego korzystać krok po kroku.
Krok 1: Otwórz pulpit nawigacyjny
Use the AI powered dashboard, no code needed.
Step 2: Build Without Code
Run jobs without deep technical expertise.
Oto jak to wygląda:
✓ Punkt kontrolny: Your output matches the fields you asked for.
Step 3: Manage Everything
Track every scrape and use ScrapeGraphAI effectively from one screen.
✅ Wynik: You ran a full scrape with zero code.
💡 Wskazówka: Bookmark saved jobs to reuse them across scraping projects.
ScrapeGraphAI Pro Tips and Shortcuts
After six months of scraping projects, here are my best tips.
Quick Setup Shortcuts
| Goal | Skrót |
|---|---|
| Debug a run | Verbose mode that enables detailed logging |
| Save output | Export to JSON file or CSV files |
| Avoid blocks | Add rotating proxies |
| Lock structure | Pydantic schema |
Ukryte funkcje, których większość ludzi nie dostrzega
- Detailed logging: A verbose flag that enables detailed logging for every node, so error handling is far easier.
- Proxy rotation: Rotating proxies keep you under api rate limits and dodge ip blocks on guarded sites.
- Local models: Run open models via Ollama to extract information without paying per token.
ScrapeGraphAI Common Mistakes to Avoid
Mistake: Ignoring website terms
❌ Źle: Scraping without checking website terms or legal considerations first.
✅ Po prawej: Read the site policy and respect website terms before any scraping data run.
Mistake: Hammering the server
❌ Źle: Firing requests so fast the site returns too many requests errors.
✅ Po prawej: Add delays between requests so you stay under api rate limits.
Mistake: Vague prompts
❌ Źle: Writing loose natural language prompts that return messy data.
✅ Po prawej: Give exact fields and a schema so you get clean data every time.
ScrapeGraphAI Troubleshooting
Problem: Too many requests error
Przyczyna: You hit the api rate limits by sending requests too quickly.
Naprawić: Space out calls and add a delay; upgrade your plan for higher limits.
Problem: Blank or partial results
Przyczyna: The target is a JavaScript heavy site, so dynamic content loaded late.
Naprawić: Switch to the Smart Agentic Scraper, which renders the page before reading it.
Problem: Getting blocked or IP blocks
Przyczyna: The site flags scraping operations and serves a block page.
Naprawić: Add rotating proxies so each request looks like a fresh visitor.
📌 Notatka: These cover the most common challenges; for the rest, contact ScrapeGraphAI support.
Czym jest ScrapeGraphAI?
ScrapeGraphAI is an open-source Python library for intelligent web scraping.
It pairs large language models LLMs with direct graph logic to build a scraping pipeline.
Each node in the scraping graph runs one task, which makes any data extraction easy to update.
Pomyśl o tym jako o inteligentnym asystent that reads web pages and returns clean json data.
Obejrzyj ten krótki przegląd:
Zawiera następujące kluczowe funkcje:
- Smart Scraper: pull structured data from any single page using a plain natural language prompt
- Search Scraper: gather web data straight from live search results without opening each link yourself
- Markdownify: transform web content into clean Markdown that AI models read without extra noise
- Spidy Agent: crawl multiple pages as a multi page scraper for larger scraping projects
- Universal Data Extraction: handle many data extraction tasks across product data, news articles, and more
- Łatwe integracje: connect extracted data to your data science and machine learning models in minutes
- Smart Agentic Scraper: read dynamic content on JavaScript heavy sites that break traditional scrapers
- Harmonogram zadań: run scraping operations on a schedule so the data extraction repeats on its own
- Prosty interfejs: use ScrapeGraphAI effectively from a no-code dashboard without deep technical expertise
Because it reads context, it can extract meaningful data even when a website changes its layout.
It reads web pages and local documents, though it will not transcribe an audio file.
With plain natural language instructions, you can utilize data like news articles for sentiment analysis.
Aby zapoznać się z pełną recenzją, zobacz naszą ScrapeGraphAI review.
Cennik ScrapeGraphAI
Here is what ScrapeGraphAI costs in 2026:
| Plan | Cena | Najlepsze dla |
|---|---|---|
| Bezpłatny | $0 | Testing on a few pages |
| Rozrusznik | 17 USD/miesiąc | Solo data extraction tasks |
| Wzrost | 85 USD/miesiąc | Regular scraping projects |
| Zawodowiec | 425 USD/miesiąc | Large scale scraping |
| Przedsiębiorstwo | Zwyczaj | Zespoły o dużej objętości |
Bezpłatny okres próbny: Yes — the Free plan lets you test scraping data at no cost.
Gwarancja zwrotu pieniędzy: Cancel anytime from your dashboard.
💰 Najlepszy stosunek jakości do ceny: Growth — enough volume for steady scraping projects without overpaying.
ScrapeGraphAI kontra alternatywy
How does ScrapeGraphAI compare? Here is the landscape:
| Narzędzie | Najlepsze dla | Cena | Ocena |
|---|---|---|---|
| ScrapeGraphAI | AI-native extraction | 17 USD/mies. | ⭐ 4,5 |
| Scrapy | Code-first crawling | Bezpłatny | ⭐ 4.4 |
| Przeglądaj AI | No-code monitoring | 48 USD/mies. | ⭐ 4.3 |
| Jasne dane | Proxy network | $0.50/mo | ⭐ 4,5 |
| Ośmiornica | Visual scraping | 99 USD/mies. | ⭐ 4.3 |
| ScrapingBee | Render-heavy sites | 49 USD/mies. | ⭐ 4.4 |
Szybkie typy:
- Najlepszy ogółem: ScrapeGraphAI — natural language extraction beats rigid selectors.
- Najlepszy budżet: Scrapy — free if you can write the code yourself.
- Najlepsze dla początkujących: Browse AI — point and click, no scripts.
- Best for proxies: Bright Data — huge rotating proxy pool.
🎯 Alternatywy dla ScrapeGraphAI
Szukasz alternatyw dla ScrapeGraphAI? Oto najlepsze opcje:
- 🚀 Scrapy: Open-source Python framework for developers who want full control over every crawl.
- 👶 Przeglądaj AI: No-code tool that records your clicks and turns any site into an API.
- 🏢 Jasne dane: Enterprise proxy network with massive rotating IPs for large scale scraping.
- 🎨 Ośmiornica: Visual point-and-click scraper aimed at non-coders building scraping projects.
- 🔧 ScrapingBee: API that renders JavaScript heavy sites so you skip your own browser setup.
Aby zobaczyć pełną listę, zobacz naszą Alternatywy dla ScrapeGraphAI przewodnik.
⚔️ Porównanie ScrapeGraphAI
Here is how ScrapeGraphAI stacks up against each competitor:
- ScrapeGraphAI kontra Scrapy: ScrapeGraphAI wins on speed to first result; Scrapy wins on raw control for coders.
- ScrapeGraphAI kontra Browse AI: ScrapeGraphAI handles messier pages; Browse AI is simpler for fixed, repeating layouts.
- ScrapeGraphAI kontra Bright Data: Bright Data leads on proxies; ScrapeGraphAI leads on turning pages into structured data.
- ScrapeGraphAI kontra Octoparse: ScrapeGraphAI adapts when websites change; Octoparse needs you to rebuild templates.
- ScrapeGraphAI kontra ScrapingBee: Both render hard sites, but ScrapeGraphAI also reasons about the content with AI models.
Start Using ScrapeGraphAI Now
You learned how to use every major ScrapeGraphAI feature:
- ✅ Smart Scraper
- ✅ Search Scraper
- ✅ Markdownify
- ✅ Spidy Agent
- ✅ Universal Data Extraction
- ✅ Easy Integrations
- ✅ Smart Agentic Scraper
- ✅ Job Scheduler
- ✅ Simple Interface
Here are the core benefits at a glance:
Następny krok: Wybierz jedną funkcję i wypróbuj ją teraz.
Most people start with the Smart Scraper single page scraper.
It takes less than five minutes to extract data from your first page.
Często zadawane pytania
Is ScrapeGraphAI free to use?
Yes. The Free plan covers basic web scraping at no cost, and paid plans start at $17/month when you need more volume or features.
Do I need to know how to code?
No. You can use ScrapeGraphAI from a no-code dashboard with natural language prompts, though a Python API is there if you want it.
Which large language models does it support?
It works with multiple LLM providers, including OpenAI models like GPT 4o, Anthropic, Google Gemini, and local models through Ollama.
Can it handle JavaScript heavy sites?
Yes. The Smart Agentic Scraper renders dynamic content first, so it reads JavaScript heavy sites that break traditional scrapers.
How do I avoid getting blocked?
Respect website terms, add delays to dodge too many requests errors, and use rotating proxies to prevent ip blocks during scraping.
English 
Spanish 
Chinese 
German 
French 
Arabic 
Russian 
Portuguese 
Japanese 
Korean 
Italian 
Turkish 
Dutch 
Polish 
Indonesian 
Thai 
Vietnamese 