[Blog](https://scrapfly.io/blog) / [ai](https://scrapfly.io/blog/tag/ai) / [12 Python Web Scraping Projects for 2026](https://scrapfly.io/blog/posts/python-web-scraping-projects-from-beginner-to-advanced) # 12 Python Web Scraping Projects for 2026 by [Mayada Shaaban](https://scrapfly.io/blog/author/mayada-shaaban-90143e67) Aug 24, 2026 15 min read [\#ai](https://scrapfly.io/blog/tag/ai) [\#data-parsing](https://scrapfly.io/blog/tag/data-parsing) [\#headless-browser](https://scrapfly.io/blog/tag/headless-browser) [\#python](https://scrapfly.io/blog/tag/python) [\#scrapeguide](https://scrapfly.io/blog/tag/scrapeguide) [ ](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fpython-web-scraping-projects-from-beginner-to-advanced "Share on LinkedIn") [ ](https://x.com/intent/tweet?url=https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fpython-web-scraping-projects-from-beginner-to-advanced&text=12%20Python%20Web%20Scraping%20Projects%20for%202026 "Share on X") [ ](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fpython-web-scraping-projects-from-beginner-to-advanced "Share on Facebook") Summarize this article with [ ](https://chat.openai.com/?q=Summarize%20this%20article%20and%20explain%20how%20Scrapfly%20helps%20me%20scrape%20any%20website%20at%20scale%20and%20bypass%20anti-bot%20systems%20for%20my%20use%20case%3A%20https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fpython-web-scraping-projects-from-beginner-to-advanced) [ ](https://claude.ai/new?q=Summarize%20this%20article%20and%20explain%20how%20Scrapfly%20helps%20me%20scrape%20any%20website%20at%20scale%20and%20bypass%20anti-bot%20systems%20for%20my%20use%20case%3A%20https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fpython-web-scraping-projects-from-beginner-to-advanced) [ ](https://x.com/i/grok?text=Summarize%20this%20article%20and%20explain%20how%20Scrapfly%20helps%20me%20scrape%20any%20website%20at%20scale%20and%20bypass%20anti-bot%20systems%20for%20my%20use%20case%3A%20https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fpython-web-scraping-projects-from-beginner-to-advanced) [ ](https://www.perplexity.ai/search/new?q=Summarize%20this%20article%20and%20explain%20how%20Scrapfly%20helps%20me%20scrape%20any%20website%20at%20scale%20and%20bypass%20anti-bot%20systems%20for%20my%20use%20case%3A%20https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fpython-web-scraping-projects-from-beginner-to-advanced) [ ](https://www.google.com/search?udm=50&aep=11&q=Summarize%20this%20article%20and%20explain%20how%20Scrapfly%20helps%20me%20scrape%20any%20website%20at%20scale%20and%20bypass%20anti-bot%20systems%20for%20my%20use%20case%3A%20https%3A%2F%2Fscrapfly.io%2Fblog%2Fposts%2Fpython-web-scraping-projects-from-beginner-to-advanced) **Web Scraping API**Scrape any website with anti-bot bypass, proxy rotation, and JS rendering. [ Learn More ](https://scrapfly.io/products/web-scraping-api) [ Docs ](https://scrapfly.io/docs/scrape-api/getting-started) You can finish one BeautifulSoup tutorial, scrape a table of fake books, and still stall the moment you try something real. The jump from a toy script to a scraper that survives an actual website is where the learning happens, and no single tutorial covers it. This list ladders 12 projects from static-page parsing to production-grade monitoring and AI agents. Each one names the skills it teaches, a data source to start on, and a build guide where a complete one exists. [Everything to Know to Start Web Scraping in Python TodayComplete introduction to web scraping using Python: http, parsing, AI, scaling and deployment.](https://scrapfly.io/blog/posts/everything-to-know-about-web-scraping-python) ## Key Takeaways - **Requests plus BeautifulSoup carries every beginner project** on a static practice site. - **The next jump is content that changes**, rendered pages, hidden APIs, and storage. - **The jump after that is scale**, Scrapy crawls, rate limits, and blocking. - **Portfolio projects mirror commercial work**, not one-off scripts. - **Every project below lists its skills, data source, and build guide** where one exists. **Get web scraping tips in your inbox**Trusted by 100K+ developers and 30K+ enterprises. Unsubscribe anytime. ## Which Python Web Scraping Project Should You Build First? Complete beginners should start with the product catalog scraper on a practice site. Anyone already comfortable with `requests` and BeautifulSoup should skip ahead to the price drop tracker instead. Three quick picks by goal: project 1 covers the fundamentals. Projects 4, 10, and 11 build a portfolio, and project 12 covers AI-assisted scraping. | \# | Project | Difficulty | Core skills taught | Suggested tools | Full build guide | |---|---|---|---|---|---| | 1 | Product Catalog Scraper | Beginner | HTTP GET, CSS selectors, pagination | requests, BeautifulSoup | Code below | | 2 | News Headline Collector | Beginner | Multi-source parsing, deduplication | httpx, BeautifulSoup | Related Google News API guide | | 3 | Weather Data Logger | Beginner | Hidden API discovery, JSON parsing | requests, JSON | Hidden APIs guide | | 4 | Price Drop Tracker | Intermediate | Scheduling, price parsing, alerting | httpx, SQLite | Price tracker guide | | 5 | Grocery Price Comparison Tool | Intermediate | Multi-site scraping, schema matching | pandas | Idea only | | 6 | Job Market Analyzer | Intermediate | Rendered listings, deep pagination | Playwright | Indeed guide | | 7 | Real Estate Market Tracker | Intermediate | Hidden data, longitudinal storage | requests, SQLite | Real estate guide | | 8 | Review Sentiment Analyzer | Intermediate | Text cleaning, sentiment scoring | pandas | Sentiment analysis guide | | 9 | Large Product Catalog Crawler | Advanced | Crawl architecture, rate limiting | Scrapy | Scrapy guide | | 10 | B2B Lead Database | Advanced | Entity resolution, dedup at scale | requests, pandas | Lead scraping guide | | 11 | Competitor Price and MAP Monitoring | Advanced | Recurring crawls, violation rules | Scrapy, alerting | MAP monitoring guide | | 12 | AI Web Scraping Agent | Advanced | LLM tool calling, structured output | Python, an LLM API | AI agent guide | The tiers track the new concept each project introduces, not how many lines of code it takes to write. ## Beginner Python Web Scraping Projects (requests + BeautifulSoup) Beginner projects share one trait. The data sits in the HTML the server sends, so `requests` plus BeautifulSoup is the whole stack. There's no rendering step and no login wall to work around yet. Start on a dedicated practice site instead of a live commercial one. web-scraping.dev is a mock e-commerce site built for scraping practice, so nothing here touches a real business while you learn. [How to Parse Web Data with Python and BeautifulsoupBeautifulsoup is one the most popular libraries in web scraping. In this tutorial, we'll take a hand-on overview of how to use it, what is it good for and explore a real -life web scraping example.](https://scrapfly.io/blog/posts/web-scraping-with-python-beautifulsoup) ### 1. Product Catalog Scraper (requests + BeautifulSoup on web-scraping.dev) Scrape a paginated product catalog into a list of names and prices. This project teaches an HTTP GET request, CSS selectors, and a pagination loop, the three moves that show up in almost every scraper after this one. The data source is [web-scraping.dev's product pages](https://webscraping.dev/products). #### Project Setup Install the two packages this project needs before running the snippet below. bash```bash pip install requests beautifulsoup4 ``` This installs `requests` for making the HTTP call and BeautifulSoup for parsing the returned HTML. The snippet below fetches one page and prints each product's name and price. python```python import requests from bs4 import BeautifulSoup response = requests.get("https://web-scraping.dev/products") soup = BeautifulSoup(response.text, "html.parser") for product in soup.select("div.product"): name = product.select_one("h3.mb-0 > a").text.strip() price = product.select_one("div.price-wrap > div.price").text.strip() print(name, "-", price) ``` text```text Box of Chocolate Candy - 24.99 Dark Red Energy Potion - 4.99 Teal Energy Potion - 4.99 Red Energy Potion - 4.99 Blue Energy Potion - 4.99 ``` The `div.product` selector matches each product card, and `h3.mb-0 > a` and `div.price-wrap > div.price` pull the name and price out of it. Add a loop over the `?page=` query parameter and a CSV writer to turn the script into a full catalog dump. ### 2. News Headline Collector (httpx + BeautifulSoup) Pull headlines, timestamps, and links from a handful of news homepages into a dated CSV, then re-run it daily and diff the results. This project works through multi-source parsing, encoding quirks, and deduplication, since the same story often runs on two sites. Swap `requests` for [httpx](https://scrapfly.io/blog/posts/web-scraping-with-python-httpx) here if you want HTTP/2 support and async requests for pulling several homepages at once. Scoring headlines by keyword afterward is a light first step into text analysis, which project 8 builds on. No dedicated news-scraping guide exists yet. The [Google News API guide](https://scrapfly.io/blog/posts/guide-to-google-news-api-and-alternatives) documents a close alternative, pulling headlines from an API instead of HTML. ### 3. Weather Data Logger (hidden JSON APIs) Instead of parsing rendered HTML, find the JSON endpoint a weather site's frontend calls and log a clean time series from it. The skills here are browser devtools network inspection, hidden API discovery, and JSON parsing. The [guide to scraping hidden APIs](https://scrapfly.io/blog/posts/how-to-scrape-hidden-apis) covers finding and calling that endpoint directly. An accessible JSON endpoint can make a site easier to scrape than its rendered HTML. There's no markup to walk at all. Once you've pulled the JSON, parse it with Python. The [guide to parsing JSON with Python](https://scrapfly.io/blog/posts/how-to-use-python-to-parse-json) handles navigating nested response structures. Beginner projects build the stack every later project reuses. Each one repeats a request, a selector or a JSON key, and a loop. Intermediate projects add two things beginner projects skip. Pages render in the browser, and you keep data across runs. ## Intermediate Python Web Scraping Projects (rendered pages and persistence) Intermediate projects add what beginner tutorials leave out. Pages render in the browser instead of the response body, and you store, clean, and compare data across runs. The stack grows to include a rendering tool, [SQLite](https://www.sqlite.org)for history, and [pandas](https://pandas.pydata.org) for cleanup. [Web Scraping with Playwright and PythonPlaywright is the new, big browser automation toolkit - can it be used for web scraping? In this introduction article, we'll take a look how can we use Playwright and Python to scrape dynamic websites.](https://scrapfly.io/blog/posts/web-scraping-with-playwright-and-python) ### 4. Price Drop Tracker (httpx + SQLite + alerts) Track prices for a set of chosen products on a schedule and store the history in SQLite. Send an alert when a price drops. You'll set up scheduling with cron, price parsing, change detection, and simple alerting through email or a webhook. The [price tracker guide](https://scrapfly.io/blog/posts/how-to-build-a-price-tracker-using-python-web-scraping) walks through the full build. This is usually the first scraper that stays useful after the day you wrote it. ### 5. Grocery Price Comparison Tool (pandas product matching) Scrape the same shopping basket from two or three grocery stores. Normalize the results into one comparison table with pandas. This one centers on multi-site scraping, schema normalization, and product matching. The hard part is reconciling differently formatted names for the same item across stores, which is real data-engineering practice. No dedicated build guide exists for this one yet. ### 6. Job Market Analyzer (Playwright + hidden APIs) Collect postings for one role across job boards and analyze the skills, salary ranges, and locations that show up. Expect Playwright-rendered listings, deep pagination, and structured extraction from postings that often load through an internal API. Build guides exist for two common targets. [Indeed](https://scrapfly.io/blog/posts/how-to-scrape-indeedcom)and [Glassdoor](https://scrapfly.io/blog/posts/how-to-scrape-glassdoor) each cover the site's own listing structure and pagination pattern. ### 7. Real Estate Market Tracker (hidden web data) Track listings in one city over several weeks, following price, days on market, and price cuts. The work here is finding structured or hidden data embedded in listing pages, handling geo fields, and storing longitudinal data without duplicating listings. The [real estate scraping guide](https://scrapfly.io/blog/posts/how-to-scrape-real-estate-property-data-using-python)covers a working listings target. The [hidden web data guide](https://scrapfly.io/blog/posts/how-to-scrape-hidden-web-data) explains the technique for pulling structured data that never renders as plain HTML. ### 8. Review Sentiment Analyzer (pandas + text processing) Collect a sample of product or company reviews and score sentiment trends over time. You'll practice text cleaning, review pagination, basic sentiment scoring, and plotting a trend from the results. [Trustpilot](https://scrapfly.io/blog/posts/how-to-scrape-trustpilot-com-reviews) is a reliable review source to start with. The [sentiment analysis guide](https://scrapfly.io/blog/posts/intro-to-using-web-scraping-for-sentiment-analysis) walks through turning raw review text into a trend line. Intermediate projects add rendering and persistence on top of the beginner stack. Advanced projects add a third layer on top of both. Volume and the anti-bot systems that come with it define this tier. ## Advanced Python Web Scraping Projects (scale and AI) Advanced projects stop being about parsing and start being about staying up against large page counts, rate limits, and retries. Anti-bot systems block naive scrapers fast. This is where proxy rotation and fingerprinting become real engineering concerns. The linked guides cover the mechanics. [How to Crawl the Web with PythonIntroduction to web crawling with Python. What is web crawling? How it differs from web scraping? And a deep dive into code, building our own crawler and an example project crawling Shopify-powered websites.](https://scrapfly.io/blog/posts/crawling-with-python) ### 9. Large Product Catalog Crawler (Scrapy) Crawl a large catalog with [Scrapy](https://scrapfly.io/blog/posts/web-scraping-with-scrapy). Expect link discovery, concurrency, retries, and incremental re-crawls for pages that changed. The skills at this tier are crawl architecture, rate limiting, queue management, and resuming a crawl after it fails partway through. The Scrapy guide covers the framework's crawl architecture in full. Scrapy 2.17.0 adds HTTP/2 support through the new HTTPX\_HTTP2\_ENABLED setting. The same release adds SOCKS proxy support for Scrapy's experimental HttpxDownloadHandler, not its default download handler. The [Scrapy release notes](https://docs.scrapy.org/en/latest/news.html) cover both changes. ### 10. B2B Lead Database (public data + entity resolution) Build a company-and-contact dataset for one niche from public directories and websites. This one leans on entity resolution, deduplication at scale, and data quality scoring, using public data only and skipping personal-data collection. The [lead scraping guide](https://scrapfly.io/blog/posts/how-to-scrape-leads) covers the build. The [public data sources for lead generation](https://scrapfly.io/blog/posts/best-public-data-sources-for-lead-generation) guide lists where to start looking. This project mirrors a real commercial deliverable, which is why it shows up again in the portfolio section below. ### 11. Competitor Price and MAP Monitoring System (crawling + alerts) Monitor competitor listings for price changes and minimum-advertised-price violations, with alerting and per-seller history. Expect recurring crawl scheduling, seller matching, violation rules, and alerting that runs in production instead of on a single manual run. This is where teams start weighing a managed crawl setup against self-hosting at volume. The [MAP monitoring guide](https://scrapfly.io/blog/posts/how-to-build-minimum-advertised-price-monitoring-tool) documents the build. A managed-crawler variant uses the [Crawler API](https://scrapfly.io/blog/posts/competitor-price-monitoring-with-crawler-api). A self-hosted variant uses [tracking competitor pricing](https://scrapfly.io/blog/posts/how-to-track-competitor-pricing-using-web-scraping) instead. ### 12. AI Web Scraping Agent (LLM + Python) Build an agent that takes a natural-language goal, fetches pages, and returns structured data through LLM tool calls. You'll work through function calling, structured extraction, agent loop design, and guarding against output the model made up. The [AI agent web scraping guide](https://scrapfly.io/blog/posts/ai-agent-web-scraping) covers the architecture behind this pattern. This pattern turns the fundamentals from every earlier tier into an agent that can use them on its own. The tiers above cover what to build. Next comes how to pick one for where you are, and what belongs in a portfolio once you've built a few. Scrapfly #### Need a cloud browser for scraping? Run headless browsers at scale with Scrapfly Cloud Browser — no infrastructure to manage. [Try Free →](https://scrapfly.io/register)## How Do You Pick the Right Web Scraping Project for Your Skill Level? Pick the lowest tier that still has a concept you haven't used. If every beginner skill already sounds familiar, start at intermediate instead of repeating it. Run a quick tier test: can you name what `requests` does, what a CSS selector matches, and what a hidden API is? Each "no" drops you one tier. Match the project to your goal too. Projects 1 through 3 cover learning, and 4, 5, and 7 make a useful personal tool. Projects 6, 10, and 11 build employability, and project 12 gives AI experience. A [March 2021 r/learnpython thread](https://www.reddit.com/r/learnpython/comments/m5kb9x/beginner_projects_for_web_scraping_using/) put the counterpoint well: "scrape whatever it is you're interested in scraping... the internet becomes your database." Interest finishes more projects than any difficulty ladder does. Finish one project per tier before jumping to the next, rather than three projects in one tier. Each tier introduces one new class of concept, and repeating a tier without a new concept doesn't move you forward. Once you've finished a few, some of those projects are worth showing off and some aren't. ## Which Web Scraping Projects Belong in Your Portfolio? Projects that mirror commercial scraping jobs, like price monitoring, lead databases, and market trackers, make stronger portfolio candidates than one-off scripts. Reviewers look for evidence a project kept working over weeks, past the first run. Check a project against this list before you show it: - Does it run on a schedule instead of once? - Does it store history instead of overwriting a single CSV? - Does it handle failure with retries and logging? - Does a README explain the data and its limits? Three projects from this list make the strongest picks: - The price drop tracker with real alert history (project 4). - The B2B lead database with documented dedup logic (project 10). - The competitor price monitor with violation reports (project 11). A paragraph in the README about request pacing and failures tells a reviewer more than a fancier parser does. Publish the repo with sample output data attached. A screenshot proves the page rendered once. A dataset with a commit history proves the project kept running. ## Scale Past a Practice Site with Scrapfly Every project above works fine against a practice site or a forgiving target. The moment one graduates to a real, protected site, blocking becomes the bottleneck instead of parsing. ScrapFly's [Web Scraping API](https://scrapfly.io/products/web-scraping-api) collects public web data through one HTTP endpoint, with a **98% success rate on the hardest public pages** and residential and datacenter coverage in **190+ countries**. - [Anti-Scraping Protection bypass](https://scrapfly.io/docs/scrape-api/anti-scraping-protection) - enables Scrapfly's managed anti-bot adaptation for supported public targets. - [Smart proxy rotation](https://scrapfly.io/docs/scrape-api/proxy) - residential and datacenter pools with country and ASN level geo-targeting. - [JavaScript rendering](https://scrapfly.io/docs/scrape-api/javascript-rendering) - render SPAs and changing pages through real cloud browsers. - [Browser automation scenarios](https://scrapfly.io/docs/scrape-api/javascript-scenario) - scroll, click, fill forms, and wait for elements without managing a browser fleet. - [Format conversion](https://scrapfly.io/docs/scrape-api/getting-started#api_param_format) - return pages as HTML, JSON, clean text, or LLM ready Markdown. - [Session management](https://scrapfly.io/docs/scrape-api/session) - keep cookies, headers, and IPs consistent across multi step flows. - [Smart caching](https://scrapfly.io/docs/scrape-api/getting-started#api_param_cache) - cache successful responses to cut cost on repeat scraping jobs. - [Python](https://scrapfly.io/docs/sdk/python), [TypeScript](https://scrapfly.io/docs/sdk/typescript), [Scrapy](https://scrapfly.io/docs/sdk/scrapy), and [no-code integrations](https://scrapfly.io/docs/integration/getting-started) including [Make](https://scrapfly.io/integration/make), [n8n](https://scrapfly.io/integration/n8n), [Zapier](https://scrapfly.io/integration/zapier), [LangChain](https://scrapfly.io/integration/langchain), and [LlamaIndex](https://scrapfly.io/integration/llamaindex). ### Power your scraping with Scrapfly Forget about getting blocked. Scrapfly handles anti-bot bypasses, browser rendering, and proxy rotation so you can focus on the data. [Try for FREE!](https://scrapfly.io/register) ## FAQ Where can I find Python web scraping projects with source code?Use the linked build guides above for runnable Python code on each target. For a wider collection, [israel-dryer/Web-Scraping-Projects](https://github.com/israel-dryer/Web-Scraping-Projects)on GitHub gathers examples across several sites. Can you make money from web scraping projects?Freelance data collection, price-intelligence services, and lead-database building are the common paid paths. Projects shaped like price monitoring, competitor tracking, and lead generation are the strongest candidates here, which is why they anchor the portfolio picks above. Do beginners need Scrapy, or is BeautifulSoup enough?BeautifulSoup with `requests` covers every beginner project on this list. Scrapy becomes useful once a crawler needs concurrency, retries, and item pipelines. See the [Scrapy overview](https://docs.scrapy.org/en/latest/intro/overview.html). Is it legal to build these web scraping projects?No legal answer covers every project. Check a site's terms, robots.txt, and privacy rules, keep request rates polite, and avoid personal data. Start on practice surfaces built for scraping rather than assuming a live target allows it. Are Python web scraping projects still worth building in 2026 now that AI can scrape?Yes, AI scraping agents raise the ceiling but don't remove the fundamentals. AI agents still need safeguards for blocking, rendering, and data validation, the exact skills project 12 turns into agent-building experience. ## Summary Ship scraping projects in order of new concepts. Start with static parsing, add rendered pages and persistence, then move to scale and AI. Every project above has a concrete next step, whether that's a build guide or an extension idea. A project that outgrows a practice site and lands on a real, protected target trades a parsing problem for a blocking one. Scrapfly's Web Scraping API can take on that layer, so the project code stays focused on the data. Pick one project from the tier that matches where you are, finish it, and move up. Legal Disclaimer and PrecautionsThis tutorial covers popular web scraping techniques for education. Interacting with public servers requires diligence and respect: - Do not scrape at rates that could damage the website. - Do not scrape data that's not available publicly. - Do not store PII of EU citizens protected by GDPR. - Do not repurpose *entire* public datasets which can be illegal in some countries. Scrapfly does not offer legal advice but these are good general rules to follow. For more you should consult a lawyer. [ Add as a preferred source ](https://google.com/preferences/source?q=scrapfly.io) Table of Contents Table of Contents- [Key Takeaways](#key-takeaways) - [Which Python Web Scraping Project Should You Build First?](#which-python-web-scraping-project-should-you-build-first) - [Beginner Python Web Scraping Projects (requests + BeautifulSoup)](#beginner-python-web-scraping-projects-requests-beautifulsoup) - [1. Product Catalog Scraper (requests + BeautifulSoup on web-scraping.dev)](#1-product-catalog-scraper-requests-beautifulsoup-on-web-scraping-dev) - [2. News Headline Collector (httpx + BeautifulSoup)](#2-news-headline-collector-httpx-beautifulsoup) - [3. Weather Data Logger (hidden JSON APIs)](#3-weather-data-logger-hidden-json-apis) - [Intermediate Python Web Scraping Projects (rendered pages and persistence)](#intermediate-python-web-scraping-projects-rendered-pages-and-persistence) - [4. Price Drop Tracker (httpx + SQLite + alerts)](#4-price-drop-tracker-httpx-sqlite-alerts) - [5. Grocery Price Comparison Tool (pandas product matching)](#5-grocery-price-comparison-tool-pandas-product-matching) - [6. Job Market Analyzer (Playwright + hidden APIs)](#6-job-market-analyzer-playwright-hidden-apis) - [7. Real Estate Market Tracker (hidden web data)](#7-real-estate-market-tracker-hidden-web-data) - [8. Review Sentiment Analyzer (pandas + text processing)](#8-review-sentiment-analyzer-pandas-text-processing) - [Advanced Python Web Scraping Projects (scale and AI)](#advanced-python-web-scraping-projects-scale-and-ai) - [9. Large Product Catalog Crawler (Scrapy)](#9-large-product-catalog-crawler-scrapy) - [10. B2B Lead Database (public data + entity resolution)](#10-b2b-lead-database-public-data-entity-resolution) - [11. Competitor Price and MAP Monitoring System (crawling + alerts)](#11-competitor-price-and-map-monitoring-system-crawling-alerts) - [12. AI Web Scraping Agent (LLM + Python)](#12-ai-web-scraping-agent-llm-python) - [How Do You Pick the Right Web Scraping Project for Your Skill Level?](#how-do-you-pick-the-right-web-scraping-project-for-your-skill-level) - [Which Web Scraping Projects Belong in Your Portfolio?](#which-web-scraping-projects-belong-in-your-portfolio) - [Scale Past a Practice Site with Scrapfly](#scale-past-a-practice-site-with-scrapfly) - [FAQ](#faq) - [Summary](#summary) Join the Newsletter Get monthly web scraping insights Scale Your Web Scraping Anti-bot bypass, browser rendering, and rotating proxies, all in one API. Start with 1,000 free credits. No credit card required 1,000 free API credits Anti-bot bypass included [Start Free](https://scrapfly.io/register) [View Docs](https://scrapfly.io/docs/onboarding) Not ready? Get our newsletter instead. ## Related Articles [ python xpath ### Web Scraping With Scrapy: The Complete Guide in 2026 Build and run a Scrapy 2.18 project with async start(), pagination, selector tests, item validation, pipelines, and JSON... ](https://scrapfly.io/blog/posts/web-scraping-with-scrapy) [ http python ### Web Scraping with Python Introduction tutorial to web scraping with Python. How to collect and parse public data. Challenges, best practices and ... ](https://scrapfly.io/blog/posts/web-scraping-with-python) [ python api ### Web Scraping for AI Agents in 2026 How AI agents consume the web, why their fetch layer breaks, and how to build agent-grade web access that holds up in pr... ](https://scrapfly.io/blog/posts/ai-agent-web-scraping) Run headless browsers at scale, **1,000 free credits** [Start Free](https://scrapfly.io/register)