#scraper api

[scrapingdog]

Want to stay ahead of Amazon price changes? Learn how to automate price tracking using Scrapingdog’s Amazon Scraper API and Make.com. A step-by-step guide for smarter, hands-free eCommerce monitoring.

[webdatacrawler0]

E-commerce Web Scraping | Data Scraping for eCommerce

Are you in need of data scraping for eCommerce industry? Get expert E-commerce web scraping services to extract real-time data. Flat 20%* off on ecommerce data scraping.

[scrapin1]

Automate LinkedIn Data Collection Using Advanced Scraper APIs and Tools

Data scraping at scale depends on automation, and the LinkedIn scraper api plays a vital role in this process. It allows developers and analysts to pull relevant profiles or company data directly from LinkedIn in structured formats.

[iwebscrapingblogs]

E-commerce Web Scraping API for Accurate Product & Pricing Insights

Access structured e-commerce data efficiently with a robust web scraping API for online stores, marketplaces, and retail platforms. This API helps collect data on product listings, prices, reviews, stock availability, and seller details from top e-commerce sites. Ideal for businesses monitoring competitors, following trends, or managing records, it provides consistent and correct results. Built to scale, the service supports high-volume requests and delivers results in easy-to-integrate formats like JSON or CSV. Whether you need data from Amazon, eBay, or Walmart. iWeb Scraping provides unique e-commerce data scraping services. Learn more about the service components and pricing by visiting iWebScraping E-commerce Data Services.

[tagx01]

Amazon Scraper API Made Easy: Get Product, Price, & Review Data

If you’re in the world of e-commerce, market research, or product analytics, then you know how vital it is to have the right data at the right time. Enter the Amazon Scraper API—your key to unlocking real-time, accurate, and comprehensive product, price, and review information from the world's largest online marketplace. With this amazon scraper, you can streamline data collection and focus on making data-driven decisions that drive results.

Accessing Amazon’s extensive product listings and user-generated content manually is not only tedious but also inefficient. Fortunately, the Amazon Scraper API automates this process, allowing businesses of all sizes to extract relevant information with speed and precision. Whether you're comparing competitor pricing, tracking market trends, or analyzing customer feedback, this tool is your secret weapon.

Using an amazon scraper is more than just about automation—it’s about gaining insights that can redefine your strategy. From optimizing listings to enhancing customer experience, real-time data gives you the leverage you need. In this blog, we’ll explore what makes the Amazon Scraper API a game-changer, how it works, and how you can use it to elevate your business.

What is an Amazon Scraper API?

An Amazon Scraper API is a specialized software interface that allows users to programmatically extract structured data from Amazon without manual intervention. It acts as a bridge between your application and Amazon's web pages, parsing and delivering product data, prices, reviews, and more in machine-readable formats like JSON or XML. This automated process enables businesses to bypass the tedious and error-prone task of manual scraping, making data collection faster and more accurate.

One of the key benefits of an Amazon Scraper API is its adaptability. Whether you're looking to fetch thousands of listings or specific review details, this amazon data scraper can be tailored to your exact needs. Developers appreciate its ease of integration into various platforms, and analysts value the real-time insights it offers.

Why You Need an Amazon Scraper API

The Amazon marketplace is a data-rich environment, and leveraging this data gives you a competitive advantage. Here are some scenarios where an Amazon Scraper API becomes indispensable:

1. Market Research: Identify top-performing products, monitor trends, and analyze competition. With accurate data in hand, businesses can launch new products or services with confidence, knowing there's a demand or market gap to fill.

2. Price Monitoring: Stay updated with real-time price fluctuations to remain competitive. Automated price tracking via an amazon price scraper allows businesses to react instantly to competitors' changes.

3. Inventory Management: Understand product availability and stock levels. This can help avoid stock outs or overstocking. Retailers can optimize supply chains and restocking processes with the help of an amazon product scraper.

4. Consumer Sentiment Analysis: Use review data to improve offerings. With Amazon Review Scraping, businesses can analyze customer sentiment to refine product development and service strategies.

5. Competitor Benchmarking: Compare products across sellers to evaluate strengths and weaknesses. An amazon web scraper helps gather structured data that fuels sharper insights and marketing decisions.

6. SEO and Content Strategy: Extract keyword-rich product titles and descriptions. With amazon review scraper tools, you can identify high-impact phrases to enrich your content strategies.

7. Trend Identification: Spot emerging trends by analyzing changes in product popularity, pricing, or review sentiment over time. The ability to scrape amazon product data empowers brands to respond proactively to market shifts.

Key Features of a Powerful Amazon Scraper API

Choosing the right Amazon Scraper API can significantly enhance your e-commerce data strategy. Here are the essential features to look for:

Scalability: Seamlessly handle thousands—even millions—of requests. A truly scalable Amazon data scraper supports massive workloads without compromising speed or stability.

High Accuracy: Get real-time, up-to-date data with high precision. Top-tier Amazon data extraction tools constantly adapt to Amazon’s evolving structure to ensure consistency.

Geo-Targeted Scraping: Extract localized data across regions. Whether it's pricing, availability, or listings, geo-targeted Amazon scraping is essential for global reach.

Advanced Pagination & Sorting: Retrieve data by page number, relevance, rating, or price. This allows structured, efficient scraping for vast product categories.

Custom Query Filters: Use ASINs, keywords, or category filters for targeted extraction. A flexible Amazon scraper API ensures you collect only the data you need.

CAPTCHA & Anti-Bot Bypass: Navigate CAPTCHAs and Amazon’s anti-scraping mechanisms using advanced, bot-resilient APIs.

Flexible Output Formats: Export data in JSON, CSV, XML, or your preferred format. This enhances integration with your applications and dashboards.

Rate Limiting Controls: Stay compliant while maximizing your scraping potential. Good Amazon APIs balance speed with stealth.

Real-Time Updates: Track price drops, stock changes, and reviews in real time—critical for reactive, data-driven decisions.

Developer-Friendly Documentation: Enjoy a smoother experience with comprehensive guides, SDKs, and sample codes—especially crucial for rapid deployment and error-free scaling.

How the Amazon Scraper API Works

The architecture behind an Amazon Scraper API is engineered for robust, scalable scraping, high accuracy, and user-friendliness. At a high level, this powerful Amazon data scraping tool functions through the following core steps:

1. Send Request: Users initiate queries using ASINs, keywords, category names, or filters like price range and review thresholds. This flexibility supports tailored Amazon data retrieval.

2. Secure & Compliant Interactions: Advanced APIs utilize proxy rotation, CAPTCHA solving, and header spoofing to ensure anti-blocking Amazon scraping that mimics legitimate user behavior, maintaining access while complying with Amazon’s standards.

3. Fetch and Parse Data: Once the target data is located, the API extracts and returns it in structured formats such as JSON or CSV. Data includes pricing, availability, shipping details, reviews, ratings, and more—ready for dashboards, databases, or e-commerce tools.

4. Real-Time Updates: Delivering real-time Amazon data is a core advantage. Businesses can act instantly on dynamic pricing shifts, consumer trends, or inventory changes.

5. Error Handling & Reliability: Intelligent retry logic and error management keep the API running smoothly, even when Amazon updates its site structure, ensuring maximum scraping reliability.

6. Scalable Data Retrieval: Designed for both startups and enterprises, modern APIs handle everything from small-scale queries to high-volume Amazon scraping using asynchronous processing and optimized rate limits.

Top 6 Amazon Scraper APIs to Scrape Data from Amazon

1. TagX Amazon Scraper API

TagX offers a robust and developer-friendly Amazon Scraper API designed to deliver accurate, scalable, and real-time access to product, pricing, and review data. Built with enterprise-grade infrastructure, the API is tailored for businesses that need high-volume data retrieval with consistent uptime and seamless integration.

It stands out with anti-blocking mechanisms, smart proxy rotation, and responsive documentation, making it easy for both startups and large enterprises to deploy and scale their scraping efforts quickly. Whether you're monitoring price fluctuations, gathering review insights, or tracking inventory availability, TagX ensures precision and compliance every step of the way.

Key Features:

High-volume request support with 99.9% uptime.

Smart proxy rotation and CAPTCHA bypassing.

Real-time data scraping with low latency.

Easy-to-integrate with structured JSON/CSV outputs.

Comprehensive support for reviews, ratings, pricing, and more.

2. Zyte Amazon Scraper API

Zyte offers a comprehensive Amazon scraping solution tailored for businesses that need precision and performance. Known for its ultra-fast response times and nearly perfect success rate across millions of Amazon URLs, Zyte is an excellent choice for enterprise-grade projects. Its machine learning-powered proxy rotation and smart fingerprinting ensure you're always getting clean data, while dynamic parsing helps you retrieve exactly what you need—from prices and availability to reviews and ratings.

Key Features:

Ultra-reliable with 100% success rate on over a million Amazon URLs.

Rapid response speeds averaging under 200ms.

Smart proxy rotation powered by machine learning.

Dynamic data parsing for pricing, availability, reviews, and more.

3. Oxylabs Amazon Scraper API

Oxylabs delivers a high-performing API for Amazon data extraction, engineered for both real-time and bulk scraping needs. It supports dynamic JavaScript rendering, making it ideal for dealing with Amazon’s complex front-end structures. Robust proxy management and high reliability ensure smooth data collection for large-scale operations. Perfect for businesses seeking consistency and depth in their scraping workflows.

Key Features:

99.9% success rate on product pages.

Fast average response time (~250ms).

Offers both real-time and batch processing.

Built-in dynamic JavaScript rendering for tough-to-reach data.

4. Bright Data Amazon Scraper API

Bright Data provides a flexible and feature-rich API designed for heavy-duty Amazon scraping. It comes equipped with advanced scraping tools, including automatic CAPTCHA solving and JavaScript rendering, while also offering full compliance with ethical web scraping standards. It’s particularly favored by data-centric businesses that require validated, structured, and scalable data collection.

Key Features:

Automatic IP rotation and CAPTCHA solving.

Support for JavaScript rendering for dynamic pages.

Structured data parsing and output validation.

Compliant, secure, and enterprise-ready.

5. ScraperAPI

ScraperAPI focuses on simplicity and developer control, making it perfect for teams who want easy integration with their own tools. It takes care of all the heavy lifting—proxies, browsers, CAPTCHAs—so developers can focus on building applications. Its customization flexibility and JSON parsing capabilities make it a top choice for startups and mid-sized projects.

Key Features:

Smart proxy rotation and automatic CAPTCHA handling.

Custom headers and query support.

JSON output for seamless integration.

Supports JavaScript rendering for complex pages.

6. SerpApi Amazon Scraper

SerpApi offers an intuitive and lightweight API that is ideal for fetching Amazon product search results quickly and reliably. Built for speed, SerpApi is especially well-suited for real-time tasks and applications that need low-latency scraping. With flexible filters and multi-language support, it’s a great tool for localized e-commerce tracking and analysis.

Key Features:

Fast and accurate search result scraping.

Clean JSON output formatting.

Built-in CAPTCHA bypass.

Localized filtering and multi-region support.

Conclusion

In the ever-evolving digital commerce landscape, real-time Amazon data scraping can mean the difference between thriving and merely surviving. TagX’s Amazon Scraper API stands out as one of the most reliable and developer-friendly tools for seamless Amazon data extraction.

With a robust infrastructure, unmatched accuracy, and smooth integration, TagX empowers businesses to make smart, data-driven decisions. Its anti-blocking mechanisms, customizable endpoints, and developer-focused documentation ensure efficient, scalable scraping without interruptions.

Whether you're tracking Amazon pricing trends, monitoring product availability, or decoding consumer sentiment, TagX delivers fast, secure, and compliant access to real-time Amazon data. From agile startups to enterprise powerhouses, the platform grows with your business—fueling smarter inventory planning, better marketing strategies, and competitive insights.

Don’t settle for less in a competitive marketplace. Experience the strategic advantage of TagX—your ultimate Amazon scraping API.

Try TagX’s Amazon Scraper API today and unlock the full potential of Amazon data!

Original Source, https://www.tagxdata.com/amazon-scraper-api-made-easy-get-product-price-and-review-data

[realdataapi01]

RealdataAPI is the one-stop solution for Web Scraper, Crawler, & Web Scraping APIs for Data Extraction in countries like USA, UK, UAE, Germany, Australia, etc.

[reviewgatorsusa]

Best Zomato Web Scraping Services by ReviewGators

Our online Zomato web scraping service makes it easy for you to get all the information you need to focus on providing value to your customers. We develop our Zomato Review Scraper API with no contracts, no setup fees, and no upfront costs to satisfy the needs of our clients. Customers have the option to make payments as needed. You can efficiently and accurately scrape Zomato data about reviews and ratings from the Zomato website using our Zomato Scraper.

[foodspark-scraper]

Foodpanda API will extract and download Foodpanda data, including restaurant details, menus, reviews, ratings, etc. Download the data in the required format, such as CSV, Excel, etc.

[iwebdatascrape]

Google Shopping Data Scraper

Scrape Google Shopping data, including price, merchant name, etc., using Google Shopping data scraper. Our Google Shopping scraping tool can scrape data across the USA, UK,

[bypasscloudflare]

Google SERP Scraping With Python

The video shows a easy Google SERP scraping process with Python. 👉 Go to ScrapingBypass website: https://www.scrapingbypass.com Google SERP scraping code: https://www.scrapingbypass.com/tutorial/google-serp-scraping-with-python

[scrapin1]

How to Access LinkedIn API - Step-by-Step Guide

LinkedIn has proven its worth as one of the most authentic professional networking platforms. It offers a wide array of structured data points for talent, marketing, sales, etc. Companies can access this data by using LinkedIn APIs (Application Programming Interface). An API serves as a gateway for integrating LinkedIn data into applications created by businesses.

Visit Here :- https://www.scrapin.io/blog/linkedin-api

[iwebscrapingblogs]

Zomato API - Zomato Scraper - Zomato Review API

In the realm of food and restaurant discovery, Zomato stands as a significant player. For developers and data enthusiasts, the platform offers several APIs that provide access to its extensive database of restaurants, reviews, and user-generated content. In this blog, we delve into the Zomato API ecosystem, focusing on three key components: the Zomato API, Zomato Scraper, and Zomato Review API. Understanding these tools can unlock a wealth of opportunities for creating innovative applications and gaining insights into dining trends.

The Zomato API

Overview

The Zomato API is a powerful tool that allows developers to access Zomato’s vast collection of restaurant data. Whether you’re building a restaurant recommendation app, a food delivery service, or conducting market research, this API provides a plethora of endpoints that can meet your needs.

Key Features

Restaurant Search and Details:

Retrieve information about restaurants, including name, location, cuisine, and average cost.

Search for restaurants based on various criteria like location, cuisine type, and budget.

Location Data:

Access details about specific locations including cities, and neighborhoods, and their popularity.

Use geo-coordinates to find restaurants nearby.

Cuisine and Establishment Types:

Get a list of available cuisines in a specified location.

Discover different types of establishments such as cafes, bars, and fine dining options.

User Reviews:

Fetch reviews and ratings for restaurants.

Access user-generated content that provides insights into customer experiences.

How to Use

To get started with the Zomato API:

Sign Up: Register on the Zomato Developers portal to get an API key.

Documentation: Review the API documentation to understand the available endpoints and how to use them.

Integration: Use your API key to authenticate requests and integrate the data into your application.

Zomato Scraper

Overview

While the official Zomato API offers extensive access to data, some information might not be available through the API. In such cases, a Zomato Scraper can be a valuable tool. Web scraping involves extracting data directly from web pages, providing a way to collect information not exposed by the API.

Key Uses

Custom Data Extraction:

Extract details that might not be available through the API, such as additional reviews or specific dish information.

Data for Analysis:

Collect large amounts of data for sentiment analysis, market research, or machine learning models.

Monitoring Changes:

Track changes in restaurant details, menu items, and pricing over time.

Ethical Considerations

Using a Zomato Scraper requires careful consideration of Zomato’s terms of service and legal guidelines. It's crucial to:

Respect Robots.txt: Check and comply with Zomato’s robots.txt file to ensure you are not violating their scraping policies.

Avoid Overloading: Implement rate limits to avoid overloading Zomato’s servers.

Use Responsibly: Ensure that the scraped data is used ethically and for legitimate purposes.

Zomato Review API

Overview

For applications that focus on user-generated content and feedback, the Zomato Review API is an invaluable resource. This API specifically targets reviews and ratings provided by users, offering detailed insights into customer satisfaction and dining experiences.

Key Features

Review Data:

Access detailed reviews including the user’s comments, ratings, and review date.

Filter reviews by date, rating, or relevance.

User Information:

Obtain information about the reviewers, such as their user profile and review history.

Analyze patterns in reviews from specific users or demographics.

Sentiment Analysis:

Use review data to perform sentiment analysis, gauging public opinion and trends.

Identify key themes and sentiments in user feedback.

How to Use

To leverage the Zomato Review API:

Obtain Access: Similar to the Zomato API, secure access by registering and obtaining an API key.

Explore Endpoints: Use the provided endpoints to fetch reviews and associated data.

Integrate and Analyze: Integrate the review data into your system and use it for various analysis and insights.

[tagx01]

Best Shopify Scraper APIs for 2025: Our Top 10 Picks

E-commerce businesses are more competitive than ever, and access to accurate, real-time data is crucial for staying ahead. Whether you track competitor pricing data, analyze product trends, or monitor stock availability, a Shopify Scraper API can make the process seamless and efficient.

With the right scraping API, businesses can automate data collection, reduce manual effort, and make informed decisions to optimize their strategies. However, with so many options available, choosing the best Shopify Scraper API can be overwhelming.

In this detailed guide, we’ll walk you through the 10 best Shopify Scraper APIs for 2025, covering their features, advantages, and why they are worth considering for your business.

What is a Shopify Scraper API?

A Shopify Scraper API allows users to extract structured data from Shopify stores. It helps businesses collect information on product listings, prices, reviews, inventory status, and more. By automating Shopify scraping, businesses can analyze competitors and make informed pricing and inventory decisions.

These APIs are designed to efficiently gather large volumes of data while ensuring accuracy and reliability. Whether you’re an e-commerce entrepreneur, a dropshipper, or a market analyst, using a Shopify Scraper API can streamline your data collection process.

How to Choose the Right Shopify Scraper API?

Selecting the best Shopify Scraper API depends on your business needs, technical expertise, and the required scale of data extraction. Here are five key factors to consider before making your choice:

1. Data Accuracy & Completeness

The quality of extracted data is crucial for effective decision-making. Choose an API that provides accurate, structured, and up-to-date Shopify data, ensuring you get complete information on products, prices, inventory, and reviews without errors or missing details.

2. Anti-Blocking & IP Rotation Capabilities

Shopify has security measures that can block scrapers. A good Shopify Scraper API should have IP rotation, CAPTCHA bypassing, and anti-blocking mechanisms to ensure uninterrupted data extraction without getting banned.

3. Scalability & Performance

Whether you need data from a few Shopify stores or thousands, the API should handle large-scale scraping efficiently. Look for APIs that offer fast response times, high request limits, and cloud-based scalability to accommodate growing business needs.

4. Ease of Integration & Usability

If you’re a developer, choose an API that supports multiple programming languages (Python, Node.js, etc.) for easy integration. For non-technical users, opt for a no-code Shopify scraper with a simple interface and pre-built templates.

5. Pricing & Support

Compare pricing plans based on API request limits, data volume, and additional features. Also, check for customer support options, API documentation, and user reviews to ensure you get the necessary help when needed.

Why Use a Shopify Scraper API in 2025?

The e-commerce industry is evolving rapidly, and keeping up with trends requires access to real-time data. Here are some key reasons why businesses need a Shopify Scraper API:

1. Competitor Analysis

Understanding what your competitors are selling and how they price their products is vital for staying competitive. A Shopify Scraper API can help you monitor:

Best-selling products in competing stores

Frequent price changes and promotional strategies

New product launches and market trends

By tracking this data consistently, businesses can adjust their pricing and marketing strategies to stay ahead of the competition.

2. Price Monitoring & Dynamic Pricing

Pricing plays a crucial role in consumer decision-making. Using a Shopify Scraper API, businesses can:

Compare competitor pricing and adjust their own prices accordingly

Set up dynamic pricing strategies based on market demand

Monitor discounts and promotional offers in real-time

This allows businesses to maximize profitability while remaining competitive in their niche.

3. Product Trend Analysis

Identifying trending products before they become mainstream can give your business a major advantage. A Shopify scraping tool helps in:

Detecting rising trends based on sales volume and search demand

Identifying new product categories that are gaining traction

Understanding customer preferences and seasonal demand fluctuations

By leveraging this data, businesses can optimize their inventory and marketing efforts to capitalize on emerging trends.

4. Inventory Tracking & Stock Availability

Nothing frustrates customers more than discovering a product is out of stock. A Shopify Scraper API can help businesses:

Monitor inventory levels of competitors

Detect stock shortages in the market to adjust their own pricing

Ensure their own inventory meets customer demand

For e-commerce stores, real-time stock insights can significantly improve customer experience and revenue.

5. Automating Data Extraction for Efficiency

Manually collecting Shopify data is not only time-consuming but also prone to errors. A Shopify Scraper API automates this process, ensuring:Accurate and structured data collectionFaster processing timesIntegration with existing business tools and dashboards

With automation, businesses can focus on strategy and execution rather than data collection.

Top 10 Best Shopify Scraper APIs for 2025

Shopify has become one of the most dominant e-commerce platforms, with millions of online stores competing for customer attention. To stay ahead, businesses need access to real-time data on competitor pricing, product availability, customer reviews, and sales trends. A Shopify Scraper API automates this data extraction, providing structured insights that help businesses optimize their pricing, marketing, and inventory strategies.

In this section, we will explore the top 10 best Shopify Scraper APIs for 2025, highlighting their features, benefits, and why they are the best choices for e-commerce professionals.

1. TagX Shopify Scraper API – Best for High-Speed, Reliable Shopify Scraping

Features:

TagX Shopify Scraper API is a high-performance data extraction tool designed for businesses that require fast, accurate, and scalable Shopify data scraping. It enables users to extract critical store data, including product details, pricing, stock availability, and customer reviews, with minimal effort. TagX ensures real-time data delivery, making it a powerful solution for businesses looking to track market trends and competitor pricing.

Equipped with anti-blocking mechanisms and robust infrastructure, TagX prevents IP bans and maintains smooth data extraction even on heavily protected Shopify stores. The API also offers customizable scraping parameters, allowing businesses to extract only the data they need.

Best For:

E-commerce businesses that require real-time Shopify data extraction.

Dropshipping and retail stores looking to track retail competitor pricing.

Developers and analysts who need a scalable Shopify scraping solution.

Why Choose TagX?

High-speed data extraction: Processes large data volumes efficiently.

Real-time competitor tracking: Keeps your pricing strategy up to date.

Anti-blocking technology: Ensures uninterrupted Shopify scraping.

Customizable data extraction: Allows users to define specific data points.

Secure and reliable API: Built for high scalability and performance.

2. ScraperAPI – Best for Developers & Large-Scale Data Extraction

Features:

ScraperAPI is a powerful Shopify Scraper API that specializes in large-scale data extraction while preventing IP blocks. It offers intelligent IP rotation, CAPTCHA solving, and bot detection bypassing, making it ideal for developers who need seamless Shopify data collection.

This API integrates with multiple programming languages and allows users to customize requests to extract precise Shopify store data such as product information, pricing trends, and inventory levels.

Best For:

Developers and businesses requiring mass Shopify data extraction.

Market researchers monitoring price changes across multiple stores.

Data analysts looking for automated, high-speed Shopify scraping.

Why Choose ScraperAPI?

Advanced anti-blocking mechanisms: Avoids Shopify security restrictions.

Supports multiple coding languages: Works with Python, Node.js, PHP, and more.

Handles millions of requests per month: Ideal for high-volume scraping.

Custom request parameters: Allows targeted data extraction.

Fast response times: Ensures real-time Shopify data retrieval.

3. Bright Data – Best for Proxy-Based Shopify Scraping

Features:

Bright Data (formerly Luminati) is a leading web scraping solution that provides a vast proxy network for Shopify data extraction. It ensures undetectable scraping by using residential, mobile, and data center proxies, helping businesses bypass Shopify’s security systems.

With its real-time data retrieval capabilities, Bright Data is perfect for businesses that need to track pricing trends, stock levels, and product updates across multiple Shopify stores.

Best For:

Enterprise-level businesses conducting large-scale Shopify data collection.

E-commerce brands and analysts need real-time market insights.

Companies requiring a secure, stealthy Shopify scraping solution.

Why Choose Bright Data?

Access to millions of residential IPs: Ensures undetectable scraping.

Reliable Shopify data extraction: Supports large-scale operations.

Fast and secure: Protects against bans and restrictions.

Flexible integration: Can be used with APIs, browser extensions, and scripts.

4. Scrapy – Best Open-Source Shopify Scraper API for Developers

Features:

Scrapy is a Python-based, open-source web scraping framework that allows developers to build custom Shopify scraping applications. It provides full control over the data extraction process, enabling users to create advanced Shopify scraping workflows tailored to their specific needs.

With scalable architecture and built-in support for data pipelines, Scrapy is perfect for businesses that require efficient and customizable Shopify data scraping.

Best For:

Developers and data scientists who need custom Shopify scraping solutions.

Tech-savvy users looking for a free, scalable Shopify scraper.

Businesses with in-house development teams managing large-scale Shopify data extraction.

Why Choose Scrapy?

Completely free and open-source: No subscription required.

Highly customizable: Developers can modify scraping rules as needed.

Supports large-scale scraping projects: Works well with big data applications.

Efficient and fast: Optimized for high-performance web scraping.

5. Apify Shopify Scraper – Best for No-Code Data Extraction

Features:

Apify’s Shopify Scraper is a cloud-based, automated tool that enables businesses to extract Shopify store data without writing code. It comes with a pre-built scraping template, making Shopify scraping accessible to non-developers.

Apify supports structured data extraction, meaning users receive clean data formats such as CSV or JSON, ready for analysis.

Best For:

E-commerce marketers need quick access to Shopify data.

Business owners looking for an easy-to-use Shopify scraping tool.

Researchers who need structured Shopify store insights.

Why Choose Apify?

No coding required: Perfect for non-technical users.Cloud-based automation: Allows scheduled scraping tasks.Extracts structured data: Provides clean CSV and JSON output formats.Supports API integration: Works with business intelligence tools.

6. DataScraper API – Best for AI-Powered Data Extraction

Features:

DataScraper API utilizes artificial intelligence and machine learning to extract Shopify store data with extreme accuracy. It is designed for businesses that need clean, structured product and pricing data without manual intervention.

Best For:

Data-driven e-commerce businesses looking for automated Shopify data insights.

Companies using AI analytics for market research and competitive analysis.

Why Choose DataScraper API?

AI-powered accuracy: Ensures clean Shopify data extraction.

Automated cleaning and structuring: Delivers ready-to-use insights.

7. Octoparse – Best for Non-Developers with Pre-Built Templates

Features:

Octoparse is a user-friendly, no-code web scraping tool that offers pre-built Shopify scraping templates. It enables businesses to collect Shopify store data without technical expertise.

Best For:

Business owners and marketers who need quick, hassle-free Shopify scraping.

Why Choose Octoparse?

Drag-and-drop interface: No coding required.

Cloud-based: Runs Shopify scraping tasks 24/7.

8. WebScraper.io API – Best Budget-Friendly Shopify Scraper API

Features:

WebScraper.io API is an affordable and beginner-friendly Shopify Scraper API designed for small businesses and individual users. It provides an intuitive interface that allows users to extract product details, pricing information, customer reviews, and inventory status from Shopify stores with minimal effort. Unlike complex scraping tools that require coding knowledge, WebScraper.io API offers pre-configured extraction settings that make Shopify scraping accessible to non-technical users.

Additionally, WebScraper.io API offers cloud-based scraping, which means users can run their data extraction processes without relying on local machine resources. The API also includes basic anti-blocking mechanisms, helping users retrieve data smoothly without frequent bans.

Best For:

Small businesses looking for a cost-effective Shopify scraping solution.

Freelancers and solopreneurs who need structured Shopify product data for market research.

Beginners in web scraping who want an easy-to-use Shopify Scraper API without complex setup.

Why Choose WebScraper.io API?

Affordable pricing: One of the most budget-friendly Shopify Scraper APIs.

User-friendly interface: No coding required, making it easy for beginners.

Cloud-based scraping: Runs in the background without consuming local resources.

Pre-configured scraping settings: Simplifies Shopify data extraction.

Supports various export formats: Download Shopify data in CSV, JSON, or Excel files.

9. Import.io – Best for Data-Driven Decision Making

Features:

Import.io is a powerful, AI-driven Shopify Scraper API that enables businesses to collect and analyze Shopify store data for in-depth market insights. Unlike standard scraping tools that only extract raw data, Import.io transforms Shopify data into structured reports that help businesses make data-driven decisions.

With automated data refresh capabilities, Import.io ensures that your extracted Shopify data stays up-to-date without requiring manual intervention. The platform is designed for business intelligence and market analysis, making it a preferred choice for enterprises that need to monitor Shopify trends continuously.

Import.io also provides advanced data cleaning and transformation features, allowing businesses to filter and refine Shopify store data before analysis. This ensures that companies work with accurate and well-structured data, leading to more reliable business insights.

Best For:

E-commerce analysts and business intelligence teams needing continuous Shopify data tracking.

Companies that require AI-powered Shopify data processing and transformation.

Organizations looking for automated, scheduled Shopify scraping with minimal manual effort.

Why Choose Import.io?

AI-powered data extraction: Ensures structured, insightful Shopify data.

Automated data updates: Keeps Shopify data fresh with scheduled refresh options.

Advanced data transformation: Converts raw Shopify data into meaningful reports.

Enterprise-grade security: Ensures safe and compliant Shopify scraping.

Integrates with BI tools: Works seamlessly with Tableau, Power BI, and Google Data Studio.

10. ParseHub – Best for Advanced Web Scraping

Features:

ParseHub is an advanced, AI-powered Shopify Scraper API that uses machine learning algorithms to extract data from Shopify stores with high accuracy. It is built for users who need custom scraping solutions, allowing them to create complex data extraction workflows tailored to their business needs.

One of ParseHub's standout features is its visual web scraping interface, which allows users to point and click on Shopify store elements to set up extraction rules without writing any code. For more advanced users, ParseHub offers script-based customization, enabling businesses to handle complex Shopify scraping scenarios, such as tracking price fluctuations, detecting out-of-stock products, and monitoring seasonal trends.

Additionally, ParseHub includes cloud-based execution, meaning users can schedule Shopify scraping tasks and retrieve data at regular intervals without keeping their devices running.

Best For:

Data analysts and researchers who require advanced, customizable Shopify scraping workflows.

Businesses needing real-time Shopify data tracking for competitor monitoring and pricing optimization.

Tech-savvy users and developers looking for a powerful, scriptable Shopify Scraper API.

Why Choose ParseHub?

AI-powered scraping: Uses machine learning to extract structured Shopify data.

Visual point-and-click interface: Allows users to build scrapers without coding.

Advanced script customization: Supports custom rules for complex data extraction.

Cloud-based scheduling: Runs Shopify scraping tasks automatically in the background.

Handles dynamic content: Extracts data even from JavaScript-heavy Shopify pages.

Final Thoughts

A Shopify Scraper API is an essential tool for businesses that need to extract valuable Shopify data effortlessly. From competitor pricing to inventory tracking, these APIs help e-commerce brands stay competitive in 2025.

Among the top 10 picks, TagX Shopify Scraper API stands out as a reliable and efficient solution for businesses seeking high-quality data extraction.

Ready to supercharge your e-commerce strategy? Start using a Shopify Scraper API today and gain a competitive edge in the ever-evolving online marketplace!

Original Source, https://www.tagxdata.com/best-shopify-scraper-apis-for-2025-our-top-10-picks

[mostlysignssomeportents]

Are the means of computation even seizable?

I'm on a 20+ city book tour for my new novel PICKS AND SHOVELS. Catch me in PITTSBURGH in TOMORROW (May 15) at WHITE WHALE BOOKS, and in PDX on Jun 20 at BARNES AND NOBLE with BUNNIE HUANG. More tour dates (London, Manchester) here.

Something's very different in tech. Once upon a time, every bad choice by tech companies – taking away features, locking out mods or plugins, nerfing the API – was countered, nearly instantaneously, by someone writing a program that overrode that choice.

Bad clients would be muscled aside by third-party clients. Locked bootloaders would be hacked and replaced. Code that confirmed you were using OEM parts, consumables or adapters would be found and nuked from orbit. Weak APIs would be replaced with muscular, unofficial APIs built out of unstoppable scrapers running on headless machines in some data-center. Every time some tech company erected a 10-foot enshittifying fence, someone would show up with an 11-foot disenshittifying ladder.

Those 11-foot ladders represented the power of interoperability, the inescapable bounty of the Turing-complete, universal von Neumann machine, which, by definition, is capable of running every valid program. Specifically, they represented the power of adversarial interoperability – when someone modifies a technology against its manufacturer's wishes. Adversarial interoperability is the origin story of today's tech giants, from Microsoft to Apple to Google:

https://www.eff.org/deeplinks/2019/10/adversarial-interoperability

But adversarial interop has been in steady decline for the past quarter-century. These big companies moved fast and broke things, but no one is returning the favor. If you ask the companies what changed, they'll just smirk and say that they're better at security than the incumbents they disrupted. The reason no one's hacked up a third-party iOS App Store is that Apple's security team is just so fucking 1337 that no one can break their shit.

I think this is nonsense. I think that what's really going on is that we've made it possible for companies to design their technologies in such a way that any attempt at adversarial interop is illegal.

"Anticircumvention" laws like Section 1201 of the 1998 Digital Millennium Copyright Act make bypassing any kind of digital lock (AKA "Digital Rights Management" or "DRM") very illegal. Under DMCA, just talking about how to remove a digital lock can land you in prison for 5 years. I tell the story of this law's passage in "Understood: Who Broke the Internet," my new podcast series for the CBC:

https://pluralistic.net/2025/05/08/who-broke-the-internet/#bruce-lehman

For a quarter century, tech companies have aggressively lobbied and litigated to expand the scope of anticircumvention laws. At the same time, companies have come up with a million ways to wrap their products in digital locks that are a crime to break.

Digital locks let Chamberlain, a garage-door opener monopolist block all third-party garage-door apps. Then, Chamberlain stuck ads in its app, so you have to watch an ad to open your garage-door:

https://pluralistic.net/2023/11/09/lead-me-not-into-temptation/#chamberlain

Digital locks let John Deere block third-party repair of its tractors:

https://pluralistic.net/2022/05/08/about-those-kill-switched-ukrainian-tractors/

And they let Apple block third-party repair of iPhones:

https://pluralistic.net/2022/05/22/apples-cement-overshoes/

These companies built 11-foot ladders to get over their competitors' 10-foot walls, and then they kicked the ladder away. Once they were secure atop their walls, they committed enshittifying sins their fallen adversaries could only dream of.

I've been campaigning to abolish anticircumvention laws for the past quarter-century, and I've noticed a curious pattern. Whenever these companies stand to lose their legal protections, they freak out and spend vast fortunes to keep those protections intact. That's weird, because it strongly implies that their locks don't work. A lock that works works, whether or not it's illegal to break that lock. The reason Signal encryption works is that it's working encryption. The legal status of breaking Signal's encryption has nothing to do with whether it works. If Signal's encryption was full of technical flaws but it was illegal to point those flaws out, you'd be crazy to trust Signal.

Signal does get involved in legal fights, of course, but the fights it gets into are ones that require Signal to introduce defects in its encryption – not fights over whether it is legal to disclose flaws in Signal or exploit them:

https://pluralistic.net/2023/03/05/theyre-still-trying-to-ban-cryptography/

But tech companies that rely on digital locks manifestly act like their locks don't work and they know it. When the tech and content giants bullied the W3C into building DRM into 2 billion users' browsers, they categorically rejected any proposal to limit their ability to destroy the lives of people who broke that DRM, even if it was only to add accessibility or privacy to video:

https://www.eff.org/deeplinks/2017/09/open-letter-w3c-director-ceo-team-and-membership

The thing is, if the lock works, you don't need the legal right to destroy the lives of people who find its flaws, because it works.

Do digital locks work? Can they work? I think the answer to both questions is a resounding no. The design theory of a digital lock is that I can provide you with an encrypted file that your computer has the keys to. Your computer will access those keys to decrypt or sign a file, but only under the circumstances that I have specified. Like, you can install an app when it comes from my app store, but not when it comes from a third party. Or you can play back a video in one kind of browser window, but not in another one. For this to work, your computer has to hide a cryptographic key from you, inside a device you own and control. As I pointed out more than a decade ago, this is a fool's errand:

https://memex.craphound.com/2012/01/10/lockdown-the-coming-war-on-general-purpose-computing/

After all, you or I might not have the knowledge and resources to uncover the keys' hiding place, but someone does. Maybe that someone is a person looking to go into business selling your customers the disenshittifying plugin that unfucks the thing you deliberately broke. Maybe it's a hacker-tinkerer, pursuing an intellectual challenge. Maybe it's a bored grad student with a free weekend, an electron-tunneling microscope, and a seminar full of undergrads looking for a project.

The point is that hiding secrets in devices that belong to your adversaries is very bad security practice. No matter how good a bank safe is, the bank keeps it in its vault – not in the bank-robber's basement workshop.

For a hiding-secrets-in-your-adversaries'-device plan to work, the manufacturer has to make zero mistakes. The adversary – a competitor, a tinkerer, a grad student – only has to find one mistake and exploit it. This is a bedrock of security theory: attackers have an inescapable advantage.

So I think that DRM doesn't work. I think DRM is a legal construct, not a technical one. I think DRM is a kind of magic Saran Wrap that manufacturers can wrap around their products, and, in so doing, make it a literal jailable offense to use those products in otherwise legal ways that their shareholders don't like. As Jay Freeman put it, using DRM creates a new law called "Felony Contempt of Business Model." It's a law that has never been passed by any legislature, but is nevertheless enforceable.

In the 25 years I've been fighting anticircumvention laws, I've spoken to many government officials from all over the world about the opportunity that repealing their anticircumvention laws represents. After all, Apple makes $100b/year by gouging app makers for 30 cents on ever dollar. Allow your domestic tech sector to sell the tools to jailbreak iPhones and install third party app stores, and you can convert Apple's $100b/year to a $100m/year business for one of your own companies, and the other $999,900,000,000 will be returned to the world's iPhone owners as a consumer surplus.

But every time I pitched this, I got the same answer: "The US Trade Representative forced us to pass this law, and threatened us with tariffs if we didn't pass it." Happy Liberation Day, people – every country in the world is now liberated from the only reason to keep this stupid-ass law on their books:

https://pluralistic.net/2025/01/15/beauty-eh/#its-the-only-war-the-yankees-lost-except-for-vietnam-and-also-the-alamo-and-the-bay-of-ham

In light of the Trump tariffs, I've been making the global rounds again, making the case for an anticircumvention repeal:

https://www.ft.com/content/b882f3a7-f8c9-4247-9662-3494eb37c30b

One of the questions I've been getting repeatedly from policy wonks, activists and officials is, "Is it even possible to jailbreak modern devices?" They want to know if companies like Apple, Tesla, Google, Microsoft, and John Deere have created unbreakable digital locks. Obviously, this is an important question, because if these locks are impregnable, then getting rid of the law won't deliver the promised benefits.

It's true that there aren't as many jailbreaks as we used to see. When a big project like Nextcloud – which is staffed up with extremely accomplished and skilled engineers – gets screwed over by Google's app store, they issue a press-release, not a patch:

https://arstechnica.com/gadgets/2025/05/nextcloud-accuses-google-of-big-tech-gatekeeping-over-android-app-permissions/

Perhaps that's because the tech staff at Nextcloud are no match for Google, not even with the attacker's advantage on their side.

But I don't think so. Here's why: we do still get jailbreaks and mods, but these almost exclusively come from anonymous tinkerers and hobbyists:

https://consumerrights.wiki/Mazda_DMCA_takedown_of_Open_Source_Home_Assistant_App

Or from pissed off teenagers:

https://www.theverge.com/2022/9/29/23378541/the-og-app-instagram-clone-pulled-from-app-store

These hacks are incredibly ambitious! How ambitious? How about a class break for every version of iOS as well as an unpatchable hardware attack on 8 years' worth of Apple bootloaders?

https://pluralistic.net/2020/05/25/mafia-logic/#sosumi

Now, maybe it's the case at all the world's best hackers are posting free code under pseudonyms. Maybe all the code wizards working for venture backed tech companies that stand to make millions through clever reverse engineering are just not as mad skilled as teenagers who want an ad-free Insta and that's why they've never replicated the feat.

Or maybe it's because teenagers and anonymous hackers are just about the only people willing to risk a $500,000 fine and 5-year prison sentence. In other words, maybe the thing that protects DRM is law, not code. After all, when Polish security researchers revealed the existence of secret digital locks that the train manufacturer Newag used to rip off train operators for millions of euros, Newag dragged them into court:

https://fsfe.org/news/2025/news-20250407-01.en.html

Tech companies are the most self-mythologizing industry on the planet, beating out even the pharma sector in boasting about their prowess and good corporate citizenship. They swear that they've made a functional digital lock…but they sure act like the only thing those locks do is let them sue people who reveal their workings.

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2025/05/14/pregnable/#checkm8

[ao3-anonymous]

there is a dip in the fic count of all fandoms between february 26 and march 3, is there a reason for that? just something I noticed while looking at the dashboard

So I finally had time to look into this properly - at first I couldn't figure it out, because I didn't make any changes to my workflow around that time.

However, I had a hunch and checked everyone's favorite RPF fandom (Hockey RPF) and the drop was wayyy more dramatic there. This confirmed my theory that my stats were no longer including locked works (since RPF fandoms tend to have a way higher percentage of locked fics).

It looks AO3 made some changes to how web scrapers can interact with their site, likely due to the DDOS attacks / AI scrapers they've been dealing with. That change caused my scraper to pull all fic counts as if it was a guest and not a member, which caused the drop.

~

The good news: I was able to leverage the login code from the unofficial python AO3 api to fix it, so future fic counts should be accurate.

The bad news: I haven't figured out what to do about the drop in old data. I can either leave it or I can try to write some math-based script that estimates how many fics there were on those old dates (using the data I do have and scaling up based on that fandom's percentage of locked fics). This wouldn't be a hundred percent accurate, but neither are the current numbers, so we'll see.

~

Thanks Nonny so much for pointing this out! I wish I would've noticed & had a chance to fix earlier, but oh well!