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Best Instagram Scraping APIs in 2025

Best Instagram Scraping APIs in 2025: Complete Comparison and Review

Instagram data remains one of the most valuable sources for social media marketing, competitive intelligence, and market research. With Instagram's official API becoming increasingly restrictive, third-party scraping APIs have filled the gap. Here's a comprehensive comparison of the best Instagram scraping APIs available in 2025. The Instagram Scraping Landscape in 2025 Instagram scraping services fall into two main categories: public data scrapers that work without authentication, and behind-the-login services that can access private information but carry higher risks. Understanding this distinction is crucial for choosing the right solution for your needs. Public data scrapers focus on information visible without logging in - profiles, posts, engagement metrics, and comments on public accounts. Behind-the-login scrapers can access follower lists, private profiles, and contact information, but risk account bans and legal complications. Top Instagram Scraping APIs Compared 1. Apify's Instagram Scraper Website: apify.com/apify/instagram-scraper Data Access: Public data only Pricing: Moderate, usage-based Apify's Instagram scraper represents the established, enterprise-grade approach to Instagram data extraction. Built on Apify's robust web scraping platform, it provides reliable access to publicly available Instagram information. What You Get: Profile information and statistics Post data including captions, likes, and comments Hashtag analysis and trending content Story highlights (but not current stories) Reliable uptime and consistent data quality Strengths: Part of Apify's comprehensive web scraping ecosystem Well-documented API with extensive examples Enterprise-level reliability and support Transparent pricing structure Good integration with other Apify tools Limitations: Limited to public data only Pricing can scale up quickly for high-volume usage May have delays during Instagram's anti-scraping updates 2. Scrape Creators Website: docs.scrapecreators.com/v1/instagram/profile Data Access: Public data only Pricing: Pay-as-you-go, similar to Apify Scrape Creators focuses specifically on social media scraping with a developer-friendly approach. Their Instagram API targets the same public data as Apify but with a more flexible pricing model. What You Get: Complete profile analytics and metadata Post engagement metrics and content analysis Comment extraction and sentiment analysis Real-time data with fast response times Cross-platform compatibility for multi-platform analysis Strengths: True pay-as-you-go pricing with no monthly commitments Fast response times optimized for real-time applications Simple REST API that's easy to integrate Specialized focus on social media data Competitive pricing for smaller-scale operations Limitations: Newer service with less established track record Public data only, no access to private information Limited advanced features compared to enterprise platforms 3. Hiker API Website: hikerapi.com Data Access: Behind-the-login (high risk) Pricing: Variable Hiker API operates in the higher-risk, higher-reward category by providing access to data typically hidden behind Instagram's login wall. This includes private profile information, complete follower lists, and contact details. What You Get: Email addresses and phone numbers from profiles Complete follower and following lists Access to private account information Direct message capabilities Advanced targeting data Important Warnings: High Risk: Using behind-the-login scrapers violates Instagram's terms of service Legal Concerns: May face legal challenges depending on usage and jurisdiction Account Safety: Risk of having accounts banned or suspended Data Ethics: Accessing private information raises ethical concerns Service Reliability: Higher likelihood of service disruptions due to Instagram countermeasures Use Case Considerations: This type of service might be considered for competitive intelligence or lead generation, but users should carefully evaluate legal risks, ethical implications, and potential business consequences before proceeding. 4. Scraping Dog Website: scrapingdog.com/instagram-scraper-api Data Access: Public data only Pricing: Subscription-based, higher cost Scraping Dog positions itself as a premium Instagram scraping solution with subscription-based pricing. They focus on data quality and reliability but at a higher price point. What You Get: High-quality profile and post data Reliable uptime and consistent performance Customer support and documentation Integration with other Scraping Dog services Enterprise-grade infrastructure Strengths: Consistent, high-quality data extraction Reliable service with good uptime Comprehensive customer support Part of larger web scraping platform Limitations: Subscription model may be expensive for variable usage Higher cost compared to pay-per-use alternatives Limited flexibility in pricing plans Public data only 5. Ensemble Data Website: ensembledata.com/apis/docs#tag/Instagram Data Access: Public data only Pricing: Premium pricing, highest cost Ensemble Data represents the high-end option for Instagram scraping, focusing on data quality and enterprise features but at premium pricing levels. What You Get: Premium data quality with extensive validation Enterprise-level API reliability and uptime Advanced analytics and data processing features Comprehensive documentation and support Integration with business intelligence tools Strengths: Highest data quality and accuracy standards Enterprise-grade reliability and support Advanced features for large-scale operations Excellent documentation and API design Limitations: Most expensive option in the comparison May be overkill for smaller operations Subscription-based pricing lacks flexibility Public data limitations same as other legitimate services Choosing the Right Instagram Scraping API For Small to Medium Businesses Scrape Creators or Apify provide the best balance of features, reliability, and cost-effectiveness. Scrape Creators' pay-as-you-go model works well for variable usage, while Apify offers more comprehensive platform features. For Enterprise Applications Ensemble Data or Apify offer the enterprise-grade reliability and support that large organizations require. The higher costs are justified by superior uptime, support quality, and integration capabilities. For High-Risk, High-Reward Operations Hiker API provides access to otherwise unavailable data, but users must carefully weigh the legal, ethical, and business risks. Consider consulting legal counsel before using behind-the-login services. For Budget-Conscious Projects Scrape Creators offers the most flexible pricing for projects with unpredictable usage patterns, while Apify provides good value for consistent, moderate usage.

How to Scrape YouTube Video Transcripts

How to Scrape YouTube Video Transcripts: Step-by-Step Developer Guide

YouTube transcripts are a goldmine of content data, perfect for SEO analysis, content research, accessibility tools, and automated video processing. While YouTube's official API has limitations, there's a reliable method to extract transcripts by understanding how YouTube's web interface works internally. Understanding YouTube's Transcript Architecture YouTube uses a two-phase approach for transcript access: first obtaining a continuation token that authenticates your request, then using that token to fetch the actual transcript data. This system ensures transcripts are only accessible when legitimately requested, just like when you click the transcript button on YouTube's interface. The key insight is that YouTube embeds the transcript access credentials directly in the video page's HTML, then uses these credentials for subsequent API calls to retrieve the actual transcript content. Phase 1: Reverse Engineering the Browser Process Before diving into code, let's understand exactly what happens when you request a transcript through YouTube's interface. Open an incognito browser window and navigate to any YouTube video that has transcripts available. Open Developer Tools (F12), go to the Network tab, and refresh the page. Click on the first request (the HTML page load) and examine the Response tab. Search for "getTranscriptEndpoint" - this contains the critical continuation token needed for transcript access. Copy the "params" value for later verification. Clear the network console, then click the "Show transcript" button in the video description. You'll see a new request to get_transcript that includes both the video ID and the continuation token you found earlier. This is the exact pattern we need to replicate programmatically. Phase 2: Implementing Token Extraction To get the transcript continuation token in code, make a POST request to YouTube's player endpoint: The response contains deeply nested JSON where the transcript token is buried. Rather than manually navigating this complex structure, use a recursive search function: Phase 3: Fetching Transcript Data With the continuation token secured, request the actual transcript: Phase 4: Parsing the Response YouTube returns transcript data in a complex nested structure that requires careful parsing: Essential Production Considerations Proxy Requirements YouTube actively blocks automated requests. Using proxies is mandatory for any serious transcript scraping operation: Recommended Providers: Evomi: Reliable residential proxies with good YouTube success rates Webshare: Cost-effective option for moderate volume operations Decodo: Premium service with highest reliability for large-scale operations Configure your HTTP client to route all requests through proxy servers to avoid IP-based blocking. Skip the Complexity: Use Scrape Creators Instead If you want to skip all this technical overhead and get straight to using transcript data in your application, the YouTube Video Transcript API on Scrape Creators handles all these complexities for you. Check out the YouTube video transcript API at ScrapeCreators: https://docs.scrapecreators.com/v1/youtube/video/transcript. Use code TWITTER for 25% off your first usage. Whether you're building content analysis tools, accessibility features, or educational applications, this API provides the reliability and simplicity that production applications require.

Why Scrape Creators is the Go-To API for Social Media Intelligence

Why Scrape Creators is the Go-To API for Social Media Intelligence

In today's creator-driven economy, access to social media data isn't just useful. It's essential. Whether you're building a creator onboarding platform, conducting influencer research, or monitoring social media trends, having reliable access to social data can make or break your application. Here's why Scrape Creators has become the preferred API for businesses serious about social media intelligence. Lightning-Fast Implementation and Response Times The most immediate advantage of Scrape Creators is how quickly you can get up and running. The API is designed for developers who need to ship features fast, not spend weeks wrestling with complex implementations. Instant Integration: With simple REST endpoints and clear documentation, you can have social data flowing into your application within minutes, not days. There's no complex authentication flows, no SDK dependencies, and no lengthy approval processes. Real-Time Performance: Response times are optimized for user-facing applications. When you're onboarding creators and need to import their social profiles instantly, speed matters. Users expect immediate results, and Scrape Creators delivers with response times that keep your application feeling snappy and responsive. This combination of easy implementation and fast responses makes it perfect for applications where social data needs to feel integrated and seamless, rather than like an afterthought bolted onto your platform. Comprehensive Creator Analytics and Monitoring Beyond basic profile data, Scrape Creators enables sophisticated creator analytics that would be impossible to achieve manually or through official APIs with restrictive rate limits. Ongoing Performance Tracking Track creator statistics over time by scraping their posts daily or weekly. This enables powerful analytics: Growth Tracking: Monitor follower counts, engagement rates, and content performance trends Content Analysis: Understand what types of content perform best for different creators Engagement Patterns: Identify optimal posting times and content formats Competitive Intelligence: Benchmark creator performance against industry peers This ongoing monitoring capability transforms static social profiles into dynamic, data-rich creator intelligence that informs better business decisions. Link-in-Bio Intelligence Modern creators use link-in-bio tools to manage their online presence and monetize their audience. Scrape Creators extracts emails and links from popular platforms including: Linktree: The most popular link-in-bio platform used by millions of creators Komi: Growing platform focused on creator monetization Pillar: All-in-one creator commerce platform Lnk.bio: Simple, elegant link management for creators This capability provides unprecedented insight into creator monetization strategies, partnership opportunities, and contact information that's often hidden behind these aggregation platforms. Amazon Creator Economy Integration The recent addition of Amazon Creator Shop scraping represents a major expansion into e-commerce intelligence. This feature enables: Product Recommendation Analysis: Understand what products creators are promoting Affiliate Strategy Research: Analyze how successful creators structure their Amazon partnerships Market Intelligence: Identify trending products across creator shops Competitive Research: Monitor what products competing brands' creator partners promote This Amazon integration bridges the gap between social media influence and actual commerce, providing complete visibility into creator monetization strategies. Unmatched Platform Coverage While many scraping services focus on the "big three" platforms (Instagram, Twitter, TikTok), Scrape Creators provides coverage across virtually every social platform that matters: Established Platforms Instagram: Posts, stories, reels, and profile data Twitter/X: Tweets, profiles, and engagement metrics TikTok: Videos, user profiles, and trending content YouTube: Channel data, video statistics, and comment analysis Facebook: Public posts, page data, and engagement metrics Emerging and Niche Platforms Threads: Meta's Twitter competitor gaining rapid adoption Bluesky: The decentralized social network attracting Twitter refugees Pinterest: Visual discovery platform crucial for certain verticals LinkedIn: Professional networking essential for B2B creator strategies This comprehensive coverage means you can build applications that work with creators regardless of where their audience is concentrated, without needing separate integrations for each platform. Reliability Through Authentic Data Sources The technical approach behind Scrape Creators sets it apart from competitors who rely on unofficial scraping methods that frequently break. API-First Methodology Rather than scraping HTML that changes frequently, Scrape Creators targets the actual APIs that social media platforms use to power their own applications. This approach provides: Higher Reliability: Official APIs change less frequently than HTML structures Better Data Quality: Access to structured data rather than parsed HTML Improved Performance: Direct API access is faster than browser automation Enhanced Accuracy: Less risk of parsing errors or missing data Public Data Focus All scraping focuses exclusively on publicly available data, ensuring both legal compliance and ethical data collection practices. This approach provides: Transparent Operations: Clear boundaries about what data is accessible Reduced Legal Risk: Focus on publicly available information Sustainable Practices: Respect for platform terms and user privacy Reliable Access: Public data is less likely to be restricted or blocked Real-World Applications Creator Onboarding Platforms Instantly populate creator profiles with comprehensive social media data, including follower counts, engagement rates, and content samples. This eliminates manual data entry and provides immediate value to creators joining your platform. Influencer Marketing Agencies Monitor client performance across all platforms, track campaign results, and identify new partnership opportunities through comprehensive creator intelligence and Amazon shop analysis. Social Media Analytics Tools Build sophisticated analytics dashboards that track creator performance, industry trends, and competitive intelligence across dozens of platforms from a single API integration. E-commerce and Affiliate Platforms Understand creator monetization strategies, identify successful product partnerships, and optimize affiliate programs based on real performance data across social platforms and Amazon creator shops. Getting Started with Scrape Creators The API is designed for immediate productivity: Sign Up: Create an account and get your API key instantly Test Endpoints: Use the interactive documentation to explore available data Integrate: Add social data to your application with simple HTTP requests Scale: Pay only for what you use with transparent, usage-based pricing Special Offer for New Users First-time customers can use code TWITTER to get 25% off their initial usage, making it even easier to explore the full capabilities of comprehensive social media intelligence. The Future of Social Media Intelligence As the creator economy continues to grow and diversify across platforms, having reliable access to social media data becomes increasingly valuable. Scrape Creators provides the foundation for building applications that can adapt to new platforms, changing creator behaviors, and evolving social media landscapes. Whether you're building the next great creator tool, conducting academic research, or optimizing influencer marketing campaigns, Scrape Creators offers the speed, reliability, and comprehensive coverage needed to succeed in the data-driven creator economy. The combination of easy implementation, fast responses, comprehensive platform coverage, and reliable data extraction makes Scrape Creators the obvious choice for businesses serious about social media intelligence.

How to Scrape Google Search Results: A Simple Implementation Guide

How to Bypass Google’s New Anti-Scraping Restrictions (2025 Update)

Google has recently tightened its grip on search results, making life harder for SEOs, scrapers, and tool builders. If you’ve noticed strange redirects or missing parameters when scraping Google, you’re not alone. In this post, I’ll show you what changed, why it matters, and how you can still scrape Google search results reliably. Google’s Lockdown on Search Results Over the last few months, Google rolled out a couple of major changes: JavaScript requirement for search results If you try visiting Google search pages without JavaScript, you might see something like this instead of real results: This forces bots into a dead end unless they run a full browser. The removal of the num parameter For years, SEOs relied on &num=100 to grab 100 results per query. That parameter is now gone. Tools like Ahrefs and Semrush even had public issues when this broke. Search Engine Land covered the update here. Translation: Google is making it harder to scrape. Much harder. The Workaround: Using the AdsBot User-Agent First, shoutout to Jacob Padilla for figuring this out and telling me about it. The good news? There’s still a way around the JavaScript wall. When you send requests to Google with this user agent, the normal HTML SERP is returned, no redirect required: "User-Agent": "AdsBot-Google (+http://www.google.com/adsbot.html)" This tricks Google into thinking you’re their own AdsBot crawler, which is allowed to fetch results directly. Parsing the Results Once you bypass the redirect, you can parse Google’s search results like before. Here’s an example of how I extract titles, links, and snippets from the returned HTML. This works without needing Puppeteer or a headless browser. Faster, cheaper, and less resource-intensive. Why This Matters for SEOs and Scrapers SEO tools need reliable access to SERPs for keyword research and rank tracking. Scraping projects depend on bulk data collection. Developers want efficient ways to analyze search results without spinning up costly browser clusters. Bypassing these blocks keeps your workflows running smoothly. Final Thoughts Google keeps making scraping harder, and they’ll keep experimenting with new restrictions. But with the right techniques, you can stay one step ahead. If you’re looking for easy social media scraping APIs (Instagram, TikTok, YouTube, Reddit, Twitter/X, and more), check out Scrape Creators. We handle the messy parts of scraping so you don’t have to.

Amazon Creator Shop Scraping by Scrape Creators

NEW: Amazon Creator Shop Scraping - Extract Influencer Product Data

We're thrilled to announce a powerful new addition to the Scrape Creators API: Amazon Creator Shop scraping. This feature opens up entirely new possibilities for analyzing the rapidly growing Amazon creator economy, tracking influencer product recommendations, and understanding affiliate marketing strategies at scale. What Are Amazon Creator Shops? Amazon Creator Shops are personalized storefronts where influencers, content creators, and brand ambassadors curate and recommend products to their audiences. These shops have become a cornerstone of Amazon's creator economy, allowing influencers to monetize their recommendations while providing audiences with trusted product suggestions. Each creator shop typically features handpicked products across various categories, complete with creator commentary, pricing information, and direct purchase links. For businesses and researchers, these shops represent valuable insights into creator marketing strategies and consumer preferences. Introducing Amazon Shop Scraping The new /v1/amazon/shop endpoint enables you to programmatically extract comprehensive data from any Amazon Creator Shop page. This includes product listings, creator recommendations, pricing information, and metadata about the shop itself. Whether you're analyzing competitor strategies, researching product trends, or monitoring influencer partnerships, this API provides the data foundation for sophisticated creator economy analysis. Key Data Points Available The Amazon shop scraping endpoint captures extensive information about creator storefronts: Product Information: Complete product details including titles, descriptions, images, and ASIN identifiers for cross-referencing with Amazon's main catalog. Pricing Data: Current prices, discount information, and deal status to understand pricing strategies and promotional patterns. Creator Context: Shop descriptions, creator branding elements, and organizational structure showing how influencers present their recommendations. Category Organization: How creators organize their product recommendations, revealing insights into their audience targeting and content strategy. Real-World Applications Competitive Intelligence Track what products your competitors' partner creators are recommending. Understanding which influencers promote competing products helps identify potential partnership opportunities and market positioning strategies. Influencer Vetting Before partnering with creators, analyze their existing Amazon shops to understand their recommendation patterns, audience alignment, and promotional strategies. This data helps ensure brand-creator compatibility. Market Research Identify trending products across multiple creator shops. When multiple influencers start recommending similar products, it often signals emerging market opportunities or consumer behavior shifts. Affiliate Program Optimization For brands with Amazon affiliate programs, monitor how different creators present and organize your products. This intelligence helps optimize creator relationships and identify top-performing partnership strategies. Conclusion Whether you're a marketing agency tracking competitor strategies, a brand researching potential creator partnerships, or a researcher analyzing the creator economy, this new capability provides unprecedented access to Amazon's influential creator marketplace data.

The JavaScript Utility That Should Be Built Into Node.js

The JavaScript Utility That Should Be Built Into Node.js: Recursive Object Key Search

When working with deeply nested JavaScript objects, especially when scraping complex APIs or parsing intricate data structures, there's one utility function that has become absolutely indispensable. It's so useful that it really should be built into JavaScript itself. The Problem: Deep Object Navigation Nightmare Anyone who has worked with modern web APIs knows the pain of navigating deeply nested JSON structures. Take Twitter's API responses, for example. Finding a simple piece of data might require traversing through multiple levels of objects, arrays, and nested properties. When you're scraping or analyzing data, you often know what key you're looking for, but finding its exact path in a complex object can be incredibly time-consuming. You end up spending more time navigating the data structure than actually using the data. The Solution: Recursive Key Search Here's the utility function that has saved countless hours of debugging and manual object exploration: This simple function recursively traverses an object structure, searching for a specific key and returning its value regardless of how deeply nested it is. How It Works The function operates on a straightforward recursive algorithm: Direct Check: First, it checks if the target key exists directly on the current object level Recursive Traversal: If not found, it iterates through all properties of the current object Type Validation: For each property that is itself an object (and not null), it recursively calls itself Result Handling: Returns the first matching value found, or undefined if no match exists Error Management: Includes comprehensive error handling with debugging information Real-World Applications Web Scraping API Response Parsing Configuration Management Why This Should Be Native JavaScript's built-in object methods are surprisingly limited when it comes to deep traversal. While we have Object.keys(), Object.values(), and Object.entries(), there's no native way to search nested structures efficiently. This functionality is so commonly needed that developers frequently reinvent this wheel, leading to: Code Duplication: Every project ends up with its own version Performance Variations: Different implementations have varying efficiency Bug Potential: Hand-rolled solutions often miss edge cases Learning Curve: New developers need to understand multiple implementations

Logo.dev: The Simple API That Solves a Universal Developer Problem

Logo.dev: The Simple API That Solves a Universal Developer Problem

Sometimes the most valuable APIs are the ones that solve seemingly trivial problems. Logo.dev is a perfect example. It's an API whose sole purpose is fetching company logos, yet it addresses a pain point that virtually every developer building business applications encounters. The Problem: Logo Hell If you've ever built a CRM, directory, portfolio site, or any application displaying company information, you've experienced logo hell. The process typically goes like this: Manual hunting: Search Google Images for each company logo Quality inconsistency: Find logos in different formats, resolutions, and styles Legal concerns: Wonder about usage rights and trademark issues Maintenance nightmare: Companies rebrand, logos change, links break Performance problems: Host images yourself or rely on unstable external URLs What should be a simple task—displaying a company's logo—becomes a time-consuming, error-prone process that distracts from building actual features. The Clearbit Legacy For years, Clearbit's logo API was the go-to solution for this problem. Developers could simply call https://logo.clearbit.com/company.com and get a clean, high-quality logo back. It was elegant, reliable, and free for basic usage. Then Clearbit was acquired by HubSpot, and like many useful developer tools post-acquisition, the logo API was quietly discontinued. Thousands of applications suddenly had broken image links, and developers were back to logo hell. Enter Logo.dev: Filling the Gap Recognizing this market need, Alex Baldwin created Logo.dev—a modern take on the company logo API concept. The service promises to solve the original problem while addressing some of Clearbit's limitations: Key Features Global CDN delivery for fast loading worldwide Always up-to-date logos through automated monitoring Multiple format support (PNG, SVG, WebP) Consistent quality with standardized dimensions Simple integration requiring just a company domain The Value Proposition Logo.dev's tagline says it all: "Company logos, completely solved." By focusing exclusively on this one problem, they can: Maintain higher quality standards Provide better reliability Offer specialized features for logo usage Build deep expertise in brand asset management Why This Matters More Than You Think The existence and success of logo-focused APIs reveal something important about modern software development: The Micro-Service Economy Developers increasingly prefer specialized services over monolithic solutions. Rather than building everything in-house, teams assemble applications from focused, reliable components. Time-to-Market Pressure In competitive markets, spending weeks on logo management isn't viable. A $10/month API that solves the problem instantly provides enormous ROI. Quality Expectations Users expect professional-looking applications. Inconsistent, low-quality, or missing logos immediately signal an amateur product. Legal Risk Management Using official, properly sourced logos reduces trademark infringement risks compared to random Google Images downloads. Conclusion Logo.dev represents the power of solving simple problems exceptionally well. While fetching company logos might seem trivial, the cumulative time savings, improved user experience, and reduced maintenance burden provide genuine value to developers worldwide. Whether you're building a CRM, directory site, or any application that displays company information, consider how specialized APIs like Logo.dev can eliminate common pain points and let you focus on your core product features. Sometimes the best solution is the simplest one.

How I Built a Twitter Thread Scraper in 5 Simple Steps

How I Built a Twitter Thread Scraper in 5 Simple Steps

Building tools to extract and analyze Twitter threads has become increasingly valuable for researchers, content creators, and marketers. With Twitter's official API becoming more restrictive and expensive, alternative approaches have emerged. Here's a step-by-step guide to building your own Twitter thread scraper using readily available tools. Why Twitter Thread Scraping Matters Twitter threads contain some of the platform's most valuable content—detailed explanations, tutorials, storytelling, and analysis that often gets buried in the platform's fast-moving timeline. Having the ability to extract, preserve, and analyze these threads opens up possibilities for: Content research and competitive analysis Academic research on social media discourse Building thread reader applications Creating content summaries and insights Preserving important discussions Step 1: Set Up Twitter Data Access with Old Bird v2 The foundation of any Twitter scraping operation is reliable data access. Old Bird v2 on RapidAPI provides an alternative to Twitter's official API with more flexible access patterns. Why Old Bird v2? No complex authentication requirements More generous rate limits than official Twitter API Designed specifically for data extraction use cases Handles Twitter's anti-bot measures automatically Visit the Old Bird v2 RapidAPI page to get started. You'll need to subscribe to a plan (they typically offer free tiers for testing) and obtain your API key. The service provides various endpoints, but for thread scraping, you'll primarily use their conversation/thread endpoint. Step 2: Understanding the Thread Extraction Endpoint The key to extracting Twitter threads lies in understanding how Twitter structures conversation data. When you view a thread on Twitter, you're actually looking at a conversation view that includes the original tweet and all its replies in chronological order. The endpoint you need: The threaded conversation endpoint Required parameter: Tweet ID (found in any Twitter URL) For example, in the URL https://twitter.com/user/status/1234567890, the tweet ID is 1234567890. How it works: Pass the tweet ID of any tweet in the thread (usually the first one) The API returns the complete conversation structure Filter and extract the tweets that belong to the original thread author Step 3: Parsing Twitter's Complex Response Structure This is where most developers get stuck. Twitter's API responses are notoriously complex, with deeply nested JSON structures that can be intimidating to navigate. The Challenge: Twitter's response includes not just the tweets you want, but also: Promoted tweets and ads Recommended follows Various metadata objects UI injection points Analytics data The Solution: Here's the key code pattern for extracting the actual tweets from the response: What this code does: Finds the TimelineAddEntries instruction in the response Extracts entries that contain actual tweet data Filters out non-tweet content (ads, suggestions, etc.) Returns only tweets from the original thread author Step 4: Creating an API Wrapper Service Rather than building the scraping logic directly into your application, it's better to create a separate API service. This approach provides: Separation of concerns: Keep scraping logic separate from UI Reusability: Use the same API for multiple applications Rate limiting: Implement proper request management Caching: Store frequently requested threads Step 5: Building the Frontend with AI Code Generation Modern AI coding assistants can dramatically speed up frontend development. Instead of writing boilerplate React code from scratch, you can describe what you want and get a working application. Example prompt for AI assistant: "I need a very simple app, written in Vite+React, where a user enters a Twitter thread URL, clicks a button to extract the thread, and sees all the tweets displayed in a clean, readable format. Include loading states and error handling." What you'll get: Complete Vite+React setup Form handling for URL input API integration with your backend Loading and error states Clean UI for displaying thread content Alternative Social Media Scraping The techniques described here extend beyond Twitter. Many social platforms have similar patterns for extracting threaded content: LinkedIn post comments and discussions Reddit comment threads Facebook post comments Instagram comment threads Services like Scrape Creators offer APIs for multiple social platforms. Try your first 100 requests for free.

Firecrawl's Social Media Scraping Restrictions

Firecrawl's Social Media Scraping Restrictions: Market Gap or Strategic Decision?

A curious discovery emerged while testing popular web scraping tools: Firecrawl, a well-funded scraping platform, actively blocks social media scraping across major platforms including Instagram, YouTube, and TikTok. This restriction reveals fascinating insights about the current state of the web scraping industry and potential market opportunities. The Discovery: "This Website Is No Longer Supported" When attempting to scrape social media URLs through Firecrawl's interface, users encounter a consistent error message: "This website is no longer supported, please reach out to help@firecrawl.com for more info on how to activate it on your account." Testing revealed this restriction applies universally across: Instagram profiles and posts YouTube channels and videos TikTok accounts and content Likely other major social platforms The phrasing "no longer supported" suggests these platforms were previously accessible, indicating this is a deliberate policy change rather than a technical limitation. Why Would Firecrawl Block Social Media? Several factors likely drive this decision: Legal Risk Management Social media platforms aggressively protect their data through: Sophisticated anti-bot measures Strict Terms of Service enforcement Active litigation against scrapers Rate limiting and IP blocking For a venture-backed company like Firecrawl, avoiding legal entanglements with major platforms makes business sense. Technical Complexity Modern social media sites present significant scraping challenges: Heavy JavaScript rendering requirements Dynamic content loading Constant API structure changes Advanced bot detection systems Maintaining reliable social media scraping requires specialized infrastructure and continuous updates. Partnership Considerations Firecrawl may be positioning itself as a "legitimate" scraping solution that respects platform boundaries, potentially opening doors for official API partnerships or enterprise deals. The Market Opportunity This restriction creates an interesting market dynamic. While Firecrawl focuses on general web content, there's clearly demand for social media data extraction, evidenced by: Persistent User Demand The fact that users consistently attempt to scrape social platforms through Firecrawl indicates strong market demand for this functionality. Specialized Tool Necessity Users seeking social media data must turn to: Custom-built scrapers Specialized social media APIs Underground scraping services Platform-specific tools Partnership Potential As noted in the original observation, this creates partnership opportunities for companies like Scrape Creators that specialize in social media data extraction. The Broader Industry Implications Firecrawl's approach highlights a growing divide in the scraping industry: The "Legitimate" Path Companies like Firecrawl are positioning themselves as compliant, enterprise-friendly solutions that work within legal boundaries and focus on publicly available web content. The Specialist Approach Other companies are doubling down on specialized, high-demand niches like social media scraping, accepting the associated risks and complexities. The Underground Market The restrictions from mainstream tools inevitably drive demand toward less regulated, potentially riskier scraping solutions. Technical Workarounds and Alternatives For developers needing social media data, several alternatives exist: Official APIs Instagram Basic Display API YouTube Data API TikTok for Developers Twitter API (now X API) Specialized Services Social media monitoring platforms Academic research APIs Industry-specific data providers Custom Solutions Browser automation tools (Puppeteer, Selenium) Reverse-engineered mobile APIs Direct HTTP request manipulation Strategic Considerations for Scraping Companies Firecrawl's decision reveals important strategic considerations for scraping businesses: Risk vs. Reward Analysis Companies must weigh the revenue potential of social media scraping against legal risks, technical complexity, and maintenance overhead. Market Positioning The choice between being a "safe" general-purpose tool versus a specialized, higher-risk solution significantly impacts business model and growth strategy. Compliance as Competitive Advantage Some companies may find that explicit compliance and platform respect actually opens more business opportunities than aggressive scraping capabilities. The Partnership Angle The suggestion of partnership opportunities is particularly intriguing. A collaboration between a compliant general scraping service and a social media specialist could offer: Complementary Services Firecrawl handles general web scraping Partners handle specialized social media extraction Combined offering provides comprehensive data solutions Risk Distribution Each company focuses on their area of expertise Legal and technical risks are distributed Market coverage is maximized Customer Convenience Single point of contact for diverse scraping needs Integrated billing and support Seamless data delivery across different source types Looking Forward Firecrawl's social media restrictions represent more than just a business decision. They reflect the maturing web scraping industry's evolution toward specialization and risk management. As platforms become increasingly protective of their data and legal frameworks around scraping continue to develop, we'll likely see more companies making similar strategic choices about which battles to fight. For entrepreneurs and businesses in the space, this creates both challenges and opportunities. The key is understanding where the market is heading and positioning accordingly.

how to scrape youtube videos

How to Scrape All Videos from Any YouTube Channel: A Step-by-Step Guide

Want to extract all videos from a YouTube channel for analysis, research, or competitive intelligence? While YouTube's official API has strict quotas and limitations, there's a more direct approach using the same endpoints that power YouTube's web interface. Here's how to scrape any channel's complete video library. Understanding YouTube's Data Structure YouTube's web interface loads video data through internal API calls that we can reverse-engineer. The key is understanding that YouTube embeds initial page data in a JavaScript object called ytInitialData, then uses continuation tokens for pagination. Let's walk through the process using Starter Story's channel as an example, though this method works for any YouTube channel. Step 1: Finding the Initial Data Start by navigating to any YouTube channel's videos page. Open your browser's developer tools (F12), go to the Network tab, and refresh the page. Look for the first request named "videos". This contains all the initial video data. In the response, search for "ytInitialData". This JavaScript object contains the structured data that powers the entire videos page, including video titles, IDs, thumbnails, and view counts. To verify you've found the right data, search for one of the visible video titles within this object. Step 2: Extracting and Parsing the Data The ytInitialData is embedded as a string within a script tag, so we need to extract and parse it into usable JSON. Using a library like Cheerio in Node.js, locate the script tag containing ytInitialData and extract the JSON portion: Step 3: Navigating YouTube's Nested Structure YouTube's JSON structure is notoriously complex, but there's a pattern: everything important is wrapped in "renderer" objects. For video listings, you need to find the "tabRenderer" where the title equals "Videos". Once you locate this tab renderer, the actual videos array is nested at content.richGridRenderer.contents. This array contains all the video data for the current page, with each video wrapped in a "videoRenderer" object containing metadata like videoId, title, view count, and publication date. Step 4: Handling Pagination The initial page only shows the first batch of videos. To get subsequent pages, YouTube uses continuation tokens. Clear your browser console, filter by "Fetch/XHR", and scroll down on the videos page to trigger loading more content. You'll see a request to an endpoint called "browse?prettyPrint=false". This is YouTube's pagination API. Click on this request and examine the response. You'll find the newly loaded videos in the same structure as before. Step 5: Understanding Continuation Tokens The magic happens through continuation tokens. In the original videos array, the last item isn't a video at all, it's a "continuationItemRenderer" containing a token. This token is what you pass to the browse endpoint to get the next page of videos. Right-click on the browse request and select "Copy as Fetch (Node.js)" to see the exact headers and payload structure YouTube expects. The continuation token goes in the POST body along with other required parameters. Step 6: Building the Complete Solution Here's the process flow for scraping all videos from a channel: Initial Request: Load the channel's videos page and extract ytInitialData Parse Videos: Extract video data from content.richGridRenderer.contents Get Token: Find the continuation token from the last item in the contents array Paginate: Use the token to request the next page via the browse endpoint Repeat: Continue until no more continuation tokens are available Technical Implementation Tips When implementing this approach, keep several factors in mind: Headers Matter: YouTube checks for specific headers including User-Agent, cookies, and referrer information. Copy the exact headers from your browser's network tab. Rate Limiting: Don't hammer YouTube's servers. Implement delays between requests to avoid triggering anti-bot measures. Error Handling: YouTube's responses can vary, and continuation tokens sometimes expire. Build robust error handling for edge cases. Data Validation: Always verify that the expected data structure exists before trying to parse it, as YouTube occasionally changes their internal formats. Parsing Video Metadata Each video renderer contains rich metadata: videoId: Unique identifier for building video URLs title: Video title with formatting preserved thumbnails: Multiple resolution options for video previews viewCountText: Human-readable view counts publishedTimeText: Relative publication dates lengthText: Video duration information This data enables comprehensive analysis of channel content, posting patterns, and performance metrics. Limitations and Considerations This reverse-engineering approach has important limitations: Unofficial Method: YouTube could change their internal API structure at any time, breaking your scraper Terms of Service: Ensure your usage complies with YouTube's terms and doesn't violate their policies Scale Constraints: Large-scale scraping may trigger anti-bot measures or IP blocking Maintenance Overhead: Internal APIs change more frequently than public ones Practical Applications This scraping technique enables various applications: Competitive Analysis: Monitor competitors' content strategies, posting frequencies, and performance trends Market Research: Analyze content patterns across industry channels to identify successful formats Content Planning: Study high-performing videos in your niche to inform your own content strategy Academic Research: Gather data for studies on digital media, content creation, or platform dynamics Conclusion Scraping YouTube channel data requires understanding both the technical implementation and the broader context of web scraping ethics and sustainability. While the reverse-engineering approach provides deep insight into how YouTube structures their data, production applications often benefit from purpose-built APIs that handle the complexity and maintenance overhead.

new feature Facebook Comments API

NEW: Facebook Comments API - Extract Comments from Posts & Reels

We're excited to announce a major expansion to the Scrape Creators API: you can now extract comments from Facebook posts and reels! This powerful new endpoint opens up entirely new possibilities for social media research, sentiment analysis, and engagement tracking on the world's largest social platform. Introducing Facebook Comments Extraction The new Facebook comments endpoint allows you to programmatically access comment data from any public Facebook post or reel, providing deep insights into audience engagement and community sentiment that was previously difficult to obtain at scale. API Endpoint GET /v1/facebook/post/comments This simple endpoint takes a Facebook post or reel URL and returns comprehensive comment data, making it easy to integrate Facebook comment analysis into your existing workflows. What Data You Get The Facebook comments API provides rich comment data including: Comment Content: Full text of user comments and replies User Information: Commenter names and profile links (where publicly available) Engagement Metrics: Like counts, reply counts, and reaction data for individual comments Timestamps: When comments were posted for temporal analysis Thread Structure: Parent-child relationships for comment replies Reaction Types: Specific Facebook reaction types (like, love, angry, etc.) This comprehensive data set enables sophisticated analysis of how audiences engage with content beyond simple like and share metrics. Why Facebook Comments Matter Understanding True Engagement While likes and shares provide surface-level engagement metrics, comments reveal the depth of audience connection with content. Comments show: Genuine Interest: People who comment are typically more invested than those who simply react Sentiment Analysis: Comments provide rich text data for understanding audience opinions Community Building: Comment threads reveal how content sparks conversations and builds communities Content Performance: Comment quality and quantity often correlate with content virality Business Intelligence Applications For businesses and marketers, Facebook comment data unlocks powerful insights: Brand Sentiment Monitoring: Track what people actually say about your brand, not just whether they like posts Competitor Analysis: Understand how audiences respond to competitor content and messaging Content Optimization: Identify which types of posts generate meaningful conversations Crisis Management: Monitor comment sentiment for early warning signs of reputation issues Real-World Use Cases Social Media Marketing Agencies Marketing agencies can now provide clients with deeper engagement analysis: Campaign Performance: Move beyond vanity metrics to understand actual audience sentiment Content Strategy: Identify topics and formats that generate meaningful discussions Influencer Vetting: Analyze comment quality on influencer posts to assess audience authenticity Competitive Intelligence: Monitor competitor engagement patterns and audience feedback Market Research Researchers gain access to authentic consumer opinions: Product Feedback: Analyze comments on product launches and announcements Brand Perception Studies: Understand how audiences discuss brands in natural conversation Trend Analysis: Identify emerging topics and sentiment shifts in real-time Consumer Behavior: Study how different demographics engage with various content types Customer Service and Support Customer service teams can monitor and respond more effectively: Issue Detection: Identify customer complaints and concerns mentioned in comments Response Optimization: Analyze which types of responses generate positive community reactions FAQ Development: Use common comment questions to improve support documentation Community Management: Understand conversation patterns to guide engagement strategies Technical Implementation Getting Started The Facebook comments API follows the same simple pattern as other ScrapeCreators endpoints: Processing Comment Data The API returns structured comment data that's easy to process: Batch Processing For large-scale analysis, implement batch processing workflows: Advanced Analysis Opportunities Sentiment Analysis Combine Facebook comment data with natural language processing: Engagement Pattern Analysis Identify what drives meaningful conversations: Temporal Analysis Track how comment sentiment and volume change over time: Privacy and Ethical Considerations Public Data Only The Facebook comments API only accesses publicly available comment data. Private posts, restricted content, and user information requiring authentication are not accessible through this endpoint. Respectful Usage When using Facebook comment data: Respect User Privacy: Don't attempt to correlate comments with private user information Follow Platform Guidelines: Ensure your usage complies with Facebook's terms of service Data Protection: Handle user-generated content responsibly and in accordance with privacy regulations Ethical Analysis: Use comment data for legitimate business purposes, not harassment or stalking Integration with Existing Workflows Social Media Dashboards Add Facebook comment analysis to your existing social media monitoring: CRM Integration Connect comment insights with customer relationship management: Performance and Scalability Rate Limiting The Facebook comments endpoint includes intelligent rate limiting to ensure reliable access: Reasonable Limits: Designed for real-world usage patterns without unnecessary restrictions Transparent Pricing: Pay-per-use model scales with your actual needs Batch Optimization: Efficient processing for large-scale comment extraction Caching Strategy Implement caching to optimize performance and costs: Future Enhancements We're continuously improving the Facebook comments API with planned features: Coming Soon: Enhanced Filtering: Filter comments by sentiment, engagement level, or keywords Historical Analysis: Track comment sentiment changes over time for the same post User Analytics: Aggregate insights about frequent commenters and community leaders Multi-language Support: Improved handling of comments in different languages Real-time Monitoring: Webhook notifications for new comments on tracked posts Getting Started Today Immediate Access The Facebook comments API is available now for all ScrapeCreators users. No special setup required – just start making requests to the new endpoint. Testing the Feature To test Facebook comment extraction: Find a public Facebook post with active comments Use the /v1/facebook/post/comments endpoint with the post URL Analyze the returned comment data structure Integrate comment analysis into your existing workflows Documentation Complete API documentation with request/response examples is available at docs.scrapecreators.com/v1/facebook/post/comments.

new feature: TikTok Shop Product Detection

NEW: TikTok Shop Product Detection in Scrape Creators API

We're excited to announce a game-changing update to the Scrape Creators API that will revolutionize how you analyze creator commerce on TikTok. You can now identify the exact products that creators are promoting in their videos, complete with direct links to TikTok Shop listings. What's New: Product Promotion Detection The latest update adds a powerful new data field to TikTok video responses: shop_product_url. This field appears when creators include product promotions in their videos, providing direct access to the TikTok Shop listing they're promoting. How It Works When you scrape a TikTok video through the ScrapeCreators API, the response now includes product promotion data: The shop_product_url field provides a direct link to the TikTok Shop product page, allowing you to immediately understand what the creator is promoting and analyze the commercial intent behind their content. Why This Matters for Your Business Affiliate Marketing Intelligence For affiliate marketers and agencies, this update provides unprecedented visibility into creator commerce strategies: Competitor Analysis: See exactly what products your competitors' sponsored creators are promoting Product Research: Identify trending products across different creator niches Commission Tracking: Understand which creators are eligible for commissions on specific products Campaign Optimization: Analyze successful product promotions to inform your own campaigns E-commerce Research Retailers and brands can now: Monitor Brand Mentions: Track when and how your products appear in creator content Identify Opportunities: Find creators already promoting similar products in your category Market Intelligence: Understand pricing, positioning, and promotion strategies for competing products Trend Analysis: Spot emerging product trends before they go mainstream Creator Economy Analysis Researchers and analysts gain access to: Monetization Patterns: Understand how creators incorporate product promotions into their content Commerce Trends: Track the evolution of social commerce on TikTok Creator Performance: Analyze which types of product promotions generate the most engagement Technical Implementation API Response Structure The product URL appears as a new field in your standard TikTok video scraping response. Here's what to expect: When Product Promotion is Present: When No Product Promotion: The field will be absent or null, keeping response sizes minimal. Integration Examples Python Implementation: JavaScript Implementation: Real-World Use Cases Case Study: Beauty Brand Monitoring A cosmetics company can now: Identify Influencers: Find creators promoting competing beauty products Analyze Pricing: Compare promoted product prices across different creators Track Trends: Monitor which beauty products are gaining traction through creator promotions Outreach Strategy: Identify successful creators for potential partnerships Case Study: Affiliate Network Management Affiliate networks can: Performance Tracking: Monitor which products their creators promote most frequently Commission Optimization: Understand the relationship between product type and creator engagement Fraud Detection: Verify that creators are promoting the products they claim Market Intelligence: Identify high-performing products for network expansion Enhanced Workflow Integration Automated Monitoring Workflows Set up automated systems to: Daily Scans: Monitor specific creators for new product promotions Competitor Alerts: Get notified when competitors' products appear in creator content Trend Tracking: Build databases of product promotion patterns over time ROI Analysis: Correlate product promotions with engagement metrics Getting Started Immediate Access This feature is available immediately for all Scrape Creators API users. No changes to your existing integration are required – the new field simply appears when relevant. Testing the Feature To test the new functionality: Find a TikTok video with visible product promotion (look for shopping bag icons or "Shop" buttons) Use the standard video scraping endpoint Check the response for the shop_product_url field Use the product URL to scrape detailed product information if needed API Documentation Full documentation for the updated response structure is available in the ScrapeCreators API docs. The shop_product_url field follows TikTok's standard product URL format: https://www.tiktok.com/shop/pdp/[product_id]. Future Enhancements This product detection feature is just the beginning. We're working on additional e-commerce intelligence features: Coming Soon: Product Metadata: Price, ratings, and seller information directly in video responses Historical Tracking: Monitor product promotion changes over time Bulk Analysis: Batch processing for large-scale creator commerce analysis Enhanced Filtering: Search for videos promoting specific product categories or price ranges Impact on Creator Economy Analysis This update represents a significant step forward in understanding the creator economy's commercial aspects. For the first time, researchers and businesses can systematically analyze the relationship between content creation and product promotion at scale. The ability to connect specific videos to specific products enables entirely new categories of analysis: Content Performance vs. Product Type: Which products generate the most engagement when promoted? Creator Specialization: Do successful creators focus on specific product categories? Seasonal Patterns: How do product promotions change throughout the year? Cross-Platform Analysis: How do TikTok product promotions compare to other platforms?

3 ways to use proxies

3 Ways to Use Proxies in Node.js: Impit, Axios, and Fetch

When building Node.js applications that need to route traffic through proxies, you have several excellent options. Here's a comprehensive guide to the three most effective methods for implementing proxy support in your Node.js applications. Why Use Proxies in Node.js? Before diving into implementation, it's worth understanding when and why you'd want to route your Node.js requests through proxies: Web Scraping: Avoid IP bans and rate limiting by rotating through different proxy servers Geographic Restrictions: Access region-locked content or APIs from different locations Corporate Networks: Route traffic through company proxies when required by network policies Privacy and Anonymity: Hide your application's real IP address from target servers Load Distribution: Spread requests across multiple exit points to avoid overwhelming single IPs Method 1: Impit - The Modern Browser-Like Solution Impit represents the evolution of browser automation and HTTP client libraries, offering a more sophisticated approach to proxy management with browser-like capabilities. Basic Impit Implementation Impit Advantages Browser Emulation: Impit provides browser-like behavior, making it excellent for scraping JavaScript-heavy sites Built-in Proxy Support: Native proxy configuration without additional dependencies TLS Flexibility: The ignoreTlsErrors option helps with proxy configurations that have certificate issues Multiple Browser Engines: Support for both Chrome and Firefox behavior patterns When to Use Impit Impit is ideal when you need browser-like capabilities combined with proxy support: Scraping single-page applications that rely heavily on JavaScript Accessing sites with complex authentication flows When you need to maintain sessions across multiple requests Sites that detect and block non-browser user agents Method 2: Axios with HTTPS Proxy Agent - The Reliable Classic Axios remains one of the most popular HTTP clients for Node.js, and combining it with https-proxy-agent provides robust proxy support with familiar syntax. Implementation Advanced Axios Proxy Configuration For more complex scenarios, you can configure different agents for HTTP and HTTPS: Axios Advantages Mature Ecosystem: Extensive documentation, middleware, and community support Flexible Configuration: Detailed control over request/response interceptors, timeouts, and headers Error Handling: Built-in error handling and retry mechanisms Familiar API: Most developers already know Axios syntax When to Use Axios Axios with proxy agents works best for: API integrations that don't require browser-like behavior High-performance applications where you need fine-tuned control Applications already using Axios throughout the codebase When you need advanced features like request/response interceptors Method 3: Native Fetch with Proxy Agent - The Lightweight Approach Node.js's native fetch (available from Node 18+) or the node-fetch library provides a lightweight alternative that closely mirrors the browser's Fetch API. Using Node-Fetch (For Older Node Versions) Using Native Fetch (Node 18+) Fetch Advantages Lightweight: Minimal overhead compared to full-featured HTTP clients Standard API: Matches browser fetch API for code portability Promise-Based: Clean async/await syntax No Dependencies: Native fetch eliminates external dependencies (Node 18+) When to Use Fetch Fetch with proxy agents is perfect for: Simple HTTP requests that don't need advanced features Applications prioritizing minimal dependencies Code that needs to work in both browser and Node.js environments Microservices where bundle size matters Choosing the Right Method Use Impit when: You need browser-like behavior Scraping JavaScript-heavy sites Session management is important You want built-in proxy configuration Use Axios when: You need advanced HTTP client features Your application already uses Axios You require request/response interceptors Fine-grained control is important Use Fetch when: You want minimal dependencies Making simple HTTP requests Code portability between browser/Node.js is important You're using Node.js 18+ and want to avoid external dependencies

scraping infrastructure of scrape creators

Building a Production-Ready Scraping Infrastructure: Architecture Behind Scrape Creators

Building a reliable, scalable scraping infrastructure is more art than science. After running a production scraping service that handles thousands of requests daily, here's everything I've learned about architecting a system that actually works in the real world, not just in development. The Foundation: Keep It Simple, Keep It Stable The core principle behind any successful scraping operation is simplicity. Complex architectures might look impressive in system design interviews, but they become nightmares when you're debugging scraping issues at 2 AM. Core Stack Architecture Node.js Everywhere: The entire system runs on Node.js, providing consistency across all components and eliminating context switching between different runtime environments. Single Express Server: Rather than microservices or distributed architectures, everything runs through one Express server that manages all scraping endpoints. This approach reduces complexity while maintaining enough modularity to scale individual components. Redis for State Management: Redis handles two critical functions: managing user credits and reducing database load through intelligent caching. This setup prevents the database from becoming a bottleneck during traffic spikes. The beauty of this architecture lies in its predictability. When something breaks (and it will), you have fewer moving parts to diagnose and fewer potential failure points to investigate. The Real Challenge: Proxy Infrastructure Here's what no tutorial tells you about scraping: the code is the easy part. The hard part is maintaining reliable proxy infrastructure that keeps your scrapers running consistently. The Three-Tier Proxy Strategy Static Residential Proxies: The gold standard for most scraping operations. These proxies appear as genuine residential IP addresses and rarely get blocked by target sites. They're expensive but provide the highest success rates. Rotating Residential Proxies: Essential for high-volume operations where you need fresh IP addresses for each request. These automatically rotate through large pools of residential IPs, making detection much harder. Datacenter Proxies: The backup plan. While more likely to be detected and blocked, datacenter proxies are fast and cheap. They're perfect for initial testing and as fallbacks when residential proxies fail. Proxy Provider Evolution The proxy landscape changes constantly, and provider reliability can shift overnight. Initially, Evomi provided adequate service, but as scaling requirements increased, reliability became more critical than cost savings. The migration to Decodo represented a classic scaling trade-off: higher costs in exchange for significantly better reliability. When you're running a production service, a few extra dollars per thousand requests is negligible compared to the cost of downtime and failed scraping attempts. Technical Implementation: Speed and Efficiency Raw HTTP Requests Over Browser Automation The temptation to use browser automation tools like Puppeteer for everything is strong, especially when you're starting out. Browsers feel familiar and handle JavaScript rendering automatically. However, raw HTTP requests are typically 10-100x faster and consume far fewer resources. Most scraping targets don't require full browser rendering – you just need to understand their API endpoints and request patterns. When to Use HTTP Requests: API endpoints that return JSON data Simple HTML pages without complex JavaScript High-volume operations where speed matters Cost-sensitive applications When Browser Automation Is Necessary: JavaScript-heavy applications that render content dynamically Sites with complex anti-bot measures Endpoints that require user interaction simulation For the current setup, Puppeteer is reserved exclusively for specific TikTok Shop endpoints that require browser rendering. Everything else uses direct HTTP requests. Hosting and Scaling Strategy Current Setup: Render with Autoscaling Render provides a middle ground between traditional VPS hosting and full cloud infrastructure. The autoscaling capabilities handle most traffic variations automatically, spinning up new instances when demand increases. Render Advantages: Automatic deployments from Git Built-in scaling without infrastructure management Reasonable pricing for moderate traffic Simplified monitoring and logging Render Limitations: Cold start delays can cause temporary 502 errors during traffic spikes Less control over scaling parameters compared to AWS Higher per-request costs at scale Next Evolution: AWS Lambda The migration to AWS Lambda represents the next logical step for true instant scaling. Lambda's pay-per-request model aligns perfectly with scraping workloads, where traffic can be highly variable. Lambda Benefits for Scraping: Zero cold start impact on users (Lambda handles instance management) Perfect cost alignment (pay only for actual usage) Infinite scaling capacity Integrated monitoring and error tracking The main challenge will be adapting the current architecture to Lambda's stateless model, particularly around proxy session management and Redis connections. Why This Architecture Works Node.js Event Loop Advantage Scraping is inherently I/O intensive – you're constantly waiting for network requests to complete. Node.js's event loop model excels at this workload, efficiently managing thousands of concurrent requests without the overhead of thread management. Traditional multi-threaded approaches would require significantly more memory and CPU resources to handle the same throughput. Redis as the Performance Multiplier Database queries can quickly become bottlenecks in high-traffic scraping applications. Redis serves as both a cache and a fast data store for frequently accessed information: Credit Management: User credit balances are stored in Redis, eliminating database queries for every scraping request. Rate Limiting: Request throttling data stays in Redis for instant access during request validation. Caching: Frequently requested scraping results can be cached temporarily, reducing load on target sites and improving response times. Proxy Reliability as Infrastructure Treating proxy management as core infrastructure rather than an afterthought prevents the most common scraping failures. When your proxies work consistently, everything else becomes much more manageable. Operational Lessons Learned Solo Maintainability Complex architectures require teams to maintain effectively. As a solo operation, keeping the system simple enough for one person to understand and debug is crucial. This means: Clear, documented code patterns Minimal external dependencies Straightforward deployment processes Comprehensive error logging and monitoring Scaling Decisions Each scaling decision involves trade-offs between cost, complexity, and reliability. The key is making these decisions based on actual constraints rather than theoretical performance concerns. Moving from Evomi to Decodo wasn't about finding cheaper proxies – it was about eliminating a reliability bottleneck that was affecting user experience. Monitoring and Alerting Production scraping systems fail in interesting ways. Effective monitoring goes beyond basic uptime checks: Success Rate Tracking: Monitor scraping success rates by endpoint and proxy provider Response Time Analysis: Track performance degradation before it becomes user-visible Error Pattern Recognition: Identify when target sites change their anti-scraping measures Resource Utilization: Monitor proxy usage and credit consumption patterns Future Architecture Considerations Microservices vs. Monolith While the current monolithic approach works well, certain components might benefit from separation as scale increases: Proxy Management Service: Dedicated service for proxy health monitoring and rotation Credit Management Service: Separate billing and usage tracking from core scraping logic Queue Management: Background job processing for long-running scraping tasks Database Strategy The current setup relies heavily on Redis with a traditional database for persistent storage. As data volume grows, consider: Time-series Databases: For scraping analytics and performance metrics Document Stores: For flexible storage of scraped content with varying structures Data Warehousing: For historical analysis and business intelligence Implementation Best Practices Error Handling and Retries Scraping operations fail regularly, and your architecture must account for this reality: Exponential Backoff: Gradual retry delays prevent overwhelming target sites Circuit Breakers: Stop attempting requests when failure rates exceed thresholds Fallback Strategies: Multiple proxy providers and endpoints for critical operations Security Considerations Production scraping services face unique security challenges: API Rate Limiting: Prevent abuse while maintaining legitimate access Proxy IP Protection: Avoid exposing proxy infrastructure to potential attackers Data Privacy: Handle scraped content responsibly and in compliance with regulations Cost Optimization Scraping costs can escalate quickly without careful management: Proxy Cost Monitoring: Track usage patterns and optimize proxy allocation Caching Strategies: Reduce redundant scraping through intelligent caching Request Optimization: Minimize unnecessary requests through better endpoint design

Guide to Ad Library APIs

The Ultimate Guide to Ad Library APIs: Facebook, Google, LinkedIn & Reddit

Every major advertising platform maintains a public ad library, yet most marketers barely scratch the surface of what's available through these treasure troves of competitive intelligence. These official repositories contain live and historical advertising data that can transform your marketing strategy if you know how to access and use them effectively. The Big Four: Platform-by-Platform Breakdown 1. Facebook Ad Library: The Goldmine of Social Advertising Facebook's Ad Library stands as the most comprehensive advertising database available to the public. Originally created for political ad transparency, it has evolved into an invaluable resource for competitive research across all industries. What You Can Access: Live and Historical Ads: Complete archive of active and past advertisements Campaign Duration: Start and end dates for most ad campaigns Creative Assets: Full ad creatives, copy, and visual elements Targeting Information: Demographic and geographic targeting data (when available) Performance Metrics: Impression ranges and spend estimates for many campaigns The depth of Facebook's ad data is staggering. You can literally track a competitor's entire advertising history, analyzing their messaging evolution, seasonal campaigns, and creative strategies over time. This level of insight was previously only available to agencies with massive budgets and insider connections. 2. Google Ads Transparency Center: Search Advertising Intelligence Google's approach to ad transparency focuses primarily on search advertising and verification advertiser information. While less comprehensive than Facebook's offering, it provides unique insights into search marketing strategies. Available Data: Search Ad Copy: Complete text of search advertisements (requires OCR processing for visual ads) Active Campaign Tracking: Real-time view of companies' current search advertising Creative Previews: Visual representations of how ads appear in search results Advertiser Verification: Information about who's behind the ads For businesses heavily invested in search marketing, Google's transparency center offers direct insight into competitors' keyword strategies, ad copy approaches, and messaging frameworks. 3. LinkedIn Ad Library: The Hidden Professional Marketing Gem LinkedIn's ad library remains one of the most underutilized resources in competitive intelligence, despite containing valuable B2B advertising data that's nearly impossible to find elsewhere. Key Features: Professional Ad Copy: Business-focused messaging and value propositions Creative Assets: Visual elements optimized for professional audiences Performance Data: Impression ranges where available B2B Campaign Insights: Industry-specific advertising approaches For B2B marketers, LinkedIn's ad library is particularly valuable because professional advertising strategies are often more difficult to reverse-engineer through casual platform browsing. 4. Reddit Ad Library: Niche but Powerful for Specific Verticals Reddit's ad library might offer the smallest dataset, but for certain industries – particularly DTC brands, SaaS companies, and political campaigns – it provides unique insights into community-based advertising approaches. What's Available: Creative Assets: Visual and text-based ad content Destination Links: Where ads direct users Community Context: Understanding how brands approach Reddit's unique culture Niche Targeting: Insights into subreddit-specific advertising strategies Reddit's advertising approach differs significantly from other platforms, making this data especially valuable for brands trying to crack the code of authentic community engagement. Why Ad Library APIs Matter for Modern Marketing Competitive Intelligence Revolution Traditional competitive analysis relied on manual observation, expensive tools, or insider knowledge. Ad libraries democratize this intelligence, providing comprehensive views of competitors' strategies, spending patterns, and messaging evolution. You can now answer questions that were previously impossible to research: What messaging is your competitor testing in different markets? How has their advertising strategy evolved over the past year? Which creative formats are they investing in most heavily? What seasonal campaigns do they run annually? Marketing Research and Trend Analysis Beyond individual competitor tracking, ad libraries provide macro-level insights into industry trends, successful creative formats, and messaging strategies that resonate with specific audiences. This data enables: Industry Benchmarking: Understanding typical campaign durations, creative approaches, and seasonal patterns Creative Inspiration: Analyzing successful ad formats and messaging frameworks Market Timing: Identifying when competitors increase advertising spend and why Transparency and Accountability The original purpose of ad libraries – providing transparency around political and issue-based advertising – remains crucial. These tools enable journalists, researchers, and civic organizations to track spending on political campaigns and advocacy efforts. Growth Hacking and Channel Discovery Ad libraries reveal new marketing channels and approaches that competitors are testing. This intelligence can help you identify emerging opportunities before they become saturated. Technical Implementation and Access API vs. Manual Access While most ad libraries provide web interfaces for manual searching, programmatic access through APIs enables large-scale analysis and automated competitive monitoring. API Advantages: Scale: Analyze thousands of ads across multiple competitors Automation: Set up ongoing monitoring and alerts Integration: Combine ad library data with your existing analytics stack Historical Analysis: Track changes and trends over time Data Processing Challenges Working with ad library data presents several technical challenges: Image Processing: Many ad creatives are visual, requiring OCR (Optical Character Recognition) to extract text for analysis. Data Normalization: Different platforms structure their data differently, requiring standardization for cross-platform analysis. Rate Limiting: APIs typically impose limits on request frequency, requiring careful planning for large-scale data collection. Data Quality: Not all ads include complete information, requiring strategies to handle missing data points. Strategic Applications Campaign Planning and Optimization Use ad library data to inform your own campaign strategies: Message Testing: Identify successful messaging frameworks in your industry Creative Development: Understand visual trends and successful ad formats Timing Strategy: Learn from competitors' seasonal and event-based campaigns Audience Targeting: Discover new demographic or geographic opportunities Budget Allocation Decisions Understanding competitors' advertising investment patterns helps inform your own budget decisions: Channel Prioritization: See where competitors invest most heavily Seasonal Planning: Understand industry-wide spending patterns Market Entry: Identify less competitive advertising opportunities Content and Creative Strategy Ad libraries provide endless inspiration for content teams: Copywriting Frameworks: Analyze successful ad copy structures Visual Trends: Understand effective creative approaches Value Proposition Testing: See how competitors position similar products A/B Test Ideas: Generate hypotheses based on competitor creative variations Future of Ad Library Intelligence The advertising transparency trend shows no signs of slowing. We can expect: Expanded Data Access: Platforms will likely provide more detailed performance metrics and targeting information. Cross-Platform Integration: Tools that aggregate data across multiple ad libraries will become more sophisticated. AI-Powered Analysis: Machine learning will automate insight generation from ad library data. Real-Time Monitoring: More sophisticated alert systems for competitor campaign changes. Implementation Best Practices Start with Strategic Questions Before diving into ad library data, define what you want to learn: Which competitors should you monitor most closely? What specific strategies or channels are you trying to understand? How will you use the insights to improve your own campaigns? Combine Multiple Data Sources The most valuable insights come from analyzing data across multiple ad libraries: Cross-Platform Strategies: How do competitors adapt their messaging for different platforms? Channel Investment Patterns: Where do competitors invest most heavily? Seasonal Variations: How do strategies change throughout the year? Focus on Actionable Insights Raw ad library data is overwhelming. Focus on insights you can act upon: Testable Hypotheses: What can you try in your own campaigns? Strategic Gaps: Where are competitors not advertising that you could? Message Opportunities: What value propositions are underexplored in your market?

public vs private data scraping on instagram

How to Scrape Instagram Data: The Complete 2025 Guide

Instagram remains one of the most valuable sources of social media data, but scraping it requires careful navigation of both technical challenges and legal considerations. The platform offers two distinct data territories: public information accessible without login, and private data that requires authentication. The Two Worlds of Instagram Scraping Instagram data exists in two distinct realms, and understanding the difference is crucial for anyone considering data extraction from the platform. Public Data (Safe Zone): Information visible without logging in Private Data (Risk Zone): Content requiring authentication to access The fundamental rule is simple: if you can see it in an incognito browser without logging in, it's generally safe to scrape. If you need to be logged in to view it, you're entering risky territory where Meta's enforcement becomes aggressive. What You Can Safely Scrape (Public Data) Opening Instagram in an incognito browser reveals exactly what's available for public scraping. While Instagram has become increasingly restrictive about public data access, several valuable data points remain accessible: Profile Information Public profiles offer a wealth of basic information including bio content, post counts, follower numbers (though not the actual follower lists), website links, and profile images. Notably, email addresses aren't directly exposed unless creators include them in their bio text. Post Data Individual posts provide comprehensive metrics including like counts, comment counts, view numbers for videos, full captions, and access to the actual media files (images and videos). This represents some of the most valuable public data available. Comment Analysis While viral posts may not expose every single comment due to Instagram's loading limitations, a substantial portion of comments remain accessible through public scraping. This provides valuable sentiment analysis and engagement data. Reel Transcripts Instagram automatically generates transcripts for many Reels, and these transcripts are often accessible through public endpoints, providing valuable content analysis opportunities. Story Highlights Unlike current stories (which require login access), story highlights remain publicly accessible and can provide insights into a creator's key content themes and messaging. Creative Workarounds for Limitations Instagram's restrictions on public search functionality have forced creative solutions. Since Instagram no longer exposes search results publicly, clever scrapers have developed workarounds: Google Site Search Method: Using Google's site search with the query site:instagram.com/p/ [keyword] can reveal relevant posts. Once you have post URLs from Google results, you can then scrape detailed statistics using standard post endpoints. This method effectively bypasses Instagram's search restrictions by leveraging Google's indexing of Instagram content. The Forbidden Zone: Private Data Behind Instagram's login wall lies significantly more valuable information, but accessing it comes with substantial risks: Contact Information: Email addresses and phone numbers from profile contact buttons Social Networks: Complete followers and following lists Native Search: Direct hashtag and keyword search within Instagram Engagement Metrics: Share counts and other private metrics Current Stories: Active story content (as opposed to archived highlights) While this data is undeniably valuable for marketing, research, and competitive analysis, Meta's enforcement against behind-the-login scraping is notoriously aggressive. The Risk-Reward Calculation Meta has made it clear that unauthorized access to private Instagram data violates their terms of service, and they actively pursue enforcement action. This includes: Account suspensions and bans IP address blocking Legal action against large-scale operations Technical countermeasures that make scraping increasingly difficult However, the data behind the login wall often represents the most valuable information for business intelligence, marketing research, and competitive analysis. Technical Implementation Approaches For those choosing the safer public scraping route, several technical approaches exist: Direct API Calls: Making HTTP requests to Instagram's public endpoints that power their web interface Browser Automation: Using tools like Selenium or Puppeteer to programmatically browse public pages Specialized Services: Third-party APIs designed specifically for Instagram data extraction The choice depends on scale requirements, technical expertise, and risk tolerance. Legal and Ethical Considerations Public data scraping generally falls under fair use provisions, especially when: Only publicly available information is accessed Data is used for research, journalism, or legitimate business purposes Scraping doesn't overload Instagram's servers The scraped data isn't redistributed commercially without permission However, behind-the-login scraping enters murkier legal territory and may violate both terms of service and potentially computer fraud laws, depending on jurisdiction and implementation. Scaling Considerations Public Instagram scraping can be scaled effectively with proper infrastructure: Rate Limiting: Respecting Instagram's server capacity to avoid detection Proxy Rotation: Distributing requests across multiple IP addresses Data Storage: Efficiently storing and organizing extracted information Error Handling: Managing Instagram's anti-scraping measures gracefully The Evolution of Instagram's Defenses Instagram continuously evolves its anti-scraping measures, including: Implementing more sophisticated bot detection Reducing publicly available data Adding CAPTCHA challenges Implementing rate limiting and IP blocking Successful long-term scraping operations must adapt to these changing conditions. Alternative Approaches For businesses requiring Instagram data, several alternatives to direct scraping exist: Official Instagram API: Limited but legitimate access to certain data types Third-Party Services: Specialized companies offering Instagram data through legitimate partnerships Manual Collection: For smaller-scale needs, manual data collection remains viable Future Outlook The Instagram scraping landscape continues to evolve, with the platform generally becoming more restrictive over time. The trend suggests: Decreasing public data availability Increased enforcement against unauthorized access Growing demand for legitimate data access solutions Rising costs for Instagram marketing intelligence

Twitter's Pay-Per-Use API

Twitter's Pay-Per-Use API: Could This Finally Kill the Scraping Economy?

The Twitter API pricing saga has been a wild ride of extremes, and it looks like we might finally be heading toward some middle ground. According to recent announcements, Twitter (now X) is testing a pay-per-usage model that could dramatically reshape how developers and data scrapers interact with the platform. The Pendulum Swings Back Twitter's API pricing history reads like a case study in how not to manage developer relations. The platform started with a completely free API that, while generous, created massive problems with abuse, scraping, and system strain. When Elon Musk took over, the pendulum swung hard in the opposite direction – suddenly, API access became prohibitively expensive for most developers and small businesses. The result? A thriving underground economy of scrapers and unofficial API alternatives, along with frustrated developers who were priced out of legitimate access to Twitter data. Pay-Per-Use: The Obvious Solution The announcement hints at what many in the developer community have been calling for: a reasonable, pay-as-you-go pricing model. This approach makes intuitive sense for several reasons: Scalability for Everyone: Small developers and researchers can access the API without massive upfront commitments, while larger enterprises pay proportionally for their usage. Better Cost Control: Instead of paying for unused quota or being locked into expensive tiers, users pay only for what they actually consume. Reduced Scraping Incentive: If official API access becomes affordable, the economic motivation to build and maintain scraping infrastructure diminishes significantly. The Scraper's Dilemma For those currently running Twitter scraping operations, this development presents an interesting calculation. Scraping Twitter has always been a cat-and-mouse game. You're constantly dealing with rate limits, IP blocks, CAPTCHA systems, and constantly changing HTML structures. It's expensive to maintain and inherently unreliable. If Twitter prices their pay-per-use API competitively, many scrapers might find it cheaper and more reliable to simply pay for official access. The question becomes: what constitutes "competitively priced"? What "Reasonable" Might Look Like For a pay-per-use model to truly disrupt the scraping economy, it needs to be: Transparent: Clear pricing with no hidden fees or surprise charges Granular: Pay for exactly what you use, whether that's 100 requests or 100,000 Competitive: Priced low enough that it's cheaper than building and maintaining scraping infrastructure Reliable: Stable pricing and terms that developers can build long-term plans around The Bigger Picture This shift could signal a broader maturation in how social media platforms think about data access. The all-or-nothing approaches of the past – either completely free or prohibitively expensive – haven't served anyone well. A well-implemented pay-per-use model could: Reduce the technical arms race between platforms and scrapers Enable more legitimate research and business applications Provide platforms with sustainable revenue from data access Create a healthier ecosystem for developers Impact on the Scraping Ecosystem If Twitter gets this right, it could set a precedent for other social media platforms. The current ecosystem of scraping tools and services exists largely because official APIs are either unavailable, unreliable, or unaffordably priced. A shift toward reasonable pay-per-use pricing across major platforms could fundamentally change this landscape, potentially making legitimate API access the norm rather than the exception. Looking Forward The scraping community is watching this development closely. Many scraper operators would probably prefer the predictability and reliability of official API access – if the price is right. For now, it's a waiting game. The pilot program will provide the first real indication of whether Twitter has learned from their pricing missteps or if we're headed for another swing of the pendulum.

how to find tiktok creator region

How to Find TikTok Creator Regions: The Hidden Method TikTok Doesn't Want You to Know

Remember the good old days when TikTok made it simple to discover where your favorite creators were based? Those days when you could just hop onto someone's profile and instantly see their region displayed right there for everyone to see? Well, those days are long gone. The Disappearing Region Feature TikTok quietly removed the region display from creator profiles, leaving users in the dark about where their favorite content creators are located. Whether this was for privacy reasons, platform streamlining, or something else entirely, the result is the same: finding a creator's region became significantly more challenging. But here's the thing, the information is still there. TikTok hasn't completely scrubbed region data from their platform. They've just hidden it from plain sight. The Developer's Secret: API Data Still Contains Regions While casual users lost easy access to region information, the data still exists in TikTok's backend. Every time you load a TikTok video, the platform's API returns a wealth of metadata about both the content and the creator – including their region. Here's where it gets interesting: this region data is embedded in the "author" object of every video's metadata. That means with the right tools, you can still access this information. The Simple Solution: Video Scraping The workaround is surprisingly straightforward: Target any video from the creator – it doesn't matter which one, but their first post often works well Extract the video's metadata using a TikTok scraping tool Look for the "author" object in the returned data Find the "region" field – there's your answer The beauty of this method is that you only need to scrape one video per creator to get their region information. The author data remains consistent across all of a creator's content. What You'll Find in the Data When you examine the metadata structure, you'll see something like this: json Notice that "region" field? That's exactly what used to be displayed on profile pages. In this case, "US" clearly indicates the creator is based in the United States. Why This Method Works This approach works because TikTok's infrastructure still relies on region data for various backend processes – content recommendation algorithms, advertising targeting, compliance with local regulations, and more. While they've removed the public display of this information, they haven't eliminated it from their system entirely. The region data helps TikTok understand their global user base, comply with different countries' data protection laws, and serve region-appropriate content and advertisements. Removing it completely would break many of these essential functions. Tools for the Job Several scraping tools can help you access this metadata, with services specifically designed for social media data extraction. The key is finding a reliable scraper that can handle TikTok's current API structure and return complete metadata objects. The Bigger Picture This situation highlights an interesting trend in social media platforms: the tension between transparency and privacy. While removing region displays might protect creator privacy to some degree, it also reduces transparency for users who want to understand the global nature of the content they're consuming. For researchers, marketers, and curious users, knowing creator regions can provide valuable context about content, cultural perspectives, and global trends. The fact that this information is still technically accessible suggests that TikTok recognizes its continued value, even if they've chosen to hide it from casual browsing. Looking Forward Will TikTok eventually remove region data entirely from their backend? It's possible, but unlikely given its utility for their own operations. More probably, we'll see continued evolution in how this data is handled – perhaps with more granular privacy controls that let creators choose whether to display their region. Until then, this metadata method remains a reliable way to satisfy your curiosity about where your favorite TikTok creators are creating their content from around the world.

Personal story about building a profitable scraping API

Lululemon Leggings Led Me to Build a Profitable Scraping API

People often ask me how I got started in web scraping. The answer involves LinkedIn endorsements, a frustrated wife trying to buy workout clothes, and a 2 AM Reddit community of dedicated shoppers. Here's the real story of how I stumbled into building a profitable API business. The LinkedIn Revelation After my coding bootcamp, we were all doing what bootcamp grads do—frantically endorsing each other on LinkedIn, hoping to boost our chances in the job market. Then someone in our cohort wrote a Selenium script to automate the whole process. I was blown away. THIS is why I wanted to code. These kinds of superpowers that could automate the tedious parts of life. That moment sparked something. I wanted to build tools that could do the impossible. My First (Failed) Attempt Inspired by the automation possibilities, I built a project called "Auto Apply." The concept was simple but ambitious: Scrape LinkedIn for hiring managers Automatically email them with personalized messages Land job interviews without manual outreach Looking back, it was way ahead of its time. The problem? I was absolutely terrible at scraping. Picture this: one lonely Puppeteer instance struggling along, getting blocked constantly, failing half the time. I was fighting HTML parsing, dealing with dynamic content, and basically losing every battle against modern web applications. It was frustrating, slow, and completely unreliable. The Lululemon Lightbulb Moment Then my friend Jake had a problem that would change everything. His wife was trying to buy Lululemon athletic wear, but everything was always sold out. She'd obsessively check the website, hoping to catch restocks. Jake discovered there was even a subreddit where women would literally wake up at 2 AM to grab new drops. The dedication was incredible, but the process was insane. "Can you build a bot that texts her when stuff comes back in stock?" Jake asked. I said yes, naturally. How hard could it be? The API Discovery That Changed Everything At first, I did what I knew—scraping HTML with Puppeteer. It was painful. Constantly blocked. Always breaking. Then Jake, who was actually my PM at work, asked a simple question that changed my entire approach: "Why not just use the API that Lululemon calls?" Genius. I opened the browser developer tools, watched the network requests, and discovered the hidden APIs that the website was actually using. Clean JSON responses. No HTML parsing. No browser automation. Just direct access to the data I needed. That experience changed everything. To this day, I preach: stop scraping HTML → start finding hidden APIs. It's faster, cleaner, and infinitely less brittle than traditional scraping methods. From Side Project to Real Business The Lululemon bot worked perfectly. I sold it for a small sum, but more importantly, I'd learned the fundamental lesson that would shape my entire career. I started freelancing, teaching others about API discovery, and even launched a course about finding hidden APIs in web applications. Then I tried building other projects. One was a TikTok creator database—an ambitious attempt to catalog social media influencers. The MicroAcquire Moment The real turning point came when a follower sent me a MicroAcquire listing for a social media scraping API business. The numbers shocked me. Someone was making serious money selling access to social media data through APIs. I realized I already had endpoints built from my various projects. I thought, why not put them up and see what happens? The First Customer (And How Twitter Came Full Circle) Randomly, I got my first customer. They're still with me today, over a year later. Here's the funny part: I had scraped their company's website to build a tutorial, posted it on Twitter, their CTO replied to the tweet, and then asked about my APIs. Full circle. The scraping tutorial led to my first paying customer. The Pivot That Made It All Work For six months, I juggled both projects: the TikTok creator database and the scraping API. But the TikTok database was expensive to maintain and messy to operate. The API business, on the other hand, was clean, scalable, and actually profitable. So I made the call: go all in on the scraping API. That's how Scrape Creators was born. What I Learned Building a Scraping Business Hidden APIs Are Everywhere Most modern websites rely on internal APIs for their functionality. Instead of parsing HTML, find these APIs and use them directly. It's like having a secret backdoor to clean, structured data. Solve Real Problems The best business ideas come from genuine frustration. Jake's wife wanting Lululemon leggings was a real problem with a clear solution. My first customer needed social media data for their business—another real problem. Start Small, Scale Smart I didn't set out to build a massive enterprise platform. I started with simple endpoints that solved specific problems, then gradually expanded based on customer requests. Customer Feedback Is Everything My current customers often request new platforms or data types. These requests directly shape the product roadmap. When customers ask for something, they're essentially pre-ordering it. The Current State: Bootstrapped and Growing Today, Scrape Creators is: Bootstrapped - No VC funding, no investors Profitable - Recurring revenue from day one Growing - Adding new customers and platforms regularly Sustainable - Built for long-term operation, not explosive growth The business provides structured data from social media platforms through clean APIs. Customers include marketing agencies, content creators, researchers, and SaaS companies building social features. Why This Model Works Low Overhead No office, no employees, minimal infrastructure costs. The profit margins are excellent because the operational complexity is manageable. Recurring Revenue Once customers integrate your APIs into their workflows, they tend to stick around. Data needs are ongoing, not one-time purchases. Scalable Technology APIs can serve multiple customers simultaneously. The same infrastructure that serves one customer can serve hundreds. Defensible Moat Building reliable scraping infrastructure is harder than most people think. The technical expertise becomes a competitive advantage. The Unexpected Journey Looking back, it's wild how everything connected: Bootcamp endorsements led to automation curiosity LinkedIn scraping taught me the fundamentals Jake's wife's shopping problem introduced hidden APIs Twitter tutorials attracted my first customer Real customer needs shaped the final product None of it was planned. Each step just led naturally to the next. What's Next The scraping API space is evolving rapidly. Platforms change, new data sources emerge, and customer needs continue expanding. I'm focused on: Adding new platforms based on customer requests Improving reliability and speed Building tools that make data extraction even easier Helping other developers discover the power of hidden APIs For Aspiring API Entrepreneurs If you're thinking about building an API business, here's my advice: Start with a real problem. Don't build an API because APIs are cool. Build one because someone needs the solution. Learn to find hidden APIs. This skill alone will set you apart from developers who only know traditional scraping methods. Talk to potential customers early. My biggest mistakes were building features nobody wanted. Customer conversations prevent this. Keep it simple initially. You don't need enterprise features on day one. Solve one problem really well, then expand. The Lululemon Legacy It's funny to think that a profitable API business started because someone wanted to buy athletic wear without staying up until 2 AM. But that's how the best businesses often begin—with someone frustrated by an everyday problem and a developer willing to build a solution. Jake's wife got her Lululemon leggings. I got a career in API development. And somewhere along the way, I learned that the most boring problems often lead to the most profitable solutions.

social media extraction process

How I Built a One-Person API Business That Extracts Structured Data from Every Social Platform

From YouTube transcripts to competitor ads—here's how one tool simplifies social media data extraction The internet is drowning in public data, but accessing it in a structured, usable format? That's where things get complicated. Browser automation breaks constantly. Rate limits kill your scripts. APIs change without warning. And don't even get me started on parsing HTML that shifts every few weeks. So I built something different: Scrape Creators is a tool that gives you instant access to structured public data from every major social media platform. Yes, the name might sound intimidating, but here's the thing: it's all public data that anyone can access. I just made it fast, reliable, and structured. What Scrape Creators Actually Does Think of it as a universal translator for social media data. Instead of wrestling with different APIs, browser automation, or parsing messy HTML, you get clean JSON responses in 2-4 seconds. YouTube & TikTok Transcripts Need the full transcript from a video? Whether it's for content repurposing, analysis, or building searchable archives, you get the complete text instantly. No more manually transcribing or dealing with broken subtitle files. Comprehensive Ad Intelligence Competitive research just got easier. The tool searches across: Meta Ad Library - Every Facebook and Instagram ad Google Ads Transparency Center - Search and display campaigns LinkedIn Ads Library - Professional advertising insights Want to see every ad your competitor is running? Now you can, in seconds. Social Media Data Extraction Access public data from any major platform: Twitter tweets, bios, and engagement metrics YouTube comments and channel information Reddit posts and discussions Public profiles and posts across social networks All delivered as clean, structured JSON—no browser automation required. The Real-World Applications For Founders Building Social Tools Stop reinventing the wheel. Whether you're building analytics dashboards, content management tools, or social listening platforms, you need reliable data infrastructure. Scrape Creators becomes your data layer. For Marketers Running Campaigns Trend analysis, competitor monitoring, and content inspiration all require data. Instead of spending hours manually collecting information, get structured insights that fuel your strategy. For Researchers and Agencies Academic research, market analysis, and client reporting demand accurate, comprehensive data. Access historical posts, engagement patterns, and content trends without technical headaches. Why I Built This as a Solo Developer This is exactly the type of "boring" but essential tool that works perfectly for a one-person business. Here's why: High Value, Low Complexity: Everyone needs social media data, but most solutions are either expensive enterprise tools or unreliable scripts. There's a sweet spot in the middle. Sticky Use Case: Once you integrate data extraction into your workflow, you don't switch providers unless something breaks. It becomes infrastructure. Recurring Revenue: Data needs are ongoing. A research project might need thousands of requests over months. A marketing team needs daily competitive insights. The Technical Reality Building this wasn't about creating something revolutionary—it was about solving a real, everyday problem reliably. No browser automation that breaks when sites update. No rate limit headaches. No parsing HTML that changes every week. Just fast, consistent access to public data in the format you actually need. Who This Actually Helps The customers aren't always who you'd expect: Content creators repurposing video transcripts across platforms Marketing agencies monitoring competitor campaigns at scale Academic researchers analyzing social media trends SaaS founders building social features without data infrastructure headaches Growth teams identifying viral content patterns Getting Started Want to test it out? I've made it simple: 100 free requests to explore what's possible 30% off your first purchase with code TWITTER30 Direct email support (I answer everything quickly) The Solo Developer Advantage Running this as a one-person business means I can: Respond to feature requests in days, not months Provide actual human support instead of chatbots Keep pricing fair since I don't have massive overhead Focus on reliability over fancy features Why "Boring" Businesses Work Scrape Creators isn't trying to be the next unicorn. It's solving a specific problem for people willing to pay for a solution. No venture capital. No growth hacking. No viral marketing campaigns. Just a useful tool that works reliably and generates steady revenue. That's the beauty of API businesses—they don't need to be exciting to be profitable. Ready to stop fighting with data extraction? Check out Scrape Creators and see how structured social media data can simplify your workflow. Try it with 100 free requests →

how api businesses are the lawn mowing business of the internet benefits and features

API Businesses: The Lawn-Mowing Business of the Internet

Why building a simple API might be the most underrated path to online freedom There's something beautifully mundane about lawn-mowing businesses. They're not sexy, they won't make headlines, and they certainly won't get you invited to TechCrunch Disrupt. But they're also steady, profitable, and nearly impossible to kill. API businesses are the digital equivalent. Simple, steady, boring… but perfect for a solo developer or tiny team looking to build real freedom online. The API Advantage: Why Boring Wins Low Barrier to Entry You don't need VC money, a co-founder, or even an office. Just time, code, and the discipline to solve a real problem. While others are pitching investors and building complicated SaaS platforms, you can ship an API in weeks. Few Competitors Most APIs live in small, specific niches rather than winner-take-all bloodbaths. There's room for multiple players because the market isn't trying to be everything to everyone. Sticky as Glue Once your API is integrated into a company's system, they don't rip it out unless it breaks. The switching costs are real, and "if it ain't broke, don't fix it" is the default mindset. High Leverage Economics You only need a handful of paying customers to make a solid living. No massive user acquisition funnels or complex conversion paths—just businesses paying monthly for a service that works. The "Set It and Forget It" Reality Low churn isn't just a nice-to-have; it's built into the model. As long as your API works reliably, customers leave it in place for years. That's recurring revenue you can actually count on. Real Examples: Tiny Teams, Big Results The proof is in the businesses already crushing it: ScrapingBee – 4 people building a web scraping API Scrape Creators – 1 person solving content extraction ScreenshotOne – 1 developer making screenshot generation simple Cobalt Intelligence – 2 people in the data intelligence space FinancialDatasets.ai – Solo founder serving financial data needs These aren't unicorns. They're profitable, sustainable businesses run by small teams who chose boring over buzzy. The Playbook: Lessons from Lawn Care The strategy mirrors successful service businesses: Be Ridiculously Accessible - Plaster your email everywhere. Respond to every message. Let people easily schedule calls with you. Most API providers hide behind support tickets and chatbots. Just being human wins deals. Speed Matters More Than Polish - Answer emails as quickly as possible. Most competitors are faceless and unresponsive. While they're optimizing their automated responses, you're closing deals by actually showing up. Reliability Over Features - Your customers don't want the most innovative API. They want the one that works every single time. Stability beats novelty in the API game. The Reality Check It's not all roses. You might get woken up at 3 AM when something breaks. Your friends won't understand what you do. And yeah, it's "boring." You're not building the next viral app or revolutionary platform. But boring is beautiful. While others chase unicorn valuations and viral growth, you're building something more valuable: predictable income, low stress, and actual freedom. Why API Businesses Are Underrated In a world obsessed with venture capital and exponential growth, API businesses get overlooked. They don't scale to billions of users. They don't generate press coverage. They don't fit the startup narrative. That's exactly why they work. Simple. Profitable. Low churn. Hard to kill. If you're a solo developer tired of the startup circus, an API business might be your path to online freedom. Not through disruption or innovation, but through the most old-school business principle of all: solving real problems for people willing to pay. Just like mowing lawns, but with better margins and no grass stains.

api calls reveal social media scraping trends in 2025

What 10M+ API Calls Reveal About Social Media Scraping Trends in 2025

I pulled the numbers on the most-used Scrape Creators API routes, and the results from 10+ million real API calls tell a fascinating story about what people are actually scraping in 2025. The data doesn't lie, and it reveals some surprising trends about the evolution of social media intelligence. The Clear Winner: Instagram Profiles Still Rule With 4.31 million calls and a 99.57% success rate, /v1/instagram/profile absolutely dominates our usage statistics. This makes perfect sense – everyone wants to know who a creator is first. Why Instagram profiles are king: Bios, follower counts, and basic profile data form the foundation of influencer discovery It's the starting point for any creator research or outreach campaign The data is reliable and consistently formatted across profiles But here's where it gets interesting... The Surprise Runner-Up: TikTok Transcripts The real story is at #2: /v1/tiktok/video/transcript with 3.82 million calls and an incredible 99.99% success rate. This represents a fundamental shift in how people approach social media intelligence. Instead of just asking "who they are," millions of requests are asking "what they say." Why TikTok transcripts are exploding: Actual social listening – understanding the content, not just the creator Trend identification – spotting emerging topics and conversations Content analysis – parsing what's actually being discussed in videos Brand monitoring – tracking mentions within video content, not just captions This is still an underutilized goldmine. The ability to analyze what creators are actually saying opens up massive opportunities for: Competitive intelligence Trend forecasting Brand sentiment analysis Content strategy development The Pattern Emerges: Profile → Content Looking at the top routes, a clear two-step pattern emerges: Step 1: Find the creator (profile data) /v1/instagram/profile – 4.31M calls /v1/tiktok/profile – 3.05M calls /v1/youtube/channel – 302K calls Step 2: Understand their content /v1/tiktok/video/transcript – 3.82M calls /v2/instagram/user/posts – 2.38M calls /v1/youtube/video – 2.31M calls This workflow makes perfect business sense: identify promising creators, then dive deep into their content to understand their messaging, audience engagement, and brand fit. Platform-Specific Insights TikTok: The Content Analysis Leader TikTok dominates the content analysis category with transcripts, profiles, and video data all in the top 10. With success rates consistently above 99.97%, it's also the most reliable platform for data extraction. Key TikTok endpoints: Video transcripts: 3.82M calls (99.99% success) Profiles: 3.05M calls (99.97% success) Video metadata: 1.50M calls (100% success) Instagram: The Profile Powerhouse Instagram leads in profile discovery but shows strong secondary usage for posts and reels analysis. The success rates are excellent across all endpoints (99%+). Instagram's strength: Profile discovery: 4.31M calls User posts: 2.38M calls Stories tracking: 176K calls YouTube: The Reliable Archive YouTube maintains steady millions of calls, but compared to TikTok and Instagram, it's more of a "reliable archive" – consistent and valuable, but not the fastest-growing category. YouTube's role: Long-form content analysis Channel research for partnerships Historical content tracking The Unexpected Players Truth Social: The Political Tracker One major surprise? /v1/truthsocial/user/posts appearing in the top routes with 1.29M calls and 99.98% success rate. This is primarily driven by people wanting to track specific political figures and conversations. It shows how niche platforms can generate significant API usage when they host high-value content. Facebook: The Declining Giant Facebook barely makes the list with just 155K calls for user posts. This reflects the platform's reduced relevance for creator marketing and the increasing difficulty of accessing meaningful public data. Technical Performance Insights Success Rates Tell a Story The success rates across platforms reveal important technical insights: Perfect performers (100% success): YouTube video data TikTok video metadata TikTok profile videos Near-perfect (99%+ success): Most Instagram endpoints TikTok transcripts and profiles YouTube channels and comments The outliers: Instagram user/reels (99.75% success) – likely due to private accounts Facebook user posts (99.62% success) – platform restrictions impacting reliability Response Times Matter Average request times range from 1.21 seconds (YouTube comments) to 8.19 seconds (TikTok profile videos). The variation suggests different levels of data processing complexity across endpoints. What This Means for Your Strategy Content Analysis is the Future The massive usage of transcript and content analysis endpoints shows that surface-level creator data isn't enough anymore. Businesses are digging deeper into: What creators actually talk about How they discuss topics and brands The sentiment and tone of their content Multi-Platform Approach is Standard The top routes span Instagram, TikTok, YouTube, and even Truth Social, indicating that comprehensive social media intelligence requires a multi-platform strategy. Real-Time Monitoring is Critical With millions of calls across these endpoints, it's clear that businesses are monitoring creator activity in real-time, not just doing one-off research projects. The Bottom Line These 10+ million API calls reveal that social media scraping has evolved far beyond basic profile scraping. We're seeing sophisticated content analysis, cross-platform intelligence gathering, and real-time monitoring at massive scale. The winners are clear: Instagram for discovery, TikTok for content intelligence, and YouTube for deep-dive analysis. But the real opportunity? TikTok transcripts. With 3.8M+ calls, this remains one of the most powerful and underutilized data sources for understanding what's actually being said in the creator economy.

Scrape Creators Community Node announcement

Scrape Creators Community Node Now Available on n8n Cloud - No More HTTP Calls!

We're excited to announce that the Scrape Creators Community Node is now officially available on n8n Cloud! This means you can finally ditch those complex HTTP requests and API calls for a simple, dropdown-based scraping experience. What's New? The Scrape Creators node brings real-time social media data scraping directly into your n8n workflows with zero technical complexity. Instead of wrestling with API endpoints, headers, and authentication tokens, you can now: Select from a dropdown menu what you want to scrape Get real-time social media data without coding Integrate seamlessly with your existing n8n automations How to Get Started Step 1: Enable Community Nodes You may need to enable the Verified Community Nodes option in your n8n Cloud settings to see the Scrape Creators node. Here's how: Go to your n8n Cloud dashboard Navigate to Settings → Community Nodes Enable "Verified Community Nodes" Refresh your workflow editor Step 2: Add the Node to Your Workflow Once enabled, you'll find "Scrape Creators" in your node palette. Simply: Search for "Scrape Crea" in the node search Drag the Scrape Creators node into your workflow Configure your scraping parameters from the dropdown options Connect it to your trigger and output nodes Why This Changes Everything Before: The HTTP Call Nightmare Previously, scraping social media data in n8n meant: Setting up complex HTTP request nodes Managing authentication and headers Handling rate limiting manually Parsing JSON responses Dealing with API changes and updates After: Point-and-Click Simplicity Now with the Scrape Creators node: No coding required - just select from dropdown menus Pre-built integrations for major social media platforms Automatic error handling and retry logic Real-time data access without API limitations Consistent data format across all platforms Perfect for These Use Cases The Scrape Creators node is ideal for: Social Media Monitoring Track mentions of your brand across platforms Monitor competitor activity and engagement Collect hashtag performance data Content Research Gather trending topics and content ideas Analyze successful posts in your niche Track influencer content strategies Lead Generation Find potential customers mentioning relevant keywords Identify active users in your target market Build prospect lists from social media activity Analytics and Reporting Create custom social media dashboards Generate automated reports on social performance Track campaign effectiveness across platforms Workflow Examples Here are some powerful workflows you can build: 1. Brand Mention Alert System Trigger (Schedule) → Scrape Creators → Filter mentions → Send Slack notification 2. Competitor Analysis Dashboard Trigger (Webhook) → Scrape Creators → Process data → Update Google Sheets → Generate report 3. Content Curation Pipeline Trigger (Schedule) → Scrape Creators → Filter by engagement → Save to Airtable → Email digest Technical Benefits Simplified Integration No API keys needed for basic scraping Built-in rate limiting prevents platform blocks Automatic data normalization across different social networks Error handling with retry mechanisms Performance Optimized Efficient data retrieval without overwhelming target servers Cached responses for frequently requested data Batch processing for large-scale operations Real-time updates when new data is available Getting the Most Out of Your Node Best Practices Start small - test with a few data points before scaling up Use filters - leverage n8n's filtering capabilities to process only relevant data Set appropriate schedules - don't over-scrape; respect platform limits Combine with other nodes - integrate with databases, CRMs, and notification systems Pro Tips Use the Set node to clean and structure your scraped data Combine with IF nodes to create conditional logic based on scraped content Leverage HTTP Request nodes for custom post-processing when needed Set up error workflows to handle edge cases gracefully What's Next? This is just the beginning! The Scrape Creators Community Node will continue to evolve with: More platform integrations based on user feedback Advanced filtering options for more precise data collection Custom field mapping for specific use cases Enhanced data export formats for better integration flexibility Ready to Get Started? Head over to your n8n Cloud dashboard and search for "Scrape Creators" in the node palette. Remember to enable Verified Community Nodes if you don't see it immediately. The era of complex HTTP calls for social media scraping is over. Welcome to the age of drag-and-drop data collection!

What Happens When Social Media Companies Catch You Scraping

What Happens When Social Media Companies Catch You Scraping? A Platform-by-Platform Guide

So you've decided to scrape social media data. You know it's legal (based on recent court rulings), but what actually happens when these platforms catch you in the act? Having seen countless scraping operations over the years, I can tell you that each platform has its own playbook for dealing with scrapers. Here's the real-world breakdown of what to expect: Meta (Facebook & Instagram): The Legal Intimidation Masters What They'll Do: Send you really intimidating cease-and-desist letters (probably 2 or more) Demand you hand over your scraping code and any money you've made from the project Delete your Instagram and Facebook accounts immediately Threaten legal action with scary lawyer language Reality Check: Just ignore them and you'll be fine. Meta loves to flex their legal muscles, but as we've seen in recent court cases like Bright Data vs. Meta, they consistently lose when it comes to public data scraping. Their C&D letters are designed to scare you into compliance, not because they have strong legal grounds. Pro Tip: Don't respond to their demands for your code or revenue. You're under no legal obligation to comply with these requests for public data scraping. Twitter/X: The Selective Enforcers What They'll Do: Only send cease-and-desist letters if you're scraping behind the login wall Delete your Twitter account (this one they actually follow through on) Generally leave you alone if you stick to public tweets The Strategy: Twitter has learned from the court losses. They focus their legal threats on scrapers who are accessing private or authenticated data, where they actually have legal standing. Bottom Line: Stay in the public timeline and you're mostly safe from legal action, though your account might still get the axe. YouTube: The Hypocritical Giant What They'll Do: Basically nothing. Why: Google literally scrapes the entire internet for their search engine. It would be pretty hypocritical for them to come after you for scraping their publicly available video data. The Exception: They do care about downloading actual video files or circumventing their monetization systems, but public metadata scraping? They've got bigger fish to fry. TikTok: The Wild Card What They'll Do: Varies widely, but enforcement is inconsistent. The Reality: TikTok's enforcement seems less systematic than other platforms. Their legal team appears more focused on national security concerns and government relations than individual scrapers. Cultural Note: Different legal frameworks and enforcement priorities mean their response patterns are less predictable than US-based platforms. General Patterns Across All Platforms What Every Platform Will Do: Account Suspension: This is universal. If they detect scraping from your account, it's getting banned. Rate Limiting: Expect your requests to get throttled or blocked entirely. IP Blocking: Persistent scraping often leads to IP-based blocks. What Most Won't Do: Actually Sue You: Despite the threats, lawsuits for public data scraping are rare and expensive. Pursue Small Operators: Legal action is typically reserved for large-scale commercial operations. Follow Through on Revenue Demands: These are scare tactics without legal backing for public data. The Legal Reality vs. Platform Policies Here's the key distinction: platform terms of service violations are not criminal acts. Courts have repeatedly ruled that simply violating a website's terms of service doesn't constitute illegal activity under laws like the Computer Fraud and Abuse Act. What this means: Getting banned from a platform ≠ breaking the law Cease-and-desist letters ≠ valid legal claims Terms of service violations ≠ criminal activity How to Minimize Platform Retaliation Best Practices: Use Residential Proxies: Rotate IP addresses to avoid detection Respect Rate Limits: Don't hammer their servers Scrape Public Data Only: Stay away from anything behind login walls Use Throwaway Accounts: Assume any accounts you use will get banned Don't Respond to C&D Letters: Engaging often escalates the situation Red Flags That Increase Enforcement: Creating fake accounts for scraping Accessing private/authenticated data Overwhelming their servers with requests Commercial use that directly competes with their business model Public announcements about your scraping activities The Bottom Line Most social media platforms bark louder than they bite when it comes to public data scraping. They rely heavily on intimidation tactics because their actual legal standing is weak for publicly accessible data. The Pattern: Account bans are certain, legal action is rare, and court precedent is on your side for public data. The Strategy: Build your scraping infrastructure assuming accounts will get banned, use proper technical measures to avoid detection, and don't let scary lawyer letters deter you from legally permissible activities. Remember: there's a big difference between what platforms want you to think is illegal and what's actually illegal under current law.

legal or illegal web scraping

Is Web Scraping Legal? A Guide Based on Recent Court Rulings

One question I hear all the time is: is web scraping legal? I'm going to walk through the major lawsuits and court rulings to help clarify what the law actually says about web scraping. The short answer? If you can access the data in an incognito browser without logging in, you can probably scrape it. The Golden Rule of Web Scraping Rule of thumb: If you can access the data in an incognito browser, you can scrape it. Why do I feel confident saying that? Because multiple court rulings have consistently supported this principle. Let me break down the key cases that established this precedent. Case 1: hiQ Labs vs. LinkedIn - The Foundation Case This is probably the OG web scraping lawsuit that set the legal foundation we rely on today. The Setup: LinkedIn tried to sue hiQ Labs under the Computer Fraud and Abuse Act (CFAA), which prohibits accessing protected computer systems without authorization. The Ruling: The Ninth Circuit Court ruled against LinkedIn, stating that the CFAA did not apply to the automatic collection of publicly accessible data. The court found that platforms like LinkedIn and Meta could not designate portions of their public platforms as "off limits" to only certain individuals or companies. Key Quote from the Ruling: The court noted that interpreting the CFAA so broadly would allow "companies like LinkedIn free rein to decide, on any basis, who can collect and use publicly available data, which would risk possible creation of information monopolies that would disserve the public interest." Important Exception: hiQ did get in trouble for one specific activity - hiring contractors to create fake LinkedIn accounts for the explicit purpose of collecting logged-in data (what the court called the "turkers" conduct). This reinforces that creating fake accounts crosses the legal line. Case 2: Meta Platforms vs. BrandTotal Ltd. - Reinforcing the Precedent In another important summary judgment ruling in the scraping space, the court refused to grant summary judgment to Meta Platforms on CFAA claims related to two categories of data collection, further supporting the principle that public data scraping is generally permissible. Case 3: Bright Data vs. Meta - 2024 Confirmation The Setup: Meta sued Bright Data for web scraping activities. The Outcome: Meta lost because they couldn't prove that Bright Data was scraping data behind login walls. Key Insight: This 2024 ruling reaffirmed that scraping publicly available data remains legally defensible, while accessing data that requires authentication does not. Case 4: Bright Data vs. Twitter/X - The Judge's Scathing Ruling A few months after the Meta lawsuit, Twitter (now X) sued Bright Data, arguing that the company violated Twitter's copyright. The Judge's Response: The court delivered a particularly pointed ruling against Twitter, noting that giving social networks complete control over public web data "risks the possible creation of information monopolies that would disserve the public interest." The judge added that Twitter was not "looking to protect users' privacy," and was "happy to allow the extraction and copying of users' content so long as it gets paid." What This Means for You Based on these court rulings, here are the key takeaways: Generally Legal: Scraping publicly available data that doesn't require login Accessing information visible in an incognito browser Collecting data from public portions of websites Potentially Illegal: Creating fake accounts to access private data Scraping data behind login walls or paywalls Violating explicit technical barriers (like CAPTCHAs designed to prevent automated access) Gray Areas: Terms of Service violations (courts have generally not treated these as criminal violations) Rate limiting and server load considerations Copyright implications for specific types of content The Bottom Line The legal precedent is clear: only scrape public data - data that you can access in an incognito browser without being logged in. Multiple courts have consistently ruled that publicly accessible web data can be scraped, while creating fake accounts or bypassing authentication measures crosses legal boundaries. These rulings serve to reaffirm the broad general ability to web scrape publicly available portions of websites where an account login/password has not been utilized, while making it clear that accessing private or authenticated data remains legally risky.

Prices of 3 best residential proxy options 2025

Best Cheap Residential Proxies for Web Scraping in 2025

When scraping websites with sophisticated anti-bot protection, residential proxies often make the difference between success and failure. These proxies route your requests through real residential IP addresses, making your scraping activities appear as legitimate user traffic rather than automated bot requests. Why Residential Proxies Matter for Web Scraping Many modern websites employ advanced security measures that can easily detect and block datacenter IPs. Residential proxies solve this problem by providing IP addresses that belong to real internet service providers and appear as genuine user connections. The key benefits include: bypassing IP-based blocking avoiding rate limiting detection accessing geo-restricted content maintaining consistent scraping operations even on heavily protected sites. Top Budget-Friendly Residential Proxy Providers Evomi - $0.49/GB Evomi offers what might be the most aggressive pricing in the residential proxy market at just $0.49 per gigabyte. This pricing makes it incredibly attractive for high-volume scraping projects where cost is a primary concern. However, there's an important caveat with Evomi: reliability can be inconsistent. The service tends to experience frequent outages or connection issues, which means while the price is unbeatable, you may face interruptions during critical scraping operations. Best for: Budget-conscious projects where occasional downtime is acceptable and cost savings are the primary priority. Dataimpulse - $1/GB At $1 per gigabyte, Dataimpulse sits in the middle ground for pricing while potentially offering better reliability than ultra-cheap options. The pricing is still highly competitive compared to premium providers. The main limitation is that this provider hasn't been tested extensively at large scale, so performance under high-volume scraping scenarios remains somewhat unknown. For smaller to medium-scale operations, it could be a solid choice. Best for: Medium-scale scraping projects looking for a balance between cost and reliability. Webshare Static Proxies - $230/month for 1,000 proxies Webshare takes a different approach by offering static residential proxies in bulk packages. For $230 per month, you get access to 1,000 proxies, which works out to approximately $0.23 per proxy per month. This model is particularly valuable if you need consistent IP addresses for your scraping operations or if you're running multiple concurrent scraping sessions that benefit from dedicated proxy allocation. Best for: Operations requiring consistent IP addresses or high-concurrency scraping across multiple targets. Choosing the Right Provider for Your Needs Your choice should depend on several factors: For experimental or low-stakes projects: Evomi's ultra-low pricing might be worth the reliability trade-offs, especially if you can build retry mechanisms into your scraping infrastructure. For production applications: Consider Dataimpulse or Webshare, where slightly higher costs may provide better uptime and consistency for business-critical scraping operations. For high-concurrency scraping: Webshare's bulk static proxy model could provide the dedicated resources needed for complex scraping architectures. Implementation Considerations Regardless of which provider you choose, successful residential proxy implementation requires proper rotation strategies, request timing optimization, and robust error handling for proxy failures. Consider implementing failover mechanisms that can switch between multiple proxy providers if your primary service experiences outages. This redundancy becomes especially important when using budget providers that may have occasional reliability issues. Cost-Effectiveness Analysis When evaluating proxy costs, consider the total cost of ownership including potential downtime, the need for backup services, and the time investment required to manage less reliable providers. Sometimes paying slightly more for proven reliability can actually reduce your total costs when you factor in lost productivity from service interruptions and the engineering time needed to build resilient scraping systems. Final Recommendations For most developers getting started with residential proxies, I'd recommend beginning with one of these budget options to understand your specific needs and usage patterns. As your scraping operations mature and become more critical to your business, you can always upgrade to premium providers with better SLAs and support. Remember that proxy costs are just one component of a successful scraping operation. Factor in the value of your time, the criticality of your data collection, and the potential cost of service interruptions when making your decision.

Tiktok slider captcha and web scraping by scrape creators

How to Solve TikTok Slider Captchas: A Developer's Guide

If you've ever tried scraping TikTok Shop or other TikTok content, you've probably encountered their slider captcha. While these captchas are designed to stop automated scraping, there are legitimate ways to solve them programmatically for business and research purposes. Why This Approach is Necessary To my everlasting resentment, we have to use Puppeteer for this solution. While it might be tempting to try reverse engineering TikTok's desktop API, that path is significantly more complex and prone to breaking when TikTok updates their systems. Puppeteer provides a more stable, browser-based approach that mimics real user behavior. Understanding the TikTok Slider Captcha TikTok's slider captcha presents users with a background image containing a missing puzzle piece and a separate piece that needs to be dragged to the correct position. To solve this programmatically, we need to: Extract the puzzle background image Capture the puzzle piece image Calculate the exact distance needed to slide the piece Simulate human-like dragging behavior Step 1: Extracting the Required Images When the captcha appears, you need to capture three essential elements: the puzzle background image, the puzzle piece image, and the container width for accurate positioning calculations. Here's the code to do that: The key is identifying the correct DOM elements that contain these images. TikTok typically uses specific CSS classes and image elements for the captcha components. You'll need to wait for the captcha to fully load before attempting to extract these elements. Step 2: Using SadCaptcha for Distance Calculation Rather than implementing complex computer vision algorithms yourself, we can leverage SadCaptcha, a service specifically designed to solve slider captchas. This service analyzes the puzzle images and returns the precise distance needed to position the piece correctly. Code: The process involves sending both the background image and puzzle piece to SadCaptcha's API, which then returns coordinates indicating where the piece should be placed. This eliminates the need to implement image recognition and puzzle-solving algorithms from scratch. Step 3: Implementing the Drag Movement Once you have the target distance, you need to simulate the actual dragging motion. However, there's a crucial detail: you can't simply slide the piece directly to the target position. TikTok's system detects overly mechanical movements. Code: You'll likely need to add a "fudge factor" to the calculated distance, a small adjustment that accounts for variations in how the captcha system interprets positioning. This often requires some trial and error to get right for your specific use case. Step 4: Simulating Human-Like Behavior The most critical aspect of solving these captchas is making the movement appear human. Simply sliding the piece slowly and steadily to the target position will fail TikTok's detection systems. Instead, you need to implement an algorithm that mimics natural human dragging behavior, including: Variable speed throughout the drag motion Slight overshooting and correction movements Natural acceleration and deceleration patterns Minor positioning adjustments Code: The SadCaptcha team has developed sophisticated algorithms for this human simulation, which can save you significant development time. Deployment Considerations Once you have your captcha-solving solution working locally, deployment requires careful consideration. AWS Lambda can work but comes with complexity around browser dependencies and execution time limits. Alternative platforms like Replit may offer simpler deployment options for Puppeteer-based applications. Consider your specific requirements around execution time, memory usage, and scaling needs when choosing a deployment platform. The Alternative Approach While building your own captcha solver can be educational and give you complete control, it's also time-intensive and requires ongoing maintenance as captcha systems evolve. If you're looking to focus on your core business logic rather than captcha-solving infrastructure, consider using a pre-built API solution that handles all the complexity for you. Services like Scrape Creators provide ready-to-use APIs that handle TikTok scraping, including captcha solving, so you can focus on what matters most to your project. Best Practices and Legal Considerations Respect rate limits and avoid overwhelming target servers Ensure your use case complies with TikTok's terms of service Consider the ethical implications of automated data extraction Implement proper error handling for failed captcha attempts Monitor your success rates and adjust parameters as needed Conclusion Solving TikTok slider captchas programmatically requires a combination of browser automation, image processing services, and sophisticated movement simulation. While the technical implementation can be complex, understanding these core concepts will help you build robust scraping solutions. Whether you choose to implement your own solution or use a pre-built service, the key is balancing effectiveness with maintainability for your specific use case.

Firecrawl vs scrape creators features at a glance

Firecrawl vs Scrape Creators: A Detailed Platform Comparison

When evaluating web scraping solutions, developers often compare different platforms to find the best fit for their specific needs. Today, I'm breaking down the key differences between Firecrawl and Scrape Creators—two platforms that serve the scraping community but take distinctly different approaches. Full disclosure: I actually recommend and have used Firecrawl myself, and I'm the creator behind Scrape Creators. This comparison aims to help you understand the technical differences, not to criticize either platform. Scope and Specialization Firecrawl positions itself as a comprehensive web scraping solution capable of handling virtually any website across the internet. Whether you're extracting data from e-commerce platforms, news sites, documentation, or complex web applications, Firecrawl is designed to be your universal scraping tool. Scrape Creators takes a specialized approach, focusing exclusively on social media platforms and creator-related content. If your project involves extracting data from Instagram, TikTok, YouTube, or other social networks, this platform is purpose-built for that specific use case. Data Format and Processing The way these platforms deliver data represents one of their most fundamental differences. Firecrawl typically returns raw HTML responses, requiring you to implement your own parsing logic to extract the specific data points you need. While they do offer an AI feature that can assist with data extraction, the standard approach involves additional processing steps on your end. Scrape Creators eliminates this complexity by returning clean, structured JSON responses. The data arrives pre-parsed and ready for immediate integration into your applications, potentially saving significant development time and reducing the complexity of your data pipeline. Performance and Concurrency Management Firecrawl implements concurrent request limitations based on your subscription tier, which means you'll need to manage your request flow to stay within their defined limits. Scrape Creators removes these constraints by offering unlimited concurrent requests. This approach gives you complete control over scaling your scraping operations without worrying about hitting concurrency walls, which can be crucial for high-volume or time-sensitive data extraction projects. Pricing Philosophy and Credit Systems The two platforms take fundamentally different approaches to billing and credit management. Firecrawl operates on a subscription model where credits don't carry over to the next billing cycle. This means any unused credits expire at the end of your billing period, which can result in waste if your usage patterns are inconsistent or unpredictable. Scrape Creators uses a pay-as-you-go model with credits that never expire. This approach provides maximum flexibility for projects with variable scraping needs and ensures you never lose value from unused credits, regardless of how your usage fluctuates over time. Choosing the Right Platform Your decision should be based on your specific project requirements and working preferences: Choose Firecrawl if you need to scrape a wide variety of websites beyond social media, are comfortable implementing data parsing logic, have consistent scraping volumes that align with subscription models, or want access to their AI-powered extraction features. Choose Scrape Creators if your focus is specifically on social media and creator platforms, you prefer ready-to-use JSON responses over raw HTML, you need unlimited concurrent requests for high-volume operations, or you want flexible pricing with credits that never expire. Final Thoughts Both Firecrawl and Scrape Creators contribute valuable solutions to the web scraping ecosystem, but they've evolved to address different market needs. Firecrawl excels as a general-purpose scraping platform with broad website compatibility, while Scrape Creators offers specialized social media scraping with developer-optimized features and flexible pricing. The key is matching the tool to your specific requirements. Consider your target websites, preferred data formats, scalability needs, and budget structure when making your choice. Both platforms continue to evolve, so it's worth staying updated on their feature developments as your projects grow.

Side by side comparison of apify and scrape creators

Apify vs Scrape Creators: Understanding the Key Differences

This comparison comes up frequently in my conversations with developers and businesses looking for scraping solutions. As someone who's actually an Apify ambassador, I want to provide an honest, balanced perspective on how these two platforms differ. This isn't a criticism of Apify—both platforms serve important roles in the scraping ecosystem, but they approach the market from very different angles. Full transparency: I'm an Apify ambassador and the creator behind Scrape Creators, so I have insider knowledge of both platforms. Target Audience and User Experience Apify primarily targets no-code and low-code users as their main demographic, with developers as a secondary audience. The platform excels at providing visual workflows and user-friendly interfaces that allow non-technical users to set up complex scraping operations without writing code. Scrape Creators flips this approach by primarily targeting developers while remaining accessible to no-code users. The platform is built with API-first thinking, though the no-code experience will improve significantly once the planned n8n integration launches. Developer Access and Support One of the most significant differences lies in who you're actually working with when you need help. Apify operates as a marketplace where various developers can publish their scraping actors. While you might know the name of an actor's creator, getting direct access to them for support, customization, or questions can be challenging. You're often working through Apify's support channels rather than directly with the person who built the specific tool you're using. Scrape Creators offers direct access to me. If you encounter issues, need customizations, or have questions about any API endpoint, you can email me directly or even schedule a same-day meeting. This direct line of communication can be invaluable when you're working on time-sensitive projects or need custom solutions. Pricing Structure and Costs The cost structures between these platforms reflect their different philosophies and target markets. Apify uses a multi-layered pricing model that includes monthly subscription fees, individual actor costs, and storage charges. While this provides flexibility, it can make cost prediction more complex, especially for projects with varying usage patterns or storage requirements. Scrape Creators has a straightforward pay-as-you-go model. You pay only for what you use, with credits that never expire. There are no monthly fees, no per-actor charges, and no storage costs to factor into your budget planning. Technical Approach and Flexibility Apify shines in its marketplace diversity. With hundreds of pre-built actors covering countless websites and use cases, you're likely to find existing solutions for most scraping challenges. The platform's strength lies in this breadth of available tools and the visual workflow capabilities. Scrape Creators focuses on depth rather than breadth, specializing specifically in social media and creator platforms. While the scope is narrower, the APIs are designed to be more developer-friendly with consistent JSON responses and specialized features for social media data extraction. Making the Right Choice Your decision should align with your project needs and technical comfort level: Choose Apify if you need to scrape diverse websites beyond social media, prefer visual workflow builders, work in a no-code environment, or want access to a large marketplace of pre-built solutions. Choose Scrape Creators if you're primarily focused on social media data, prefer direct API access with JSON responses, value direct creator support and communication, or want predictable pay-per-use pricing without expiring credits. The Bottom Line Both platforms serve the scraping community effectively, but they've evolved to meet different needs. Apify excels as a comprehensive marketplace with strong no-code capabilities, while Scrape Creators offers specialized social media scraping with developer-centric features and direct support access. Understanding these differences will help you choose the platform that best aligns with your project requirements and working style.

Difference between scrape creators and scraping bee

Scrape Creators vs Scraping Bee: A Comprehensive Comparison

When it comes to web scraping tools, developers often find themselves choosing between different services that cater to various needs. Let's take a detailed look at two popular options: Scrape Creators and Scraping Bee. While both serve the scraping community, they take distinctly different approaches to solving data extraction challenges. Disclaimer: This comparison is meant to highlight the technical differences between these services, not to diminish either platform or their creators. Scope and Focus Scraping Bee positions itself as a comprehensive web scraping solution designed to handle virtually any website on the internet. Whether you're extracting data from e-commerce sites, news platforms, or complex web applications, Scraping Bee aims to be your go-to tool for general-purpose scraping. Scrape Creators, on the other hand, takes a more specialized approach. It focuses exclusively on social media platforms and creator-related content. If your project involves extracting data from social networks, influencer profiles, or creator platforms, this service is built specifically for that use case. Data Format and Parsing One of the most significant differences lies in how these services deliver data to developers. Scraping Bee typically returns raw HTML responses, which means you'll need to implement your own parsing logic to extract the specific data points you need. While they do offer an AI feature that can help with data extraction, the default approach requires additional processing on your end. Scrape Creators takes a developer-friendly approach by returning clean, structured JSON responses. The data comes pre-parsed and ready to integrate into your applications, potentially saving significant development time and reducing complexity in your data pipeline. Performance and Concurrency Scraping Bee implements concurrent request limitations, which means you'll need to manage your request flow to stay within their defined limits. Scrape Creators offers unlimited concurrent requests, giving you the flexibility to scale your scraping operations without worrying about hitting concurrency walls. This can be particularly valuable for high-volume applications or time-sensitive data extraction projects. Pricing and Credit System The two services also differ in their approach to billing and credit management. Scraping Bee operates on a subscription model where credits don't roll over to the next billing cycle. This means unused credits expire, potentially leading to waste if your usage patterns are inconsistent. Scrape Creators uses a pay-as-you-go model with credits that never expire. This approach offers more flexibility for projects with variable scraping needs and ensures you never lose value from unused credits. Which Service Should You Choose? Your choice between these services should depend on your specific needs: Choose Scraping Bee if: You need to scrape a wide variety of websites beyond social media You're comfortable implementing your own data parsing logic You have consistent, predictable scraping volumes that align with subscription models Choose Scrape Creators if: Your focus is specifically on social media and creator platforms You prefer ready-to-use JSON responses over raw HTML You need unlimited concurrent requests for high-volume operations You want flexible, never-expiring credits with pay-as-you-go pricing Final Thoughts Both Scrape Creators and Scraping Bee serve important roles in the web scraping ecosystem. The best choice depends entirely on your project requirements, technical preferences, and business model. Consider your specific use case, data format preferences, scalability needs, and budget structure when making your decision. Remember that the web scraping landscape is constantly evolving, so it's worth evaluating these tools based on your current needs while keeping an eye on how they develop their features over time.

An image illustrating the varied responses of social media platforms to data scraping

The Social Media Scraping Wars: How Platforms Really Respond When You Mine Their Data

Social media scraping has become a contentious battleground between platforms protecting their data and researchers, developers, and businesses trying to extract valuable insights. Not all platforms fight back with the same intensity. In fact, some barely put up a fight at all. Truth Social's Half-Hearted Defense Take Truth Social's recent anti-scraping efforts as a perfect example of corporate surrender disguised as security. When scrapers started mining their platform, they initially deployed Cloudflare protection, a standard first line of defense. But when that didn't work, they simply threw in the towel. Instead of implementing sophisticated anti-scraping measures, Truth Social took the nuclear option: they just stopped showing most users' posts unless you're logged in. The irony? Trump's posts still show up without authentication. Either way, it's hardly the robust defense you'd expect from a platform serious about protecting its data. The Real Scraping Landscape: Platform by Platform Each major social media platform has developed its own approach to the scraping problem, and the responses range from aggressive legal threats to complete indifference. Meta (Facebook/Instagram): The Legal Intimidator Meta doesn't mess around. Cross them, and you'll likely receive not one, but multiple cease-and-desist letters. They'll demand your source code, want to know how much money you've made, and will absolutely nuke your personal Facebook and Instagram accounts. But here's the kicker: if you just ignore them entirely, you'll probably be fine. The legal threats are mostly bark with little bite, especially for smaller operations. Twitter/X: The Conditional Enforcer Twitter's approach is more nuanced. They generally don't care if you're scraping public data, but cross the authentication barrier and scrape behind the login wall? That's when the cease-and-desist letters start flying. It's a reasonable middle ground that acknowledges the difference between public and private data access. YouTube/Google: The Hypocritical Giant Google's position on scraping is perhaps the most fascinating. YouTube rarely sends takedown notices for scraping, and there's a good reason: Google has built its entire business model on scraping the internet. Sending aggressive anti-scraping notices when you're literally indexing the entire web would be the height of hypocrisy. TikTok: The Indifferent Dragon TikTok's response to scraping can be summed up in one word: apathy. Whether this stems from different cultural attitudes toward data protection, resource allocation, or simply not caring about Western scrapers is unclear. The practical result is that TikTok scraping faces fewer legal challenges than other platforms. The Bigger Picture What these varied responses reveal is that anti-scraping enforcement is less about technical capability and more about business priorities and legal resources. Smaller platforms often lack the resources or expertise to wage effective anti-scraping wars. The Scraper's Playbook Target the platforms that fight back the least, avoid the ones with deep legal pockets, and always remember that the threat of legal action is often scarier than the actual consequences. Why "Wars" Is the Wrong Word The scraping wars aren't really wars at all. Most platforms are simply too busy dealing with other priorities to put up a serious fight. Truth Social's surrender is just the latest reminder that in the battle between data miners and platform owners, the winners are often determined more by persistence than technical sophistication.

Treasure chest with ESPN logo bursting open, spilling free sports data in JSON format labeled Stats, Scores, API.

ESPN’s Hidden API: How to Access Free Sports Data

Introduction Did you know ESPN gives away an incredible amount of data...for free? Hidden in plain sight, ESPN’s own website uses an open API that anyone can tap into. With a few clicks in your browser’s developer tools, you can unlock a treasure trove of sports stats, play-by-play data, scores, schedules, and more. In this guide, we’ll break down how to access ESPN’s API, what kind of information you can extract, and why this is a goldmine for developers, sports analysts, and data enthusiasts. Where the ESPN API Lives ESPN’s site makes API calls to: https://site.web.api.espn.com/apis This endpoint is wide open. You don’t need authentication keys or tokens, just a simple GET request will return structured JSON data. Real Example: 2016 NBA Finals, Game 7 Let’s take one of the greatest games in sports history, Cavaliers vs. Warriors, 2016 Game 7. Open the ESPN page for the game: Cavs vs Warriors, Game 7 Now, do the following: Right-click → Inspect → Open Network tab. Filter traffic by Fetch/XHR. Look at the requests firing in the background. You’ll notice an endpoint like this: summary?region=us&lang=en&contentorigin=espn&event=400878160 That event parameter is the unique game ID. The Full ESPN API Endpoint Here’s the complete URL for the 2016 Finals Game 7: https://site.web.api.espn.com/apis/site/v2/sports/basketball/nba/summary?region=us&lang=en&contentorigin=espn&event=400878160 Paste it directly into your browser, or hit it with curl, Python, or Node.js, and you’ll see ESPN return a ton of structured JSON data. In Node.js, you would do: What Data Can You Get? The API returns far more than just the score. For a single game, you can access: Team and player stats Play-by-play details Box scores Highlights and recaps Injuries, rosters, and schedules This makes ESPN’s API incredibly powerful if you’re building apps, scraping sports data, or analyzing historical matchups. Here is a sample of the json that gets returned for that game: How to Explore More Data To grab more games, just swap out the event ID in the URL. For example: Change /basketball/nba/ to /football/nfl/ for NFL data. Replace the event=400878160 with another game’s ID. Tip: You can find event IDs just by browsing ESPN game pages and checking the URLs. Why This Matters Sports APIs usually require paid subscriptions, API keys, or limited free tiers. But ESPN is (intentionally or not) giving developers free, open access to world-class sports data. Whether you’re building a fantasy sports tool, a live stats dashboard, or running data analysis, this API can save you time and money. Final Thoughts The ESPN API is one of the easiest ways to get high-quality, real-time sports data, without credentials or paywalls. By leveraging simple GET requests, you can extract detailed stats, play-by-play logs, and game summaries for NBA, NFL, and more. If you’re into sports analytics or app development, it’s worth experimenting with. Looking for More Than ESPN? While ESPN’s API is a fun hidden gem, it’s limited to what they expose on their own site. If you need serious scale or access to other platforms, check out Scrape Creators. Scrape Creators gives you: Ready-made APIs for TikTok, Instagram, YouTube, Twitter (X), Reddit, and more. Pay-as-you-go pricing, no expensive contracts. Fast support from real developers (not bots). Billions of profiles and posts available via clean JSON. Instead of reverse engineering APIs one by one, you can plug into Scrape Creators and start pulling the data you need today. Try Scrape Creators, your shortcut to reliable social media data.

Dusty toolbox labeled Last Resort with Puppeteer and Selenium logos inside, beside clean tools labeled API, HTTP, and JSON

Don’t Ever Use Puppeteer or Selenium (At Least Not Initially)

Introduction When developers start scraping, they often grab Puppeteer or Selenium. After all, these tools spin up a real browser, mimic human clicks, and “just work.” But here’s the truth: headless browsers are almost always the wrong place to start. They’re heavy, slow, costly, and break at scale. You should only reach for them as a last resort when simpler, faster methods don’t cut it. Let’s dig into why. Why Puppeteer and Selenium Shouldn’t Be Your First Choice 1. They’re Painfully Slow Spinning up a Chromium instance for every scrape means high CPU, high memory, and way fewer pages scraped per second. A simple HTTP client can chew through hundreds of pages in the time a browser handles just a handful. 2. They’re Expensive at Scale Running dozens, or hundreds, of browser sessions is server-intensive and eats proxy bandwidth fast. That makes large-scale scraping financially unsustainable. 3. They’re Easier to Detect Headless browsers leak signals. Anti-bot scripts look for subtle mismatches in navigator objects, missing fonts, or other quirks of “fake” Chrome. Unless you’re constantly patching with stealth plugins, you’re painting a target on yourself. 4. They Break Often Every Chrome update risks breaking your setup. Browser automation means dependency hell; version mismatches, patches, and maintenance headaches. When Puppeteer or Selenium Actually Make Sense The key isn’t “this site uses JavaScript → use Puppeteer.” The real question is: 👉 Is reverse-engineering the API more expensive than just running a headless browser? 1. When Reverse Engineering Costs Too Much Some sites intentionally make it painful to scrape their APIs. Endpoints are hidden behind obfuscated scripts. Request signatures are encrypted or constantly changing. Authentication flows are intentionally brittle. Take TikTok’s desktop site as a prime example. Reverse-engineering their signatures and crypto tokens is a rabbit hole. In this case, Puppeteer is often cheaper in developer time, even if slower and heavier in runtime. 2. Short-Term or Proof of Concept Work If you just need to grab a dataset quickly, or test feasibility before investing in a full reverse-engineered scraper, Puppeteer can be a pragmatic shortcut. What to Use Instead (in Most Cases) 1. Direct HTTP Requests Start with lightweight HTTP libraries (axios, got-scraping, Python’s requests). Fast Easy to scale Works with rotating proxies 2. Leverage Hidden APIs Most “JavaScript-heavy” sites still fetch data in the background via JSON/XHR. Use DevTools once to find these calls, then scrape the API directly. 3. Headless Request Libraries Tools like got-scraping give you realistic headers and fingerprints without the overhead of spinning up a browser. Ready to Skip the Headaches? If you don’t want to waste time fighting headless browsers, proxies, and broken scrapers, we built Scrape Creators for you. Fast, scalable APIs for TikTok, Instagram, YouTube, Reddit, Truth Social, and more Simple pay-as-you-go credits (no bloated subscriptions) Built for developers; raw JSON responses, easy integrations, and personalized support Stop struggling with Puppeteer. Start building with clean data. Try Scrape Creators today and focus on shipping your product, not fixing scrapers.

Twitter bird in jail

The Legality of Scraping Twitter in 2025: A Developer's Guide

Web scraping has always existed in a legal gray area, but when it comes to Twitter in 2025, the lines are becoming clearer albeit more restrictive. If you're a developer looking to extract data from Twitter, understanding what's legal and what's not could save you from serious headaches down the road. The Golden Rule: Public vs. Private Data Here's the bottom line that every developer needs to understand: anything in front of the login wall is legal and fair game. This principle was solidified last year when Meta dropped its high-profile lawsuit against BrightData. Meta was furious about the scraping, but they couldn't prove that BrightData was accessing data behind login walls, and that made all the difference legally. The problem? All the really valuable data such as the user’s latest tweets, comprehensive search results, real-time feeds, now sits behind Twitter's login wall. This represents a fundamental shift in how Twitter operates compared to its pre-Elon era. How Twitter Changed the Game Before Elon Musk's acquisition, Twitter was much more open. Search results were publicly accessible, and you could scrape chronological tweets without authentication. Those days are long gone. Now, if you visit someone's Twitter profile in an incognito browser, you'll discover you can only access their top 100 tweets. Everything else requires logging in. This change has dramatically reduced what's legally scrapable from Twitter. The platform has essentially moved most of its valuable content behind a paywall, making legitimate scraping much more challenging. Creative Workarounds (With Limitations) Some developers have found interesting ways to work around these restrictions. One clever hack involves using Google search to retrieve a user's last 10 tweets. You can search for something like "twitter username" and Google will often return recent posts in the results. However, this method is finicky and doesn't work consistently. For unknown reasons, it fails for certain users entirely. While creative, these workarounds highlight the lengths developers must go to access what was once freely available public data. The Risky Business of Login-Based Scraping Despite the legal restrictions, Twitter scrapers continue to proliferate. The demand for Twitter data is simply too high for developers to ignore completely. Third-party services offering Twitter scraping APIs have popped up on platforms like RapidAPI, often at incredibly attractive price points. However, the story of SocialData.tools serves as a cautionary tale. Created by my friend Brian, the service gained popularity among developers seeking Twitter data. Twitter cracked down hard, not only shutting down the service but reportedly nuking Ships' personal Twitter profile and forcing him to eliminate most of his API endpoints. This aggressive enforcement demonstrates that while these services exist, they operate in legally questionable territory. Any scraping that occurs behind the login wall violates Twitter's terms of service and potentially breaks the law. Your Legal Options in 2025 So what can developers do if they need Twitter data while staying above board? Option 1: Use Twitter's Official API The safest route is Twitter's official API. While it comes with rate limits and costs, it provides legitimate access to Twitter data with proper authorization. Option 2: Stick to Public Data Only If you must scrape, limit yourself strictly to publicly accessible content that doesn't require authentication. Remember, this severely limits what you can access. Use Scrape Creators for this. Option 3: Alternative Services Use an API on Rapid API called Old Bird V2. It has very generous pricing plans, but does scrape behind the login. But has been around for years. The Bottom Line The landscape of Twitter scraping in 2025 is clear: respect the login wall. While the temptation to use unauthorized scrapers is understandable given the attractive pricing and extensive data access they offer, the legal and professional risks simply aren't worth it. The recent crackdowns show that Twitter is serious about protecting its data, and developers who cross the line face real consequences. For sustainable, long-term projects, investing in official APIs or building solutions around truly public data remains the only viable path forward.

Infographic titled ‘5 Web Scraping Mistakes’ showing icons and checklist for common errors: relying on Puppeteer, scraping behind a login, parsing HTML instead of APIs, using a plain HTTP library, and scraping without a proxy

Web Scraping Best Practices: 5 Common Mistakes to Avoid

Web scraping can be one of the most powerful tools in your data arsenal...if you do it right. Done poorly, it leads to headaches: broken scripts, wasted resources, or even compliance risks. In this guide, we’ll walk through five common web scraping mistakes developers make and how to avoid them. Whether you’re building a prototype or scraping at scale, following these best practices will save you time, money, and frustration. 1. Relying on Puppeteer or Selenium as Your First Option It’s tempting to jump straight into browser automation tools like Puppeteer or Selenium. They sound impressive, but they should be your last resort, not your first. Why? Slow and expensive at scale: launching headless browsers for every request chews up CPU and memory. Harder to deploy: especially if you’re scaling across cloud servers. Most sites don’t require it: static HTML, APIs, or lightweight scraping libraries often do the job better. Best Practice: Start with lightweight HTTP libraries. Keep Puppeteer in your toolbox, but only use it as a last resort. 2. Scraping Behind a Login Scraping behind login walls (like Facebook, LinkedIn, or Instagram) is risky. Not only does it raise legal and ethical concerns, but it also adds unnecessary complexity: maintaining sessions, handling CAPTCHAs, and being easily flagged by anti-bot systems. Best Practice: Focus on public-facing data. Many sites expose the same information via APIs or pre-login endpoints. Challenge yourself to find the open data path. And often it’s easier, cleaner, and more sustainable. 3. Parsing HTML Instead of Using APIs Another rookie mistake: scraping raw HTML for data that’s already being fetched via an underlying API call. HTML parsing = fragile (changes to page layout break your scraper) APIs = cleaner JSON (structured data, fewer headaches) Avoid double work: parsing HTML and handling browser rendering when you could just hit an endpoint directly. Best Practice: Before writing a single scraper, inspect the network tab in your browser’s dev tools. If the content loads dynamically, chances are there’s a hidden API request you can mimic. 4. Using a Generic HTTP Library Yes, you can scrape with Axios, Fetch, or Python’s Requests library. But at scale, these options lack the robustness needed for modern web scraping. Better Tools: got-scraping (Apify): purpose-built for scraping, handles headers, cookies, retries, etc. Impit (Apify): a solid scraping-friendly HTTP client. Best Practice: Use a library built for scraping, not just for generic HTTP calls. You’ll avoid anti-bot pitfalls and cut down debugging time. 5. Scraping Without Proxies Perhaps the biggest mistake: not using proxies. Without them, you’ll hit rate limits, get blocked, or worse, burn your IPs. Recommended Providers: Decodo (Smartproxy) Webshare Evomi Bright Data Best Practice: Always rotate proxies and pair them with proper headers (user agents, etc) for more natural traffic patterns. Final Thoughts Web scraping is both art and engineering. Avoiding these five mistakes: overusing Puppeteer, scraping behind logins, parsing fragile HTML, using the wrong HTTP library, and skipping proxies, will set you up for faster, more reliable, and more scalable scraping projects.

Digital composite showing neon green Crocs, tan UGG boots, a Celsius orange energy drink can, and a Barbie movie poster. TikTok-style comment bubbles read 'I need these ASAP,' 'Sold out everywhere 😭,' and 'Obsessed 🔥.' A blue stock market chart rises upward in the background with the text overlay: 'It was all in the comments.'

How One Investor Turned $20K into $80M Just by Reading TikTok Comments (And How You Can Too)

Most people scroll through TikTok comments for entertainment. Chris Camillo, on the other hand, turned it into an $80 million investing strategy. Without a background in Wall Street finance, Chris pioneered a method he calls “social arbitrage”, essentially spotting cultural shifts in real time before traditional analysts even notice them. His secret weapon? TikTok comments. Why TikTok Comments Matter for Investing Wall Street firms spend millions on data feeds, research reports, and predictive models. But Chris realized something most people overlooked: “We can watch the world unfold in real time simply by reading comments.” TikTok comments are where consumers express raw, unfiltered emotions about products, trends, and cultural moments. When UGG Minis exploded, he saw it first in TikTok comments. When Crocs made a comeback, the hype was obvious from thousands of passionate replies. When misinformation slowed down Celsius drinks, he knew it before earnings reports confirmed it. Comments aren’t just noise, they’re early signals of demand shifts that can move billions in market value. The Problem: Manual Research Takes Thousands of Hours Chris admitted he spends 4 hours a night, seven days a week, reading TikTok comments. Over nearly a decade, he’s read close to a million of them. That’s not realistic for the average investor or entrepreneur. Most people don’t have the time (or obsession) to manually sift through endless comment sections to find the next big trend. The Solution: Automating TikTok Comment Scraping This is where tools like the Scrape Creators API come in. Instead of manually clicking through videos, you can programmatically scrape TikTok comments at scale. With our TikTok Comments API, you can: Collect comments from any TikTok video automatically. Analyze sentiment (positive, negative, neutral) across thousands of comments. Spot breakout trends early, before Wall Street catches on. Build your own “social arbitrage dashboard” to track hype around products, brands, or niches. Here’s a simple example request using our API: https://api.scrapecreators.com/v1/tiktok/video/comments?url=https://www.tiktok.com/@stoolpresidente/video/7540421471189945631 Here's a sample response: Real-World Use Cases Retail Investing – Track products trending in comments (like energy drinks, shoes, or tech gadgets) before earnings season. E-commerce – See what customers are raving about, then stock or resell those items. Market Research – Identify pain points in real time by monitoring sentiment around competitors. Social Listening SaaS – Build a tool that analyzes TikTok conversations at scale and sells insights to brands. Why This Matters Now Culture shifts faster than ever. Trends that start as a TikTok meme can translate into billions of dollars in sales (and investment opportunities) within weeks. Chris spent nearly a decade manually decoding this process. With APIs like Scrape Creators, you don’t need to. You can automate the collection of TikTok comments and focus on building insights, or even an entire SaaS platform around them. Ready to Spot Trends Before Wall Street? Stop scrolling and start scraping. With the Scrape Creators TikTok Comments API, you can automatically collect and analyze comments at scale, the same raw data Chris used to turn $20K into $80M. Try it out for free today, no credit card required, first 100 requests are on us.

image of youtube search for tariffs on the left and the json representation of the search results on the right

Unlock YouTube Insights with Scrape Creators Unofficial API, Fast, Flexible, and Feature Rich

Introduction In a world where content reigns supreme, getting actionable data from YouTube can supercharge your content strategy, SEO, and analytics. Instead of dealing with the cumbersome official YouTube Data API with its rate limits, quota issues, and complex auth, you can lean on Scrape Creators Unofficial YouTube API for real time access to search results, channel stats, video & short listings, transcripts, and comments, all with a sleek REST interface. 1. Search YouTube Videos & Shorts Need to identify trending videos or shorts quickly? Scrape Creators offers endpoint support to search YouTube directly and return results in JSON. It handles page parsing, metadata extraction, and bypasses roadblocks like IP bans or bot detections, so you can focus on insights, not scraping mechanics. Use cases: keyword research, trend monitoring, competitive content discovery. Benefit: Faster setup and more granular, flexible results than official API. 2. Fetch Channel Details Want to gather channel details like subscriber count, video counts, descriptions, and metadata? There’s an endpoint just for that. No need to manage OAuth or API keys beyond Scrape Creators simple API key authentication Use cases: influencer identification, competitor analysis, channel profiling. Benefit: Straightforward, reliable access to public channel data. 3. Retrieve Shorts & Videos of a Channel Aggregate all the content types a creator publishes video posts and YouTube Shorts with Scrape Creators API. You can retrieve structured lists of videos and Shorts from any channel, grouped by type. Use cases: content gap spotting, format performance comparison. Benefit: Unified retrieval across content formats—no switching endpoints. 4. Lightning Fast Transcripts Transcripts are essential for SEO, accessibility, and search indexing. Scrape Creators delivers lightning-fast transcript retrieval. While the official YouTube API doesn’t offer transcripts directly, open-source tools like the YouTube Transcript API (Python package) do, but they rely on scraping and have to manage parsing on your end Scrape Creators skips that hassle by giving transcripts in JSON, ready for your workflows. 5. Extract Comments Comments are gold for sentiment analysis, engagement metrics, and trending topics, yet the YouTube Data API limits access. Scrape Creators includes comments extraction as part of its API offering. Output includes comment text, author and timestamp, Great for analyzing viewer sentiment, feedback, or surfacing discussion trends. Examples Search Lets say you want to search for videos about tariffs. Scrape Creators makes it super easy, all you have to do is make a GET request like this: https://api.scrapecreators.com/v1/youtube/search?query=us tariffs&includeExtras=true includeExtras is an optional param that will return the like + comment count and description The response will look something like this: You'll need continuationToken to get additional pages of results. Channel Details Lets say you want to get the subscriber count, country, socials, and avatar of a channel, lets say https://www.youtube.com/@IShowSpeed Just make a GET request using his handle (IShowSpeed) https://api.scrapecreators.com/v1/youtube/channel?handle=ishowspeed The response will look like: Channel Videos If you want to get the videos of a channel, like MrBeast, here's how you would do it: Make a GET request like so: https://api.scrapecreators.com/v1/youtube/channel-videos?handle=mrbeast&includeExtras=true The response will look like: Transcript Let's get the transcript of one of those videos, like this one: https://www.youtube.com/watch?v=TDv56whosPQ Well, you'd just make a GET request like so: https://api.scrapecreators.com/v1/youtube/video/transcript?url=https://www.youtube.com/watch?v=TDv56whosPQ Example response: Comments Now lets get the comments on that video. To do that you would make a GET request to: https://api.scrapecreators.com/v1/youtube/video/comments?url=https://www.youtube.com/watch?v=TDv56whosPQ Example Response: In Summary If you're serious about enriching your SEO, analytics, content discovery, or influencer strategies using YouTube data, Scrape Creators unofficial YouTube API is a compelling solution. It offers: Powerful, ready-to-use endpoints for search, channels, videos, transcripts, and comments Real-time data sans rate limits or OAuth frustrations A clean REST interface with free tier access Reliability built for production apps

image of tiktok shop searching for makeup brush and the json representation of that search on the right

TikTok Shop API: How to Search and Scrape TikTok Shop Products

TikTok Shop is super popular, letting creators and brands sell products directly inside TikTok. But if you want to research products, track shops, or analyze performance at scale, TikTok doesn’t give you much visibility. That’s where the Scrape Creators TikTok Shop Search API comes in. This endpoint lets you enter any search term and instantly find TikTok Shop products. From there, you can grab product urls and feed them into the TikTok Product API for deeper insights. What Can You Do With It? Once you’ve found products in TikTok Shop, you can scrape their details and unlock valuable data: Get the shop’s TikTok profile → Identify the actual seller and see what else they sell. Check real stock levels → Know how many units are available (great for demand & trend analysis). See TikToks promoting the product → Analyze which influencers are pushing it, and how they’re marketing. With this data in hand, you can: Find winning products: Spot trending items before they go viral. Monitor competitors: See what shops in your niche are selling and how well they’re doing. Build your own TikTok Shop dashboard: Track product performance, pricing, and stock automatically. Fuel your influencer marketing strategy: Identify creators promoting specific products and reach out for collaborations. Power custom e-commerce tools: Enrich your Shopify or Amazon arbitrage workflows with TikTok Shop data. Example Workflow Step 1 Call the TikTok Shop Search API with a keyword like makeup brush and the amount of products you want (TikTok caps you at around 500 I believe) How you would do that would be making a GET request like this: https://api.scrapecreators.com/v1/tiktok/shop/search?query=makeup brush&amount=60 Step 2 Get back a list of products including title, price, id, url, sold_count, and seller_info. JSON response will look something like this: Step 3 Plug a product url into the TikTok Product API to see: The seller’s TikTok profile Exact stock numbers TikToks driving sales For example, for the product above we would do: https://api.scrapecreators.com/v1/tiktok/product?url=https://www.tiktok.com/shop/pdp/flat-foundation-brush-by-paw-paw-rose-gold-f36-for-blending/1729410103929704593&get_related_videos=true And then the response looks something like: Use this data to validate products, track demand, or export to your internal tools. Why Use Scrape Creators? Fast & reliable: APIs designed for scale. No reverse engineering or parsing headaches: We handle the scraping logic and return clean JSON Flexible use cases: From product research to full blown analytics dashboards. Final Thoughts The TikTok Shop API is perfect for anyone who wants to research, monitor, or build tools around TikTok commerce. Whether you’re an agency, e-commerce entrepreneur, or developer, you can quickly plug it into your workflow. Try it now! 100 free requests!

Image of ninja twitch profile on the right and the json representation on the left

Scrape Twitch Creator Profiles with the Scrape Creators Unofficial Twitch Profile API

Introduction If you’ve ever tried using Twitch’s official API, you know the struggle, OAuth authentication, rate limits, and restricted endpoints make it nearly impossible to quickly pull the creator data you need. The Scrape Creators Unofficial Twitch Profile API solves that. With a single request, you can scrape any Twitch creator’s profile and get detailed JSON data in seconds, no login, no API key from Twitch required. Whether you’re building a streamer analytics dashboard, doing market research, or finding influencers for campaigns, this API gives you all the essentials, instantly. What You Can Scrape from Twitch Profiles? With Scrape Creators Twitch Profile API, you can get: Basic Profile Info: username, display name, profile image, bio Follower Count: total followers for the creator Social Links: YouTube, Twitter/X, Instagram, Discord, and more Top Clips: most popular clips from their channel, with video URLs and titles Similar Streamers: related creators in the same niche or category Example response (simplified): How to Use the Unofficial Twitch Profile API Making a request is simple: Endpoint: GET https://api.scrapecreators.com/v1/twitch/profile?handle=ninja Example in Node.js: Use Cases Influencer Marketing: find Twitch creators in your niche with large followings and active audiences Competitive Analysis: compare similar streamers to see who’s gaining traction Market Research: analyze follower growth and social reach of gaming influencers Content Discovery: surface trending clips from top Twitch channels Why Use Scrape Creators Over the Official Twitch API? No OAuth: skip the hassle of getting client IDs and secrets, get started immediately No Rate Limit Headaches: designed for higher request volumes Instant JSON: no parsing headaches or multiple calls for basic data Conclusion If you need Twitch creator data without the friction of the official API, the Scrape Creators Unofficial Twitch Profile API is the fastest way to get it. You can pull profile details, follower counts, socials, clips, and similar streamer recommendations in seconds, perfect for marketing, analytics, and research tools. Get started with the Twitch Profile API

Image of Zucks threads profile on the left and the json representation on the right

Scrape Threads Data Instantly with the Scrape Creators Unofficial Threads API

Meta’s Threads is quickly becoming a major player in the social media space, but if you’ve ever tried to access their official API, you know it’s no walk in the park. To use it, you need to create a developer app, connect a business account, and navigate a pile of review requirements before you can make a single request. For developers, marketers, and analysts who just want to pull public Threads data right now, that’s… less than ideal. That’s where the Scrape Creators Unofficial Threads API comes in. With our API, you can start making requests immediately, no business account, no app review, no OAuth flow. Just grab your API key and you’re ready to go. What You Can Do with the Unofficial Threads API We’ve built endpoints to cover the most useful data on Threads. Here’s what’s available: 1. Profile Retrieve complete public profile data for any Threads user. Returns: username, bio, profile image, follower count, following count, and more. Example use cases: Build an influencer database Monitor competitor profiles Enrich social media reports 2. Posts Pull all public posts from a user in chronological order. Returns: post text, images, videos, timestamps, and engagement stats. Example use cases: Track posting frequency and engagement trends Archive content for analysis Study content formats that perform well 3. Post Retrieve details for a single post by ID. Returns: full text, media, engagement stats, and metadata. Example use cases: Run deep sentiment or keyword analysis Share a single post in another app Store high-value posts for later reference 4. Search by Keyword Search Threads posts by a keyword or phrase. Returns: matching posts with their metadata. Example use cases: Monitor brand mentions Track trending industry topics Discover organic conversations 5. Search Users Find users based on their name or bio keywords. Returns: usernames, bios, profile links, and profile stats. Example use cases: Identify influencers in your niche Build targeted outreach lists Research communities around specific interests Example API Request Here’s how easy it is to start pulling Threads data with Scrape Creators: Sample JSON response: Why Use the Unofficial Threads API Instead of the Official One? Real World Use Cases Influencer Marketing: Discover and track relevant creators in your niche Brand Monitoring: Get alerted whenever someone mentions your brand Content Analysis: See what formats, hashtags, and posting times work Market Research: Understand audience sentiment on trends and products Archiving & Compliance: Keep a historical record of posts for audits Getting Started in 3 Steps Sign Up: Create a free account at Scrape Creators. Get Your API Key: Copy it from your dashboard. Make Your First Request: Use curl, JavaScript, Python, or your favorite language.

Image with pinterest search of chocolate cake on the left and the json representation on the right

Scrape Creators Unofficial Pinterest API - The Easiest Way to Get Pinterest Data

If you’ve ever tried using Pinterest’s official API, you know the drill, you need a business account, and even then the documentation is hard to navigate. You just want to search, get pins, boards, or a user’s pins, but instead you’re stuck wading through permissions, auth flows, and limited endpoints. That’s exactly why we built the Scrape Creators Unofficial Pinterest API, no hoops to jump through, no confusing auth, just JSON results instantly. Why Use the Unofficial Pinterest API? No Business Account Required – Anyone can use it. Fast JSON Responses – Get clean, structured data you can use right away. Simple Search – Search for any keyword and get relevant pins in seconds. Rich Data – Each pin includes: Image URLs (full-size) Pin link URL (destination) Video details (if available) Recipe metadata (if applicable) Board details User profile info Example: Search Pinterest Pins with the API Let’s say you want to scrape Pinterest dessert recipes for “chocolate cake” and instantly get all the image URLs, recipe links, and even the ingredient lists. Example Response: In just a few lines of code, you now have: Direct links to each pin’s full-size image The original recipe source URL Board and user info for categorization Recipe ingredients and instructions if Pinterest has them Available Endpoints Search Pins – Find pins by keyword. Get Board Pins – List all pins from a specific board. Get Boards – See all boards from a user Get Individual Pin – Pull detailed info on a single pin. Real-World Use Cases Recipe Aggregation Pull recipe pins (ingredients, steps, links) into your own cooking app or website. E-Commerce Inspiration Track trending product pins and see what’s getting shared in your niche. Content Curation Power a blog or social media scheduler with the latest visual content from Pinterest. Market Research Analyze how people are pinning products, styles, and trends in real time. Video Pin Discovery Find all video pins for a topic (e.g., “DIY furniture”) and embed them in your site. Why This Beats the Official Pinterest API Pinterest’s official API is designed for marketers and advertisers, not developers who want direct content access. With Scrape Creators’ Unofficial Pinterest API, you skip the bureaucracy and get exactly what you need, data, not red tape. Try It Today Whether you’re building a B2C app, doing Pinterest SEO research, or just want instant Pinterest data in JSON, the Scrape Creators Unofficial Pinterest API gets you there faster. Get started here and start pulling Pinterest data in seconds.

Screenshot of the Goli Nutrition TikTok Shop

TikTok Shop Products API – Scrape Products, Track Sales, and Analyze Marketing Strategies

TikTok Shop is exploding in popularity, giving brands, sellers, and affiliates a powerful way to sell directly through TikTok videos. But if you’ve ever tried to track product data, stock levels, or sales trends across TikTok Shop, you know TikTok doesn’t make it easy. That’s where the Scrape Creators TikTok Shop Products API comes in. With just a TikTok Shop store URL, you can retrieve every product that store is selling, including pricing, availability, images, and more. What Is the TikTok Shop Products API? Our TikTok Shop Products API lets you pull all products from any TikTok Shop store by passing the store’s URL, for example: https://www.tiktok.com/shop/store/goli-nutrition/7495794203056835079 Once you have that, you can: Scrape the full product list from any TikTok Shop Get real-time stock quantities and price data Collect product images and titles Track affiliate videos promoting each product Link products back to the creator’s TikTok account Example API Call Get API key Make a GET request with an x-api-key header to: https://docs.scrapecreators.com/v1/tiktok/shop/products?url=https://www.tiktok.com/shop/store/goli-nutrition/7495794203056835079 Example Response Going Deeper - Scraping Individual Product Details Once you have the product IDs, you can use our TikTok Product API to pull even more details: *Exact* inventory count Product descriptions Full-size images Affiliate videos TikTok account selling it And with our TikTok Transcript API, you can even get the script, and then extract the hook from affiliate videos, perfect for analyzing what messaging converts best. Use Cases for Businesses Whether you’re a seller, agency, or competitor researcher, here’s how this API can help you: 1. Competitor Product Tracking See what your competitors are selling on TikTok Shop, monitor their stock levels, and track new product launches in real time. 2. Sales Trend Monitoring Watch stock quantities change over time to estimate sales volume and spot fast-selling items. 3. Affiliate Marketing Research Find influencers already promoting a product and study their content strategy. 4. Product Research for TikTok Shop Sellers Identify high-demand products by analyzing prices, descriptions, and marketing videos. 5. Creative Analysis Pull transcripts from top-performing affiliate videos to reverse-engineer hooks, scripts, and offers that drive conversions. Important Note on URLs Right now, the API requires a TikTok Shop store URL, not just the TikTok username. For example: ✅ Works https://www.tiktok.com/shop/store/goli-nutrition/7495794203056835079 ❌ Doesn't work (yet) https://www.tiktok.com/@golinutrition Get Started Today If you want to scrape TikTok Shop products, track sales trends, and analyze marketing strategies, our TikTok Shop Products API is the fastest way to do it. API Docs: TikTok Shop Products API TikTok Product API TikTok Video Transcript API Start scraping today, 100 free requests.

Graphic with text: pay as you go on the left, and monthly subscription on right

Best Pay-As-You-Go Scraping APIs (No Monthly Commitment Required)

Most software these days wants to lock you into a monthly subscription. And honestly… that’s kinda lame. Unless there’s no way to measure exact usage, a flat monthly fee doesn’t always make sense. The best pricing models are the ones where the value you get from the software is directly aligned with what you pay. That’s why pay-as-you-go APIs are so great. A perfect example is the OpenAI API, you’re charged for usage, and if you don’t use it, you don’t pay. Simple. Fair. Transparent. The same idea applies to web scraping APIs. If you only scrape occasionally, why commit to a monthly plan you might barely use? Below are the only scraping APIs that are truly usage-based, and a few that aren’t. True Pay-As-You-Go Scraping APIs (No Subscription) 1. Scrape Creators - Social Media Scraping Without Subscriptions Scrape Creators is built for social media data extraction. It offers API endpoints for TikTok, Instagram, YouTube, Twitter (X), Facebook, and more. Why it’s awesome: ✅ 100% pay-as-you-go pricing – no subscriptions ✅ Credits *never* expire ✅ JSON-ready responses (no messy HTML to parse) ✅ Built specifically for creator & influencer data ✅ Easy documentation & fast setup If you need to pull data on creators, posts, profiles, or even ad libraries this is one of the most cost-effective, commitment-free options out there. 2. Serper.dev - Google Search, Maps & Shopping Data Serper.dev is a Google Search API that covers: Google search Google Maps & Places Google Shopping results Why it’s awesome: ✅ Usage-based pricing with no monthly minimum ✅ Fast, clean JSON responses ✅ Focused entirely on Google-related data sources If your scraping project is about ranking data, map locations, or product listings, Serper.dev makes it dead-simple. *Credits do expire after 6 months, which kinda sucks. Scraping APIs That Require Monthly Commitments While these APIs can be powerful, they require a monthly plan—even if you don’t use them much. Firecrawl.dev - General-purpose scraper that can target almost any page. Has AI-assisted parsing but still requires a subscription. ScrapingBee - Another general-purpose scraper with AI features, but you’ll need a monthly plan. Apify - Huge library of “Actors” (pre-built scrapers). Requires a monthly plan plus usage fees. SerpAPI - Popular Google Search API with subscription pricing. SearchAPI.io - Another SERP data API, also subscription-based. Final Thoughts If you hate being locked into software you barely use, true pay-as-you-go scraping APIs are the way to go. For social media data: go with Scrape Creators For Google search, maps, and shopping data: choose Serper.dev Everything else? Great tools, but you’ll need to commit to a monthly plan.

Image with the text Top Proxy providers in 2025

Scraper's Honest Review: Top Proxy Providers in 2025 (Plus a Bonus Pick)

If you’re running a serious scraping operation in 2025, proxies are your lifeblood. They’re the difference between pulling millions of rows of clean data or burning through IP bans and timeouts. At Scrape Creators, I've tested many proxy providers over the years, and today I’m giving you the real talk about the ones I’ve actually used (or seriously considered). This list isn’t just a ranking of "top" proxies, it’s my honest experience with each provider: what worked, what sucked, and what you should expect if you try them. Let’s get into it. 1. Decodo (formerly Smartproxy) Price: starts at $3/GB residential Type: Rotating Residential, Static Residential, Datacenter I’ve been a long-time user of Smartproxy, which recently rebranded as Decodo. Honestly, they're probably still one of the better deals out there for web scraping. Their rotating residential proxies are solid. I rarely have day to day issues with them. That said, they really pissed me off when they randomly changed their proxy endpoint URLs and broke a bunch of my scripts. And then they rebranded weirdly. If you go with Decodo, be ready for occasional reconfigurations. Verdict: Still one of my go-tos for daily scraping. Just expect once a quarter or once a year to have to change a domain or something. 2. Evomi Price: $0.49/GB residential, incredibly cheap Type: Rotating Residential, Static Residential Evomi looks like a dream on paper: dirt-cheap residential proxies and simple dashboard. But once I started running real volume through them, the problems showed up fast. Requests would hang, not fail, just hang, which is arguably worse because you can't even retry. Their static proxies had the same issue. Customer service? Unprofessional as hell. And they don't communicate outages, which became frequent toward the end when I used them. I still use them, but not to a large scale. I have to pray that nothing breaks when I use them. Verdict: Not worth the headache, no matter how cheap. If they fixed their infrastructure, happy to divert all traffic back to them. 3. Webshare Price: Starts at $3.50/GB residential Type: Static Residential, Datacenter, Rotating Residential I haven’t personally used Webshare, but I know a lot of scrapers who do. For static IPs, they’re probably the cheapest game in town, $0.30 per IP starting out. You’ll want to test heavily before going all-in, but for small projects or non-sensitive scraping, they’re hard to beat on price. Verdict: Budget-friendly static proxy provider. Worth testing for low-risk scraping. 4. IPRoyal Price: $3.50/GB residential Type: Residential, Mobile, Datacenter Another one I haven’t run at scale myself, but I’ve seen other developers use them without major complaints. They offer a wide variety of proxy types (including mobile), which is a plus if you’re scraping harder targets. They haven’t earned a permanent spot in my rotation yet, but they’re on my radar. Verdict: A wildcard option. Could be solid, but I’d run controlled tests before relying on them. 5. DataImpulse Price: Starts at $1/GB (rotating residential) Type: Rotating Residential, ISP, Datacenter This is one of the newer players I’ve tried. For $1/GB, it’s honestly a steal. I’ve only used them lightly, as a backup when other proxies failed, but I had zero problems. No hangs, no weird errors. For the price, the performance was impressive. Thinking about switching back to them for more regular usage just based on cost-effectiveness alone. Verdict: Great bang-for-your-buck proxy provider. Could be the hidden gem of this list. Bonus: Bright Data Price: $4.20/GB (residential) Type: Residential, ISP, Mobile, Datacenter Bright Data (formerly Luminati) is the biggest and most enterprise-tier proxy provider in the space. Their founder, Or Lenchner, is a genuinely good guy, and their platform is solid. The only downside? Price. They are the most expensive out there. At $4.20+/GB, you’re definitely paying premium. If you’re running a lean operation, it might be hard to justify the cost. Verdict: Enterprise-grade performance, if you can afford it. Final Thoughts Your proxy provider can make or break your scraping workflow. My recommendation: Decodo. As of August 2025 that is my preferred proxy provider. Competitive pricing and you don't have to babysit the proxies. But if you are scraping social media or ad libraries, we can handle all this for you, don't even worry about proxies. If you just want clean data and a simple scraping experience, skip the proxy headaches entirely. Use Scrape Creators, we handle all the proxy management, rotation, retries, and edge cases for you. Focus on building your product. We'll handle the messy stuff.

Image of Instagram profile on left and the json of their age and gender on right

How to Get the Estimated Age & Gender of a Social Media Creator (Using Just Their Profile Pic)

Ever wish you could instantly figure out how old a creator is, or whether they're male or female, just by looking at their profile picture? Well…now you can! With Amazon Rekognition, you can analyze any profile picture and get things like: Age range (e.g. 25–34) Gender (Male/Female) Confidence score (%) Whether they’re smiling, wearing glasses, have a beard, etc. Even their emotion (happy, sad, confused, etc.) This is crazy powerful, especially for anyone doing influencer research, ad targeting, or demographic analysis. How It Works To get this kind of insight, here’s what you’d need to do: Scrape the creator’s social profile Download their avatar/profile image Send it to Amazon Rekognition Boom. Get the age/gender back Here’s an example of the AWS Rekognition portion in Node.js: Pretty slick, right? Or… Just Use Scrape Creators (No Code Needed) Don’t worry, we already built this for you. With Scrape Creators, you can: Just paste in a profile URL We scrape the profile + download the image Then run it through Amazon Rekognition for you You get back age, gender, confidence It’s one simple API call. No scraping or AWS setup required. All you need is a GET request to our API, like this: https://api.scrapecreators.com/v1/detect-age-gender?url=https://x.com/adrian_horning_ Then you will get a response that will look like: And this is scary accurate. When I got that picture taken I was 32 🤯 Try It Now Use our /detect-age-gender endpoint and pass a social profile URL. 📄 Docs here Or check out our full suite of APIs for TikTok, Instagram, YouTube, Reddit and more, including ad libraries.

Image of Goli bottle with estimated daily revenue

How to See How Much a TikTok Shop is Making Daily (And Build Your Own FastMoss/Kalodata)

You ever wonder how much money a TikTok Shop product is making per day? Well guess what, it's actually super easy to estimate, and I’ll show you how to build your own version of FastMoss or Kalodata using public data and Scrape Creators. Let’s dive in. The Basic Idea Get the product URL Call the Scrape Creators endpoint to get the stock + price Store it in your DB 24 hours later, call it again Subtract yesterday’s stock from today’s Multiply by the price Bada bing, bada boom: daily sales estimate Example Product Let’s use this product, from popular store, Goli Nutrition: https://www.tiktok.com/shop/pdp/goli-ashwagandha-gummies... How to Do It All we'd need to do is make a GET request to Scrape Creators like this: https://api.scrapecreators.com/v1/tiktok/product?url=https://www.tiktok.com/shop/pdp/goli-ashwagandha-gummies-with-vitamin-d-ksm-66-vegan-non-gmo/1729587769570529799 Check out the docs for more information. Then get the stock and price_val (Note: price_val is a string, so you'll want to convert it into a float first) Just store stock and price in your DB every day per product. Do a simple subtraction the next day to get: Done ✅ Why This Is Useful Find winning products TikTok creators can search for what's selling well and make videos on those products Spy on competitors Validate product demand before selling Track TikTok Shop trends Build a FastMoss competitor Attract brands & creators with actual sales data Want to Build This at Scale? Scrape Creators makes it dead simple to scale this out. Just loop through product URLs, record daily stats, and you’ve got a mini FastMoss/Kalodata. Start with this endpoint: https://docs.scrapecreators.com/v1/tiktok/product

Screenshot of the new TikTok Shop

HUGE Update: TikTok Shop is Now Public on Desktop (No Login Needed!)

Big news just dropped for developers, data geeks, and SaaS builders... TikTok Shop is now fully accessible on desktop, publicly, and without requiring a login. Yeah, you heard that right. That means we can scrape the hell out of it. Why This Is Game Changing Until now, TikTok Shop was mostly locked down behind mobile apps and required authentication. Scraping product listings, affiliate videos, or shop details was a serious pain, often requiring workarounds, reverse engineering, or mobile device emulation. But now? It’s wide open. And that changes everything. You can now easily: Scrape hundreds or thousands of TikTok Shop products See affiliate videos promoting those products Get *exact* stock counts Scrape product + shop details (including the shop’s TikTok profile) Explore entire shop inventories All of this data is now sitting there, publicly, waiting to be collected. The Data Gold Rush Has Begun If you’ve ever thought about building a product around TikTok Shop data, now is the time. Massive SaaS products like: Fastmoss Kalodata Are already built on scraping this exact type of TikTok data. But until now, they had to jump through hoops to get it. With TikTok Shop open on desktop, the barrier to entry is lower than ever. This is the perfect time to build a competitor. Whether you’re creating a dropshipping tool, an affiliate campaign analyzer, or a product research dashboard, the raw data is just sitting there! Scrape Creators Has You Covered We already have a ready to use endpoint that scrapes TikTok Shop product data: TikTok Product Details API It returns: Full product details (title, price, images, etc.) Exact stock available TikTok shop details (including TikTok url) Affiliate videos promoting the product And that’s just the beginning. More endpoints are coming soon to help you: Scrape full shop inventories Get all affiliate content for a given product Discover top-selling items across TikTok Shop Stay tuned on Scrape Creators and our Docs page for updates. What’s Next? Right now, TikTok still doesn’t expose the product link directly on desktop video pages, that’s still mobile-only. But we’re hopeful that’ll change soon. Once they make product links more visible in video metadata, you’ll be able to tie videos to exact products even more easily. TL;DR TikTok Shop is now publicly available on desktop No login required = easy scraping Get product details, affiliate videos, shop info, stock counts The data is wide open, and it’s the perfect time to build tools around it Check out our TikTok Product API to get started instantly 🔥 Let the scraping begin. Got questions or want early access to upcoming endpoints? Email me adrian@thewebscrapingguy.com or hit up Scrape Creators.

Picture of a Tiktok users followers on the left and the json representation on the right

How to Get Someone’s TikTok Followers (and What You Can Do With Them)

If you’ve ever wanted to see who follows a certain TikTok creator, TikTok doesn’t exactly make that easy… unless you know where to look. With Scrape Creators, you can pull *thousands* of a creator’s followers, quickly, reliably, and at scale. What You Can Get Using our TikTok Followers endpoint, you can grab: Username (unique_id) Region (country) Avatar (profile picture URL) Biography (signature) Example JSON snippet: *you can't view the avatars because the url's expire after a while How to Get the Data Check out the docs: https://docs.scrapecreators.com/v1/tiktok/user/followers Sign Up For an API Key Make a GET request to https://api.scrapecreators.com/v1/tiktok/user/followers *Make sure you put the API key in a x-api-key header Paginate with min_time Use min_time from the response and pass that as a query parameter to get more followers! The Cool Stuff You Can Do With That Data Once you’ve got a creator’s followers, that’s just the start. Here’s where it gets interesting: Enrich with profile info – Use our TikTok Profile endpoint to get bios, follower counts, See their content – Use our TikTok Profile Videos endpoint to pull their videos to understand what they post and how well they perform. Audience demographics – Use our Detect Age & Gender endpoint to figure out the gender and approximate age of each follower. Combine that with the region field and you’ve got a full breakdown of where a creator’s audience is from and who they are. Competitor analysis – See who follows your competitors, then reach out or target similar audiences. Lead generation – Build marketing lists of highly engaged users in your niche. Why Use Scrape Creators? We make it dead simple to get clean, structured TikTok data without dealing with browser automation or getting blocked: High request limits Multiple social media platforms (TikTok, Instagram, YouTube, X/Twitter, and more) Fast, clean JSON output you can plug straight into your tools or database Try It If you’re ready to get a list of someone’s TikTok followers (and unlock all the insights that come with it), sign up here and start pulling data in minutes.

Image of mock linktree page on left and the json representation on the right

How to Scrape Linktree (and Find Emails or Social Links)

Why Scrape Linktree? Linktree is a popular tool used by creators to display all their important links, emails, social media accounts, websites, and more. That makes it a goldmine for anyone looking to extract useful contact info like: Emails Social media links (Instagram, YouTube, TikTok, etc.) Websites or personal blogs Step-by-Step: How Linktree Works Under the Hood Let’s walk through scraping a Linktree page using this example: https://linktr.ee/miguelangeles Open Dev Tools Right-click → Inspect → Go to the Network tab. Refresh the Page The very first request is for the HTML document. Click on the first request It should be miguelangeles Go to the response tab Search for __NEXT_DATA__ In the HTML response, search for __NEXT_DATA__. This is where Linktree stores a full JSON blob of the page’s data (thanks Next.js for making this super easy to scrape). This includes things like: EMAIL_ADDRESS Social links URLs Profile Data Scrape Linktree with Node.js Here’s how to do it in code using got-scraping and cheerio: Use a Proxy for Scale If you're scraping lots of Linktree pages, use a proxy to avoid rate limits or bans. Good options include: Decodo (formerly Smartproxy) Evomi Webshare Brightdata Bonus: Scrape Linktree's Public Directory You can discover thousands of profiles using their discover API: https://linktr.ee/discover/_next/data/zd5lRJ4hQhc2caWwdfD1Z/profile-directory/c/all/page-1.json?category=all&page=page-1 Just change the page number to increment. ⚠️ If Linktree updates their site, that zd5lRJ4hQhc2caWwdfD1Z hash will change. To get the latest: Visit https://linktr.ee/discover/profile-directory/c/all/page-1/ Open Dev Tools → Network → Watch for requests when you paginate Or Use our Prebuilt Linktree Scraper! Don’t want to code this yourself? Use my Linktree Scraper, quick, easy, and real-time. Need more? Scrape Creators also supports: Instagram TikTok YouTube Truth Social Ad libraries for Meta, LinkedIn, Google, and Reddit Sign up for 100 free requests, no credit card required!

image of a mock youtube page on the left and the json representation on the right

How to Find Emails of YouTube Creators (Without Breaking the Rules)

If you're trying to find a YouTube creator's email for outreach or research, you’ll quickly hit some limits. YouTube makes it tough to get contact info in bulk. But with the right tools or APIs, you can collect emails from public sources, no CAPTCHA-solving or login hacking required. Here are three proven ways to do it: 1. Use a Paid Tool Like Influencers.Club influencers.club is a premium database of influencers across platform, including YouTube. Their platform is easy to use, and gives you verified emails in bulk with a nice UI, no coding required. 2. Use an API Like Scrape Creators (Best for Public Bio Emails) If you're technical and don't want to spend as much as Influencers.club will charge, consider using an API to scrape the email directly in their bio, description, or "about" section. These emails are visible without logging in and can be pulled via an API. Scrape Creators gives you access to this public data quickly and cheaply. For example, if you wanted to get the email for the Triggernometry YouTube channel, here's what you'd do: Make a GET request to https://api.scrapecreators.com/v1/youtube/channel?handle=triggerpod *Remember to add your API key as a x-api-key header And among other things, it will return 3. Use a Link Aggregator Scraper (e.g., RapidAPI) Some creators don’t list their email directly in their bio, but they link to a personal website, Linktree, or other social media. These often contain contact info. This is where YouTube Channel Email Contact Finder on RapidAPI comes in clutch. It scrapes publicly available data only, and is surprisingly good at finding emails from linked sources (like websites or other social accounts). No login. No CAPTCHA solving. Just smart scraping. What About the “View Email Address” Button on YouTube? You’ve probably seen the “View Email Address” button on the About tab of a YouTube channel. It does give access to email, but: You need to be logged in You can only access 10 emails/day per account You must solve a CAPTCHA Sadly these limitations make this method completely unusable. It’s not worth the headache (or legal risk). Summary Final Recommendation If you want to build a real list of YouTube influencers: Start with Scrape Creators to grab emails directly from bios Use the RapidAPI tool to catch additional emails from linked websites and social media Consider Influencers.club if budget isn’t an issue and you want it all done for you

Image representing getting emails from Instagram

How to Find Emails and Followers of Public Instagram Accounts (3 Proven Methods)

If you’re trying to get the email address or follower's of a public Instagram profile, you’re probably realizing Instagram doesn’t exactly make that easy. You’ve got three real options: Use a paid service like Influencers Club Build your own system (good luck) Use an API that scrapes behind the login Let’s break down the pros, cons, and effort involved in each: 1. Use a Paid Service like Influencers Club If you want clean data, no hassle, and you're okay paying a bit more, a paid software like this is the easiest option. Influencers Club They already have massive databases of creators You get emails, bios, engagement, and more Great if you’re doing influencer outreach or building a list Downside? It’s not cheap. You're paying for polish and convenience. You don’t get full control or flexibility over how data is pulled or filtered. But if you're not technical or just want results now, this is your move. 2. Build Your Own Scraper (Good Luck) This is the DIY route. You’ll need to: Buy or create aged IG accounts Reverse engineer Instagram’s private mobile API Deal with logins, proxies, rate limits, blocks, and bans Parse out JSON responses and handle IG’s anti-bot systems It’s a mess. And Instagram makes it harder every year. The only reason to go this route is if you want full control or are doing this at massive scale. But for most people, it’s way more headache than it’s worth. 3. Use an API That Scrapes Behind the Login This is the sweet spot between DIY and done for you. There are services that already handle the hard part: logging in, navigating Instagram’s internal APIs, and returning the data you care about. Here are a couple solid ones: Hiker API Based in Russia or Ukraine UI looks like it was made in 2008 But it works, and it’s relatively cheap Use it with this endpoint: https://api.instagrapi.com/v1/user/by/id?id={IG user id} (you'll need an x-access-key API key) Social Master on RapidAPI Simple API that takes an IG username and gives you the associated email Also supports YouTube email lookups Great for devs who want programmatic access without building a full system This route gives you flexibility, a decent price point, and way less headache than building your own stack from scratch. Final Thoughts If you're technical but don’t want to waste days building scrapers and dodging bans, use an API. If you're non-technical, go with something like Influencers Club. Just know: Instagram doesn't want you doing any of this. You're operating in a gray zone. So move smart. Need Public Data From IG, TikTok, YouTube, or TruthSocial? If you're looking for an API that gives you public social media data, without logging in, check out Scrape Creators. You can: Get public Instagram, TikTok, YouTube, and TruthSocial data Make your first request in under a minute Get 100 free requests (no credit card required) It’s the easiest way to get started with social scraping, without building anything from scratch.

Image of Mr Beasts Snapchat, and then the json sample of his profile

Snapchat Public API: Get Follower Count, Stories, and Spotlights with Scrape Creators

Looking for a Snapchat API to get follower count, public stories, or Spotlight videos? Snapchat does offer an official API, but it’s locked behind a partner application process and built mostly for advertisers and business partners. If you just want to grab public profile data like follower count, related accounts, or video content, Scrape Creators is the fastest way to go. No login. No scraping headaches. No waiting for approval. You can sign up and make a successful request in under 60 seconds. Includes 100 free requests, no credit card required. What Can You Use This For? Influencer Discovery & Marketing Get a creator’s Snapchat subscriber count Preview their Stories and Spotlight content Find similar creators via related accounts Analytics & Reporting Track Snapchat profiles alongside TikTok and IG Use real media URLs for thumbnails or previews Engagement stats like viewCount, shareCount, commentCount Apps, CRMs & SaaS Tools Enrich influencer databases with Snapchat insights Automatically show a creator's Snap profile content Link directly to their public page What Snapchat Data Do You Get? The Scrape Creators Snapchat API returns clean JSON with: Follower Count "subscriberCount": "1535700" Related Creators Stories & Spotlights (with Media URLs) "mediaUrl": "https://cf-st.sc-cdn.net/d/.../spotlight-video.mp4" Engagement Stats Real Example: Scraping MrBeast’s Snapchat MrBeast’s public Snapchat profile lives at: https://www.snapchat.com/@mrbeast Using Scrape Creators, you can instantly get: His follower count Related accounts Recent story/Spotlight videos Engagement Stats on Spotlights How to Use the Snapchat API (with Node.js) Step 1: Get an API Key Sign up for free at Scrape Creators Includes 100 free requests, no credit card required Step 2: Make a GET Request to the Snapchat API Response You'll get a response that looks something like: And that's it! Why Not Use the Official Snapchat API? Snapchat’s official API exists, but it’s gated and intended for large-scale ad platforms and business partners. You can apply here, but don’t expect instant access. If all you want is to scrape public profile data like this: https://www.snapchat.com/@mrbeast https://www.snapchat.com/@zane Scrape Creators is the quickest and easiest way to go. Start Now, No Credit Card Required Read the API Docs Get an API key: https://app.scrapecreators.com/

Picture of an Instagram Post on the left and the json representation on the right

New Endpoint: Scrape Instagram Comments from Any Public Post!

You asked for it. I needed it myself. And now it’s finally live, you can now scrape Instagram comments directly from a public post using the Scrape Creators unofficial Instagram comments API. No login. No shady tactics. Just good old public data. Why This Is a Big Deal Instagram comments are a goldmine of insight: Want to know what customers really think about a product? Looking to analyze sentiment on a viral post? Need to build a dataset of user-generated content, testimonials, or audience engagement? Now you can. Until now, there weren’t many ways to get IG comments without logging in or doing something sketchy. But this endpoint works entirely from public data. That’s how all Scrape Creators endpoints work, and that’s how we stay in business. How It Works All you have to do is submit the post URL and the amount of comments you want. I handle all the pagination and complexity behind the scenes. Let's say we wanted to get the comments for this Mr Beast post: https://www.instagram.com/p/DC7Y9vyyg_b First, sign up for an API Key: https://app.scrapecreators.com/ Don't worry, you get 100 free credits. Then just make a GET request to https://api.scrapecreators.com/v1/instagram/post/comments?url=https://www.instagram.com/p/DC7Y9vyyg_b&amount=500 Make sure to include your API key as the x-api-key header. And we actually got 500 comments! It did take 4 minutes though, so if you want a lot of comments, be prepared to wait unfortunately. The response will look like this: A Few Things to Note You likely won't get *all* the comments You’ll get roughly 100–300 comments (although we did get 500 above), depending on how many IG will return publicly. For huge posts with thousands of comments, you probably won’t get all of them, that’s Instagram limiting what’s public, not me. Since I’m handling the pagination, this endpoint costs multiple credits. It’s about 1 credit per 15 comments. Most of my other endpoints cost 1 credit and return exactly what you request. This one’s different because I’m calling the IG API for each new page of results What You Can Do With This The use cases are wild: Sentiment analysis on influencer campaigns Pull UGC for DTC product pages (testimonials, feedback, reactions) Build datasets of real customer language Analyze virality, what kinds of comments do people leave on viral reels/posts? Find leads by scraping who’s engaging with posts in your niche Track reactions to a new product, feature, or campaign Seriously, if you’re in marketing, UGC, influencer research, or AI training, this is 🔥 Try It Out Now The endpoint is live: https://docs.scrapecreators.com/v1/instagram/post/comments/simple Just pass a public Instagram post URL and how many comments you want. Sit back. I’ll handle the rest. This has been one of my most requested features, and something I’ve personally wanted for a while. Now it’s here. Go crazy. Sign up for an API key and get 100 free credits.

Image with Text Twitter API Fees in 2025?

Don't Want to Pay Outrageous Twitter (X) API Fees in 2025? Here Are Your Options for Scraping Twitter

If you're building anything that relies on Twitter (X) data, you've probably come face to face with their API pricing. In 2025, it’s downright brutal. $100/month gets you just 15,000 tweets, and $5,000/month caps you at 1 million tweets. Enterprise pricing? Don’t even ask. So what do you do if you’re not a Fortune 500 company but still need Twitter data? Here are the best options in 2025: Option 1: Scraping Behind the Login (Powerful but Risky) This is where all the good stuff lives: full user timelines, Twitter Search, replies, and more. But here's the deal: scraping behind the login is against X's terms of service. It's risky. Tools that do this could be shut down overnight, just like SocialData.tools was recently. Still, there’s one standout: Old Bird V2 on RapidAPI Old Bird v2 is a third-party API that mimics the old Twitter API and scrapes behind the login. Pros: Read access to user timelines, tweet search, tweet metadata Way cheaper than Twitter/X’s official API Been around for years and still working as of 2025 Pricing (as of July 2025): Pro: $24.99/month → 100k tweets Ultra: $69.99/month → 300k tweets Mega: $179.99/month → 1M tweets Cons: It scrapes behind the login — which means it could disappear anytime No write/post access (read-only) Verdict: If you want full-featured access at a reasonable price and can accept the risk, Old Bird is your best option today. 🌐 Option 2: Scraping Only Public Twitter Data (Compliant but Limited) Want to stay fully compliant and not worry about takedowns? Then stick to scraping only public data, the kind you can see when not logged in. BUT: You can’t access search You can’t see replies A user’s profile only shows their top ~100 tweets, not their most recent Test it yourself: open a profile in an incognito browser and you’ll see what we mean. If you're okay with those limits, I’ve made it super easy with my own tool: Scrape Creators. We only scrape public data, so it’s stable and safe. Here’s an example of how easy it is to get someone's public profile: GET https://api.scrapecreators.com/v1/twitter/profile?handle=elonmusk Bonus Trick: Get Recent Tweets via Google Google’s search results often show a user’s most recent tweets. Search for: twitter austen allred This will show a block of tweets in the results. Weirdly, if you search for: austen allred twitter …it won’t work. 🤷‍♂️ So the query is a little finicky. If you want to automate this, I’ve got a Google Search scraper you can use. I’d just need to tweak it to extract tweets from the result block. Email me if you want help with that: adrian@thewebscrapingguy.com Final Thoughts There’s no perfect solution to scraping Twitter in 2025, but there are smart options. Want full power? Use Old Bird. Want safety? Use Scrape Creators. Want the most recent tweets? Hack Google or use Old Bird As long as you stay out of the login wall, you’re golden. But if you go behind it, don’t be surprised if your API provider disappears overnight. To try Scrape Creators for free sign up here: https://app.scrapecreators.com/

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Top SERP APIs for 2025 Compared: Which Google Search API Is Right for You?

If you're building a product that depends on Google search data, like an SEO tool, keyword analyzer, or lead scraper, you’re likely exploring SERP APIs. These tools let you extract structured search results from Google without worrying about proxies, headless browsers, or HTML parsing. But with multiple SERP APIs on the market, how do you choose? In this post, we’ll compare three leading search APIs in 2025: SerpApi SearchAPI.io Scrape Creators We’ll break down their pricing, features, and supported endpoints to help you choose the best fit for your use case. SERP API Pricing Overview Feature Comparison API Coverage: Search vs. Social Both SerpApi and SearchAPI.io offer rich SERP features and multiple Google-related endpoints, including: Google Maps News Images Shopping Autocomplete This makes them ideal for deep SEO platforms and location based queries. Scrape Creators, on the other hand, is built for high volume scraping across search and social, and includes powerful APIs you won’t find elsewhere at this price or scale: TikTok User, Video, and Hashtag APIs Meta Ad Library Scraping LinkedIn Company & Profile Data Instagram, Reddit, YouTube APIs Google Ad Transparency Data If your project spans across search engines and social media platforms, Scrape Creators offers a broader scraping toolkit than traditional SERP APIs. Choosing the Right API for You Final Thoughts The right SERP API depends on your goals. If you're building an SEO tool that needs full featured Google data (including maps, shopping, and knowledge panels), SerpApi and SearchAPI.io are strong candidates. If you're focused on scalable search scraping or want access to hard to access social media data, Scrape Creators offers more coverage at a fraction of the cost, and with no subscription required. Scrape Creators is built for developers who want to move fast, scrape at scale, and access both search and social platforms with one flexible API stack.

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Scrape Creators x Databar AI Partnership 🤝

Scrape Creators x Databar AI: Enrich Any Lead List with Just a Few Clicks We just partnered with Databar AI, and it unlocks some seriously powerful workflows you can now run using Scrape Creators scraping APIs, all without writing a single line of code. Databar is like a spreadsheet on steroids, it lets you call APIs and chain them together visually. And now, they’ve plugged in our TikTok, Instagram, YouTube, and Ad Library scrapers directly into their platform. Here are two game-changing use cases you can run right now: Use Case #1: Competitor Ad Intelligence by Domain Want to know what ads a company is running across the internet? Just drop a company’s domain into Databar, and it’ll use our Scrape Creators ad endpoints to fetch: LinkedIn ads Meta (Facebook/Instagram) ads Google ads Each row includes ad copy, start/end date, targeting info, and ad creative, giving you a complete view of their ad strategy. Perfect for: Competitive research Finding ad angles that are working Reverse-engineering go-to-market strategies Check out the demo below Use Case #2: Discover TikTok Creators in Any Niche + Grab All Their Followers Let’s say you want to find TikTok influencers talking about web scraping. Search TikTok for creators for “web scraping” using our search endpoint Enrich each profile to pull: Username, follower count, profile bio, and more Use our TikTok followers endpoint to grab all of their followers, turning one profile into thousands of leads Perfect for: Building outreach lists Discovering niche communities Analyzing follower overlap between creators Check out the demo below Why This Is So Powerful Zero code: Just plug in keywords or domains and Databar takes care of the rest Scrape Creators power under the hood: You get battle-tested endpoints for social scraping, ads, and more Stackable workflows: Turn a single TikTok search into a 10,000-row lead list in seconds Try It Free You can test these workflows today Start using Scrape Creators on Databar AI → Explore our API docs →

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The Ultimate Guide to Scraping LinkedIn Profiles in 2025

The Ultimate Guide to Scraping LinkedIn Profiles (2025 Edition) LinkedIn is one of the richest sources of professional data on the internet and everyone from recruiters to B2B founders to data analysts wants access to it. But scraping LinkedIn isn’t as simple as hitting an endpoint and calling it a day. There are a lot of changes, legal developments, and tradeoffs you should know about before you dive in. Here’s everything you need to know. TL;DR – Which Option is Right for You? The Big Shift: LinkedIn No Longer Shows Work History Publicly (for most profiles) Until recently, you could get a lot of value from scraping public LinkedIn profiles, even without being logged in. But LinkedIn has quietly removed work history from public profiles. That means if you’re scraping the open web version of LinkedIn, you're no longer getting the most important part of someone’s professional profile. So what’s the workaround? Option 1: Scraping Behind the Login (Full Data, Higher Risk) If you need full job history and detailed professional background, there’s only one way to get it: scrape LinkedIn while logged in. That means using buying accounts, authenticated sessions, or API services that go behind the login. Here are some options: Scrapers That Access Full Profile Data Fresh LinkedIn Profile Data (RapidAPI) Gives you job history and more. Scrapin.io Another scraper with detailed data. Like all such tools, it’s subject to takedown risk. These services work, and if you absolutely need that juicy data, they’re often the best option. Just keep in mind they could go down unexpectedly due to legal pushback. Legal Context: Why These Tools Can Disappear Several high profile legal cases explain why behind-the-login scrapers operate in a gray zone: HiQ vs. LinkedIn: The court ruled that scraping public LinkedIn data is legal, but didn’t grant protection for scraping behind login. Meta vs. Bright Data: Court rules in favor of Bright Data, stating public data can't be policed Case in point: Proxycurl, one of the most popular LinkedIn scraping APIs, recently shut down under legal pressure, because they were scraping behind the login. Read their shutdown post. Option 2: Scraping Public Profiles (Limited Data, Lower Risk) If you're looking for a stable, compliant, and cost effective solution, and you're okay with not having full job history, then public scraping is still a viable path. That’s where Scrape Creators comes in. We focus on publicly available LinkedIn data, and don’t require login or cookies. This means: No risk of your scraper being shut down overnight No need to manage sessions or proxies Affordable pricing for ongoing use You won’t get full job history, but for many use cases (light lead gen, contact enrichment, etc.), it’s more than enough. Final Thoughts There’s no “one size fits all” answer when it comes to scraping LinkedIn. If you need the full data, you'll have to go behind the login, just understand the risks. If you're looking for something lightweight and stable, a public scraper like Scrape Creators might be the better fit. Try Scrape Creators Free Want to try a compliant LinkedIn scraper that just works? Get 100 free requests here

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Unlock Facebook Group Insights with Our Facebook Groups API (Posts + Comments)

Why You Need a Facebook Groups API Facebook groups are a gold mine for niche conversations online. Whether it's fitness, crypto, parenting, SaaS, or real estate there’s a Facebook group full of your exact target audience. But good luck getting data out of it. Until now. Introducing the Facebook Groups API Our Facebook Groups API lets you scrape public group posts and comments programmatically, no browser automation or sketchy workarounds. ✅ Get the latest posts from any public group ✅ Pull all comments from a specific post ✅ Extremely fast and easy to use ✅ Designed for high-volume scraping This is simple API built for devs and data teams. What You Can Do With It 1. Lead Generation Find Facebook posts where people are asking for recommendations, then offer your service or put leads into your CRM. 2. Market Research Analyze the language your customers use. Scrape posts + comments, summarize sentiment, identify recurring pain points, or categorize discussion topics with ChatGPT or another LLM. 3. Competitor Intel See what people are saying about your competitors in niche Facebook groups. Are people complaining? Loving certain features? You'll know. 4. Trendspotting Track what’s trending inside communities before it breaks out. See what new product ideas or tools people are talking about, straight from the source. How to Use the Facebook Groups API Using the API is dead simple, here’s how you can get started in just a few lines of code. Step 1: Get Your API Key Sign up and automatically get an API Key Step 2: Grab Posts from a Public Group Lets say we want to get the posts and some of the comments from the Dad Jokes Facebook Group. Just grab the link to the group, and make a GET request to the API (docs link) https://api.scrapecreators.com/v1/facebook/group/posts?url=https://www.facebook.com/groups/1158298182085866/ Make sure include your API key as a x-api-key header. The response will look something like this: Use the cursor in your next request to get additional posts (sadly, Facebook only returns 3 posts at a time). Try It Out. 100 Free Requests on Us We made this API because scraping Facebook groups was too damn hard. Now it’s easy. If you’ve been trying to: Extract insights from niche communities Do smarter lead gen Monitor trends or competitors Or just build something cool with real data... You’re gonna love this. 👉 Get Your API Key Now, includes 100 free requests so you can try it risk-free. No credit card. No rate limit headaches. Just clean data from public Facebook groups, ready to use.

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The Best Unofficial Reddit API for Fast, Easy Access to Posts, Comments & Trends (2025)

The Unofficial Reddit API That Actually Works for You If you've ever tried using Reddit’s official API, you already know it’s hard to use, and you're severely rate limited. Whether you're a solo dev testing an idea or a data analyst building dashboards, Reddit’s official API makes it hard to move fast. That’s why we built an Unofficial Reddit API, designed to be simple, fast, and powerful, without the bloat or the headaches. What You Can Do With It Our API supports just the essentials you need: Search Reddit posts by keyword Get posts from any subreddit Get comments from any Reddit post No OAuth. No bloated response objects. No need to read a 20 page wiki just to get a list of posts. Even Reddit admits it: The Data API is not intended for use as a high-volume data source. Real World Use Case: How Notion Could Spy on ClickUp Let’s say you work on the growth team at Notion, and you want to better understand what users are saying about your competitor, ClickUp. Your goal? Find out: What frustrates users about ClickUp What features they rave about Where Notion could win over those users Here’s how you’d do it with our API: 1. Search Reddit for mentions of ClickUp First grab an API key from Scrape Creators (100 free requests) Here's the documentation if you want to follow along there. We're going to search all of Reddit for clickup, sorting by new and trimming the response to make it easier for us to read. Make sure to include a header called x-api-key and use your API key. https://api.scrapecreators.com/v1/reddit/search?query=clickup&sort=new&trim=true 2. Grab comments from high-engagement posts Let's take a look at this post: https://www.reddit.com/r/projectmanagement/comments/1lvfkgp/curious_what_people_are_doing_with_project/ https://api.scrapecreators.com/v1/reddit/post/comments?url=https://www.reddit.com/r/projectmanagement/comments/1lvfkgp/curious_what_people_are_doing_with_project&trim=true 3. Analyze with ChatGPT Paste the comments into GPT-4 and ask: “Summarize what Reddit users like and dislike about ClickUp. What problems do they mention? What features stand out? How could Notion position itself as a better alternative?” Or use the OpenAI API to automate this. Here's exactly what Chat GPT said: Example: Reddit + ChatGPT Insight Topic: ClickUp Findings: Users dislike weak automations, steep learning curve, and shallow AI features. They want tools that integrate with existing workflows (e.g. SmartSheets) and offer real AI value. Alternatives like Motion.io and custom setups with Make/N8N are preferred. Insight: Notion can win by being easier to train, more flexible, and offering deeper AI-powered workflows. Other Use Cases Reddit is a goldmine of unfiltered opinions and unmet needs. With our API, you can: Spot Trends Before They Explode Track keyword spikes across Reddit and get notified when new ideas go viral. Validate Product Ideas Just like GummySearch, you can mine niche subreddits for problems, questions, and tool requests that people are begging to solve. Monitor Your Own Brand Set up alerts to track sentiment and feedback as it happens, from product launches to bug complaints. Power Internal Tools & Automations Send Reddit threads to Slack, add quotes to your CRM, or feed your analytics dashboards. Simple, Flexible Pricing No subscriptions. No surprises. Just buy credits and each API call === 1 credit. Use them whenever you want. Scale up or down as needed. TL;DR If you want to: Skip Reddit’s API drama Get only the data you care about Build fast, iterate faster Do it all without breaking the bank Then our Unofficial Reddit API is your new secret weapon. Try it now

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5 Best Web Scraping APIs to Use in 2025 (Based on Your Use Case)

Whether you’re scraping Google results, TikTok videos, or just trying to grab structured data from a JavaScript-heavy site, the scraping tool you choose makes a big difference. Here are the top 5 scraping APIs in 2025, what they’re best at, and when you should actually use them. 1. Scrape Creators - Best for Social Media Data (TikTok, IG, YouTube, etc.) Scrape Creators is built specifically for social media, including the social media Ad Libraries. With over 100+ endpoints across TikTok, Instagram, YouTube, Twitter/X, Reddit, the Meta Ad Library and more, it’s the most complete social media scraping API out there. Unlike general-purpose scraping tools that give you HTML, Scrape Creators gives you clean, structured JSON, already parsed and ready to use. Want TikTok trending videos, IG bios, YouTube transcripts, or TikTok Shop detection? It’s one API call away. ✅ 100+ social endpoints ✅ Real-time data from social platforms ✅ JSON out-of-the-box (no parsing needed) ✅ Available via API or prebuilt Apify actors Best for: Building influencer tools Monitoring creators Social media lead generation Anything social-related at scale Ad Spying Ad Inspiration 2. ScrapingBee - Best for Headless HTML Scraping (No Setup Required) ScrapingBee is a solid, general-purpose scraping API. It's the OG scraping API and was recently acquired by OxyLabs. It renders JavaScript, manages proxies, and returns the HTML of the page (you parse it yourself). It’s great when you want something quick and reliable for scraping content-heavy sites like blogs, ecommerce pages, or product listings. ✅ Headless browser ✅ Handles JavaScript & CAPTCHAs ✅ Simple HTML extraction Best for: Scraping non-social websites General purpose use Devs who want to write their own parsing logic 3. Firecrawl – Best for AI-Powered Extraction via Natural Language Firecrawl is the new kid on the block that’s building around natural language extraction, meaning you can ask for what you want using plain English, and it tries to give you back the structured data. Under the hood, it also uses headless browsing to fetch pages. ✅ Headless browser ✅ Handles JavaScript & CAPTCHAs ✅ Use AI to parse the page, or return straight up HTML Best for: AI agents or LLM tools that need structured data People who don't want to parse the html themselves and want AI to extract content for them General Purpose use 4. ScrapingDog – ScrapingBee Alternative With Built-In Endpoints ScrapingDog offers a very similar experience to ScrapingBee: pass it a URL, and it handles headless browsing, proxy rotation, and returns the raw HTML. Where it stands out is in pricing (generally cheaper) and having more built-in scrapers, like for Google Search, some social media, or even job boards, without needing to build your own logic from scratch. ✅ Headless + proxy support ✅ Built-in endpoints for Google, LinkedIn, etc. ✅ HTML response (you parse) Best for: Developers comparing against ScrapingBee Projects that benefit from built-in endpoints Anyone who wants general-purpose scraping at scale 5. Apify – Best for No-Code + Scraping Automation Apify isn’t just a scraping API, it’s a scraping platform. Meaning any dev can write a scraper and put it up on Apify. You can run bots ("actors") that scrape and automate workflows, then send the data to Airtable, Google Sheets, or an API. And yes, Scrape Creators APIs are also available as Apify actors, so you can connect social scraping to no-code tools like n8n, Zapier, Make, or Retool. ✅ Marketplace of prebuilt actors ✅ Great for non-coders and automation ✅ Powerful for teams Best for: No-code teams Workflow automation Connecting scraped data to apps, CRMs, or Airtable Final Thoughts Not all scraping APIs are built the same, and you’ll save hours (and dollars) if you pick the right tool for the job. Need structured social media data? → Scrape Creators Want AI to extract data with no selectors? → Firecrawl Need fast, cheap HTML scraping? → ScrapingDog Want no-code workflows? → Apify Just need a simple headless scraper? → ScrapingBee

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Track Influencers and Analyze Instagram Bios at Scale

Most people don’t realize this, but Instagram actually does offer an official API. The catch? You have to get your app reviewed and approved, have users log in and authorize your app, and deal with strict rate limits. Oh, and good luck if you’re just trying to look at public info like bios, follower counts, or recent posts, most of that isn’t even accessible unless the user authenticates. That’s why I built something better. The Scrape Creators Instagram Profile API gives you real-time access to public Instagram data, no login, no approval process, no rate limits. You give it a user's handle, it gives you the info you actually want. What You Get with One Call Here’s what the API returns when you pass in an Instagram handle: Bio text Follower count Following count Links Profile image URL Last 12 posts (with captions and media URLs) Related accounts (when Instagram suggests them) No friction. Just public facing profile data, at scale. Why This Works (And Keeps Working) We don’t rely on hacky workarounds like headless browsers or logging into fake accounts. Instead, this API pulls directly from Instagram’s public facing endpoints. That means: Real-time results: every time you call it, you’re getting fresh info No rate limits: make as many concurrent calls you want Sustainable: no sketchy tactics that get shut down in 3 months It’s built for devs, SaaS tools, marketers, anyone who needs creator intel, fast and reliably. Use Cases: How People Are Using It You can plug this API into a bunch of different workflows: Build internal influencer databases for outreach Enrich lead lists with bio info and follower counts Monitor creators over time to track growth or posting habits Discover related creators in a niche using Instagram’s “related profiles” Pull recent posts to analyze content themes or brand collabs Whether you’re a marketing agency, a B2B SaaS product, or just running your own research workflow, this unlocks a ton of value with very little setup. How to Use It You can either use this in code, or no code. Check out the instructions below if you are using code. If you are using n8n, check out our integration. Sign up for an API key View the documentation Find someone's IG page, in this case lets use Zucks. His handle is zuck Make a GET request to https://api.scrapecreators.com/v1/instagram/profile?handle=zuck Make sure you include your API key in a x-api-key And that's it! The response will look something like: Try It Out 👉 View the Docs 👉 Test the Endpoint Live 👉 Start for Free No upfront payment required. Pay as you go, scale as you need.

How to Spy on Your Competitors’ Facebook Ads with One API Call

Introduction If you're running Facebook ads, one of the easiest wins is just seeing what your competitors are doing. And yeah, you can go scroll through Meta’s Ad Library manually… but that sucks. It’s slow, clunky, and impossible to scale if you’re checking more than one or two pages. What you actually want is an API that just gives you all the ads, clean JSON, no login, no BS. That’s where the Scrape Creators Meta Ad Library API comes in. It lets you pull all the ads for any Facebook Page, even your competitors, in a few lines of code. Or you can use our Apify or n8n integrations. Let me walk you through what it gives you and how people are using it. Why It’s Worth Looking at Your Competitors’ Ads If you’re running ads and not keeping tabs on other brands in your space, you’re missing out. It’s not about copying, it’s about understanding: What kinds of offers are people pushing? What angles are they testing? How much are they spending (based on volume or how long the ads have been running)? What’s working right now in your niche? You can get a bunch of ideas for your own ads just by seeing what other brands are paying to promote. Especially if you’re doing DTC or working with clients. What You Can Actually See in the Facebook Ad Library Meta shows a lot of info in the Ad Library, most people just don’t realize how much you can get: Text + visuals (image or video) Start date (when the ad launched) Whether it’s still active Which countries it’s running in Page name and ID Categories (like political, credit, housing, etc.) It’s all public. Meta makes this data available for transparency reasons, but that doesn’t mean you have to sit there and click through it manually. The Problem with Meta’s Official API Meta has an official Ad Library API, but using it is kind of a pain: You need a developer account and access tokens You have to get app approval You’ll run into rate limits You can’t search all ad types And honestly, it’s just not that easy to use If you’re just trying to get ad data for research or to keep an eye on competitors, you probably don’t want to jump through all those hoops. A Better Way: The Scrape Creators Meta Ad Library API This API makes it dead simple to pull ad data for any Facebook Page, even if you don’t own it. Here’s what it does for you: Easy to sign up and get started No rate limits Clean JSON response Supports pagination if there are a ton of ads Works with cURL, JS, Python, whatever you want Or no code tools like Apify, n8n How It Works (Example) Let’s say you want to see what ads lululemon is running in the US right now. First sign up for an API key. You’d just hit the API like this: GET https://api.scrapecreators.com/v1/facebook/adLibrary/company/ads?companyName=lululemon&country=US&trim=true Make sure you include your API key in a x-api-key header. Response (simplified) If there are a lot of ads, you just paginate with the cursor. Easy. Check out the full documentation here: https://docs.scrapecreators.com/v1/facebook/adLibrary/company/ads Real World Use Cases Here’s how people are using it: DTC brands: tracking competitors messaging and product pushes Agencies: pulling ads for pitch decks or client reporting Growth hackers: studying ad angles before launching something new Political orgs: monitoring election ad spend AI tools: training on ad creative + messaging at scale Whether you’re doing manual research or building something automated, this saves a ton of time.

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How to Find Out If a TikTok User Has a TikTok Shop

If you're targeting TikTok creators for outreach, sales, or influencer marketing, one of the most valuable data points you can get is whether they have a TikTok Shop. And now, with Scrape Creators, you can instantly tell if any TikTok user has a shop, plus get their seller_id for further research. Why This Matters TikTok Shop is where creators monetize directly. If someone has a shop, they're already trying to sell, which makes them an ideal target for: Cold outreach: these users are warm leads eCommerce service providers: agencies, UGC creators, designers Brand partnerships: partner with creators who’ve already sold something Market research: see who’s entering the space and what they’re selling How It Works: The Scrape Creators Endpoint We made it dead simple. Sign up for an API Key: https://app.scrapecreators.com/ Check out the endpoint in the documentation. Make a GET request to: https://api.scrapecreators.com/v1/tiktok/user/is-shop And you need a header called x-api-key, and the value will be your API key. The response will look like this: No headless browser. No proxies. No captcha headaches. It just works. Why Use Scrape Creators? Blazing fast API. Most responses return in 3 seconds or less No scraping headaches, we handle all that for you Pay-as-you-go pricing Use our Apify or n8n Works at scale

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How To Tell If a TikTok Video Is an Ad (And Why It Matters for Your Brand)

Why This Matters: Ad Status = Performance Signal If a brand takes a creator’s TikTok and turns it into an ad, it’s a signal that the video performed well, and that the creator likely drove real results. For marketers, influencer agencies, and competitive researchers, identifying which TikToks are ads can help you: Find high-performing creators worth working with Discover creative styles that resonate enough to get paid promotion Track brand partnerships before they’re obvious Reverse-engineer what’s converting across your industry How To Check if a TikTok Video Is an Ad TikTok doesn't display ad status in the UI, but if you're savvy you can still find it. The raw HTML of a video page contains a field called isAd. If this is set to true, the video was promoted as a paid advertisement. Here’s how to find it: Visit the TikTok video URL in a browser (e.g., https://www.tiktok.com/@noah.rolette/video/7376380452136914218) Right-click and click Inspect Go to the Network Tab Refresh the page Click on the first request, which should be the HTML document In the Response tab, search (Cmd+F or Ctrl+F) for isAd You’ll see something like this inside a JSON blob: Scrape Creators If you don't want to build and manage your own scrapers to get this information, consider using Scrape Creators, which makes is super simple to get this information with a simple API call. (On Scrape Creators the field is actually is_ad. In addition to is_ad you can also see if the video is an affiliate for a product, get the images if the tiktok is a photo carousel, get the raw video without the watermark, and much more. And get access 100 other API's for Instagram, LinkedIn, YouTube, Twitter, TruthSocial, etc. All for a pay as you go plan, no monthly subscription required. And if you don't code, we also have integrations with n8n and Apify 🙌

Example of a TikTok Shop video with eligible for commission label

How To Tell if a TikTok Video Is Promoting a TikTok Shop Product (With Examples + API Tips)

TikTok has become more than just a place for trends and dances, it’s now a full-blown e-commerce platform. With TikTok Shop, creators can earn commissions by promoting products directly in their videos. But how do you actually **tell** if a TikTok video is promoting a product through TikTok Shop? This post will show you exactly how to spot those videos both **visually** and **programmatically**, so you can analyze, track, or build tools around TikTok Shop content. Why this matters Identifying TikTok Shop videos is useful for: Marketers looking for creators who are actively promoting products Brands scouting for potential influencer partnerships Devs scraping TikTok to track product trends or build affiliate dashboards Analysts measuring which content converts into sales And they're actually pretty easy to spot. There’s one clear signal that gives them away. The Key Indicator: "Eligible for Commission" If you visit this video: https://www.tiktok.com/@thecutechiro_/video/7433747950766951723, you'll see that on the web, at the bottom of the video it will say "Eligible for commission" Check out how it looks below On the TikTok mobile app it will actually say "Creator earns commission" or "Commission paid" How it looks on mobile: How to Get This Info TikTok does not expose this data in their public API. But if you want this field at scale, you can get it using Scrape Creators, a powerful API that returns a is_eligible_for_commission field as part of every TikTok video object. Specifically you'll want to use the TikTok Profile Videos endpoint to get the users videos, or if you have an individual video you want to check, use the TikTok Video Info endpoint. Example response (using the tiktok from above) Scrape Creators helps you find videos that are monetized, allowing you to: Track product trends Build TikTok affiliate dashboards Discover top-performing promotional content Real Use Cases Affiliate Discovery: Find creators actively promoting TikTok Shop products Trend Analysis: Track what types of videos are most often linked to product sales Build Tools: Power search engines, databases, or dashboards for TikTok Shop Partnership Research: Identify affiliate-heavy creators for collabs Final Thoughts Knowing how to spot TikTok Shop content gives you a huge edge, whether you're building something, running campaigns, or just trying to understand what’s selling. Look for the “Eligible for commission” tag on videos, or tap into the is_eligible_for_commission field using Scrape Creators.

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The Best Truth Social API for Tracking Trump’s Posts

What Is the Truth Social API? If you’re trying to monitor Trump’s posts on Truth Social or build anything programmatic with the platform, you’ve probably noticed something frustrating: there’s no official Truth Social API. That’s where Scrape Creators comes in. We built an unofficial Truth Social API that gives you real-time access to posts, perfect for alerts, automations, dashboards, or just staying ahead of the news cycle. Why No Official Truth Social API Exists Truth Social was never designed with developers in mind. There's no public documentation, no API, and no developer portal. As of now, there’s no official way to pull posts, user timelines, or search content via an API. This is why we built something fast, lightweight, and reliable. How the Scrape Creators Unoffical API Works Our API hits Truth Social directly and delivers clean JSON data in a REST format. We handle all the heavy lifting behind the scenes, rotating proxies, bypassing detection, and making sure the data stays fresh and accurate. You just hit the endpoint, and boom the latest posts are yours. Use Case: Monitor Trump Posts Want to get notified the second Trump posts something? After you sign up for an API key, here's how you would do that: API Features REST Endpoint Simple, fast GET requests with optional filters by username or date. Webhook Support (Coming Soon) Soon you’ll be able to register a URL and get new posts pushed to you in real time, no polling required. Clean JSON Response No HTML parsing, no fluff, just structured, developer-friendly data. Pay-As-You-Go Only pay for what you use. No monthly minimums, no surprise charges. No Rate Limits We don’t throttle. Use it as fast as your infrastructure allows.

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How To Scrape Images from TikTok Slideshow

Why Slideshows? TikTok photo carousels, or slideshows, are helping creators get millions of views, with relatively little effort. If you've ever wanted to scrape the images from a TikTok, here's how you do it: How to: Let's take this account as an example: https://www.tiktok.com/@mens.guidance All of their posts are photo carousels and some of their posts are popping off. First sign up for this product named Scape Creators, it grabs public social media data in real time. It only take a couple clicks to sign up. Let's use this post as a example: https://www.tiktok.com/@mens.guidance/photo/7467226363544554770 We want to grab the images from this post. The endpoint we will be hitting will be TikTok Video Endpoint (docs link) You can test it out using the playground. Pro tip, enable trim to trim the response to make it a little more manageable. Look for the key `image_post_info`. That will have an array called `images` And we actually want to go into the `thumbnail` key to get the image that doesn't have a watermark. Key into the first url in `url_list`, and we have the url of the image! Go ahead and visit that url to verify. To get all the images, simply loop over the images array! In code it would look like this: We are gonna use JavaScript (Node.js) for this example. I'm using the http client library called axios here, but feel free to use the one you want. And that's it! Those url's will expire after a few hours, so if you want to save them to view later, you will want to download them and then upload them to a cloud storage provider like supabase storage, Amazon S3, or Cloudinary, etc. In node.js you would fs to download the image. Also, if you don't want to do this for each individual video, you can use Scrape Creators Profile Videos endpoint to grab the user's first 20 tiktoks (or however many you want), and then loop through all their tiktoks and grab the images (or videos) from all of them.

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How to scrape YouTube transcripts with node.js in 2025

I’m going to show you how to scrape YouTube transcripts in node.js, but the technique can be used for any programming language. If you are just looking for a pre-built API, check out the scrape creators YouTube Transcript API. Scrape Creators also has transcript API’s for TikTok, Instagram, Facebook, and Twitter. Ok first, go to the youtube search page. In this case, I am going to search for “Charles Barkley Jussie Smollett” Next we want to see if we can find any API’s that YouTube is using to fetch the video and hopefully transcript, so open up the dev tools by Right clicking > Inspect Element Then go to the “Network Tab” To make things easier for us, filter by “Fetch/XHR” Now click on any video you want, and observe the requests. Notice the route: “next?prettyPrint=false” Click on that route and check out the Response. If you start searching for the video title or views, you’ll see them in this response: So cool, looks like we found the endpoint that YouTube is using to fetch video details. Now we want to actually call it in Node.js. Go to the next?prettyPrint=false endpoint and right click to Copy as fetch (Node.js) Make sure you have node-fetch installed with npm install node-fetch We’re going to be using async/await, so your code should look something like this: If you make the request, it should be successful. Whoohoo! 🥳 Nice job. But, we don’t want to fetch the same video over and over again, we want to dynamically fetch different videos. So if you notice in the request payload, there is a “videoId” field. And that’s pretty convenient for us, because it means we can just pass a different “videoId” and get the videos details. You can find the videoId easily because its always in the query params of the video. For example: ​​https://www.youtube.com/watch?v=Y2Ah_DFr8cw So just make sure to pass whatever videoId you want to get, and that should be it. You can get rid of that params key. Cool, now how do we get the transcript? Well lets first see how YouTube is getting the transcript. Click the “...more” in the video description Clear the Network Requests so we can get an easier view of what happens when we click on the Show Transcript button Click on the Show transcript button Now they fire off the “get_transcript” endpoint, which doesn’t take a genius to figure out that that’s how they are getting the transcript. Click on the response, and you can see that the transcript is there in nice JSON for us. Excellent. Now lets look at how they’re calling it. So if you go to the Payload tab you’ll see an “externalVideoId”, which you can see is just the videoId, and there is this “params” value, which we did not need to fetch the video details, but spoiler alert, we will need it here. So where does it come from? Well, if you still have the video details response available, search for “getTranscriptEndpoint” If you copy the params value and search for it in the video details response, you’ll see that is identical to the params value YouTube is using to get the transcript 🙌 So now, to actually call the endpoint to get the transcripts, Copy the get_transcript request like we did for the video details request. Then make sure to pass the externalVideoId and the getTranscriptEndpoint param from the video details endpoint, and thats it!

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Instagram Scraping in 2025: The Workarounds That Still Work

First, for all the lawyers out there reading this, we're only getting *public* data, so just relax. Aight lets get into it: Now, if you try to scrape via the browser, you're already cooked. Using tools like puppeteer or selenium are easy to detect. If you want to find the API that gets someone's public profile (their follower count, bio, links, etc), do this: Visit my IG page (adrianhorning) Next, we need to monitor the network requests as they're happening> Open the dev tools with right click > Inspect > Network (filter by Fetch/XHR) Scroll to the bottom, to the "Related Accounts"> Click on one Observe the requests Notice one that is named "web_profile_info"? That is probably the one we need 😅 Next, the http client you use is super important. Use got-scraping from Apify. It is incredible at getting around stuff. And lastly, you'll need residential proxies. There are a lot of providers out there, I have my personal favorites. The just pretty much do that for all the public information you want. Sometimes you need to include the headers that they are, so pay attention to that. And to get additional pages of results, they use cursor based pagination, so just look for "cursor" (most of the time), in the payload. If you want a solution that's already done for you, you can just call my IG profile endpoint, docs here: https://docs.scrapecreators.com/v1/instagram/profile

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Instagram API Without Rate Limits: How to Easily Access Public Data

The Instagram Graph API is awesome, but it has a rate limit of 200 calls per hour * the number of users. So if you're doing any kind of volume, this really sucks and is a huge bottleneck for your project. To get around this, you could try scraping Instagram yourself, using proxies, running headless browsers, constantly dodging bans, etc. But unless you want to babysit all that headache 24/7, there’s a much easier way: Scrape Creators gives you direct access to public Instagram data, without rate limits, and it's really easy to use. Here’s how easy it is to pull public Instagram data using Scrape Creators: Example: Get Public Profile Data Let’s say you want to pull public info about an Instagram user like nike. You want some basic information like bio, website, follower count, recent posts, etc. By the way the documentation for this api is here: Instagram Profile Endpoint All you need to do is make a GET request to /v1/instagram/profile like so: To get an API key, just sign up at app.scrapecreators.com (free trial, no credit card required) That will return something like this, which has that basic information, and even the users recent posts also: If you want to get just the posts of the user, use the /v2/instagram/user/posts endpoint. And that's it! How to Get Started Sign up for a Scrape Creators account Get your API key Start making requests You can check out the full API docs here. If you want reliable, no-drama access to public Instagram data, Scrape Creators makes it stupid simple. Sign up here and get started.

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How to scrape the Meta Ad Library

The Meta Ad Library is a goldmine for marketers, researchers, and growth, but it wasn’t built with automation in mind. That’s why I built the Scrape Creators API to pull real-time Meta Ad Library data using simple HTTP requests. In this post, I’ll show you exactly how to do that using **JavaScript with Axios**. But, you can use any no-code platform also like Clay, Make or Zapier. Anything where you can make API calls from. You’ll also find: - A video walkthrough on YouTube - A working code example on GitHub - Live demos for searching ads, finding companies, and more 🎥 Watch the Video 👉 Click here to watch on YouTube 🧠 What You'll Learn - How to search for ads by keyword - How to look up a company page - How to get all ads from a specific advertiser - How to retrieve a single ad by ID - Copy/paste-ready Axios code examples 🛠 Setup Before you start: - Sign up at [Scrape Creators](https://scrapecreators.com) and grab your API key - If you are using JavaScript (Node.js), install Axios in your project: 🔍 Search Ads by Keyword You know how you can search for ads by a keyword in the Meta Ad Library? Well, you can do the same thing programmatically! All you have to do is call the Search Ads endpoint with a `query` parameter, like so: And you can even search by Ad Type, Country, Status, and Start and End Date! The response will look something like this. Here are some of the valuable fields that will be returned: `ad_archive_id` -> this is the ad id `start_date_string` `end_date_string` `publisher_platform` -> to know if the ad is running on Instagram, Facebook, etc `snapshot` -> This is where all the ad copy and variations will be `body` -> body of the ad `cta_text` `link_url` -> where the user goes after they click on the ad `page_id` -> The company's ad library page id `videos` `images` And if you want more pages of results, just pass the `cursor` that is returned. Get Individual Ad Details Lets say we want to get the ad detail of a single ad. For that we just need the Library ID, in this case 1755312555404167. You will get the same details as above, including start_date_string, end_date_string, publisher_platform, snapshot, cta_text, link, etc. Search for a company's ads Now lets say we wanted to just get the ads from lululemon. First we need the lululemon page id. If you already know it, great, hold onto it. If you don't, you can find it by using this endpoint: That will return a `searchResults` array. You want to key into the first search result and return the page_id, like so: Then you can use that to fetch their ads using this endpoint: And the response will almost be identical to the Search endpoint. If you want additional pages, a `cursor` will be returned, and you need to pass that to subsequent requests like so: And that's it! 📦 Get the Full Code Want to see all this code in one file? 👉 View on GitHub ✅ Ready to Start? Create your free API key at Scrape Creators and start pulling Meta Ad Library data into your app. Questions or feedback? Hit me up at adrian@thewebscrapingguy.com Other APIs If you're looking to scrape other Ad Libraries like the LinkedIn Ad Library, or Google Ad Transparency Center, check out Scrape Creators. Also, if you want to scrape Instagram, YouTube, TikTok, Twitter, and more, you can also use scrape creators for that too!