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How to Scrape Instagram: The Complete Guide

Instagram is one of the most popular social media platforms, with over 1 billion monthly active users. With so much user engagement happening on the platform, Instagram contains a wealth of public data that can provide valuable insights for social media monitoring, influencer marketing, content analysis, and more.

However, Instagram has shut down its public API access. This makes it challenging for developers, marketers, and researchers to collect Instagram data. The solution? Web scraping.

In this complete guide, you‘ll learn how to use web scraping to extract data from Instagram profiles, posts, comments, hashtags, and more.

An important question that arises when scraping any website is – is it legal? The short answer is yes, scraping publicly available data from Instagram is legal.

However, you need to ensure you are not violating Instagram‘s Terms of Service or accessing private, copyrighted content. As long as you only scrape public Instagram data and attribute it properly, you should be in the clear legally.

Some specific things to keep in mind:

  • Only scrape public Instagram profiles and posts, not private accounts.
  • Do not scrape Instagram user emails or contact information.
  • Avoid scraping entire Instagram photos or videos, as this may violate copyrights. Small thumbnails or screenshots may be okay under fair use.
  • Attribute scraped Instagram data properly, giving credit to original posters.
  • Do not abuse Instagram‘s systems with an unreasonable scraping load.

As long as you follow common-sense web scraping best practices, you can legally collect and use public Instagram data for analysis purposes.

Tools for Scraping Instagram

There are several tools you can use to scrape data from Instagram:

Scraper APIs

Scraper APIs are services that provide ready-made scrapers for various sites, including Instagram. Some popular scraper APIs include ScraperAPI, BrightData, and Apify.

The advantage of using scraper APIs is they handle the technical scraping work for you. Just enter the URLs or keywords you want to target, configure your scrape, and extractor the data. Scraper APIs typically offer generous free plans and usage tiers to get started.

Custom Scrapers

You can build a custom scraper tailored exactly to your Instagram scraping needs. Custom scrapers give you more control, but require more technical knowledge.

Popular tools for building custom scrapers include:

  • Python – Libraries like BeautifulSoup, Selenium, and Requests make Python a top choice for web scraping.

  • Node.js – Using libraries like Puppeteer, Cheerio, and Axios, you can build robust scrapers with Node.

  • R – R has web scraping packages like rvest and RSelenium.

  • PHP – PHP scrapers can be built using libraries like Goutte, PHPHtmlParser, and DOMDocument.

GUI Tools

For non-developers, GUI web scraping tools provide a point-and-click interface for extracting data. Some examples include Octoparse, ParseHub, and

These tools simplify the scraping process, but are less flexible than coding your own scraper.

Browser Extensions

Browser extensions like Scraper and allow extracting data right within your browser. This can be handy for one-off scraping tasks. However, extensions lack the automation and scalability of other scraping tools.

Headless Browsers

Tools like Puppeteer allow controlling a browser (like Chrome) programmatically. This lets you script actions like page navigation, scrolling, clicks, etc. Headless browsers enable scraping dynamic web content that would be difficult with simple HTTP requests.

In summary, scraper APIs provide the simplest path to getting your Instagram data, while coding a custom scraper gives you the most flexibility. The right approach depends on your specific needs and technical abilities.

What Instagram Data Can You Scrape?

Now let‘s explore key data points that are publicly available to scrape from Instagram.


Every Instagram user has a public profile displaying their bio, posts, followers / following counts, etc. Scraping profile information is straightforward – simply extract text and data from a user‘s profile page HTML.

Profile data points that can be scraped include:

  • Username
  • Profile name
  • Bio text
  • Followers / Following counts
  • External URL
  • Profile photo
  • Post captions and comments

You can scrape data from both individual profiles or do bulk scrapes of target users like influencers or competitors.


Instagram profiles contain users‘ uploaded photos and videos, known as posts. Post data includes:

  • Media (image/video URL and thumbnails)
  • Captions
  • Date posted
  • Likes and comments
  • Tagged users

Scraping posts allows you to collect and analyze users‘ visual social media content and engagement. You can extract post data from specific profiles or hashtags.


Hashtags are used on Instagram posts to index topical content and increase discoverability. Each hashtag has a page displaying recent public posts using that tag.

Scraping hashtag pages lets you collect focused niche content. You can extract related post media, captions, engagement, author info, etc.


Instagram has location pages to discover content posted from a specific place. Scraping locations allows gathering geo-tagged posts.

Location page posts can be scraped for media, captions, likes/comments, author details, etc. Location data expands your Instagram scraping capabilities to a local area.


Each Instagram post displays comments from other users below the photo/video. You can scrape post comments to analyze user reactions and conversations around content.

Comments contain the text, timestamp, and author info. Scraping comments in bulk reveals engagement trends across posts and hashtags.


Instagram Stories allow sharing ephemeral photos and videos that disappear after 24 hours. Public stories from brand accounts can be scraped to collect this temporary content before it vanishes.

Story data points include the media URL, caption, viewers, location, mentions, etc. The key is quickly scraping stories before they expire.


A profile‘s followers and following lists reveal helpful social graphs. However, these require being logged into an Instagram account to access.

You cannot scrape Instagram followers or following from public pages. Doing so would violate Instagram‘s terms.

In summary, profiles, posts, hashtags, locations, comments, and public stories are all fair game for Instagram scraping. Usernames, follower lists, emails, and private content should be avoided.

Step-by-Step Instagram Scraping Process

Now that we‘ve covered the essentials, let‘s walk through the technical steps to scrape Instagram data:

1. Identify your scrape targets

First, determine the specific Instagram profiles, hashtags, locations, or posts you want to scrape. Compile a list of page URLs or keywords to target your scrape.

2. Extract profile and post URLs

For keyword searches, you‘ll first need to extract the profile and post page URLs from Instagram‘s search results. Scrape the URLs into a list for the next steps.

3. Scrape page HTML

Use a tool like Puppeteer, Requests, or BeautifulSoup to download the page HTML for each target URL.

4. Parse the HTML for data

Analyze the Instagram page HTML to extract the desired data points into structured JSON or CSV. Popular parsing libraries include BeautifulSoup, Cheerio, and HTMLParser.

5. Store and export data

As you loop through pages to scrape, store the extracted data in your programming language‘s native data structures. Once the scrape is complete, export the final dataset as a CSV or JSON file.

6. Schedule and automate (optional)

To run your Instagram scraper on autopilot, use a scheduler like cron jobs or Windows Task Scheduler. For large datasets, you may also want to integrate queueing and distributed scraping.

And that‘s it! Those are the core technical steps to build your own custom Instagram scraper in Python, Node, PHP or any language.

Depending on your specific data needs, you can customize and expand on this framework. Let‘s explore some more advanced scraping techniques next.

Advanced Scraping Techniques

Beyond the basics, there are some advanced web scraping skills that will take your Instagram scraper to the next level:

Dynamic Scraping

Modern sites like Instagram employ dynamic JavaScript to load content. To scrape this data, you‘ll need browsers like Puppeteer or Selenium that can render JavaScript. These tools allow scrolling pages and clicking buttons to trigger dynamic content loading.

Handling Rate Limiting

If you send too many scraping requests too fast, Instagram may rate limit or block your IP address. To prevent this, implement random delays in your scraper or use proxy rotation services to mask your IP.

Develop Robust Scrapers

It‘s important for scrapers to handle errors and gracefully retry failed pages. Using libraries like Cheerio and Axios make building robust scrapers in Node simple. Monitor scraper runtimes and debug issues quickly.

Scrape Anonymously

To make your scraper more discreet, route requests through proxies or rotate user agents. This helps avoid detection by Instagram‘s security systems.

Queue Scraping Jobs

Tools like Redis and Bull allow you to build scraper queues to distribute scraping jobs across threads, servers, or even a scalable cluster of workers. Queues support high volume scraping.

Integrate with Data Storage and BI Tools

For analysis at scale, export scraped Instagram data to data warehouses like PostgreSQL, data lakes, or BI tools like Tableau. Connecting your scraper to downstream analytics stacks unlocks deeper business insights.

There are countless creative ways to enhance and customize an Instagram scraper for your unique needs. Mastering techniques like these will enable you to extract maximum value from Instagram data.

It‘s important to keep Instagram‘s Terms of Service and ethical data practices in mind when scraping:

  • Attribute data properly – Give credit to Instagram and original content creators when re-posting scraped content.

  • Don‘t steal media – Avoid directly copying and reusing others‘ Instagram photos/videos without permission. Small thumbnails or screenshots may be acceptable under fair use.

  • Scrape reasonably – Don‘t overload Instagram‘s systems with an unreasonable scraping volume.

  • Respect privacy – Only collect truly public data. Avoid private profiles, emails, etc.

  • Check the legal landscape – Stay aware of any new laws or terms that may impact scraping.

Adhering to ethical scraping standards keeps your brand‘s reputation intact and avoids potential legal issues. Scraping Instagram can provide immense business value, as long as you do it responsibly.

Scraping Instagram Data at Scale

For large-scale Instagram scraping needs, self-coding and maintaining an enterprise-grade scraper in-house poses challenges. The solution many businesses turn to is outsourcing their web scraping jobs to a professional scraping services provider.

ScrapingBee offers on-demand Instagram and web scraping APIs starting at just $29/month. Our infrastructure allows extracting millions of Instagram data points fast, without headaches or blocked IPs.

Benefits of using ScrapingBee‘s enterprise web scraping platform include:

Scale and Speed – Our beefy proxy network and distributed scraping infrastructure can crawl Instagram faster than any individual could alone. We handle scraping at massive scale without bans.

Reliability – Our scrapers achieve 99%+ uptime via monitored scraping nodes around the globe that provide built-in redundancy.

Simplicity – No need to build or manage scrapers in-house. Just send API requests to instantly extract Instagram data.

Affordability – Prices starting at $29/month make ScrapingBee accessible for early-stage startups through large enterprises.

Security – ScrapingBee exceeds ISO 27001 and SOC 2 security standards to keep your data safe.

To learn more about ScrapingBee‘s Instagram and general web scraping API, visit our site or request a free trial. Our experts are also happy to discuss custom scraping solutions tailored to your business needs.


I hope this complete guide covered everything you need to start extracting powerful Instagram data at scale through web scraping. The key takeaways are:

  • Scraping public Instagram data is legal and creates business value.

  • Useful data points include profiles, posts, hashtags, locations, comments, and stories.

  • Leading scraping tools include Python, Node.js, scraper APIs, headless browsers, and services like ScrapingBee.

  • Robust scrapers require skills like handling dynamics content, preventing bans, and managing large datasets.

  • Always follow ethical practices like attributing content, minimizing load, and respecting privacy.

Scraping Instagram opens up game-changing social media intelligence, if done properly. Apply the techniques in this guide to start gaining competitive advantage from Instagram‘s wealth of public data today.

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