instascrape is a lightweight Python package that provides an expressive and flexible API for scraping Instagram data. It is geared towards being a high-level building block on the data scientist's toolchain and can be seamlessly integrated and extended with industry standard tools for web scraping, data science, and analysis.

Here are a few of the things that instascrape does well:

• Powerful, object-oriented scraping tools for profiles, posts, hashtags, reels, and IGTV
• Scrapes HTML, BeautifulSoup, and JSON
• Download content to your computer as png, jpg, mp4, and mp3
• Dynamically retrieve HTML embed code for posts
• Expressive and consistent API for concise and elegant code
• Designed for seamless integration with Selenium, Pandas, and other industry standard tools for data collection and analysis
• Lightweight; no boilerplate or configurations necessary
• The only hard dependencies are Requests and Beautiful Soup
• Proven to work as of January, 2021

• Installation
• Sample Usage
• Documentation
• Blog Posts
• Contributing
• Dependencies
• License
• Support

This library currently requires Python 3.7 or higher.

Install from PyPI using

$ pip3 install insta-scrape

WARNING: make sure you install insta-scrape and not a package with a similar name!

All top-level, ready-to-use features can be imported using:

from instascrape import *

instascrape uses clean, consistent, and expressive syntax to make the developer experience as painless as possible.

# Instantiate the scraper objects 
google = Profile('https://www.instagram.com/google/')
google_post = Post('https://www.instagram.com/p/CG0UU3ylXnv/')
google_hashtag = Hashtag('https://www.instagram.com/explore/tags/google/')

# Scrape their respective data 
google.scrape()
google_post.scrape()
google_hashtag.scrape()

print(google.followers)
print(google_post['hashtags'])
print(google_hashtag.amount_of_posts)
>>> 12262794
>>> ['growwithgoogle']
>>> 9053408

See the Scraped data points section of the Wiki for a complete list of the scraped attributes provided by each scraper.

The official documentation can be found on Read The Docs

Check out blog posts on the official site or DEV for ideas and tutorials!

• Scrape data from Instagram with instascrape
• Visualizing Instagram engagement with instascrape
• Exploratory data analysis of Instagram using instascrape and Python
• Creating a scatter matrix of Instagram data using Python
• Downloading an Instagram profile's recent photos using Python
• Scraping 25,000 data points from Joe Biden's Instagram using instascrape
• Compare major tech Instagram page's with instascrape
• Tracking an Instagram posts engagement in real time with instascrape
• Dynamically generate embeddable Instagram HTML with instascrape
• Scraping an Instagram location tag with instascrape
• Scraping Instagram reels with instascrape
• Scraping IGTV data with instascrape
• Scraping 10,000 data points from Donald Trump's Instagram with Python

All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome!

Feel free to open an Issue, check out existing Issues, or start a discussion.

Beginners to open source are highly encouraged to participate and ask questions if you're unsure what to do/where to start ❤️

• Requests
• BeautifulSoup

This library operates under the MIT license.

Check out the FAQ

Reach out to me if you want to connect or have any questions!

• Email:
  • [email protected]
• Twitter:
  • @ChrisGreening
• LinkedIn
  • Chris Greening

DISCLAIMER: With great power comes great responsibility. This is a research project and I am not responsible for how you use it. Independently, the library is designed to be responsible and respectful and it is up to you to decide what you do with it.