instascrape: powerful Instagram data scraping toolkit

Note: This module is no longer actively maintained.

DISCLAIMER:

Instagram has gotten increasingly strict with scraping and using this library can result in getting flagged for botting AND POSSIBLE DISABLING OF YOUR INSTAGRAM ACCOUNT. 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. I don't claim any responsibility if your Instagram account is affected by how you use this library.

What is it?

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.

Key features

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

Installation
Sample Usage
Documentation
Blog Posts
Contributing
Dependencies
License
Support

💻 Installation

Minimum Python version

This library currently requires Python 3.7 or higher.

pip

Install from PyPI using

$ pip3 install insta-scrape

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

🔎 Sample Usage

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.

📚 Documentation

The official documentation can be found on Read The Docs

📰 Blog Posts

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

🙏 Contributing

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 ❤️

🕸️ Dependencies

💳 License

This library operates under the MIT license.

❔ Support

Check out the FAQ

Reach out to me if you want to connect or have any questions and I will do my best to get back to you

Email:
- [email protected]
Twitter:
- @ChrisGreening
LinkedIn
- Chris Greening
Personal contact form:
- www.christophergreening.com

chris-greening / instascrape Goto Github PK

instascrape's Introduction