insta-scrape 1.3.4

Super lightweight Instagram web scraper for data analysis

instascrape: Instagram scraping for humans

What is it?

instascrape is a powerful, lightweight Python library for scraping Instagram data and content with no configurations necessary! It is designed with flexibility and developer productivity in mind so you can stop wasting valuable time preparing Instagram data and just start analyzing it :muscle:

Official website

Key features

• :muscle: Powerful, object-oriented scraping tools
• :dancer: Flexibly determines whether you want to scrape HTML, JSON, BeautifulSoup, or request and scrape the URL itself
• :floppy_disk: Download content to your computer as png, jpg, mp4, and mp3
• :art: Dynamically retrieve HTML embed code for posts
• :musical_score: Expressive and consistent API for concise and elegant code
• :bar_chart: Designed for seamless integration with Selenium, Pandas, and other industry standard tools for data collection and analysis
• :hammer: Lightweight: you don't have to build a hammer factory when all you need is the hammer
• :spider_web: The only hard dependencies are Requests and Beautiful Soup; no more worrying about configurations or webdrivers
• :watch: Proven to work as of December, 2020

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Table of Contents

• :computer: Installation
• :mag_right: Sample Usage
• :books: Documentation
• :newspaper: Blog Posts
• :pray: Contributing
• :spider_web: Dependencies
• :credit_card: License
• :grey_question: Support

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:computer: 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!

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:mag_right: 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()

After being scraped, relevant attributes can be accessed with dot or bracket notation

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

:books: Documentation

The official documentation can be found on Read The Docs :newspaper:

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:newspaper: Blog Posts

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

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:pray: 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 :heart:

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:spider_web: Dependencies

Instascrape primarily relies on two third-party libraries for requesting and scraping Instagram HTML content:

1. Requests: HTTP requests
2. BeautifulSoup: Scraping and parsing HTML data.

The rest of its functionality is provided directly from Python 3's standard library for unobtrusive code under the hood with little to no overhead.

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:credit_card: License

MIT

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:grey_question: Support

Check out the FAQ

Reach out to me if you have questions or ideas!

• Email:
  • [e-mail]
• Twitter:
  • @ChrisGreening2
• LinkedIn
  • Chris Greening

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