This repository includes information of scrapping data from instagram Web scraping data from Instagram involves extracting publicly available information from Instagram profiles, posts, hashtags, or comments. This can be done for various purposes, such as market research, trend analysis, or content aggregation. This is typically done using tools and libraries designed to simulate human browsing behavior and interact with Instagram's web interface. One such popular tool is Instaloader, which is a Python library used to download Instagram photos, videos, and metadata.Here's a detailed guide on how to scrape data from Instagram: Key Components of Instagram Web Scraping: 1.Authentication:
Login Credentials: To access private data or perform actions that require authentication, you need to provide your Instagram username and password. Two-Factor Authentication (2FA): If enabled, you will need to handle 2FA by entering a code sent to your device.
2.Profile Information:
User Details: Extract basic information such as username, user ID, biography, external URL, followers, followees, and the number of posts. Posts: Retrieve detailed information about posts, including captions, hashtags, timestamps, likes, comments, and URLs.
3.Followers and Followees:
Followers: Get the list of usernames that follow the profile. Followees: Get the list of usernames that the profile follows.
Conclusion Instagram web scraping can be a powerful tool for gathering data and insights, but it requires careful handling of login processes, session management, and compliance with Instagram's policies. Instaloader simplifies many aspects of this process, but ethical and responsible usage is paramount.