Are you eager to leverage Instagram data to enhance your profile’s engagement? My latest blog post provides a step-by-step tutorial on creating a Python application using the Instagram Scraper 2023 API on RapidAPI. Here’s a preview of what you can expect:
Our Goal
We’re aiming to develop a Python application that can:
- Identify users who are liking your posts.
- Calculate the engagement rate by comparing the number of likes to the total number of followers.
This information is invaluable for deciding whether to focus on growing your follower base, increasing likes, or improving your content.
Essential Endpoints
To achieve our goals, we will utilize the following endpoints from the Instagram Scraper 2023 API:
- User Posts: Retrieves a list of posts by a specific user ID.
- Post Likes: Lists users who have liked a particular post.
- User Followers: Lists the followers of a specific user.
Key Implementation Details
Our RapidApiClient class in Python is designed to simplify data retrieval:
- get_user_posts: Fetches posts by user ID and supports pagination with
end_cursor. - get_post_likes: Retrieves the list of users who liked a specific post.
- get_user_followers: Fetches followers of a particular user.
Example Code
Here’s how to fetch more than 50 posts using pagination — end_cursor:
end_cursor = None
for i in range(2):
posts = api_client.get_user_posts('11579415180', 50, end_cursor)
if not posts["data"]["next_page"]:
break
end_cursor = posts["data"]["end_cursor"]
print(posts)Skopiuj kThis script runs twice, retrieving up to 100 posts by using end_cursor for pagination.Next Steps
With our client set up, the next part of the tutorial will focus on analyzing the data to provide actionable insights for optimizing your Instagram profile.
Ready to dive deeper? Read the full tutorial here and start enhancing your Instagram strategy today!
