Hola Sir
The solution for a python scraper for Instagram posts would be to use the Instagram API to gather the necessary information from the platform. This can be done by creating a developer account and obtaining an access token for the API. Other APIs such as RapidAPI can also be used in conjunction with the Instagram API to enhance the scraping process.
The first step in the scraping process would be to take the .txt file of the project and extract relevant information such as the username, hashtags, and any other specified criteria. This information can then be fed into the scraper to gather posts from the specified Instagram account.
Next, the API can be used to gather the posts from the specified account. This can be done by using the "user-posts" endpoint, which will return all the recent posts from the account. The API also allows for filtering by hashtags, location, and other criteria, which can be specified in the scraper.
Once the posts have been gathered, the API response will contain all the necessary information such as the post caption, likes, comments, and media files. The scraper can then parse through this data and extract the necessary information to be stored in a designated format, such as a CSV file.
The scraping process can be made even more efficient by using the Instagram API's pagination feature, which allows for the retrieval of more posts in a single request. This can be done by specifying a limit for the number of posts to be retrieved and using the "pagination" endpoint to retrieve the next set of posts.
Finally, the scraper can also use the API to collect additional information such as the profile picture, bio, and follower count for the specified user. This information can also be included in the output file along with the scraped posts.
In summary, a python scraper for Instagram posts using the Instagram API would involve extracting project information from a .txt file, using the API to gather posts, parsing through the data, and exporting it in a desired format. Additional features such as pagination and gathering profile information can also be implemented to make the scraping process more efficient.
Best regards,
Phạm Phước Duyên