Scraping Instagram Followers Ultimate Guide

scraping instagram

Scraping Instagram refers to extracting data from Instagram’s website. This can be done manually, but it is more commonly done using a software program. There are many reasons someone might want to scrape data from Instagram, such as for marketing research or creating a user database.

Instagram is a popular social media platform with over 1 billion monthly active users. It is a great platform for businesses and individuals to connect with potential customers and followers. However, Instagram does not make it easy to get data about its users. This is where web scraping comes in.

Web scraping can get data about Instagram users, such as their username, full name, profile picture, bio, and number of followers. This data can be very valuable for businesses and individuals who want to target potential customers on Instagram.

Many software programs can be used for scraping Instagram. Some of these programs are free, while others are paid. It is important to choose a program that is reliable and easy to use.

Web scraping can be time-consuming, but it is worth it if you need data from Instagram. This guide shows the basic tools you need and gives you a sense of what it’s like to scrape Instagram. 

scraping instagram

What’s Instagram Scraping?

Web scraping is the process of extracting data from websites. It can be done manually, but it is often done using automated software.

There are many reasons why someone might want to scrape data from Instagram. For example, they might want to collect data on a particular hashtag, or they might want to collect data on the followers of a particular account. 

Scraping Instagram can be done using a number of different tools and methods. Some people use specialized software, while others use more general-purpose web scraping tools.

Once the data has been scraped, it can be analyzed and used for various purposes. For example, it could be used to create a list of potential customers, or it could be used to track the growth of a particular hashtag.

There is no definitive answer to this question as the legality of web scraping Instagram (or any other website) depends on a number of factors, including the jurisdiction in which the scraping is taking place, the purpose of the scraping, and how the scraping is conducted.

Generally speaking, web scraping is legal in jurisdictions where it is not expressly prohibited by law. However, there are some exceptions to this rule. For example, in the United States, the Computer Fraud and Abuse Act (CFAA) prohibits unauthorized access to protected computer systems, which could potentially be interpreted to include web scraping.

The purpose of web scraping also has an impact on its legality. If the scraping is done for commercial purposes, it is more likely to be considered illegal, as it could be seen as a form of competition. However, if the scraping is being done for non-commercial purposes, such as research or data analysis, it is more likely to be considered legal.

Finally, how web scraping is conducted also impacts its legality. If the scraping is done in a way that is disruptive or damaging to the website, it is more likely to be considered illegal. For example, suppose the scraping is conducted in a way that overloads the website’s servers or prevents other users from accessing the website. In that case, it is more likely to be considered illegal.

Checklist for scraping Instagram.

To web scrape Instagram, you will need a few tools. 

Web Scraping Tools

There are a few different web scraping tools for Instagram that can be used to gather data from the site. The most popular of these is probably the Instagram API, which allows developers to access certain data from Instagram’s servers. However, the API has some limitations, so it’s not always the best option.

Another popular web scraping tool is the Instagram Scraper, a Python-based tool that allows you to scrape data from public Instagram accounts. It’s open source and relatively easy to use, so it’s a good option if you’re looking to get started with web scraping.

Finally, there’s also the option of using a web scraping service to do the scraping for you. These services are usually more expensive, but they can be a good option if you don’t want to deal with the technical aspects of web scraping.

Data Storage

There are several ways to store scraped data from Instagram. One way is to use a database, such as MySQL. Another way is to use a data file, such as a CSV file.

You will need to create a table to store the data using a database. The table should have columns for all the data you want to store, such as the username, the post URL, the image URL, and the caption.

Using a data file, you must create a header row with the same columns as the table. Then, you can add each row of data underneath the header.

Multiple Instagram Profiles

There are a few reasons someone might want to use multiple profiles to bypass Instagram scraping limits. Maybe they are trying to collect data for a research project and need to gather a large amount of information. Or, they could be running a business that relies on Instagram data and needs to reach the limit to continue operating.

Whatever the reason, using multiple profiles is one way to get around the limit. The process is simple: create multiple accounts, each with its unique IP address. Then, use a tool to rotate between the accounts and scrape the needed data.

There are a few things to keep in mind when using this method. First, make sure that the accounts you create are all active and have been verified. Otherwise, Instagram may flag them, and you won’t be able to use them to scrape data. Second, you’ll need to be careful about how much data you scrape from each account. If you go too far, Instagram may detect what you’re doing and block all of the accounts you’re using.

Overall, using multiple profiles to bypass Instagram scraping limits is a simple and effective way to get the data you need. Just be sure to use active and verified accounts, and don’t go overboard with the amount of data you collect.

Instagram Proxies

A proxy is an IP address that can be used to mask your real IP address. This is useful when you want to scrape Instagram because it means you can make requests to the Instagram servers without them being able to trace them back to you.

There are a few things to keep in mind when using proxies for scraping:

1. Make sure to use a reputable proxy service. Many free and paid proxy services are available, but not all are created equal. Do your research to make sure you’re using a service that will give you a reliable connection.

2. Rotate your proxies often. If you’re making a lot of requests to Instagram, they will start to notice if they all come from the same IP address. By rotating your proxies, you can make it more difficult for them to track your activity.

3. Be careful not to abuse the API. If you make too many requests quickly, Instagram may throttle your access or even ban your IP address. Use proxies judiciously to avoid getting in trouble.

Building your own Instagram Scraper vs. Instagram Scraping APIs

There are a few reasons you might want to scrape Instagram data. Maybe you want to collect data for research purposes or build your own marketing tool. Whatever the reason, you have two main options for scraping Instagram data: building your own scraper or using an Instagram scraping API.

Building your own scraper has a few advantages.

  • It gives you more control over the data you collect. You can customize your scraper to collect exactly the data you need.
  • Building your own scraper can be more cost-effective than using an API since you don’t have to pay for an API subscription.

Using an Instagram scraping API has a few advantages.

  • It’s easier and faster to use an API than to build your own scraper.
  • You don’t need any technical skills to use an API.
  • An API is more likely to be updated if Instagram changes its website.

There are some disadvantages to building your own scraper.

  • It takes more time and effort to build a scraper than to use an API.
  • You need to have some technical skills to build a scraper.
  • If Instagram changes its website, your scraper might stop working.

However, there are also some disadvantages to using an API.

  • You have to pay for an API subscription.
  • You might not be able to collect exactly the data you need.
  • An API can be rate-limited, which means you might not be able to collect as much data as you want.

So, which should you choose? It depends on your needs. If you need more control over the data you collect or want to save money, you might want to build your own scraper. If you need to collect data quickly and easily, or if you don’t have any technical skills, you might want to use an API.

Scraping Instagram using Python.

Instagramy is a Python library that allows you to scrape data from Instagram. It is relatively simple to use and can be used to get data such as user information, posts, and comments.

To use Instagramy, you first need to install it using pip:

pip install instagramy

Once Instagramy is installed, you can create a script to scrape data from Instagram. For example, the following script will scrape data for a specific user:

from instagramy.client import InstagramyClient
client = InstagramyClient(‘your-instagram-username’, ‘your-instagram-password’)
user = client.get_user(‘username’)
print(user.username)
print(user.full_name)
print(user.bio)
print(user.profile_picture_url)
print(user.followers_count)
print(user.following_count)
print(user.posts_count)

The script above will print the username, full name, bio, profile picture URL, followers count, the following count, and posts for the specified user.

Instagramy can also be used to scrape data for a specific post. For example, the following script will scrape data for a specific post:

from instagramy.client import InstagramyClient
client = InstagramyClient(‘your-instagram-username’, ‘your-instagram-password’)
post = client.get_post(‘post-id’)
print(post.id)
print(post.caption)
print(post.likes_count)
print(post.comments_count)
print(post.media_url)

The script above will print the ID, caption, likes count, comments count, and media URL for the specified post.

Instagramy can also be used to scrape comments for a specific post. For example, the following script will scrape data for a specific post:

from instagramy.client import InstagramyClient
client = InstagramyClient(‘your-instagram-username’, ‘your-instagram-password’)
comments = client.get_comments(‘post-id’)

for comment in comments:

print(comment.id)
print(comment.text)
print(comment.author.username)

The script above will print the ID, text, and username of the author of each comment for the specified post.

Where to get proxies for Scraping Instagram.

If you’re looking for a way to scrape Instagram data, you may want to consider using IPBurger proxies. Proxies can help you bypass any restrictions that Instagram may have and allow you to collect data more easily.

When using proxies for scraping, it’s important to ensure they are high quality and reliable. IPBurger proxies are both of these things, and they can help you get the data you need without any issues.

Another benefit of using proxies is that they can help you stay anonymous. This is important if you don’t want Instagram to know that you’re scraping data.

Overall, using IPBurger proxies for scraping Instagram can be a great way to get the data you need while staying anonymous and avoiding any restrictions.

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