How To Scrape Instagram Using Python - ProxyScrape

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What is this trendy thing called Instagram that all kids are into? It is a social networking platform where you can share your photos and videos. It has become a popular way to connect with celebrities, brands, family, friends, and thought leaders as it has over one billion users worldwide. Instagram is just a simplified version of Facebook having emphasis on mobile use and visual sharing. You interact with other users by following them, letting others follow you, liking, tagging, commenting, and private messaging. So, Instagram has a vast array of features from short-form videos to live streaming. 

With the help of Instagram scraping, you can gather publicly available data from Instagram users. You can manually extract the data, or use scraping tools and Instagram scraping services. You can scrape data such as bio, likes, comments, images, phone numbers, emails etc. But let first understand why you need to scrape this data.

Why Do You Need To Scrape Instagram?

Instagram unites individuals and attracts people with its multifaceted topics like fashion, food, fitness, and travelling. You can scrape particular user data such as:

  • Contact number
  • Email
  • Hashtags
  • Comments
  • Locations
  • Bios 
  • Followers
  • User ID
  • Following Accounts

Businesses scrape data from Instagram everyday as scraping provides them with rich datasets. It also helps them in:

  • Identifying trends – They enable you to make posts that have a better chance of being:
    • Viewed
    • Liked
    • Engaged with
  • Learning more about target audience – The data about target audience can determine:
    • Engagement level among your audience
    • Followers and following of your audience
    • How frequently your audience posts
    • Hashtags your audience uses most often
    • Age and gender of the most active users
  • Expanding Follower Base – It ensures that your follower base is relevant and targeted and it also helps you build your brand and expand your reach. 
  • Knowing what your competitors are doing – The competitors provide a gold mine of information. So, you can scrape the information of your competitors to your advantage. You can gather the following information:
    • Users to follow
    • Users that are most engaged
    • Hashtags to use
    • Posts that work well now
  • Finding Inspiration for new content – You can get new ideas for your own content by scraping Instagram data. You can also see the hashtags that your followers use when posting photos and videos. This way, you can have an idea what type of content they prefer.

Scraping Instagram Using Python

You can use the Instagram scrapers to access the data you require. They save your time by

rapidly scraping Instagram data from profiles, and saving all the available information to a ready-to-use .csv file. In short you can use the scrapers to:

  • Scrape data from Instagram profiles
  • Enumerate the count of posts created, followers, following
  • Identify email addresses specified within the bio of scraped profiles
  • Determine if accounts are private or public
  • Get ready-to-use scraped data in an Excel file

Let’s see how we can scrape Instagram data using Python. We will use instaloader which is a reliable Python package.


You can use pip to install the instaloader package.

pip install instaloader

Scraping Instagram User Profiles

First of all, we import the instaloader package.

import instaloader

We create an instance of the Instaloader class. Remember that the class name is different from the package name.

bot = instaloader.Instaloader()

The above instance of the class comes with lots of built-in properties that are specific for this unique instance within bot.context. It contains the following:

  • User profile credentials if logged in
  • Helper functions for logging warning errors

Now, we use the .from_username() method of Profile class of Instaloader, and pass bot.context and the username of our choice by using the following command.

profile = instaloader.Profile.from_username(bot.context, 'python_scripts')

We use the type() function on the loaded profile that tells us that is an instance of another instaloader class i-e., instaloader.structures.Profile. 

These profile objects possess a lot of properties. The below code shows some of the examples of these properties.

# Instagram Handle and Profile ID
print("Username:", profile.username)
print("User ID", profile.userid)
# Number of Followers and Followees
print("# of followers:", profile.followers)
print("# of followees", profile.followees)  

Dealing with Followers And Followees

With the help of instaloader, we can retrieve the list of the usernames of followers and followees ( of a particular username). Remember that you need to login before trying this code.

We can use the below code to retrieve the usernames of the followers and followees.

# Retrieve the usernames of all followers
followers = [follower.username for follower in profile.get_followers()]

# Retrieve the usernames of all followees
followees = [followee.username for followee in profile.get_followees()]

Download Posts from Instagram Hashtags

To load the hashtag, we use instaloader.Hashtag.from_name() as shown below. Remember to login before trying this code.

hashtag = instaloader.Hashtag.from_name(bot.context, 'python')

We load posts with a python tag into a generator object.

python_posts = hashtag.get_posts()

We iterate over the posts and download them.

for index, post in enumarate(python_posts, 1):
    bot.download_post(post, target=f'{}_{index}')

In order to use proxies for scraping Instagram, go to your file and find the def login() function at line 178. Now, find the line 199 of this function. It will be as:

login ='', data={'password': passwd, 'username': user}, allow_redirects=True)

Just add a variable “proxies” like this:

login ='', data={'password': passwd, 'username': user}, allow_redirects=True, proxies=proxies)


'http':'YOUR PROXY',
'https':'YOUR PROXY'

Why Use Instagram Proxies?

Instagram is becoming immensely popular among market analysts, social media influencers, businesses, and online brands. It uses residential and datacenter proxies because of the following reasons:

Run multiple accounts – Instagram is particular about the number of accounts accessed via the same IP address, i-e., it’s one account per IP address. However, the digital marketing agencies and social media managers have to manage multiple Instagram accounts to expand their reach. Their activity on various accounts from one IP address can be considered spam-like and may lead to penalties from temporary activity limitation to permanent account ban.

So, to avoid getting banned on Instagram, social media managers and digital marketers use proxies for simulating multiple accounts from different IP addresses. The proxy acts as an intermediary between the Instagram servers and the user computer, masking the actual user IP address with a new one. 

Use Market Automation tools – To speed up the marketing process, Instagram marketers use bots and automation tools to gain thousands and millions of followers, likes, and comments organically. But, like most social media platforms, Instagram has strict networking policies. You can have a significant setback for yourself if you resort to any unfair means of getting traffic to your account. You may be restricted from performing specific actions such as commenting on posts, and your account may be suspended and blocked. Therefore, you have to use Instagram proxies with bots for additional security.

Bypass IP Blocking – You can use Instagram proxies to solve the problem of IP blocking and geo-restrictions. You know Instagram has strict social networking guidelines that make it challenging to use bots, and your account can get blocked if it detects any unusual activity. However, with the help of Instagram proxies, you can bypass IP blocking. These proxies hide your actual IP address from that of a proxy server’s IP address. Consequently, your original IP address gets protected from being banned. You can also use Instagram proxies to bypass geo-restrictions as they have proxy servers with diverse locations that help you access Instagram from remote locations. 


We discussed that you can use Python to scrape Instagram data like emails, hashtags, followers, following, locations, comments, etc. Scraping provides businesses with a wide range of advantages that can help build their name. Further, Instagram proxies are a blessing for social media influencers as they allow them to use multiple accounts simultaneously and bypass IP blocking and geo-restrictions. You can either use residential proxies or datacenter proxies for Instagram, but it is good to use residential proxies as they are fast and never get blocked.

Hope you got valuable insights into how to scrape Instagram using Python.