How to Scrape Instagram Data using Python in 2024: A Step-by-Step Guide

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

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, with an 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 many features, from short-form videos to live streams. 

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’s first understand why you need to scrape this data.

Feel free to jump to any section to learn more about how to scrape Instagram using python!

Table of Contents

• Why Do You Need To Scrape Instagram?
• Scraping Instagram Using Python InstallationScraping Instagram User ProfilesDealing with Followers And FolloweesDownload Posts from Instagram Hashtags
• Installation
• Scraping Instagram User Profiles
• Dealing with Followers And Followees
• Download Posts from Instagram Hashtags
• Why Use Instagram Proxies?
• Best Proxy For Scraping Instagram:
• FAQs:
• Conclusion

Why Do You Need To Scrape Instagram?

Instagram unites individuals and attracts people with its multifaceted topics like fashion, food, fitness, and traveling. 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 daily 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: ViewedLikedEngaged with
• Viewed
• Liked
• Engaged with

• Learning more about the target audience – The data about the target audience can determine the following: The engagement level among your audienceFollowers and following of your audienceHow frequently your audience postsHashtags your audience uses most oftenAge and gender of the most active users
• The 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 followMost engaged usersHashtags to usePosts that work well now
• Users to follow
• Most engaged users
• 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 your followers’ hashtags when posting photos and videos. This way, you can know what type of content they prefer.

Scraping Instagram Using Python

You can use 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.

Installation

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 the 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')
print(type(profile))

We use the type() function on the loaded profile that tells us that it 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 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 an instaloader, we can retrieve the list of the usernames of followers and followees ( of a particular username). Remember that you need to log in 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'{hashtag.name}_{index}')

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

login = session.post('https://www.instagram.com/accounts/login/ajax/', data={'password': passwd, 'username': user}, allow_redirects=True)

Just add a variable “proxies” like this:

login = session.post('https://www.instagram.com/accounts/login/ajax/', data={'password': passwd, 'username': user}, allow_redirects=True, proxies=proxies)

where

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, 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’s 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. 

Best Proxy For Scraping Instagram:

ProxyScrape is one of the most popular and reliable proxy providers online. Three proxy services include dedicated datacentre proxy servers, residential proxy servers, and premium proxy servers. So, what is the best possible solution for how to scrape Instagram using python? Before answering that questions, it is best to see the features of each proxy server.

A dedicated datacenter proxy is best suited for high-speed online tasks, such as streaming large amounts of data (in terms of size) from various servers for analysis purposes. It is one of the main reasons organizations choose dedicated proxies for transmitting large amounts of data in a short amount of time.

A dedicated datacenter proxy has several features, such as unlimited bandwidth and concurrent connections, dedicated HTTP proxies for easy communication, and IP authentication for more security. With 99.9% uptime, you can rest assured that the dedicated datacenter will always work during any session. Last but not least, ProxyScrape provides excellent customer service and will help you to resolve your issue within 24-48 business hours. 

Next is a residential proxy. Residential is a go-to proxy for every general consumer. The main reason is that the IP address of a residential proxy resembles the IP address provided by ISP. This means getting permission from the target server to access its data will be easier than usual. 

The other feature of ProxyScrape’s residential proxy is a rotating feature. A rotating proxy helps you avoid a permanent ban on your account because your residential proxy dynamically changes your IP address, making it difficult for the target server to check whether you are using a proxy or not. 

Apart from that, the other features of a residential proxy are: unlimited bandwidth, along with concurrent connection, dedicated HTTP/s proxies, proxies at any time session because of 7 million plus proxies in the proxy pool, username and password authentication for more security, and last but not least, the ability to change the country server. You can select your desired server by appending the country code to the username authentication. 

The last one is the premium proxy. Premium proxies are the same as dedicated datacenter proxies. The functionality remains the same. The main difference is accessibility. In premium proxies, the proxy list (the list that contains proxies) is made available to every user on ProxyScrape’s network. That is why premium proxies cost less than dedicated datacenter proxies.

So, what is the best possible solution for for how to scrape Instagram using python? The answer would be “residential proxy.” The reason is simple. As said above, the residential proxy is a rotating proxy, meaning that your IP address would be dynamically changed over a period of time which can be helpful to trick the server by sending a lot of requests within a small time frame without getting an IP block. 

Next, the best thing would be to change the proxy server based on the country. You just have to append the country ISO_CODE at the end of the IP authentication or username and password authentication.

Suggested Reads:

Scrape YouTube Comments – 5 Simple StepsThe Top 8 Best Python Web Scraping Tools in 2023

FAQs:

Conclusion

We discussed that you could 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.

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