Scraping of websites can provide a great way for businesses to collect essential marketing and advertising data. Instagram in this case is one of the most interesting and rewarding platforms to test your scraping projects. However, there are also tricky parts and we will cover them in this article.
What is Instagram Scraping
Instagram scraping can be described as an automated process of harvesting data available to the public. You can also collect these data manually, but a software created specifically for tasks like that will extract much more data in a shorter period. With the help of scraping tools or custom solutions, it is pretty easy to scrape data from Instagram.
Web scrape Instagram solutions can be useful in many cases, but mostly it involves marketing tasks. Web scraping provides needed information for different kinds of analysis of the market at the same time. For instance, you can start monitoring online brands or try to find influencers specifically for your type of product.
You can also decide to scrape Instagram likes and posts, because Instagram itself doesn’t provide support for scraping and doesn’t provide any API. Keeping this in mind, it is also wise to power up your web scraper with a set of residential proxies to maximize output.
How to Safely Parse Instagram
You can stay legal while scraping social media as long as you follow the set of rules for this kind of activity. Web scraping is considered legal if data that you harvest is publicly available, not copyrighted and does not involve any personal information. This rule is implied not only to Instagram, but to all web scraping activities.
However, Instagram has one more rule to remember when you think about how to scrape Instagram data. In all of that process, it is better to scrape Instagram without login in order to get relevant results and not get IP banned in the process. Meta has a strict set of rules for cases of data misuse.
For safe Instagram parsing, you must consider IP hiding solutions. This way, you will be able to harvest needed data without flouting the limit of data that can be accessed without login. The best way here is to consider a datacenter rotating proxies solution for getting access to different IPs in a short time.
What Can Be Scraped From Instagram?
Instagram tends to change the acting rules often, so it is wise to double-check the current list of what you can scrape. In the time this article is created, Instagram allows access to several categories of data.
First, you can scrape Instagram accounts and user profiles data like their bio information, likes, images, comments and the list of followers. You also can work with hashtags information that include URLs for posts, media and popular authors IDs. Lastly, there is a possibility to scrape posts data that can include latest posts of the user, data of posts, URLs, likes and comments. But, there is a limitation and do not allow you to scrape private Instagram data.
All the information when extracted and structured can become a base for a marketing research or other commercial analysis. This in its turn can help to maintain and expand advertising horizons for certain businesses.
Instagram Scraping Tools
If you think about how to scrape Instagram posts or other data, there are special tools that can make good use. First, you can try to create your own tool with help of special frameworks like Requests or Playwright. We will cover the use of Request in Python in this article later. A solution like this can handle a complex task and most importantly, you can have control over all operations. This way your scraper can be fast and easily be adapted to any new Instagram changes in scraping policies.
Otherwise, you can try scrape instagram with pre-built solutions that are available on the market. Tools like these can provide you with basic functionality without any requirements to your programming skills.
The third way lies in the field of using API opportunities for scraping. Right now, Instagram stopped spreading his own API, so the only option here will involve the third-party API providers. You can use this API together with ready-made scrapers and get dissent results. This way you can face some limitations that can vary from provider to provider, but overall results can be achieved with this setup as well.
All of these tools involve complicated processes inside. Your chances of successful data scraping also relies on your ability to maintain patience. Some types of request can fail far more than others. A failed request will cause a proxy error, so with a big scale project you need to consider using a datacenter proxies for maintaining scraping abilities through the long time.
Step by Step Guide to Scraping Instagram Using Python
Now we can cover the topic of how to scrape data from Instagram in more detail. In this guide, we’ll be using a widely used library for Python that is called Requests. This library sends your requests only to external browsers, which can cause a much higher number of mistakes in parsing. However, with Requests you can scrape data from Instagram at higher speeds and even with mistakes get good results.
You can start with importing Requests, JSON, and Random elements in your project. After, you need to print out results, so the output of the console can be formatted. With this in hand, you can begin setting up a username list that needs to carry all the accounts that we want to scrape. Only after this, proceed with static residential proxies or other kind set up and build the dictionary to store results of scraping.
Now you can begin and write down a major part of code by calling the main() function. Put together all the headers and mask your request, so they won’t be blocked by Instagram. Keep in mind that headers need to rotate a number of user agents for start. Now add the code part that will check the account list that you need to scrape all over again. After this, write a line for finishing sending the request and turn on the private proxy and after that headers.
You can understand whether your request failed or not by checking the response form JSON. If the results you are searching for did not appear in JSON, that can mean your request failed. In this case the script will proceed scraping the next user.If you manage to get the right results in JSON response, you can start parsing your data further. If errors appear in this process, you can try to catch them with retry logic. Now you need to create a parse_data() function to gather data from JSON. For example, try to extract post captions and make them into a list.
Frequently Asked Questions
Please read our Documentation if you have questions that are not listed below.
What is Instagram scraping?
In simple terms, Instagram scraping comes as an automated process of collecting publicly available data. Businesses often use this process for adjusting or tracking marketing strategies.
What proxies are best for scraping in Instagram?
Depending on your tasks you can use different proxy setups. For example, if you look for a fast tool with a big pool of IPs, datacenter proxies can be your choice. Or, you can choose the residential proxies, if you need some geo-targeted information harvesting.
What data can be scraped from Instagram?
Right now Instagram allows users to scrape publicly accessible profiles data like their bio information, likes, images, comments and the list of followers. Also you can scrape hashtags and data like likes and comments from posts itself.
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