How To Scrape Followers Of Any Twitter User From Command Line

Due to the limit rate of twitter API I would like to know how could I scrape the number of followers from a Twitter account with Node.js in a very very fast way?Do you think Node.js is the best solution to do it?

What the below code does is, open the Twitter account page that you want to scrape followers from, and gets links of profile pages using locate element by xpath, while gradually scrolling down to get all the present followers.

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There are some online tools to export followers from Twitter but if you want to do the same thing from command line then this post will show you. This command line tool, Twint takes a username from you and then get you the list of followers on the terminal. With some tweaks, you can save the list in a text file. In the basic followers extraction, it only scrapes the Twitter handle and shows it to you. However, if you want to scrape Twitter users with some added information then you can do that.

In this way, this simple tool works to get you all the followers of any Twitter user. And not only downloading Twitter followers but you can also use this tool to scrape a lot of things from Twitter. You can see then details about this tool if you use it as a library on GitHub.

If you want to get followers of any Twitter user then you will not find much free tools for this. But if you are good at playing with command line tools, then it is a very nice methods to export Twitter Followers of a user. This tool precise scrapes Twitter followers and downloads them on your computer. No matter on what platforms you are, you will be able to us it easily. Then installation method is same for all the platforms that it supports.

Thanks for sharing the experiences and offering helps . I used two packages in Python, twarc and tweepy, to scrape the data from the twitter. I got confused at the first place after receiving the information as JSON format. Now, I learn how to convert the JSON structure to .csv format. Both stackoverflow and Github comunities are extremely helpful.

Snscrape is another approach for scraping information from Twitter that does not require the use of an API. Snscrape allows you to scrape basic information such as a user's profile, tweet content, source, and so on.

The above code is similar to the previous code, except that we changed the API method from api.user_timeline() to api.search_tweets(). We've also added tweet.user.name to the attributes container list.

As I mentioned earlier, Snscrape does not have limits on numbers of tweets so it will return however many tweets from that user. To help with this, we need to add the enumerate function which will iterate through the object and add a counter so we can access the most recent 100 tweets from the user.

Again, you can access a lot of historical data using Snscrape (unlike Tweepy, as its standard API cannot exceed 7 days. The premium API is 30 days.). So we can pass in the date from which we want to start the search and the date we want it to end in the sntwitter.TwitterSearchScraper() method.

Twint also sends unique requests to Twitter, enabling you to scrape a Twitter user's followers, Tweets likes, and who they support without the need for authentication, API, Selenium, or browser emulation.

lets start with the installation, its better that we can hack something new here, its basically scrapping the information that is available on web twitter-Twitter restricts scrolling when viewing a user's account. This means that by using. Profile or. Favorites will enable you to receive 3200 tweets..

Please keep in mind that Twitter reduces the amount of time you will spend scrolling through a user's timeline. As a result, you will not be able to see all of the tweets when running. Alternatively, Favorite Things

This simple addition tells Crawlbase to extract precise information from Twitter profiles and returns the data in JSON format. This can encompass a wide range of details, including the number of followers, tweets, engagement metrics, and more. It streamlines the data extraction process, ensuring you obtain the specific insights you require for your influence analysis.

twarc2 is a command line tool and Python library for archiving Twitter JSONdata. Each tweet is represented as a JSON object that was returned from theTwitter API. Since Twitter's introduction of their v2APIthe JSON representation of a tweet is conditional on the types of fields andexpansions that are requested. twarc2 does the work of requesting the highestfidelity representation of a tweet by requesting all the available data fortweets.

Twint utilizes Twitter's search operators to let you scrape Tweets from specific users, scrape Tweets relating to certain topics, hashtags & trends, or sort out sensitive information from Tweets like e-mail and phone numbers. I find this very useful, and you can get really creative with it too.

Twint also makes special queries to Twitter allowing you to also scrape a Twitter user's followers, Tweets a user has liked, and who they follow without any authentication, API, Selenium, or browser emulation.

This is the function that will scrape the tweets. os.system is used to run the command in the shell. snscrape is the command that will scrape the tweets. --jsonl is used to convert the output into a json file. --progress is used to show the progress of the scraping. --max-results is used to set the maximum number of tweets to scrape. --since is used to set the date from which you want to scrape the tweets

Before we get to the tutorial, maybe you'd like to start off by scraping some very specific Twitter data? Apify Store also offers a few specialized Twitter scrapers to carry out smaller scraping tasks. You only need to insert a keyword or a URL and start your run to extract your results, including Twitter followers, profile photos, usernames, tweets, images, and more.

#! python3# mapIt.py - Launches a map in the browser using an address from the# command line or clipboard.import webbrowser, sys, pyperclipif len(sys.argv) > 1: # Get address from command line. address = ' '.join(sys.argv[1:])else: # Get address from clipboard. address = pyperclip.paste()webbrowser.open(' ' + address)If there are no command line arguments, the program will assume the address is stored on the clipboard. You can get the clipboard content with pyperclip.paste() and store it in a variable named address. Finally, to launch a web browser with the Google Maps URL, call webbrowser.open().

#! python3# lucky.py - Opens several Google search results.import requests, sys, webbrowser, bs4print('Googling...') # display text while downloading the Google pageres = requests.get(' =' + ' '.join(sys.argv[1:]))res.raise_for_status()# TODO: Retrieve top search result links.# TODO: Open a browser tab for each result.The user will specify the search terms using command line arguments when they launch the program. These arguments will be stored as strings in a list in sys.argv.

Here you are using the CSS_SELECTOR to target this particular div and then extracting the visible text from it. This returns the name and username/handle with a newline character in between. You are then splitting the resulting string at the newline character and assigning the return values to name and username variables.

This recipe teaches you how to easily build an automatic data scraping pipeline using open source technologies. In particular, you will be able to scrape user profiles in LinkedIn and move these profiles into a relational database such as PostgreSQL. You can then use this data to drive geo-specific marketing campaigns or raise awareness for a new product feature based on job titles.

Both plans also advertise being able to scrape follower lists from any public account with Twitter API rate limits of 1 request (or 1,000 followers) per minute, per the Official Followers Endpoint Documentation.

As you can see, the data contains not just the text of the tweet, but information on who sent it, how many followers they have, and other metadata. This data is in JSON format, and can be read in and processed using the Python json library. As more tweets are sent to us from the Twitter API, they'll follow a similar format, of the length in bytes on one line, and the data for the tweet on the next length. All the tweets will be sent through the same persistent connection.

We now have all the pieces we'll need to stream data from the Twitter API! We'll just need to put everything together into a single file that we can run from the command line. This will enable us to stream tweets for as long as we want to. You can take a look at the final program that performs the streaming here. This program can be run by typing python scraper.py after which it will run forever, streaming tweets, processing them, and saving them to disk. You can use Ctrl+C to stop the program.

The website hosts many workflows shared by Automa users which a new user can add in a single click and customize according to their preferences. Some examples include downloading a series of images on Instagram, sending a WhatsApp broadcast to a list of users in a Google Sheet, scrape Twitter followers or following lists etc.

Test if the metrics have been received by Amazon Managed Service for Prometheus by using awscurl. This tool lets you send HTTP requests through the command line with AWS Sigv4 authentication. This means that you must have AWS credentials set up locally with the correct permissions in order to query from Amazon Managed Service for Prometheus.

All the VictoriaMetrics components allow referring environment variables in yaml configuration files (such as -promscrape.config) and in command-line flags via %{ENV_VAR} syntax. For example, -metricsAuthKey=%{METRICS_AUTH_KEY} is automatically expanded to -metricsAuthKey=top-secret if METRICS_AUTH_KEY=top-secret environment variable exists at VictoriaMetrics startup. This expansion is performed by VictoriaMetrics itself. be457b7860