TwitterScrape | A Twitter scraping tool using Scrapy | Scraper library

I'm trying to do a personal project for my portfolio, I would like to scrape the tweets about the president Macron but I get this error with twitterscrapper.

I am working on my first webapp project which I plan to publish using a remote server. I have a question about the architecture.

My webapp is to scrape tweets using twitterscraper Python package. A user who visits the website enters some keywords and click "Scrape" button. A Python backend scrapes the tweets containing the keywords, goes through some Natural Language Processing analysis, and visualise the result in charts. This twitterscraper package lets you scrape tweets using Beautiful Soup, therefore you don't need to create an API credential. The scraping speed depends on the bandwidth of the internet that you are using.

I made a Python script, JavaScript file, html file and css file. In my local environment the webapp works perfectly.

So the question is, after I put these files on the hosting server and publish the webapp, when a user clicks "Scrape" button, on what does the scraping speed depend? The bandwidth of the internet that the user is using? Or is there any "bandwidth" that the server is relying on?

As I said I am very new to this kind of architecture. So it would also be nice to suggest me an alternative way for structuring this kind of webapp. Thank you!

I am using twitterscraper from https://github.com/taspinar/twitterscraper to scrap around 20k tweets created since 2018. Tweet locations are not readily extracted from the default setting. Nevertheless, the search for tweets written from a location can be done by using advanced queries placed within quotes, e.g. "#hashtagofinterest near:US"

Thus I am thinking to loop through a list of country codes (alpha-2) to filter the tweets from a country and add the info of the country to my search result. Initial attempts had been done on small samples for tweets in the past 10 days.