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This article introduces how to build a Python and Flask based web application for performing text analytics on internet resources such as blog pages. To perform text analytics I will utilizing Requests for fetching web pages, BeautifulSoup for parsing html and extracting the viewable text and, apply the TextBlob package to calculate a few sentiment scores.
This is a continuation from Building a Text Analytics App in Python with Flask, Requests, BeautifulSoup, and TextBlob and will focus on deploying the previously built app to a cloud hosted Ubuntu LTS v18 server. For this article I will be running the Flask app within the Web Server Gateway Interface (WSGI) compliant Python application server known as uWSGI. The Flask app / uWSGI server will sit behind an Nginx web server which serves static content plus reverse proxy non-static requests to uWSGI