Data-File-Text-Analysis-App

After pulling from this project, you have to do a few simple steps. 

Steps:
Create a new terminal.
Select cmd.
cd into the correct directory. It should look something like this C:\Users\{user}\Downloads\Data File Analysis App\Data-File-Text-Analysis-App>
Create a virtual environment after making sure you are in the project directory. Execute python -m venv 
Execute .\venv\Scripts\activate to activate the environment. 
Install these using pip: TextBlob, newspaper, werkzeug, flask, flask_executor
Once done, run python app.py to start the host. 
Once, you get to the page, then upload a file or enter a url. 
Press the submit button, and you will get the stats.


Documentation for scaling: 
  I have recently taken a course on Amazon AWS. This application could be scaled with Amazon Elastic Beanstalk. Elastic Beanstalk automatically manages scaling and load balancing. Also Amazon S3 can be used for storage. 

  For scalability we can transform the app to be stateless, which just avoids data or results being stored locally on a single server. We can use Amazon RDS, for example, to manage user data and results.