sentiment_analysis_textblob

Sentiment Analysis using Textblob deployed through flask and docker.

To run the docker of sentiment analyzer app:

#First change the docker file to take app.py as the application script
1. Come to this directory.
2. Build the docker image : docker build -t sentiment_analysis_textblob.
3. Run the container :   docker run -p 8888:5000 --name sentiment_analysis sentiment_analysis_textblob

Now the docker is running on the port 8888 in localhost.

To run the docker of sentiment analysis to use it as a micro service for your application:

#First change the docker file to take api_app.py as the application script
1. Come to this directory.
2. Build the docker image : docker build -t sentiment_analysis_textblob.
3. Run the container :   docker run -p 8888:5000 --name sentiment_analysis sentiment_analysis_textblob

Now the docker is running on the port 8888 in localhost.

To supply the input, 
curl --request POST   
	 --url http://localhost:8888/analyse   
	 --header 'content-type: application/json'   
	 --data '{"rawtext":"Inoffensive and unremarkable."}'

The output:
	{
		"blob_sentiment": "0.5",
		"blob_subjectivity": "0.75",
		"final_time": "0.011960983276367188",
		"number_of_tokens": "9",
		"received_text": "The mother of such children would become very happy.",
		"summary": "['mothers']"
	}