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Polyglot Data Analysis and Visualization API using METACALL

In this example we show how to use Numpy and Matplotlib (Python) from an WebSocket server (NodeJS) in order to build a Polyglot Data Analysis and Visualization API.

Install

Clone the repository:

git clone https://github.com/pawxnsingh/numpy-matplotlib-websocket-node-example

Install MetaCall CLI:

curl -sL https://raw.githubusercontent.com/metacall/install/master/install.sh | sh

Navigate to the directory:

cd numpy-matplotlib-websocket-node-example

Install application dependencies:

metacall pip3 install -r requirements.txt 
metacall npm install

Run the Application

metacall index.js

For testing it, in another terminal, let's visualize this data calculating the mean, median, standard deviation of this array [10, 12, 14, 15, 10, 11, 150] (you can change the values and size for experimenting)

use postman/hoppscotch(web)

URL: ws://localhost:8080
Message: {"numbers": [10, 12, 14, 15, 10, 11, 150]}

It should output something like:

output: look for the output folder for the visualized view

Docker

An alternative version with Docker and automated testing is provided.

docker build -t metacall/numpy-matplotlib-websocket-node-example .
docker run --rm -v $(pwd)/output:/metacall/output -p 8080:8080 -it metacall/numpy-matplotlib-websocket-node-example