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BigDataIA-Spring2023-Team-03 / Assignment3

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FAST API

FASTAPI is used in the backend code to limit the user API request- monitor their subscribed plan usage and suggest an upgradation plan. There are also authentication tokens generated for each user login. The API uses the metadata.db database file to fetch values. A sign-in and authentication feature is added using JWT, which is also used for authentication for each user.

Architecture

architecture_diagram_assignment3

Streamlit

We have used Python Streamlit for the main front end of our application. This Streamlit application is hosted on port 8501 for local-host users. The app is paginated into several pages like login where users can log in to their account, register page where new users can sign up, and two other main pages that should be locked until login. These two pages or the file feature connect to the bank and fast API and the station locations for NEXRAD.

Apart from that it also monitors user activities like the number of API call requests by a user, the number of successful and unsuccessful call requests, etc

CLI

Here we have used the Typer library to define a command-line interface application that interacts with an API for data manipulation. Also, we have used the Poetry tool for dependency management and packaging in Python. It allows you to declare the libraries your project depends on and it will manage (install/update) them for you. Poetry offers a lock file to ensure repeatable installs and can build your project for distribution.

Docker

We have used Docker containers to containerize our application into three separate containers. Two of these containers, namely, the front-end and back-end container, can communicate with each other, which we have defined in the docker-compose.yaml file.

CLI

We have used typer-cli module to build CLI for our FAST Api. Typer CLI is a command line application to run simple programs created with Typer, with completion in your terminal 🚀.

You use Typer CLI in your terminal, to run your scripts as an alternative to calling python directly

Here are some Basic Commands for our cliapi.py

Usage: cliapi.py [OPTIONS] COMMAND [ARGS]...
Common Entry Point

╭─ Options ──────────────────────────────────────────────────────────────────────────────╮

│ *  --email   TEXT  Username [env var: APP_USERNAME] [default: None] [required]                                                                                                    

│ *  --password TEXT  Password [env var: APP_PASSWORD] [default: None] [required]                                                                                                      

│    --help      Show this message and exit.                                                                                                                                  

╰────────────────────────────────────────────────────────────────────────────────────────╯

╭─ Commands────────────╮

feild-selection                                                                                                                                                      

lat-long                                                                                                                                                            

s3-bucket                                                                                                                                                            

user-register  

╰─────────────────────╯

Here are list of some basic command examples: User Registration

python cliapi.py --email your_email --password password user-register First_name Last_name Tier Admin

Field Selection

python cliapi.py --email your_email --password password feild-selection table_name req_values

Example:

feild-selection-example

CLI Help can be accessed in following way:

cli_help

Command Help can be accessed in following way:

command_help

Wheels

We have used wheels as a pre-built binary package format for Python modules and libraries to access the APIs. They are designed to make it easier to install and manage Python packages, by providing a convenient, single-file format that can be downloaded and installed without the need to compile the package from source code

Pre-requisites

  1. Clone the repository: 
git clone https://github.com/BigDataIA-Spring2023-Team-03/Assignment3.git

  1. Open the Application folder on any IDE. For this example, we will be using Visual Studio Code.

  2. Open a new terminal in VSCode and type the following commands:

    docker-compose build

  3. Once the build is successful, run:

docker-compose up

  1. For running the app locally, once the above commands are still running, go to: http://52.201.212.226:8501/

  2. Here, you can register or login to the application. Once logged in, you would be redirected to the DataFetcher Page.

Acknowledgements

The CLI was built by the BigDataIA-Spring2023-Team-03 group as part of this assignment. Special thanks to the following technologies and Python Libraries:

Team Information

NAME NUID
Raj Mehta 002743076
Mani Deepak Reddy Aila 002728148
Jared Videlefsky 001966442
Rumi Jha 002172213

CLAAT Link

For Detailed documentation- Click here

Live Application Link

Application Link

Contributions