This Flask application retrieves and processes metadata from a GitHub repository, offering two main functionalities: viewing metadata as JSON and downloading metadata as a CSV file.

• View Metadata: Fetches metadata from configured GitHub repository and displays it as a JSON array.
• Download Metadata: Allows downloading the fetched metadata as a CSV file.

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

• Python 3.12
• Docker
• Git (for cloning the repository)

If you did not receive the code base as a zip file, clone it to your local machine:

git clone https://github.com/itssujeeth/file-metadata-service.git
cd file-metadata-service

Install the required Python packages:

pip install -r requirements.txt -r dev-requirements.txt

Configure the application by setting the following environment variables in your .env file or directly in your environment:

• GIT_OWNER: The owner of the GitHub repository.
• GIT_REPO: The name of the GitHub repository.
• SKIP_HEADER: (Optional) Whether to skip the CSV header in the download. Defaults to False.

To build the Docker image for the application, run:

docker build -t file-metadata .

To run the application in a Docker container:

docker run -p 5000:5000 file-metadata

This command runs the Flask application inside a Docker container and makes it accessible at http://localhost:5000. Also, it performs an initial download of the metadata and stores it within the volume as interview.csv. To download the file into your local folder run the below given command

docker ps | grep "file"
# This will help you get the running docker container id. Result will look similar to 
# CONTAINER ID   IMAGE                 COMMAND                  CREATED          STATUS          PORTS                    NAMES
# 29d03370caa6   file-metadata:0.0.1   "/app/start_and_down…"   20 minutes ago   Up 20 minutes   0.0.0.0:5000->5000/tcp   jovial_buck
#
# Next run the below command to copy interview.csv to local folder
docker cp <container_id>:/app/interview.csv </path/to/your/local/folder>

• To view metadata as JSON, navigate to http://localhost:5000/metadata in your web browser or use a tool like curl:

  curl http://localhost:5000/metadata

• To download the metadata as a CSV file, navigate to http://localhost:5000/metadata/download in your web browser. The file interview.csv will be downloaded to your local system.

To run unit tests make sure coverage is installed and then run the below given commands in the root folder of the cloned repo

coverage run -m unittest discover

coverage report -m

Prod deployment will require following additional steps:

• Update the Flask configuration for production use.
• Use a WSGI server like Gunicorn for running the application.
• Consider using a reverse proxy like Nginx in front of your application for better performance and security.