Giter Club home page Giter Club logo

pnestjs's Introduction

Project 'bgsAndSnailR' and 'nest-transactions' README

This README file explains how to set up and run the 'bgsAndSnailR' and 'nest-transactions' applications using Docker Compose.

More Information

โš ๏ธ Important: For more detailed information, including specifics about the API ENDPOINTS and any additional functionality, please refer to the README files located within each individual module's directory.

Prerequisites

You need to have Docker and Docker Compose installed on your machine. Confirm that you have them installed by running the following commands in your terminal:

docker --version
docker-compose --version

Setup

The project uses two services, bgsAndSnailR (a Python application) and nest (a NestJS application). Firstly, clone this repository to your local machine and navigate to the root directory of the project.

git clone <repository-url>
cd <repository-directory>

Environment Variables

The NestJS application requires an environment file for configuration. Please send me an email to [email protected] to request the .env file. Once you've obtained the file, place it in the ./nest-transactions directory.

Building and Running the Services

To build and run the bgsAndSnailR service, use the following Docker Compose commands:

docker-compose build bgsandsnailr
docker-compose up bgsandsnailr

Similarly, to build and run the nest service, use the following Docker Compose commands:

docker-compose build nest
docker-compose up nest

After running these commands, your bgsAndSnailR and nest applications should execute as expected. The bgsAndSnailR service is set up to run a test and then complete its execution. On the other hand, the nest service will continue running and will be accessible at http://localhost:3000.

Insomnia Setup

The repository includes an insomnia.json file which contains a pre-configured set of requests for the CRUD operations of the NestJS application. To use these pre-configured requests, you will need to import the insomnia.json file into Insomnia, a popular REST client. Follow the steps below to import the insomnia.json file into Insomnia:

  1. Install Insomnia REST client if you haven't done so already. You can download it from the official website.
  2. Open Insomnia, click on the "Application" menu (three horizontal lines on the top left of the window), and then choose "Preferences". In the Preferences window, switch to the "Data" tab.
  3. Click on the "Import Data" button, then select "From File". Navigate to your project directory and select the insomnia.json file.
  4. After importing, you should see a new set of requests in your Insomnia workspace, all set up to interact with the NestJS application.

Remember, your NestJS application needs to be running (with docker-compose up nest) for these requests to work. The application will be accessible at http://localhost:3000. With this setup, you can easily test the CRUD operations of your NestJS application without manually entering the request URLs and parameters.

pnestjs's People

Contributors

erwaen avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.