A full ecommerce app to learn react
The .env.sample
contains all the variables you need for this project to run
Make .env
in the root directory and update like this & REACT_APP_
is the compulsory prefix for the variable name.
REACT_APP_NODE_ENV="production"
REACT_APP_DB="http://localhost:5000"
Sign up for firebase and add your credentials in the .env
filea above. These credentials are found in Project Settings under the General tab
Make sure you have docker installed
Builds the docker image and runs a container from it
Stops and removes the container
Builds a production ready image
-
Follow this installation guide
-
heroku login
yarn deploy
The above is a script that builds the image and deploys to heroku
In the project directory, you can run:
Runs the app in the development mode.
Open http://localhost:3000 to view it in the browser.
The page will reload if you make edits.
You will also see any lint errors in the console.
Launches the test runner in the interactive watch mode.
See the section about running tests for more information.
Builds the app for production to the build
folder.
It correctly bundles React in production mode and optimizes the build for the best performance.
The build is minified and the filenames include the hashes.
Your app is ready to be deployed!
See the section about deployment for more information.
Deploys the app on github pages. Change the homepage
of the package.json
to your repository url
Note: this is a one-way operation. Once you eject
, you can’t go back!
If you aren’t satisfied with the build tool and configuration choices, you can eject
at any time. This command will remove the single build dependency from your project.
Instead, it will copy all the configuration files and the transitive dependencies (Webpack, Babel, ESLint, etc) right into your project so you have full control over them. All of the commands except eject
will still work, but they will point to the copied scripts so you can tweak them. At this point you’re on your own.
You don’t have to ever use eject
. The curated feature set is suitable for small and middle deployments, and you shouldn’t feel obligated to use this feature. However we understand that this tool wouldn’t be useful if you couldn’t customize it when you are ready for it.