Component — React Search API
This application connects "The Movie Database" API with a React interface and Node runtime to create a filtered search for movies, ratings, descriptions, and posters through a Fetch network request.
This application was built with React, runs on Node, and connects to "The Movie Database" API
A good movie is hard to find and sometimes you only remember part of the title, whichever the example, find the movie you were looking for with relevant suggestions, ideas, and titles. From a massive archive of movies, titles, and motion pictures connected to an efficiently programmed application that runs in your browser.
Make movie nights more enjoyable with a simple and scalable application to enhance the movie nights the way you like, for the way you watch.
Connecting to the API with event-based actions allows the developer to build upon the simplistic application to define the more views, searches, and features with integration as a simple outcome of component addition.
This application is built using React & Node with a Fetch request/promise and functional JavaScript components, providing the ability to adapt to increased usability with iteration.
This project was bootstrapped with Create React App which means all components, classes, and functions work within an unejected react application. You can learn more in the Create React App documentation. To learn React, check out the React documentation. To get started fork, download, or git clone this repository to retrieve the codebase.
This application and its components were built through Yarn, with React, and run on Node.js all prerequisites are listed below, the rest are active in the directory of the project file and become accessible with the script yarn install
.
Create your The Movie Database account & signup for an API. https://developers.themoviedb.org
Install Yarn Package Manager https://yarnpkg.com/
Clone the repo
git clone https://github.com/collectedview/react-movie-night.git
Create a new file in your project folder titled .env
Enter your API Key into .env
REACT_APP_NOT_SECRET_CODE=ReplaceWithYourAccessToken
Install the directory through yarn in your console
yarn install
In the project directory, you can run:
yarn start
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.
yarn test
Launches the test runner in the interactive watch mode. See the section about running tests for more information.
yarn build
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.
yarn eject
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.
Enhancing the use of React Movie Night, the search functionality could have actions to filter the choices, explore based on genres, and view movies based on ratings.
Added event handlers and defining more logic along with event pooling, could be deployed to create a more interactive solution. Conditional based logic could improve the experience when searching for a movie.
Integrating packages to handle more in-depth searches and indexing could allow for less browser rendering, and increase the proficiency of movie identification. Building a recommendation engine begins with connecting search-based crawlers that identify logged searches and improved terms.