Nformd is a full-stack web application inspired by Medium. It utilizes Ruby on Rails on the backend, a PostgreSQL database, and React.js with a Flux architectural framework on the frontend.
Nformd only ever loads a single webpage; all content is delivered on one static page. The children of the root element, the app component, listen to a SessionStore and render content based on calls to SessionStore.currentUser() and SessionStore.isUserLoggedIn(). Sensitive information and functionality meant only for users with accounts are kept out of the front end of the app unless a user has been successfully authenticated.
SessionStore.currentUser = function () {
return Object.assign({}, _currentUser);
};
SessionStore.isUserLoggedIn = function () {
return !!_currentUser.id;
};On the database side, the Stories are stored in one table, which contains columns for id, title, body, author_id and created_at. Upon login, all stories in the database are rendered to the stories_index component, a child of the app component (which renders the nav_bar above the stories). These stories are held in the StoryStore until the user logs out.
Individual stories are rendered as story_index_items, subcomponents of the stories_index. These show the author's customizable profile picture and name, as well as the time elapsed since the story was published, the estimated read time of the story, the story's title, a 25-word preview of the story, the number of recommendations that the story has received, and finally the number of textual responses to the story. The layout of the stories_index page is taken directly from Medium and styled to mimic Medium almost exactly:
Story creation takes advantage of the recently released Draft.js framework for rich text editing.
Implementing Responses started with a comments table in the database, which contains columns including author_id and story_id, body, and created_at.
The React component structure for responses mirrored that of stories: the comments_index component renders a list of comment_index_items as subcomponents, along with one comment_form component at the top of the list, with which users can add their own responses to stories. Newly added responses are immediately rendered inline.
The responses to a given story are continuously monitored by the CommentStore.
comment_index.jsx :
const CommentsIndex = React.createClass({
commentForm(){
if(SessionStore.isUserLoggedIn()){
return(
<CommentForm
currentUser={ this.state.currentUser }
storyId={ this.props.storyId } />
);
} else {
return(<div />);
}
},
render(){
let _comments = this.state.comments.sort(function(a, b){
return new Date(b.created_at) - new Date(a.created_at);
});
let commentIndexItems = _comments.map((comment, i) => {
return(
<CommentIndexItem key={ i } comment={ comment } />
);
});
return(
<div className="background">
<div className="comment-index">
<ul className="comment-list">
<li className="comment-list-title">Responses</li>
{ this.commentForm() }
{ commentIndexItems }
</ul>
</div>
</div>
);
}
});Users can follow and be followed by other users. These relationships are stored in their own followings table in the database. The followings table is a join table that joins followees to their followers (joins users back to users) from a follower_id column to a followee_id column.
Followings are maintained on the front end in the FollowingStore. Because viewing another user's profile page enables a Follow/Unfollow toggle button, these relationships can quickly be created and destroyed. The users total follows and total followers are displayed directly above the button, and the totals are continuously updated in real time.
In addition to the features already implemented, I plan to continue work on this project. The next steps for FresherNote are outlined below.
Below the user's profile, Medium displays a list of their followed users' stories, as well as their followed users' recent activity around the site (responses, recommendation, etc.). I plan to implement this feature for Nformd as well.
The cornerstone of Medium is their powerful story editing tools. I plan to utilize the wealth of currently unused Draft.js features to give users of Nformd a more robust and complete word processing experience.
Stories cannot currently be tagged to categorize them. Implementing this feature would allow users to more quickly discover content that they find interesting.