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GA project 4: Full-stack application with a Python back-end and a React front-end using the Mapbox and News Apis.

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GA

Project 4 - FLAGPIECES

By Raquel Cruickshank + Richard Bekoe

Overview

Richard and I built this full-stack application with a Python back-end and a React front-end using Mapbox & News APIs.
Users can click on a country button on the interactive map and browse articles from multiple news outlets (BBC, Guardian, Al Jazeera etc).
Once logged in users can:

  • Comment on articles.
  • 'React' to an article (😂😊😲😓😡).
  • Browse read articles on their 'Profile' page.
  • Browse aggregate of user articles with reactions on the 'Feed' page, and FILTER by reaction.

Take a look.

Contents

Brief

  • Build a full-stack application by making your own back-end and your own front-end.
  • Use a Python Flask API using a Flask REST Framework to serve your data from a Postgres database.
  • Consume your API with a separate front-end built with React.
  • Be a complete product - multiple relationships and CRUD functionality for at least a couple of models.
  • Implement thoughtful user stories/wireframes.
  • Have a visually impressive design.
  • Be deployed online so it's publicly accessible.

Timeframe: 1 week

Technologies Used

  • HTML5
  • SCSS
  • JavaScript
  • React
  • PostgreSQL
  • Python
  • Flask
  • SQLAlchemy
  • Marshmallow
  • TablePlus
  • Insomnia
  • Figma
  • Trello
  • Bcrypt
  • JWT
  • Mapbox API
  • News API
  • Moment
  • Bulma
  • Axios

Approach

We decided to use News API as our data source for our application. Due to it being continually updated, we decided not to scrape the data to our backend, and instead, fetch the data from the front.
We began by planning out our user journey in Figma on the wireframe below:

Wireframe

figma

We also roughly outlined the models and components we needed to build on Trello:

trello

Build

We very much pair-programmed this project (aside from the MapBox and styling, which we did separately on the penultimate day) this made our build much slower but, ultimately, was a positive outcome as it ensured we had a thorough understanding of our build, and problem solving together was a great learning experience.

Before building the map, we decided to make sure we could fetch the appropriate data. In our 'CountryArticles' component we used a prop:

const country = props.match.params.country

and template literal:

 useEffect(() => {
    axios.get(`https://newsapi.org/v2/everything?q=${country}&language=en&${API_KEY}`)
      .then(axiosResp => {
        setArticles(axiosResp.data.articles)
      })
  }, [country])

This would return articles, in English, with that country name in the headline or body of the text - a little hacky - but, given the limitations in the available country endpoints (fetching from a specific country returned articles in native language), we decided it was our best bet.

In order for users to later retrieve their read articles, we needed to save them first to our backend, by making a POST request and attaching a reader ID:

@router.route("/countryarticles/article", methods=["POST"])
@secure_route
def create():
    article_response = request.get_json()
    article_response['reader_id'] = g.current_user.id

    try:
        article = article_schema.load(article_response)
    except ValidationError as e:
        return jsonify({"errors": e.messages, "message": "Something went wrong!"})

    article.save()
    return article_schema.jsonify(article), 201

In the component on the frontend, there is a dictionary of country flag emojis and their respective country names. Inside a handleSubmit function:

  1. Each country is assigned a flag and saved to the backend using the article model.
  2. The page is pushed to the specific 'singlearticle' page using the ID of the article which has been saved to the database:
axios.post('/api/countryarticles/article', newItem
      , {
        headers: { Authorization: `Bearer ${token}` }
      }

    ).then((res) => props.history.push(`/singlearticle/${res.data.id}`))

Single Article Page

Here, users can read, react &/ comment on the article if they are logged in (we used JWT and secure routes for this).
We used the React Hook useState and a handleSubmit function so that when a user clicks on a reaction, that reaction object is made and the reaction state is updated. Then, useEffect is called, which posts the reaction to the backend reaction model.
For comments, I wrote a handleComment function to carry out an axios POST request to the backend to save the comment:

  function handleComment() {
    const token = localStorage.getItem('token')
    axios.post(`api/singlearticle/${id}/comments`, { content: comment }, {
      headers: { Authorization: `Bearer ${token}` }
    })
      .then(() => {
        setComment('')
        location.reload()
      })
  }

In JSX, I used the map Array method to display comments saved, and moment for the timestamp:

 <div className="comments-container">
          <h2>COMMENTS:</h2>
          <div className="comment-box">
            {articles.comments && articles.comments.map(comment => {
              return <div className="media-content" key={comment.id}>
                <div className="comment-content">
                  <p>{comment.content}</p>
                  <small>{moment(comment.created_at).calendar()}</small>
                </div>
              </div>
            })}
          </div>
        </div>

Feed

On our Feed page we used a useEffect hook to retrieve articles. Then, we used the filter method to filter through all the articles and then map over the array of reactions:

Wins & Challenges

Creating our models and figuring our our entity relationships took a long time, which was frustrating, and made our backend build slow. During my time at GA I realised that I lean more toward frontend development, as I relish visual design and considering user psychology. Although I was desperate to build the frontend, Richard's patience and need to thoroughly understand the backend architecture of our programme forced me to really get on board too, which was a great pay off.

Given the limited amount of time I had to design, I am pleased that the frontend came together. Richard was a joy to work with, and gave me confidence in myself as a coder and problem solver.

Key Learnings

  • Pair-programming can push you to be a better coder.
  • Don't be too ambitious about functionality, especially when this dictates complicated entity relationships, when given a short time-frame project !
  • Be adaptable. The MVP and final product may change, but you can come up with new ideas under pressure, and make necessary adjustments.

Future Features

  • Hoverable map without buttons.
  • Delete & edit comments.
  • Make reactions 'scalable'- each reaction image is attached to the article as a separate image each time it is clicked, a counter would maybe be better.
  • User avatars.
  • Incorporate Material UI for Skeleton loading.

Releases

No releases published

Packages

No packages published

Languages

  • JavaScript 54.6%
  • Python 31.3%
  • CSS 12.9%
  • HTML 1.2%