Mapbox is an open source mapping platform for developers

Mapbox

Web applications have greatly benefited from the inclusion of maps, providing users with valuable location-based information. Maps have transformed our interaction with the world, from navigating unfamiliar places to discovering nearby eateries. As a result, the integration of maps into websites has become increasingly popular in recent times. Nevertheless, designing maps that are both functional and user-friendly can present a challenge, especially for those lacking experience in this domain. In this article, I will share useful tips on how to create effective maps within your browser. Tech stack Let’s discuss technologies. When working with maps, we typically use three layers: Rendering the user interface, which includes buttons and forms. In our stack, React performs this role; Rendering the map and enabling user interaction. We use Mapbox for this; Fetching data from the server, such as information about markers or polygons. To retrieve data, we use the browser’s built-in fetch feature. Let’s review each item to gain a better understanding of our technology stack when working with maps. React The library enables you to work with page elements conveniently and efficiently. It was developed by Facebook for their own use, and includes numerous components such as buttons, forms, and other interactive elements on the pages. For example, Facebook created a to quickly compare different states. React reconciliation algorithm As changing elements on a page is the most expensive operation for a browser, it’s essential to do it as efficiently as possible. To address this issue, Facebook engineers developed the React library, which enables fast and straightforward element changes on a page. Besides providing rapid state changes on a page, React allows us to do this declaratively without working with DOM elements directly. Instead, we use an abstraction, usually , which looks like HTML. Let’s consider an example: JSX // It's our state. Is the user our friend or not?
// false by default
const [isFriend, setIsFriend] = useState(false)

// Depending on the state, we show the text on the button
const buttonText = isFriend ? 'Your my Friend' : 'Add as Friend'

// There is JSX, syntax for UI
// In this case, we display a button, when clicked, we change the state
return (
  <button onClick={() => setIsFriend(true)}>{buttonText}</button>
) It is possible to nest components with ordinary DOM elements like forms, buttons, and inputs at the bottom of the hierarchy. By assembling these simple elements, we can create more complex ones, such as a complete form: const Form = () => (
  <form>
      <input name="Email"/>
      <input name="Password"/>
  </form>
)

const App = () => (
  <main>
      <h1>My form!</h1>
      <Form />
  </main>
) How does React assist us in the context of maps? As the map on the page is interactive, similar to a button or form, we aim to optimize its rendering and interaction through events like clicks on the map. React can help achieve this optimization. Here is an example of how it works: // Use React to render the map with different event handlers
// and render markers
return (
  <BaseMap
    onInitMap={() => console.log('I am alive!')}
    onClickMap={() => console.log('Click!')}
    onDestroyMap={() => console.log('Oh no!')}
  >
    <ClustersMarkers />
    <PostsMarkers />
    <ListingsMarkers />
  </BaseMap>
) When working with React, it is essential to remember that it allows for efficient manipulation of elements on the page, quick changes, and interaction with them through events. This is achieved through an abstraction that resembles HTML, making it easy to create complex components from simpler ones. Mapbox Now, let’s discuss the map itself. Creating and using maps can be challenging, and only a few product companies can design maps from scratch. Typically, most people rely on pre-made libraries with a user-friendly API that has been tried and tested. Numerous dynamic map providers are available, including Google Maps, Leaflet, Bing Maps, Mapbox, and more. However, we will focus on due to its extensive features and fair pricing policy. For instance, Google Maps charges for 100k map views per month, while Mapbox only charges . Moreover, Mapbox offers free access for up to 50k map views per month. Mapbox $700 $250 Mapbox offers , a tool often compared to Photoshop for maps. With this tool, designers can create custom styles, hide unnecessary map elements, and remove house displays. One of its benefits is the ability to enhance the visibility of . Another advantage is the opportunity to experiment with map styling in corporate colors. However, it’s essential to consider the user experience and maintain a familiar color palette, including green grass and blue water. The best part about Mapbox Studio is that it simplifies the map design process by eliminating the need for developing and transferring requirements, ultimately reducing the cost of working with maps. Mapbox Studio Points of Interest Additionally, Mapbox provides a that can convert addresses to coordinates or vice versa, simplifying the process of locating points on a map. However, the tool’s may be insufficient, leading to difficulties for certain projects. Mapbox gathers data from , such as governments, open data initiatives like OpenStreetMap, and private companies. geocoding tool worldwide coverage numerous sources Mapbox provides a variety of , although the could benefit from some improvement. For instance, when incorporating marker functionality, examples can be more informative than the documentation. Additionally, challenges may arise when merging multiple components, such as marker clusters, custom data loading, normalization, and marker state changes. practical examples documentation Let’s revisit Mapbox maps. What does the do? Mapbox API It initializes the map in an HTML element on the page; It loads and renders images that make up the map; It draws additional elements, such as markers, using GeoJson as input data; It generates events, such as clicks or zoom changes, that can be handled. Let’s take a closer look at each of these items. Mapbox specializes in map rendering using tiles. Tiles are small square images that make up the larger map. The default size of a tile is 512x512 pixels, and it can be either . tiles are used to display roads, buildings, Points of Interest (PoI), and more. They can be dynamically styled, are lightweight, and allow for smooth interaction with the map. tiles, on the other hand, are used for displaying satellite imagery. vector or raster Vector Raster Just so you know, Mapbox Studio allows us to choose the specific data we want to include in the map tiles. These tiles are then placed onto a , which is a special DOM element in the browser that displays images and other graphical elements on the web. To give you an idea, it’s similar to how documents are displayed on a canvas in Google Docs. canvas <canvas width="100" height="100" /> Mapbox handles the loading, insertion, and updating of tiles. All we have to do is specify where we want the map to be displayed and the initial conditions, like the zoom level or the map’s coordinates. To use Mapbox, you’ll need an , which is a unique key that can be found in your Mapbox account. To set up a basic map, here’s a quick example, but for more information, check out the provided: access token link mapboxgl.accessToken = 'YOUR_MAPBOX_ACCESS_TOKEN';

const map = new mapboxgl.Map({
  container: 'map', // we can use an Id or an element
  style: 'mapbox://styles/mapbox/streets-v11', // URL for styles
  center: [-74.5, 40], // initial coordinates [lng, lat]
  zoom: 9, // initial zoom
}); After this, we will get a map on the page in an element with the id ‘map.’ To provide users with more information on the map, we often display the location of a certain establishment or the boundaries of a specific area. To achieve this, we use a specific data format called and instruct Mapbox on how to showcase this data. GeoJSON GeoJSON is the standard format for storing geographic structures on maps. It can store various primitive types that describe geographic objects such as addresses, locations, streets, highways, borders, countries, states, and combinations of these, known as multipart. GeoJSON was introduced in 2008 and is represented like this: {
  "type": "Feature", // also can be FeatureCollection, it's collection of Feature
  "geometry": {
    "type": "Point", // also can be LineString, Polygon, MultiPolygon
    "coordinates": [125.6, 10.1] // for other types you can use Array with coordinates
  },
  "properties": { // it's metadata, we can you that to show something on the map
    "name": "Dinagat Islands"
  }
} Let’s talk about the coordinate system used in Mapbox. By default, Mapbox employs , which is a way of projecting the Earth onto a flat surface to work with tiles. This is known as Web Mercator and is the standard for online maps. However, when dealing with data about markers and polygons, it uses a different coordinate system called . This system relies on latitude and longitude to describe coordinates on the Earth’s ellipsoid. Mapbox and other map providers automatically convert coordinates from EPSG 4326 to EPSG 3857. If we need to work with different , we can use the method. EPSG 3857 EPSG 4326 projections map.setProjection Now, we will discuss how to display GeoJSON on the map. Mapbox offers two entities that we will find helpful: — This is the data seed. We can create a new source with GeoJSON data and configure it, for example, to generate an ID for each feature in the feature collection. Source — This is the data representation. We can display the data from the source in different ways, such as showing boundaries. Layer To display polygons or markers on the map, we must retrieve the data in GeoJson format from the server. Then, we create a source, input the data into it, and connect it to the required layer. const geoJsonFeature = {
  'type': 'Feature',
  'geometry': {
      'type': 'Polygon',
      'coordinates': [
          [-67.13734, 45.13745],
          [-66.96466, 44.8097],
          [-68.03252, 44.3252],
          [-67.13734, 45.13745]
      ]
  }
}

// Create source with our data
map.addSource('ourSource', {
  'type': 'geojson',
  'data': geoJsonFeature
});

// Add layer for background
map.addLayer({
  'id': 'background',
  'type': 'fill',
  'source': 'ourSource', // название нашего source
  'layout': {},
  'paint': {
      'fill-color': '#0080ff',
      'fill-opacity': 0.5
  }
});

// Add layer for border
map.addLayer({
  'id': 'border',
  'type': 'line',
  'source': 'ourSource',
  'layout': {},
  'paint': {
      'line-color': '#000',
      'line-width': 3
  }
}); After running this code, we get the result: To learn more about this topic, you can refer to the provided by Mapbox. In this tutorial, we have covered the process of initializing the map and presenting our data. Next, we will explore how to handle events like clicking, dragging, and zooming. For instance, we can use Mapbox to monitor events and display the coordinates in the console as the user moves their cursor on the map. To achieve this, we simply call the method with the event type we want, similar to how we work with DOM elements. documentation on map.on('mousemove', (e) => {
  console.log(JSON.stringify(e.point));
});

// Result: {"x":330,"y":49} In summary, what do we need to remember? Mapbox allows us to display a map, draw our data on top of it, and process map events. At the same time, Mapbox takes care of loading and displaying images (tiles). Fetch A word about . We have already seen how to render data on a map, but first, we must retrieve it from the server. When we dynamically request data from the server in the background without reloading the page, we call this approach (“ synchronous avaScript nd ML”). There are many tools for loading data asynchronously from the server, such as Axios or XMLHttpRequest (native). fetch AJAX A J a X What to remember? We retrieve data from the server, and there are many libraries for this, but we will use fetch. Next, we will look at how we do this specifically when working with maps, as there are nuances. React + Mapbox Now let’s see how the technologies described above work together. First, we will retrieve the data for displaying the polygon using fetch. Then we will declare the initialization of the map, and after it loads, we will add the polygon to the map. You can also find a working example at the provided. link const useFetch = () => {
  /*
  Our data
  {
      'type': 'Feature',
      'geometry': {
          'type': 'Polygon',
          'coordinates': [
              [
                  [-67.13734, 45.13745],
                  [-68.03252, 44.3252],
                  [-68.90478, 47.18479],
                  [-67.13734, 45.13745],
              ]
          ]
      }
  }
  */
  const [data, setData] = useState(null)

  useEffect(() => {
    fetch('https://our-api.com/polygon')
      .then(response => response.json())
      .then(setData)
      .catch(e => {
        console.error(e)
      })
  }, [setData])

  return { data }
}

const BaseMap = () => {
  // Use the hook to fetch data
  const { data } = useFetch(GET_REGION);

  // Map instance
  const map = useRef(null);
  // DOM element
  const mapContainer = useRef(null);

  // Main logic - init the map and add the event
  useEffect(() => {
    if (map.current) {
      return; // initialize map only once
    }

    mapboxgl.accessToken = 'YOUR_MAPBOX_ACCESS_TOKEN';
    map.current = new mapboxgl.Map({
      container: mapContainer.current,
      style: 'mapbox://styles/mapbox/light-v10', // style URL (it's Mapbox's core style)
      center: [-68.137343, 45.137451], // starting position
      zoom: 5 // starting zoom
    });

    // Handle event
    map.on('load', () => {
      const sourceId = 'source-region'

      // Add a data source containing GeoJSON data
      map.addSource(sourceId, {
        'type': 'geojson',
        'data': data.region // our data from Apollo
      });

      // Add a new layer to visualize the polygon
      map.addLayer({
        'id': 'background',
        'type': 'fill',
        'source': sourceId, // reference the data source
        'paint': {
            'fill-color': '#0080ff', // blue color fill
            'fill-opacity': 0.5
        }
      });
      // Add a black outline around the polygon
      map.addLayer({
        'id': 'outline',
        'type': 'line',
        'source': sourceId,
        'paint': {
            'line-color': '#000',
            'line-width': 3
        }
      });
    });
  });

  return <div ref={mapContainer} />;
} Conclusion We looked at the technology stack that underpins our future architecture. In the following article, we will discuss the principles that help design a map architecture, how to achieve maximum low coupling and high cohesion of modules, and how to maintain and develop a scalable map system. Thank you very much for your attention! Have a great day.

Maps on the Web Using React and Mapbox

প্রতিক্রিয়া এবং ম্যাপবক্স ব্যবহার করে ওয়েবে মানচিত্র

Karten im Web mit React und Mapbox

Mapas en la Web usando React y Mapbox

Cartes sur le Web à l'aide de React et Mapbox

रिएक्ट और मैपबॉक्स का उपयोग करके वेब पर मानचित्र

React と Mapbox を使用した Web 上の地図

React와 Mapbox를 사용하여 웹에서 지도 만들기

Mapas na Web usando React e Mapbox

Карты в Интернете с использованием React и Mapbox

React ve Mapbox Kullanarak Web'deki Haritalar

Bản đồ trên web bằng React và Mapbox

使用 React 和 Mapbox 制作网络地图

Google Maps has always been the de-facto locational map API that developers turn to. However, a sharp increase in price and a drastic reduction in the number of free API calls has prompted to scramble for alternatives, triggering a Mapbox vs. Google Maps showdown. app developers Companies that have been enjoying 25,000 API requests per day for dynamic maps are suddenly limited to 28,000 per month. Exceeding the free quota will result in billings of $7.00 for every one thousand API calls. Popular companies like Foursquare has since migrated to Mapbox, as it seeks a cheaper alternative. Despite the outcry of Google Maps exorbitant price hike, it remains part of popular apps and companies like Lyft, Snapchat, and Groupon. While it’s tempting to switch to cheaper options, how do the competitors stack up against Google Maps? That’s the burning question you ought to ask. Most Popular Maps API’s If you’re designing an app that requires geo-location service, you’ll have more than a handful of APIs to choose from. Nevertheless, these 3 are still the most popular maps APIs amongst the developer community, although they may appeal to different design needs. Mapbox found itself in the limelight amidst Google’s decision to turn its mapping service into a business. MapBox can be easily integrated into websites and apps. Recognizable names like Shopify, Lonely Planet and Facebook have benefited from its mapping services. Openstreetmap API is an open-source initiative that generates world map data and makes them available for free. This means you don’t have to pay anything to request data from its database. In fact, you’ll even have access to the entire database of Openstreetmap, which isn’t so in paid APIs. Love it or hate it, Google’s move to monetize the use of its Maps API hardly dents its reputation of being the go-to location services for small, medium, and large enterprises. It is highly reliable, particularly in returning accurate data on routes and locations for dynamic maps. Does Google Maps remain the ideal API for your app, or should you consider the increasingly-popular Mapbox? Is the idea of using the free Openstreetmap viable at all? We’ll dive deeper into each of the API before making a verdict. Mapbox API Mapbox is an advanced and flexible map service that can be integrated into mobile apps. Developers will have access to comprehensive location information to create and customize dynamic and static maps, thanks to the Mapbox tilesets. The styled maps can be embedded into web applications with the provided JavaScript library or to mobile apps with the respective iOS and Android SDKs. The reviews on Mapbox has been encouraging amongst developers and business owners. While Mapbox isn’t entirely free, it has a generous free tier in its pricing packages that makes the service attractive for apps with a low volume of users. Pros Free for up to 25,000 mobile users and 50,000 web loads. Well organized documentation Customization of maps is easy. Visually-pleasant base map. Easy to integrate on web and mobile apps Cons Steep learning curve. It’s not a free service. Geared towards larger projects. May disrupt existing background processes. The API is not customizable. Apps that use Mapbox Snap Inc. Shopify Facebook One of the Mapbox alternatives that is absolutely free is the OpenStreetMap API. It is an open-source project where volunteers across the globe contribute to creating routes, imagery, and other data for the map. The map service and database are made available to the public. While OpenStreetMap is a free, open-source project, you can’t use the API to retrieve real-time routing data for commercial apps. OpenStreetMap API is limited to providing vector data for map editing purposes only. This means you’ll still need to turn to services like Mapbox, which is based on OpenStreetMap, to query location data from your app. Pros Open-source database. The API is free. Detailed map information on less popular locations. Cons It is meant for map-editing purposes. Excessive queries with API will result in getting blocked. Limited usage as services like routing, map clustering are dependent on 3rd party APIs. Incomplete documentation. May not integrate well with other tools. Apps That Use OpenStreetMap OpenTouchMap CycleStreets Karta GPS Google Maps API Google Maps  is the most popular SDK for embedding a map into an application. It’s known for its huge database of places and decent routing. It has all the features of Google Maps for mobile app: geocoding, routing, pictures, street view, and places information. That app is actually based on SDK available for public usage. This means that your users will be absolutely comfortable using a map from Google because they most likely are already familiar with it. Map appearance is customizable via the website and can be implemented by the designer at (no developers effort needed). Usage of the map itself is free, but you will have to pay for displaying places, their details, and directions. https://mapstyle.withgoogle.com/ Pros: first $200 of usage each month is free rich database of places with all the information about them geocoding (conversion of a location’s geographic coordinates into a human-readable street address and vice versa) street view routing decent visual customization Cons: heavy to render (first time rendering freezes app for a second) drains battery and requires some workarounds to improve energy consumption markers and shapes are 100% static routing is expensive not open sourced Apps that use Google Maps: Uber Bolt Trip advisor Our Verdict At a glance, it seems that Mapbox has the upper hand on its cheaper pricing plans. However, the difficulty in understanding the data flow on its architecture may prevent companies from migrating to it. Some apps, which are not experiencing heavy usage, are not significantly affected by Google Maps’ price hike. Besides financial viability, Google Maps is still superior in terms of accuracy, availability, and depth of its map data. The immense data in Google Maps’ database means it can outperform Mapbox when users are zooming closely into the map. When you’re paying for Google Maps, you’re paying for more than the location service. With integration into services like Google Places, Businesses, and its superior real-time accuracy, Google Maps is still rightfully the best API for your app. Previously published at https://uptech.team/blog/mapbox-vs-google-maps-vs-openstreetmap

Mapbox Or Google Maps: Which One To Choose For Your App

In this article, we are going to make a map with a software called Mapbox. This won't involve any coding at all, but I think it is a cool tool to use if you want to add a professional-looking map to your website or app. Mapbox's software is used by apps of many popular companies that all of us utilize every day. Snap Inc. The Weather Company Shopify Facebook AllTrails Ancestry Peloton And many more... For the map that we make today, we will be using the data visualization component that is provided to us in Mapbox Studio (aka Mapbox's map editor). The data we will be working with is the temperature change for US counties from 1895 to 2019. This is already pre-loaded into Mapbox studio which is really handy. Without further ado, let's get into it! Setup The setup for this is pretty simple. All you need is an internet connection and a . Once you have those 2 things you are ready to go! Mapbox account The Process Now that you are signed in you'll want to go to the Styles page. This is where all of your different designed maps be housed. If you just set up your account you won't have anything in here. would Next, we are going to click the "New style" button on this page. This will take you to a screen where you can choose a map template you'll want to use. For this scenario I'm going to choose the Basic map template, I think any template will work here (other than the blank template of course). After you have chosen your template, click the "Customize" button at the bottom of the modal. This will direct you to your new Mapbox map! : your map will be centered in Paris. Make sure to navigate to the United State before moving on to the rest of the steps. Pro tip This next paragraph is completely optional, in my opinion, but to make the map feel a little less cluttered we will delete some of the components that are added on by default. Click on the component in the menu on the left-hand side. Then click the trash can icon at the top of the menu. Below is the list of components that I deleted. Buildings Place labels Points of interest Road network Transit Walking, cycling, etc. Adding the data For this exercise, we are going to create a with data from , which analyzes warming temperatures in the United States. Our choropleth map will visualize the change in average annual temperature from 1895 to 2019. choropleth map The Washington Post's "2ºC: Beyond the Limit" series about rising temperatures In the Components panel, click the plus icon and then select "Data visualization" from the menu that pops up. You'll then be shown a dark map of the United States. Click on where it says "None selected" under Source. Then click "Add source by ID". Paste into the search bar and click "Find". mapbox.brt3djy1 Yay! We have pulled in the data. It was that easy. Now we have to decide how we want our data to look on our map. Click "Select data visualization type". Then click the choropleth option, and lastly, the "Select Choropleth" button. There you have it. The component will be added to your map and you'll see the United States illuminate with color. Finishing touches The rest is just messing around with the styles and colors. You'll notice initially that your map will have 3 colors populated. The field has values above and below 0. To make the visualization reflect divergence from 0 with color, the second stop should be 0 instead of the default value of 1.774. So let us change the middle value (2) in the Color section to 0. tempchg Also, it would be nice to make this look a little bit more like a heat map. We can do that by going down to the bottom section of the Components panel under the Colors section. Click on "Choropleth" with the 3 colors to the left. This will expand and display a dropdown. In that dropdown, select the "Temperate" option (the "Adverse" color palette is a good choice too). Finally, our colors are switched around so we need to click the "Reverse palette" button next to the dropdown. Conclusion There you have it! A super slick looking map that shows temperature change data of the United States. How easy was that? I encourage you to play around a little more in the Mapbox studio and see what other cool manipulations you can make. : adding more colors to show more details of the data, change the stroke to show or hide the polygon outlines, toggle labels on or off, and even change the opacity of your map. Some easy ones are You can preview your map by copying the share link in the top right corner, as well as publish it so you can include it in your dev project. Lastly, if you're curious about diving deeper into this, Mapbox has lots of great lessons and tutorials to help guide you through all of the available functionality. I think a logical next step after this would be to to a Mapbox map. Maybe you could look at one of my then including that data into your very own custom map! add your own data previous articles about scraping websites for data That's all for now. I hope you enjoyed this article. Happy coding!

Create A Data Visualization Map Using Mapbox

Want to use React/Redux for Mapbox apps, but aren’t sure where to start? Read on! Motivation I work in R&D in the architecture and real-estate development world at . That means two things: Ankrom Moisan Architects I use maps. A LOT. Most things we do are geospatially oriented. Mapbox has been invaluable for this. I can control every aspect of how the map looks (presentation is everything, especially for architecture), and it doesn’t complain when I throw crazy amounts of data at it. I often need to iterate on several complex applications quickly, and force my brain to change gears frequently (I’m also doing and construction work). design Building large applications using the imperative and procedural techniques typically shown in the mapbox examples can quickly make application flow difficult to understand, and state difficult to trace. That second point became a force multiplier on top of those challenges, slowing down development, and making errors more likely. The solution that ended up working perfectly for me was transitioning to building applications with and Redux; but it wasn’t immediately clear how to work Mapbox into this framework. React Fortunately, the wonderful folks at Mapbox have actually thought quite a bit about this, and wrote a very helpful on the subject. I felt it might be helpful for other geo-develeopers to have more concrete examples to looks at. Thus, I have a brief tutorial: Tom MacWright Medium post Building a simple React/Redux/Mapbox app: I recently put together a dataset combining lots of meta-data about buildings in Portland, Oregon and their 3D geometries. I needed to build a simple interface so users could switch between data-properties, like square feet and unit count, in the visualization. You can see the final product here. The entire application is very simple, and . In this post, I’ll go through the steps required to make a flexible React/Redux wrapper around mapbox. I’ve put it on github Side note: this example is simple enough to not really need react/redux, but the process shown will scale well. Stylesheets Before we code, there is one important thing to keep in mind when trying to manage application state with Mapbox: If you have the current stylesheet, you know exactly what state the map is in. the map’s stylesheet is the single source of truth for everything. To follow React’s declarative philosophy of programming then, we’d like to take the stylesheet and modify it to reflect what we want to see, and hand it back to the map to render. On its own, mapbox will not accept a stylesheet as an update. However, as they outlined in Tom’s post linked above, the Mapbox developer’s wrote a diff’ing algorithm for stylesheets that lives in the . It takes in two stylesheets, one representing how the map looks now and one representing what you want it to look like, and produces a set of commands that will take your map from one style to the other. style-spec github repo Process With this knowledge, and the diffStyles function, we can outline a process for wrapping Mapbox: Create a ‘map’ object with mapbox-gl-js inside of a React component. When the map has loaded, grab its stylesheet object and put it in the application state. When user interaction requires that the style changes, have a reducer grab a copy of the style-state and change the properties you wish inside of it. This change to the state tree will trigger an update that can be hooked with “componentWillRecieveProps” in the map component. Within this function you can grab the current stylesheet, and the new stylesheet (from nextProps). Then diff the two with diffStyles, and apply the changes. 1 We’ll start with a component that just returns an empty div identified as ‘map’, just like in traditional html: In a non-react setting, we would have a script that identifies this div and instantiates a map canvas. That’s exactly what we’ll do here too, but we need to make sure that it happens at the appropriate time in the React lifecycle, so we’ll put it in “componentDidMount”: 2 Now we have the initial stylesheet in our variable called ‘style’, and we need to save it into our application state. First a brief aside on the contents of this variable: If you’ve never really looked at the stylesheet before (I hadn’t), go ahead and explore it in the console, you will see that it is a nested JSON document who’s structure can vary depending on layer order and property choices. deeply For this reason (as well as innumerable other benefits) I highly reccomend using Immutable.js to wrap the stylesheet before you store it. Immutable has numerous methods for finding specific properties within deeply nested objects and lists, and will save you a lot of time. It will also give you confidence that only things you changing the style will be able to. want So let’s write an action and reducer to take in a JSON stylesheet and save it to our application state as an Immutable object: 3 Now let’s assume that in some other React component we have buttons a user can click to change the property governing the color of our buildings. The buttons will trigger an action called ‘CHANGE_VIZ’, and the payload will just be the ‘value’ attribute of the button. I’ll show two cases for brevity here, coloring by ‘Square Feet’ and coloring by ‘Number of Units’: 4 Great, now Redux contains a stylesheet that shows how we the map to look! The last step is diff’ing this with the way the map looks currently, and applying the changes. This happens back in our map React component in the “componentWillRecieveProps” method, and looks like this: want For bonus points, we can also capture the map click event and send it out as an action for whatever use you might have! We just add it inside of “this.map.on(‘load’…)” in our map component, we’ll also add the action creator for saving the initial style state here: And thats it! This can be expanded on to add more features (delayed source loading, hooking other events like movement and zoom, etc…) but it’s really all thats required to have a very flexible React wrapper around Mapbox. Combined with the action / reducer / re-render paradigm it has allowed me to build interfaces very quickly that I can easily modify later on without having to really trace through how everything is wired together each time. And that leaves more time for experimentation and doing work that matters! The full project is if you’d like to see everything in context with reducers, actions, and UI. here on github Finally, here is our completed ReactMap component, stylesheet reducer, and action creators: ReactMap Component Style Reducer Action Creators

React/Redux with Mapbox

My day was going great, I was in a good mood after checking our newly updated MRR on Stripe, and I decided to open my email to see if there were any questions from customers to answer. That's when I noticed an email from Google, entitled " ", and my day took a slightly different turn. Google Cloud Platform & APIs: Payment received I open the email. " ", it says in big bold letters. "Great", everything's running smoothly, right? Payment Received Wrong. Your payment of $1,000.00 was applied to Google Cloud Platform & APIs on Jun 21, 2021. Excuse me? $1000? And the month hasn't even ended. "Well maybe it's just a mistake" I think to myself, as I open the Developer API console. A beautiful colorful graph to tell you how much they're screwing you out of. But no, lo and behold, after opening 15 different Billing subsections each with less descriptive names than the next (" ", " ", " ", " ") and not finding an answer to the simple question " ", I finally manage to view what our consumption for the month was (I tried to get back to it as I wrote this article, and couldn't even find it anymore). It seems that we are paying for what we consumed. There's only one little issue: Cost table Cost breakdown Commitments Commitments analysis How many calls did we make on the API this month? in fact Just one little issue... we've made about 226,000 API calls in total this month. What? What? What? How could this be? I still don't understand it, but apparently it should make sense: Why are we paying for Atmosphere Data and what the hell does that even mean? I guess Google felt they could use an extra $100 bucks on "Contact Data", whatever that is. Just to break it down, that's: dollars for requests on the Places API $560 32,998 on Autocomplete requests $345.57 127,566 on Atmosphere Data: I've been using Places/Autocomplete, why am I even paying for Atmosphere Data? $165.01 Throw in an extra on "Contact Data", what's an extra $100 at this point? $99 Well... this explains why the pricing pages are so obscure on Google's API products. Maybe But my favorite part is that we weren't actually paying the full price, this is our ! How generous of them! discounted price Oh, and if that still doesn't make sense, here's another breakdown of the pricing for you. Yeah add a few dropdowns everywhere, that'll make it clearer: Google's reporting is hell on earth That's when I started looking into alternatives. And thankfully, there are a decent amount of them out there in 2021: , , and just to name a few. Mapbox OpenCageData LocationIQ GeoCod.IO In the end, I settled on Mapbox: it's not the cheapest of all options but it seemed to strike a good balance between affordability and data relevance, with the most relevant results in Autocomplete across the space. And coming from Google's mess of a console, their no-nonsense dashboard is also extremely refreshing: Mapbox's simple reporting UI Now, our first 100,000 calls are free every month, and we'll be paying $0.75 per extra 1000 calls, . at a maximum At this month's rate, that breaks down to around total. $94 A tenth of Google's price! By now you've guessed I surely won't be using any of Google's APIs without heavy scrutiny of the pricing and the alternatives moving forward. Hopefully this article can help a few more people think twice before blindly heading for the default choice. Footnote : While I'm highly satisfied with Mapbox's service and offering so far, this article was in no way sponsored or requested by Mapbox .I am merely a disillusioned Google customer who found a glass of water in hell. Looking to set up your own custom job board for your community? Head over to Niceboard.co to start your free 7 day trial!

Here's Why we Switched from Google Places to Mapbox for our Autocomplete API

Photo by on . Jantine Doornbos Unsplash I had a problem. I would go to a shop, maybe or , sit down, and realize that somehow I did not have the WiFi password. As I discreetly looked around for the username and password I’d inevitably come to the conclusion that I should just ask the barista as I picked up my drink. Social interaction isn’t the worst thing in the world but it usually results in a finger pointing to a sign, in plain view, that I had somehow missed. coffee Blacksmith Morningstar In order to avoid the situation described above I could just keep a running list of places I’ve visited with their associated WiFi networks and passwords. Or I could scour Foursquare for the comment with the password in it (probably from two years ago). Or I could build a single page website with a nice little 🗺 that holds all the information I need. Glitch Glitch was announced back in the December 2016. (who at the time had just become CEO of ) describes it best: Anil Dash Fog Creek Many geeks of my cohort came of age building things on the desktop using HyperCard or Visual Basic, or by using View Source in their browser to tweak HTML pages that they uploaded to Geocities. The web’s gotten a lot more mature and a lot more powerful, but the immediacy of that kind of creation has been lost. Today, even if you’re a skilled developer, the starting point you’re working from is usually a pile of unassembled parts. Glitch lets you start from a working app (or bot, or site, or whatever) and then remix it into exactly the app of your dreams. It’s an excellent place to take someone else’s template and modify it or host a prototype of an idea you have. The Glitch homepage when you’re logged in. I chose to remix an existing template that was setup to use and a simple map. jquery-csv Mapbox I added some text, modified the CSS a little, adjusted the size of the map on the page, added extra JavaScript from Mapbox for additional functionality, and populated the map with a decent initial cohort of coffee shops. What it looks like when you’re editing code on Glitch. At each step, Glitch automatically updates your site ( ) so you can see what you’re changing in real-time. This removes the headache of setting up a local testing environment and allows you to just build something 💯 insert-whimsical-name.glitch.me Mapbox I’ve always been impressed with Mapbox. Like with most of the top-tier internet companies started in the last decade, they’ve taken something would be very difficult for individual developers to implement over and over and simplified it down to a few short code snippets on a web site. In addition, allows anyone to infinitely customize their maps. Mapbox Studio I experimented with several different map styles but ultimately returned to the standard Streets style. It looks most similar to the Google and Apple Maps style and the usability is 👌🏼. I wanted zoom controls to overlay the map. Zooming in and out of a map on a mobile webpage is sometimes a little difficult and controls alleviate this slightly. In case the map is not automatically centered on the user, a geolocation button was also added. Finally, I added a search box because I would expect that on any map that I’m viewing. In the future I would like to add driving or walking directions from the current user location ☑️ Netlify I bought the domain on early on and knew that I wanted to eventually move off of . I briefly considered hosting on but decided the easiest route was using Github as the server. It’s relatively simple to set up a custom domain using Github Pages but there are always a few quirks. password.coffee Google Domains Glitch Linode I don’t know when I first came across but for whatever reason I came back to it for this. It was far better, faster, and easier than I remembered. Provided you have all the necessary files to build a functioning website, the process of setting up continuous deployment takes under a minute. Really incredible for a site hosted on GitHub, Gitlab, or Bitbucket. Netlify It takes three screens to get set up. You connect your Github (in my case) account and choose the correct . repository First step when creating a new site on Netlify. Then you select any build options, like for Jekyll, and click . jekyll build Deploy Site Deploying a site on Netlify using custom build settings. It took just a few more minutes to setup the custom domain, change nameservers, and enable HTTPS by default. Most of that time was waiting for DNS to propogate. End Overall, I’m pretty satisfied with this first iteration. If you’d like to check it out, just go to . And if you want to update an existing location or add a new one you can do that . password.coffee here

Building password.coffee ☕ ️with Glitch, Mapbox, and Netlify

Tutorial: Geotagtext, a Free Geotagging Web Application 

Coronavirus (COVID-19) which is an infectious disease caused by respiratory illness and symptoms like flu, cough, fever, difficulty breathing, on December 31, 2019, the first case was recorded in Wuhan, China and later the virus got spread around the world and as of now, around 1 million+ confirmed cases are being recorded since then. You can protect yourself from this virus by following basic precautions like washing your hand frequently, avoid touching your face, maintaining a distance of (1 meter or 3 feet) between people and most importantly if you are sick then immediately call for medical help at your nearest hospital. What is Coronavirus (COVID-19)? This article is originally published at https://hackbotone.com/blog/covid-19-full-stack-application How to build a full-stack application with interactive maps? In the current scenario, it’s quite important to track the statistics of all the cases around the world constantly and thanks to for providing the data to the public user, the data are quite well organized and sorted in very well manner and they are updating their repository every day. Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) So as I have collected the data now I have decided to build a with interactive maps so that it will be quite easier for the user to track the cases across the globe. full-stack application Node.js Backend Services maintains the data in CSV format in their repository and I need to convert the CSV data to JSON format so that it will be quite easier for the front-end framework to populate the data in an efficient way. So to convert CSV to JSON I have use npm module which is a very popular CSV parser and converts CSV into JSON at a rate of around 90,000 rows per second. JHU CSSE csv-parser And after parsing the data I have stored the data into MongoDB so that it won’t parse the data every time, it will only parse the data when new data will be available. JHU CSSE updates the data once a day around 23:59 (UTC) and to synchronize the data in my server I am using npm modules which is a task scheduler and once you register a task with the given time then it will run in the background and triggers when it reaches to the scheduled time. node-cron And in my case, the scheduled time is 23 hours 59 minutes and when it reaches the time then it will update the data into my server. Now after parsing the data next big challenge is to populate all the coordinates on the map because on the map if I traditionally populate the coordinates then the application will be much slower, so the solution to this problem is which is an open standard format for representing geographical features as a point, line strings, polygons and etc and this format is based on Javascript Object Notation and most importantly all the maps platform such as , and many others supports GeoJSON format. GeoJSON GoogleMap Mapbox So I have design one endpoint as which takes the input from the and prepares all the coordinates into GeoJSON format, so the front-end framework can call this end-point while doing the map implementation. /markers.geojson MongoDB React.js Frontend Services I have chosen as my front-end framework for this application and to maintain the application state I have also implemented which is a very popular javascript library for managing application state and both of these frameworks are quite efficient and easy to implement. react.js redux To populate the coordinates on the map i have implemented which is quite similar to GoogleMap but the major advantage of Mapbox is it’s free and provides many better functionalities such as Custom maps, Clustering and etc. Mapbox As I have already mentioned that Mapbox also supports GeoJSON format so to populate GeoJSON data over the map, Mapbox has a technique called which is an individual layer of data within a vector source and defines which type of data map should display and in this application data type is ‘geojson’ and after defining the data refers to the source for visual representation and styling of the map. And in this way, I have populated all the coordinates on the map. Source-Layer Sources Layers Open Source It will be quite difficult for me to walk you through step-by-step every lines of codes. That’s why I made the complete development open-source on my Github. So that you can also build similar types of application by following this repository. Github Link:- covid19-full-stack-application Website Link:- https://covid19.hackbotone.com/ So this is the overall explanation of this website, I hope you guys understood the tools and techniques behind this application if you find any types of issues like on improving codes then please feel free raise an issue on Github or else you can reach out to me on I’ll be happy to answer your questions. twitter Please stay safe and stay well, I want to mention it again to protect yourself from this virus wear mask, wash your hand frequently and take necessary precautions if you get sick. Thank you & Happy coding :)

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