Our client presented basic wireframes that helped us understand the core mission of the project, which was to help people find the coolest spots to hang out. Our main goal was to create a convenient, simple, and modern app that would serve as a heatmap.

We started off building the MVP and decided on basic features and other features that could be added later in the following phases.

Then we also created the design for the post-MVP version to understand how the app could grow without significant changes. Our designer built the main screens for the MVP and designed the GUI kit for our developers.

The design of the heatmap was the core concern during the development. We did research and together with our client chose the color and size of the elements that show the attendance at places on the map. The first thing that users see when they press the pin is the preview details. If they are interested to explore further, users can read the description of the spot and see the average crowd size every hour and day of the week.

Filters also play a key role in the app, helping users scan types of spots quickly and find a place they like twice as fast. The map screen also features a time loop that allows users to track business depending on the time of day.  

We built the project with the Django Python web framework. The Django REST framework powers the REST API for the mobile application.

Our team used Python Client for Google Maps Services to work with the Google Place API and populate information about places.

Celery with Redis guarantees the completion of pending tasks like updating information about places.

We settled on Amazon S3 for storing media files. AWS Lambda functions were used for making image thumbnails during upload. We used Boto3 to work with Amazon Web Services.

We chose PostgreSQL for data storage and stored the database in Amazon RDS, which ensures a secure environment and flexibility as far as the service load is concerned.

We used Django REST Swagger to provide documentation for the REST API.

Our iOS developer used Swift for the NightApp as it’s fast, safe, modern, and simple. With Swift, we built a native app with a frictionless user experience.

We made use of the MVC (Model-View-Controller) architecture to make code flexible and extendable. New features and improvements are planned for the future.

For image caching, we used SDWebImage library due to its high performance and ease of implementation. To show locations, we used Google Maps for its simplicity. This easily customizable tool allowed us to implement the map and custom pins.

We built the Android app using the MVP design pattern, which allowed us to split the business logic from the UI perfectly. To write the app, we chose Kotlin. Kotlin helped us reduce the amount of code compared to Java, and we were able to get the same result in less time.

We used the RxKotlin framework built on the basis of the Paternal Observer pattern. RxKotlin gave us the possibility to subscribe to events and work more conveniently with the background streams that are most actively used when requesting a server with the help of the Retrofit framework. To implement all of our client’s ideas, we chose Google Maps because they allowed us to customize the marker that helps users see how busy a certain place is.

As the app features photos of different places, we used the Glide library to cache photos.

The Dexter libraries were excellent for permission queries and added more convenience. With Dexter, it's easy to ask users for permission to record data to the phone's memory or access the camera or geolocation features.

For the first release, we built an MVP that featured a heatmap of nightlife in Kyiv. In the second release, we added some French cities and dynamic filters. At present, we’re working on the third phase, namely making the app multilingual (translating it into Russian, French, and Ukrainian), creating user profiles, and adding registration. We’re also building NightApp for the Android platform.