Back-end Developer Test Task

Simulation of flying objects

Create an application using Python and/or C++

Main objects

1. The World
   • The world is a finite 2D-plane with a linear coordinate system, where both the x-axis and the y-axis range from 0 to 1000km
   • The world is divided into 4 sectors
     • Sector A
       • x >= 0 and x < 500km
       • y >= 0 and y < 500km
     • Sector B
       • x >= 500 and x <= 1000km
       • y >= 0 and y < 500km
     • Sector C
       • x >= 0 and x < 500km
       • y >= 500 and y <= 1000km
     • Sector D
       • x >= 500 and x <= 1000km
       • y >= 500 and y <= 1000km
2. The Object
   • The object has following properties
     • object id
       • A string matching the regular expression /[0-9a-z]{32}/gmU
     • x-coordinate
       • x value existing in the world
     • y-coordinate
       • y value existing in the world
     • angle (rad) between direction vector and the x-axis
       • up 0, right pi/2, down pi, left 3*pi/2
       • negative values are converted to positives, eg. -pi/2 ==> 3*pi/2
     • speed
       • m/s
     • expire time
       • time to reach the destination
     • created time
       • time of object creation
     • payload
       • random hexadecimal data with the size of 100 bytes
       • data is immutable
   • All properties are mandatory, except angle, which is null at the creation time

Create a simulation application:

1. Simulated timeframe
   • 10 hours starting from an arbitrary date and time (for example 1st of December 2006 at 13:00)
2. Simulated object
   • An object is created in any initial position inside the World
   • A destination is created for the object: any point existing in the world, where the distance between the objects initial and destination point is between 150 and 400 km
   • A waypoint is created for the object: any point existing in the world, where the distance between the objects initial and waypoint is between 100 and 150 km
   • The object moves on a trajectory created as a quadratic bezier curve from the origin point, waypoint and the destination point
   • The objects speed is immutable and between 10 to 80 m/s
3. Generator
   • Create 500 simulated objects inside the timeframe selected for the simulation
   • Each object has a random starting time inside the timeframe
     • When the calculated expiration time exceeds the timeframe, it is acceptable, the object expires with the simulation
   • The object position, angle, expire time and the sector, where the object is positioned, are updated every 150 ms
     • The object position is calculated according to its trajectory, initial speed, starting time and current time
   • Every change of every object is logged with the objects data
4. API
   • Create a simple REST API for pulling data from logs
     • Query #1 – pull a specific object trajectory in a given timeframe
       • Input: object id, start time, end time
       • Output: object data including the payload and objects approximated trajectory inside queried start and end times
     • Query #2 – pull a snapshot from any sector in a given timeframe
       • Input: sector id, start time, end time
       • Output: all objects, sorted by first appearance inside queried sector, with object data without payload and approximated object trajectory inside queried sector
       • Note: any parts of trajectories outside the queried sector should be truncated to the last visible appearance inside queried sector

Notes:
* The test task is extensive, you might not be able to finish in time, this is okay. See how far you can go in 20 hours
* Use as many libraries and/or AI help as you like. Do note, that a code review follows
* The amount of data should, if my math is correct, not exceed 15Gb of uncompressed data
* The API call should work within acceptable time. Think of an architecture where the search could taken place after 100 simulations, 1000 simulations.
* Deliver the code any way you like, but do provide instructions of running it

Solutions and questions about the task to marten@trackdeep.ai