video1.0<iframe src="https://www.loom.com/embed/bfa83950acd84a1eaed195d987823b4b" frameborder="0" width="1918" height="1438" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14381918Loomhttps://www.loom.com14381918https://cdn.loom.com/sessions/thumbnails/bfa83950acd84a1eaed195d987823b4b-42d8b5109fea6c5c.gif364.43In this video, I walk you through the assessment I've completed using a .csv file and the UploadFieldData API. I explain how I'm utilizing Celery and Redis for background tasks to gather gas station data, including their latitude and longitude. I've optimized routes between Washington DC and Texas, identifying the lowest price gas station along the way, with a total distance of 1510 km and a fuel cost of 432 rupees. I've also implemented logging and error handling to ensure everything runs smoothly. Please take a look at the code and explore how I've set everything up.