Hello

List of questions which were asked during the online test
1. Optimizing Alexa Suggestions
Problem Statement:

Amazon’s Alexa team is working on optimizing the customer experience for scenarios where customers ask generic questions. One example of a generic question is “What are good vegetarian restaurants nearby?” In this example, Alexa would then search for a list of vegetarian restaurants in the city and select the nearest X vegetarian restaurants relative to the customer’s location. Given an array representing the locations of N vegetarian restaurants in the city, implement an algorithm to find nearest X vegetarian restaurants to the customer’s location.



Input:

The input to the function/method consists of two arguments:
allLocations, a list of elements where each element consists of a pair of integers representing the x and y coordinates of the vegetarian restaurant in the city;

numRestaurents, an integer representing the number of nearby vegetarian restaurants that would be returned to the customer(X)

Output:

Return a list of elements where each element of the list represent recommended vegetarian restaurant relative to customer’s location.

Constraints:
numRestaurents<=size(allLocations)

Notes:
The Customer begins at the location [0,0].
The returned output can be any order.

Example
Input:
allLocations=[[1,2][3,4][1,-1]]
numRestaurents=2
output:
[[1,-1][1,2]]


2. Order Delivery Route
Problem Statement:

Amazon Fresh is a grocery delivery service that offers consumers the option of purchasing their groceries online and having them delivered on schedule. The Amazon Fresh tram is planning a route for a delivery truck to deliver customer orders in the city of TechIandia. The planner will create a delivery area for each order to effectively plan the route. The area is abstracted as a grid. Not all location locations are accessible by road. The truck only needs to make a single delivery.

Write an s]algorithm to determine the minimum distance required for the truck to deliver the order.

Assumptions:

Some places in the delivery area cannot be accessed by the driver, as there are no roads in those locations.
The delivery area can be represented as a two-dimensional grid of integers, where each integer represents one cell.
The truck must start from the top-left corner of the area which is always accessible and move on cell up, down, left, or right at a time.
The truck must navigate around the areas without roads and cannot leave the area.
The accessible area is represented as 1, areas without roads are represented by o and the order destination is represented by 0 and the order destination is represented by 9.
Input:



The input to the function /method consists of one argument:
area, representing the two-dimensional grid of integers.

Output

Return an integer representing the total distance traversed to deliver the order else return-1

Constraints

1<= rows, columns<=103

Example

Input:
area=
[[1,0,0],
[1,0,0],
[1,9,1]]

Output:
3

Solution 1:

def kClosest(locations,k):
def sqr_dist(location):
return location[0]*location[0]+location[1]*location[1]
locations.sort(key=sqr_dist)
return locations[:k]
alllocations=[[1,2][3,4][1,-1]]
numRestaurents=2
print(kClosest(alllocations,numRestaurents))

Solution 2:
def minDistance(grid, cur, col):
if grid[cur]==9:
return 0

rInt=cur+1
dInt=cur+col

if rInt<len(grid) and dInt<len(grid) and grid[rInt]>0 and grid[dInt]>0:
return 1+min(minDistance(grid, rInt, col), minDistance(grid, dInt, col))

elif rInt<len(grid) and grid[rInt]>0:
return 1+minDistance(grid, rInt, col)

elif dInt<len(grid) and grid[dInt]>0:
return 1+minDistance(grid, dInt, col)

else:
return len(grid)

def findShortedtPath(grid):
liPath=[]
rows = len(grid)
columns = len(grid[0])
for i in grid:
liPath.extend(i)

val=minDistance(liPath, 0, columns)

if val<=len(liPath):
return val
else:
return -1

area = [[1,0,0],[1,0,0],[1,9,1]]
print(findShortedtPath(area))