answer：Okay, I need to write a Python function called earliest_wind_down_time that takes a list of tuples as input. Each tuple represents a task with a start and end time. The goal is to find the earliest time I can start winding down, which is the end time of the last task. Hmm, so the function needs to determine the end time of the last task when all tasks are considered. But wait, how are the tasks ordered? Are they in any particular sequence, or do I need to sort them based on their end times?Wait, no. Because the tasks might overlap or be in any order. So the last task isn't necessarily the one that ends the latest. Oh wait, no, the earliest time I can wind down is the maximum end time among all tasks. Because if a task ends at 17, another at 15, then 17 is the latest, so I have to wait until 17 to finish all tasks.So the approach is to find the maximum end time in the list of tasks. That makes sense.So the steps are:1. Iterate through each task in the list.2. For each task, get the end time.3. Keep track of the maximum end time encountered.4. After processing all tasks, return this maximum end time.Let me think about the example given. The tasks are [(9,12), (14,17), (13,15)]. The end times are 12, 17, 15. The maximum is 17, so the function returns 17. That's correct.Another example: if the tasks are [(10,11), (12,13), (14,15)], the maximum end is 15, so return 15.What if there are no tasks? Well, according to the problem statement, the input is a list of tuples, but it's possible that the list is empty. In that case, the earliest time to wind down would be 0, or perhaps it's undefined. But the problem says that each task has a start and end time, so perhaps the function can assume that the list is non-empty. Or maybe we should handle the empty case.Looking back at the problem statement, the function is given a list of tuples, but it's not specified whether it can be empty. So perhaps in the code, we should handle the case where the list is empty. But the example provided has a non-empty list, and the function is expected to return an integer. So perhaps the function can assume that the list is non-empty. But to make it robust, maybe we should handle the empty case, perhaps returning 0 or some default.But for now, perhaps the function can assume that the list is non-empty. So, proceed under that assumption.So, the code can be written as follows:Initialize a variable, say max_end, to 0. Then, for each task in the tasks list, get the end time (task[1]), and if it's larger than max_end, update max_end.Wait, but what if the list is empty? Then, the function would return 0, which might not be correct. But perhaps the function is intended to handle non-empty lists. So, perhaps the code can proceed as:def earliest_wind_down_time(tasks): max_end = 0 for task in tasks: if task[1] > max_end: max_end = task[1] return max_endWait, but in the example, the tasks are [(9,12), (14,17), (13,15)]. Let's see: the first task ends at 12, which is larger than 0, so max_end becomes 12. Next task ends at 17, which is larger, so max_end is 17. Third task ends at 15, which is less than 17, so no change. So the function returns 17, which is correct.Another test case: tasks = [(5, 8), (6, 7)]. The end times are 8 and 7. So the function returns 8.What if the tasks are [(10, 14), (12, 13)]? The end times are 14 and 13. So function returns 14.This seems correct.But wait, what if the tasks are not in order? Like [(15, 16), (10, 20)]. The end times are 16 and 20. So the function correctly picks 20.Yes, because the function is iterating through all tasks and taking the maximum end time, regardless of their order.So the code seems correct.But let's think about the case where the list is empty. If tasks is empty, the function will return 0. But that might not be correct because there are no tasks, so the earliest time to wind down is perhaps 0, but perhaps it's better to return 0 or maybe raise an error. But the problem statement doesn't specify, so perhaps the function can proceed as is.So the code is as follows:def earliest_wind_down_time(tasks): max_end = 0 for task in tasks: if task[1] > max_end: max_end = task[1] return max_endWait, but in the example, the function returns 17, which is correct.Another test case: tasks = [(18, 20), (20, 22)]. The end times are 20 and 22. So function returns 22.Yes.So I think this code should work.

answer：Okay, I need to write a Python function that takes a list of movie titles and formats them into a string with specific separators. Let's think about the requirements.So, the function should return a string where each title is separated by a comma and a space, except for the last two titles, which should be separated by "and". If there's only one title, just return it. If the list is empty, return an empty string.Hmm, let's break it down. First, handle the edge cases. If the list is empty, return empty string. If it has one element, return that element.For cases with two or more elements, I need to separate all but the last two with commas, then the last two with "and".Wait, no. Wait, for example, if there are three titles, it's "A, B and C". For four titles, it's "A, B, C and D".So, the approach is: take all elements except the last, join them with ", ", then add " and " plus the last element.Wait, no. Wait, for more than two elements, the last two are joined with " and ", and the rest are joined with ", ".So, for a list like [A, B, C, D], the output is "A, B, C and D".So, the steps are:1. Check the length of the list. - If 0: return "" - If 1: return the single element - Else: a. Take all elements except the last, join with ", ". b. Then, add " and " + last element.Wait, but what if the list has two elements? Then, it's "A and B".Yes, that works.So, the plan is:If len(list) == 0: return ""elif len(list) == 1: return list[0]else: all_but_last = ", ".join(list[:-1]) result = all_but_last + " and " + list[-1] return resultWait, but wait. Let's test this logic.For example, the sample input is ["The Great Escape", "Inception", "Parasite"].all_but_last is "The Great Escape, Inception", then add " and Parasite" → correct.Another test case: ["A", "B"] → "A and B" → correct.Another test case: ["A", "B", "C", "D"] → "A, B, C and D" → correct.What about a list with four elements: ["A", "B", "C", "D"] → the code would produce "A, B, C and D" which is correct.Yes, this logic should work.So, the function can be written as:def format_movie_titles(movies): if not movies: return "" if len(movies) == 1: return movies[0] else: all_but_last = ", ".join(movies[:-1]) return f"{all_but_last} and {movies[-1]}"Wait, but wait. What about when the list is empty? The function correctly returns empty string.Testing the sample input: ["The Great Escape", "Inception", "Parasite"] → the function returns "The Great Escape, Inception and Parasite" which matches the expected output.Another test: ["Inception"] → returns "Inception".Another test: [] → returns "".Another test: ["A", "B", "C"] → "A, B and C".Yes, that seems to cover all cases.So, I think this function should work.

answer：Okay, I need to write a Python function to calculate the total velocity of a spacecraft given its three velocity components. Hmm, the problem says to use the Pythagorean theorem in three dimensions. Right, so the formula is the square root of (vx squared plus vy squared plus vz squared). Wait, let me think about the steps. So, the function will take three inputs: vx, vy, vz. All of them are floats. Then, I need to compute each component squared, sum them up, take the square root, and return that as the total velocity.So, how do I implement this in Python? Well, I can start by defining the function with the three parameters. Then, inside the function, calculate each square. Oh right, in Python, I can square a number using the ** operator or by multiplying the number by itself.Let me think about the example they gave. The input was vx=3, vy=4, vz=12. So 3 squared is 9, 4 squared is 16, 12 squared is 144. Adding those gives 9+16=25, plus 144 is 169. The square root of 169 is 13, which matches the expected output.So the steps are clear. Now, how to compute this in code. Let's see:First, compute the squares:vx_squared = vx ** 2vy_squared = vy ** 2vz_squared = vz ** 2Then sum them:sum_squares = vx_squared + vy_squared + vz_squaredThen take the square root. Oh right, I can use the math.sqrt function for that. But wait, I need to import the math module first. So I should import math at the top of the function or in the code.Wait, but in the function, do I need to import math? Or is it better to import it once outside. Well, in the function, I can import it, but that's not efficient if the function is called multiple times. So I should import math before defining the function.Wait, but in the function, I can just use math.sqrt. So the function will need to have access to the math module. So I should import math at the top of the script.So putting it all together, the function will look like this:import mathdef calculate_total_velocity(vx, vy, vz): total = math.sqrt(vx**2 + vy**2 + vz**2) return totalWait, but wait, what if the inputs are negative? Oh, but when you square them, it doesn't matter. So that's handled automatically.Testing with the example: 3,4,12. 3^2 is 9, 4^2 is 16, 12^2 is 144. Sum is 169. Square root is 13. So the function returns 13.0, which is correct.What about other cases? Like if all are zero, it returns zero. If one is zero, like vx=0, vy=5, vz=0, then total is 5. So that seems right.So the function is straightforward. I think that's all I need to do.

answer：Okay, I need to write a Python function to determine if a social worker's schedule has any overlapping appointments. The function should return True if there are no overlaps, and False otherwise.Hmm, so the input is a list of tuples, each with a start and end time. The first thing I think of is that I need to check each pair of visits to see if they overlap. But wait, checking every possible pair could be inefficient, especially if the list is long. But for the problem, maybe it's manageable since the constraints aren't given as too large.Wait, but maybe there's a smarter way. Oh right! If I sort the schedule based on the start times, then I can just check each consecutive pair to see if they overlap. Because if the schedule is sorted, any overlaps would be between consecutive visits. That makes sense.So the plan is:1. Sort the list of tuples based on the start time of each visit.2. Iterate through the sorted list and check each consecutive pair.3. For each pair, if the end time of the current visit is greater than the start time of the next visit, then there's an overlap, return False.4. If all pairs are checked and no overlaps are found, return True.Wait, but what about the case where a visit ends exactly when another starts? Like (9,11) and (11,13). Those don't overlap, so that's fine. So the condition is that the end time of the current visit must be <= the start time of the next visit. If it's greater, then there's an overlap.So the steps in code:- First, sort the schedule. How? By the first element of each tuple. So in Python, I can do something like sorted_schedule = sorted(schedule, key=lambda x: x[0])- Then, loop from the first to the second last element. For each i, compare schedule[i][1] and schedule[i+1][0]. If schedule[i][1] > schedule[i+1][0], return False.- If all are okay, return True.Let me test this logic with the examples.First example:schedule = [(9,11), (11,13), (13,15)]After sorting, it's the same. Now check each consecutive pair:9-11 and 11-13: 11 <=11, no overlap.11-13 and 13-15: 13 <=13, no overlap. So returns True.Second example:overlapping_schedule = [(9,12), (11,14), (15,18)]After sorting, it's [(9,12), (11,14), (15,18)]Check first pair: 12 >11 → overlap. So function returns False.Another test case: what if a visit starts before the previous ends but not overlapping? Like [(10,12), (9,11)]. Wait, after sorting, it becomes [(9,11), (10,12)]. So 11 >10 → overlap. So function returns False.What about a case where the visits are not overlapping but in different order? Like [(15,18), (9,12), (11,13)]. After sorting, it's [(9,12), (11,13), (15,18)]. Check 12>11 → overlap. So returns False.Wait, but in the second example, the sorted list is [(9,12), (11,14), (15,18)]. The first pair 9-12 and 11-14: 12>11, so overlap. So function correctly returns False.What about a case where the visits are non-overlapping but in a different order? Like [(15,18), (10,12), (13,15)]. After sorting, it's [(10,12), (13,15), (15,18)]. Check 12 <=13 → no overlap. 15 <=15 → no overlap. So returns True.What about a single visit? Then the function should return True, as there's nothing to compare.What about two visits that are exactly back-to-back? Like (9,11) and (11,13). That's fine, no overlap.What about two visits where the second starts exactly when the first ends? That's acceptable.So the logic seems solid.Now, how to implement this in Python.The function will take the schedule as input. So:def can_visit(schedule): # Sort the schedule by start time sorted_schedule = sorted(schedule, key=lambda x: x[0]) # Iterate through each consecutive pair for i in range(len(sorted_schedule) - 1): current_end = sorted_schedule[i][1] next_start = sorted_schedule[i+1][0] if current_end > next_start: return False return TrueWait, but what if the schedule is empty? Then it returns True, which is correct.What about if the schedule has only one visit? It returns True, which is correct.Let me test the examples.Example 1:schedule = [(9,11), (11,13), (13,15)]sorted is same. Check 11 <=11 → no problem. 13 <=13 → no problem. So returns True.Example 2:overlapping_schedule = [(9,12), (11,14), (15,18)]sorted is same. 12>11 → returns False.Another test case: [(10,12), (9,11)] → sorted becomes [(9,11), (10,12)]. 11>10 → overlap, returns False.Another test: [(15,18), (10,12), (13,15)] → sorted is [(10,12), (13,15), (15,18)]. 12 <=13 → ok. 15 <=15 → ok. So returns True.Yes, this should handle all cases.Wait, but what about a case where a visit is completely inside another? Like (9,15) and (10,12). After sorting, it's [(9,15), (10,12)]. So current_end is 15, next_start is 10. 15>10 → returns False. Correct.So the function should handle all these cases.

answer：Okay, I need to write a Python function to find free time slots in a busy schedule. The daily schedule starts at 9 AM and ends at 9 PM. The input is a list of tuples, each with start and end times in 12-hour format. The output should be a list of tuples representing free slots of at least one hour.Hmm, let's think about the steps. First, I should process the given appointments and find the gaps between them, as well as the time before the first appointment and after the last one.Wait, right. So the first possible free slot is from 9 AM to the start of the first appointment. Then, between each appointment, check if there's a gap of at least an hour. Finally, after the last appointment until 9 PM.But how do I handle the times? They are strings in 12-hour format. I'll need to convert them into minutes since midnight or something to make it easier to compare.So, I should create a helper function to convert time strings into minutes. For example, "9:00 AM" is 9*60=540 minutes. "12:00 PM" is 12*60=720, and "12:00 AM" is 0 minutes. Oh wait, but in 12-hour format, 12 AM is midnight, and 12 PM is noon.So the helper function needs to handle AM and PM correctly. Let's outline that:Function to convert time string to minutes:- Split the string into time part and AM/PM.- Split the time part into hours and minutes.- Convert hours to integer. If it's AM and hour is 12, set to 0. If PM and hour is not 12, add 12.- Then, total minutes = hours * 60 + minutes.Yes. So, for example, "9:00 AM" is 9*60=540. "12:00 PM" is 12*60=720. "12:00 AM" is 0.Once I have all the times converted to minutes, I can process the appointments.So, first, I'll create a list of all the start and end times in minutes. Then, I'll sort them, but wait, the input is already sorted and no overlapping, so I can process them in order.Wait, the input is a list of tuples, each with start and end. So, for each appointment, I can extract the start and end in minutes.Let me think about the steps:1. Convert all appointment times to minutes.2. Check the time before the first appointment. If it's after 9 AM, then the free slot is from 9 AM to the first appointment's start.3. Then, for each consecutive pair of appointments, check the end of the previous and the start of the next. If the difference is >=60 minutes, add that as a free slot.4. Finally, check the time after the last appointment until 9 PM. If the end of last appointment is before 9 PM, add that as a free slot.Wait, but the initial free slot is from 9 AM to the first appointment's start. So, for example, if the first appointment is at 10 AM, then 9-10 is a free slot.So, the plan is:- Start with the initial time as 9 AM (540 minutes).- For each appointment in the list: - Get the start time in minutes. - If the start time is greater than the initial time, then the free slot is from initial time to start time. - Then, set the initial time to the end time of this appointment.- After processing all appointments, check if the initial time is before 9 PM (21*60=1080). If yes, add a free slot from initial time to 1080.But wait, the initial time starts at 540. For each appointment, we compare the start time to the initial time. If the start is after initial, then the gap is from initial to start. Then, set initial to the end of the appointment.Yes.So, let's outline this:Initialize free_slots as empty list.current_end = 540 (9 AM)for each (start, end) in appointments: start_min = convert(start) end_min = convert(end) if start_min > current_end: # there's a gap free_slot_start = current_end free_slot_end = start_min # check if the duration is >=60 if free_slot_end - free_slot_start >= 60: free_slots.append( (convert back to time string) ) current_end = end_min# after all appointments, check the endif current_end < 1080: free_slot_start = current_end free_slot_end = 1080 if free_slot_end - free_slot_start >=60: free_slots.append( (convert to time string) )Wait, but the initial current_end is 540. For each appointment, we check if the start is after current_end. If so, then the gap is from current_end to start. Then, current_end is updated to the end of the appointment.But wait, what if the first appointment starts at 9 AM? Then, current_end is 540, and the start is 540. So no gap. Then, current_end becomes the end of the appointment.Yes.So, the steps are correct.Now, the helper function to convert time string to minutes.Let's think about how to parse the string.For example, "10:00 AM" is split into "10:00" and "AM".Split the string into two parts: time_part and period.Time_part is split into hours and minutes: "10:00" becomes 10 and 0.Then, handle AM/PM:If period is AM: if hour is 12, set to 0. else, hour remains as is.If period is PM: if hour is 12, remains 12. else, add 12.So, for "12:00 AM" → 0 hours.For "12:00 PM" → 12 hours.For "9:00 AM" → 9.For "2:30 PM" → 14:30 → 14*60 +30= 870.So, the helper function can be written as:def time_to_min(time_str): time_part, period = time_str.split() hours, minutes = map(int, time_part.split(':')) if period == 'AM': if hours == 12: hours = 0 else: if hours != 12: hours +=12 return hours *60 + minutesYes.Then, the reverse function: convert minutes back to time string.How to do that:def min_to_time(m): hours = m // 60 mins = m %60 if hours ==0: period = 'AM' hours =12 elif hours <12: period = 'AM' elif hours ==12: period = 'PM' else: period = 'PM' hours -=12 return f"{hours}:{mins:02d} {period}"Wait, but for 0 minutes, it's 12:00 AM. For 720 minutes (12 PM), it's 12:00 PM.Yes.Wait, let's test:m=540 → 9*60=540 → 9 AM.m=720 → 12 PM.m=0 → 12 AM.m=60 → 1 AM.m=13*60=780 → 13:00 → 1 PM.Yes.So, the helper functions are correct.Now, putting it all together.So, the function will:1. Convert all the appointment times into minutes.But wait, the input is a list of tuples. So, for each tuple, we have start and end times.So, for each appointment in the input list:start_min = time_to_min(appointment[0])end_min = time_to_min(appointment[1])But since the input is already sorted and non-overlapping, we can process them in order.So, the code outline is:def find_free_time(appointments): # Helper functions def time_to_min(time_str): # as above def min_to_time(m): # as above # Initialize free_slots = [] current_end = 540 # 9 AM for appt in appointments: start = appt[0] end = appt[1] start_min = time_to_min(start) end_min = time_to_min(end) # Check if there's a gap before this appointment if start_min > current_end: gap_start = current_end gap_end = start_min if gap_end - gap_start >=60: free_slots.append( (min_to_time(gap_start), min_to_time(gap_end)) ) # Update current_end to the end of this appointment current_end = end_min # Check the time after the last appointment if current_end < 1080: # 9 PM is 21*60=1260? Wait wait, 9 PM is 21:00 → 21*60=1260? Wait, wait, 9 PM is 21:00, which is 21*60=1260 minutes. Oh right, earlier I thought 9 PM is 1080, but that's wrong. Wait, 9 AM is 540, 12 PM is 720, 9 PM is 1260.Wait, oh no! I made a mistake earlier. 9 PM is 21:00 → 21*60=1260, not 1080. Because 9*60=540 is 9 AM, 12 PM is 720, 13 PM is 13*60=780, etc., up to 21*60=1260.So, the initial current_end is 540 (9 AM), and the end of the day is 1260 (9 PM).So, in the code, the last check should be if current_end < 1260.So, in the code, the initial current_end is 540, and after processing all appointments, if current_end is less than 1260, then the free slot is from current_end to 1260, provided the duration is >=60.So, the code needs to be adjusted.So, the code outline:current_end = 540for each appt in appointments: process as before.after loop:if current_end < 1260: gap_start = current_end gap_end = 1260 if gap_end - gap_start >=60: free_slots.append( (min_to_time(gap_start), min_to_time(gap_end)) )So, that's a correction.Now, let's test the example.Example:appointments = [ ("10:00 AM", "11:00 AM"), ("1:00 PM", "2:30 PM"), ("4:00 PM", "5:00 PM")]Convert each to minutes:First appointment: 10 AM is 600, 11 AM is 660.Second: 1 PM is 13:00 → 780, 2:30 PM is 14:30 → 870.Third: 4 PM is 16:00 → 960, 5 PM is 1020.Processing:current_end = 540.First appt: start is 600.600 > 540 → gap is 540-600 → 60 minutes. So, add ("9:00 AM", "10:00 AM").current_end becomes 660.Next appt: start is 780.780 >660 → gap is 660-780 → 120 minutes. So, add ("11:00 AM", "1:00 PM").current_end becomes 870.Next appt: start is 960.960 >870 → gap is 870-960 → 90 minutes. So, add ("2:30 PM", "4:00 PM").current_end becomes 1020.After processing all, check if current_end < 1260.1020 <1260 → gap is 1020-1260 → 240 minutes. So, add ("5:00 PM", "9:00 PM").So, the free_slots are:[("9:00 AM", "10:00 AM"), ("11:00 AM", "1:00 PM"), ("2:30 PM", "4:00 PM"), ("5:00 PM", "9:00 PM")]Which matches the expected output.Great.Another test case: what if the first appointment starts at 9 AM?appointments = [("9:00 AM", "10:00 AM"), ...]Then, current_end is 540. The first appt's start is 540 → no gap. So, no free slot before it.Another case: what if there's no gap between two appointments?Like appointments = [("9:00 AM", "10:00 AM"), ("10:00 AM", "11:00 AM")]. Then, between them, no gap. So, no free slot.Another case: what if the last appointment ends at 8 PM (20:00 → 1200 minutes). Then, the gap is 1200-1260=60 minutes. So, add 8 PM to 9 PM.But if the last appt ends at 8:30 PM (20:30 → 1230), then 1230 to 1260 is 30 minutes → not enough. So, no slot added.So, the code should handle that.Now, let's think about the code.Implement the helper functions inside the main function.Now, code:def find_free_time(appointments): def time_to_min(time_str): time_part, period = time_str.split() hours, mins = map(int, time_part.split(':')) if period == 'AM': if hours == 12: hours = 0 else: if hours != 12: hours += 12 return hours * 60 + mins def min_to_time(m): hours = m // 60 mins = m % 60 if hours == 0: period = 'AM' hours = 12 elif 1 <= hours < 12: period = 'AM' elif hours == 12: period = 'PM' else: period = 'PM' hours -= 12 return f"{hours}:{mins:02d} {period}" free_slots = [] current_end = 540 # 9 AM for appt in appointments: start_str, end_str = appt start = time_to_min(start_str) end = time_to_min(end_str) if start > current_end: gap_start = current_end gap_end = start if gap_end - gap_start >= 60: free_slots.append( (min_to_time(gap_start), min_to_time(gap_end)) ) current_end = end # Check after last appointment if current_end < 1260: # 9 PM is 1260 gap_start = current_end gap_end = 1260 if gap_end - gap_start >= 60: free_slots.append( (min_to_time(gap_start), min_to_time(gap_end)) ) return free_slotsWait, but in the helper function min_to_time, for 0 minutes, it returns 12:00 AM. For 60 minutes, it's 1:00 AM. For 1260, which is 21:00 → 9 PM.Yes.Testing the example:The code should return the expected output.Another test case: appointments = [("9:00 AM", "10:00 AM"), ("10:00 AM", "11:00 AM"), ("11:00 AM", "12:00 PM")]. Then, the free slots would be:After 12 PM until 9 PM, but wait:current_end after last appt is 12 PM (720). So, 720 to 1260 is 540 minutes. So, the free slot is 12 PM to 9 PM.But wait, 720 to 1260 is 540 minutes, which is 9 hours. So, the free slot is added.So, the output would be [("12:00 PM", "9:00 PM")].Another test case: appointments = [("9:00 AM", "10:00 AM"), ("10:00 AM", "11:00 AM"), ("11:00 AM", "12:00 PM"), ("1:00 PM", "2:00 PM")]. Then, the free slots are:Between 12 PM and 1 PM (60 minutes) → added as ("12:00 PM", "1:00 PM"), and after 2 PM to 9 PM (7 hours) → added as ("2:00 PM", "9:00 PM").So, the function should capture that.Another edge case: appointments = [("9:00 AM", "9:00 PM")]. Then, current_end is 540. The appt starts at 540, ends at 1260. So, no free slots.Another case: appointments = [("10:00 AM", "11:00 AM"), ("12:00 PM", "1:00 PM")]. Then, the free slots are:9-10 AM, 11 AM-12 PM, 1 PM-9 PM.So, three slots.Yes.So, the code should handle all these cases.I think this should work.

answer：Okay, I need to write a Python function that takes a list of integers representing distances run each day and converts each integer into a string with " km" appended. So, for example, if the input is [5, 10, 3, 6], the output should be ["5 km", "10 km", "3 km", "6 km"]. Also, the function should handle an empty list by returning an empty list.Hmm, let's think about how to approach this. I remember that in Python, you can loop through each element in a list and perform operations on them. So, perhaps I can create a new list and for each distance in the input list, convert it to a string and add " km" to it.Wait, how do I convert each integer to a string? Oh right, I can use the str() function. So for each element d in the input list, I can do str(d) + " km" or format it as a string.Another approach is to use list comprehension, which is concise and efficient. So the function could be something like [f"{d} km" for d in distances], right?Yes, that makes sense. So the function will take the input list, iterate over each element, convert each to a string with " km" added, and collect all these into a new list.What about handling an empty list? Well, if the input is empty, the list comprehension will naturally produce an empty list, so no special handling is needed.Let me outline the steps:1. Define a function, maybe called convert_distances, that takes one parameter, which is the list of integers.2. Check if the list is empty. But wait, even if it's empty, the list comprehension will handle it, so maybe no need for an explicit check.3. Use a list comprehension to create the new list of strings.4. Return the new list.So putting it all together, the function would look like:def convert_distances(distances): return [f"{d} km" for d in distances]Wait, but what if the input is not a list? Well, the problem statement says the input is a list of integers, so we don't need to handle that case.Testing the example: distances = [5,10,3,6]. The function would loop through each number, convert to string, add " km", and return the list as expected.What about zero? Like if a distance is zero, it should become "0 km", which is correct.What about negative numbers? Well, the problem says distances, which are in kilometers, so I suppose negative numbers aren't expected, but the function will handle them as well, converting to strings like "-5 km".So I think this solution should work.