Daily App Usage Peaks - codepath/compsci_guides GitHub Wiki
Unit 4 Session 1 Advanced (Click for link to problem statements)
U-nderstand
Understand what the interviewer is asking for by using test cases and questions about the problem.
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Q: What is the structure of the input?
- A: The input is a list of 24 integers, where each integer represents the number of minutes spent on apps during a specific hour (from hour 0 to hour 23).
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Q: What is the output?
- A: The output is a tuple containing the start hour (integer) and the total screen time (integer) for the three-hour period with the highest total usage.
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Q: What should the function return if multiple periods have the same total?
- A: The function should return the earliest period.
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Q: Are there any constraints on the input, such as non-negative integers?
- A: It is assumed that the list contains non-negative integers.
P-lan
Plan the solution with appropriate visualizations and pseudocode.
General Idea: Iterate through the list of screen times, summing the values for each set of three consecutive hours. Track the maximum sum and the corresponding start hour.
1) Initialize two variables: `max_sum` to 0 and `start_hour` to 0.
2) Iterate over the list from index 0 to 21 (as each three-hour period needs three values):
a) Calculate the sum of the current hour and the next two hours.
b) If this sum is greater than `max_sum`, update `max_sum` to this value and `start_hour` to the current index.
3) Return `start_hour` and `max_sum` as a tuple.
**⚠️ Common Mistakes**
- Forgetting to stop the loop early enough to avoid index errors.
- Not properly updating the `max_sum` and `start_hour` when a new maximum is found.
I-mplement
def peak_usage_hours(screen_time):
max_sum = 0
start_hour = 0
for i in range(len(screen_time) - 2):
current_sum = screen_time[i] + screen_time[i + 1] + screen_time[i + 2]
if current_sum > max_sum:
max_sum = current_sum
start_hour = i
return start_hour, max_sum