Welcome to our new coding practice lesson! We have an intriguing problem centered around data from a social networking app. The challenge involves processing logs from this app and extracting valuable information from them. This task will leverage your skills in string manipulation, working with timestamps, and task subdivision. Let's get started!
Imagine a social networking application that allows users to form groups. Each group has a unique ID ranging from 1 to n
, where n
is the total number of groups. The app keeps track of group creation and deletion events, logging all these actions in a string.
The task before us is to create a C# method named AnalyzeLogs
within a class. This method will take as input a string of logs and output an array of strings representing the groups with the longest lifetime. Each string in the array contains two items separated by a space: the group ID and the group's lifetime. By "lifetime," we mean the duration from when the group was created until its deletion. If a group has been created and deleted multiple times, the lifetime is the total sum of those durations.
For example, if we have a log string as follows: "1 create 09:00, 2 create 10:00, 1 delete 12:00, 3 create 13:00, 2 delete 15:00, 3 delete 16:00"
, the function will return: ["2 05:00"]
.
If multiple groups have the same longest lifetime, the method should return all such groups in ascending order of their IDs. Let's say we have the log string "1 create 08:00, 2 create 09:00, 1 delete 10:00, 2 delete 11:00, 3 create 12:00, 3 delete 13:00"
. In this case, both group 1 and group 2 have the same lifetime of 02:00. The method should return ["1 02:00", "2 02:00"]
since both have the longest lifetime, and group 1 comes before group 2.
To tackle this problem, we will take the following steps:
- Split the Log Strings: Divide the input string into individual log entries based on a delimiter.
- Parse Log Components: For each log entry, identify the group ID, action type, and timestamp.
- Record and Calculate Lifetimes: Track creation times and compute lifetimes whenever a group is deleted.
- Identify Longest Lifetimes: Compare the lifetimes of all groups to determine the ones with the longest.
First, we will split the input string into individual operations. In C#, string manipulation can be handled using methods from the String
class.
C#1using System; 2using System.Collections.Generic; 3using System.Linq; 4 5public class LogAnalyzer 6{ 7 public static string[] AnalyzeLogs(string logs) 8 { 9 string[] logList = logs.Split(", ");
The Split
method in C# is a method of the String
class that splits a string into an array of substrings based on a specified delimiter. For example, logs.Split(", ")
will divide the logs
string into smaller substrings wherever it finds the delimiter ", "
and return an array of those substrings. For example, take a look at the following code:
C#1string logs = "1 create 09:00, 2 create 10:00, 1 delete 12:00, 3 create 13:00, 2 delete 15:00, 3 delete 16:00"; 2Console.WriteLine(string.Join("\n", logs.Split(", ")));
The output would return:
Plain text11 create 09:00 22 create 10:00 31 delete 12:00 43 create 13:00 52 delete 15:00 63 delete 16:00
Next, we delve deeper into the logs. For each logged group operation in the string, we need to parse its components. These include the group ID, the type of operation (create
or delete
), and the time of action.
C#1public static string[] AnalyzeLogs(string logs) 2{ 3 string[] logList = logs.Split(", "); // Split the log string by ', ' to separate individual events 4 5 Dictionary<int, int[]> timeDict = new Dictionary<int, int[]>(); // Dictionary to record the creation moment for each group in minutes 6 Dictionary<int, int> lifeDict = new Dictionary<int, int>(); // Dictionary to record the lifetime for each group in minutes 7 8 foreach (var log in logList) 9 { 10 string[] parts = log.Split(" "); // Split each log into components: groupId, action, and time 11 int groupId = int.Parse(parts[0]); // Convert groupId from string to number 12 string action = parts[1]; // The action can be either 'create' or 'delete' 13 string time = parts[2]; // The timestamp of the action (HH:MM format) 14 } 15}
Now that we can identify each group's actions and their timestamps, it's time to process these details. We convert the group ID into an integer and the timestamp into minutes from the start of the day. If the log entry marks a create
action, we register the creation time in an object under the group ID. If the entry signals delete
, we calculate the group's lifetime and store it in another object.
The Substring
method in C# returns a new string that is a subset of the original string. It creates a shallow copy of a portion of the string starting at a specified index. When used with one parameter, Substring(startIndex)
, it extracts characters from the specified start index to the end of the string. When used with two parameters, Substring(startIndex, length)
, it extracts characters starting from the specified start index for the specified length. The startIndex
is zero-based, and using a negative start index will result in an exception.
int.Parse
is used to convert the string to an integer.
Using this to parse and calculate the lifetimes, we can use the following code:
C#1string timeExample = "12:45"; 2int hour = int.Parse(timeExample.Substring(0, 2)); // '12' 3int minute = int.Parse(timeExample.Substring(3, 2)); // '45' 4int totalMinutes = hour * 60 + minute; 5 6Console.WriteLine(totalMinutes); // Output: 765 (12 hours * 60 + 45 minutes)
Generalizing this in the AnalyzeLogs
method, we can parse the time and calculate the lifetimes as follows:
C#1public static string[] AnalyzeLogs(string logs) 2{ 3 string[] logList = logs.Split(", "); 4 5 Dictionary<int, int[]> timeDict = new Dictionary<int, int[]>(); // Dictionary to record the creation moment for each group in minutes 6 Dictionary<int, int> lifeDict = new Dictionary<int, int>(); // Dictionary to record the lifetime for each group in minutes 7 8 foreach (var log in logList) 9 { 10 string[] parts = log.Split(" "); 11 int groupId = int.Parse(parts[0]); 12 string action = parts[1]; 13 string time = parts[2]; 14 15 // Parsing the time from HH:MM format 16 int hour = int.Parse(time.Substring(0, 2)); 17 int minute = int.Parse(time.Substring(3, 2)); 18 int currentTime = hour * 60 + minute; // Time in minutes from the start of the day 19 20 if (action == "create") 21 { 22 timeDict[groupId] = new int[] { hour, minute }; // If the group is created, log the creation time. 23 } 24 else 25 { 26 if (timeDict.ContainsKey(groupId)) 27 { 28 // If the group is deleted, calculate its entire lifetime and remove it from the records. 29 int creationTime = timeDict[groupId][0] * 60 + timeDict[groupId][1]; // Convert creation time to minutes 30 int lifetime = currentTime - creationTime; // Calculate the lifetime of the group 31 if (lifeDict.ContainsKey(groupId)) 32 { 33 lifeDict[groupId] += lifetime; // Add the new lifetime to the existing one 34 } 35 else 36 { 37 lifeDict[groupId] = lifetime; // Initialize with the first lifetime 38 } 39 timeDict.Remove(groupId); // Remove group from timeDict after calculating lifetime 40 } 41 } 42 }
If the action is "delete"
and the group exists in timeDict
, its lifetime is calculated. The lifetime is added to the group’s entry in lifeDict
, or a new entry is created if it doesn't exist yet.
After recording the lifetimes of all groups, we can compare them to determine which group or groups had the longest lifetime. Finally, we return the ID or IDs of that group or groups, sorted in ascending order, along with their lifetime.
C#1using System; 2using System.Collections.Generic; 3using System.Linq; 4 5public class LogAnalyzer 6{ 7 public static string[] AnalyzeLogs(string logs) 8 { 9 string[] logList = logs.Split(", "); 10 11 Dictionary<int, int[]> timeDict = new Dictionary<int, int[]>(); // Dictionary to record the creation moment for each group in minutes 12 Dictionary<int, int> lifeDict = new Dictionary<int, int>(); // Dictionary to record the lifetime for each group in minutes 13 14 foreach (var log in logList) 15 { 16 string[] parts = log.Split(" "); 17 int groupId = int.Parse(parts[0]); 18 string action = parts[1]; 19 string time = parts[2]; 20 21 // Parsing the time from HH:MM format 22 int hour = int.Parse(time.Substring(0, 2)); 23 int minute = int.Parse(time.Substring(3, 2)); 24 int currentTime = hour * 60 + minute; // Time in minutes from the start of the day 25 26 if (action == "create") 27 { 28 timeDict[groupId] = new int[] { hour, minute }; // If the group is created, log the creation time. 29 } 30 else 31 { 32 if (timeDict.ContainsKey(groupId)) 33 { 34 // If the group is deleted, calculate its entire lifetime and remove it from the records. 35 int creationTime = timeDict[groupId][0] * 60 + timeDict[groupId][1]; 36 int lifetime = currentTime - creationTime; 37 if (lifeDict.ContainsKey(groupId)) 38 { 39 lifeDict[groupId] += lifetime; 40 } 41 else 42 { 43 lifeDict[groupId] = lifetime; 44 } 45 timeDict.Remove(groupId); 46 } 47 } 48 } 49 50 // Find the longest lifetime 51 int maxLife = lifeDict.Values.Max(); 52 53 // Building the result list where each item is a string of "group ID lifetime" if it has the longest lifetime. 54 List<string> result = new List<string>(); 55 foreach (var kvp in lifeDict) 56 { 57 if (kvp.Value == maxLife) 58 { 59 int hours = kvp.Value / 60; 60 int minutes = kvp.Value % 60; 61 string timeString = hours.ToString("D2") + ":" + minutes.ToString("D2"); 62 result.Add(kvp.Key + " " + timeString); 63 } 64 } 65 66 // Sorting the result in ascending order of the group IDs 67 return result.OrderBy(r => int.Parse(r.Split(" ")[0])).ToArray(); 68 } 69 70 public static void Main(string[] args) 71 { 72 string logs = "1 create 09:00, 2 create 10:00, 1 delete 12:00, 3 create 13:00, 2 delete 15:00, 3 delete 16:00"; 73 string[] result = AnalyzeLogs(logs); 74 foreach (var entry in result) 75 { 76 Console.WriteLine("Group " + entry.Split(" ")[0] + " lifetime: " + entry.Split(" ")[1]); 77 } 78 // Outputs: 79 // Group 2 lifetime: 05:00 80 } 81}
The final return statement sorting the list will be explained below. Here is a detailed breakdown of how it works:
-
LINQ OrderBy Method: The
OrderBy
method in LINQ sorts the elements of a sequence in ascending order according to a key, which is specified by a selector function. -
Splitting Strings: Each element in the
result
list is a string formatted as"groupID lifetime"
. TheSplit(" ")
method splits these strings into an array of two parts, with the group ID at index 0 and the lifetime at index 1. -
String to Number Conversion: The selector function
r => int.Parse(r.Split(" ")[0])
converts the group ID from string to integer. -
ToString("D2")
formats numbers as a two-digit string, padding with zero if necessary.
Given this selector function, the overall effect is that the result
array will be sorted in ascending order of the group IDs, ensuring that lower group IDs appear before higher group IDs.
Bravo! You have successfully navigated a non-trivial log analysis problem and worked with timestamped data, a real-world data type, in C#. Using C#'s String
methods and dictionaries alongside traditional arithmetic, you transformed raw strings into meaningful data. Real-life coding often involves accurately understanding, dissecting, and analyzing data, and this unit's lesson has provided you with practical experience in that regard. Now, let's apply these new learnings to more practice challenges. Off to the races you go!