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 JavaScript function named analyzeLogs
. This function 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 function 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 function 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 JavaScript, string manipulation can be handled using methods from the String
class.
JavaScript1function analyzeLogs(logs) { 2 let logList = logs.split(", ");
The split
function in JavaScript 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:
JavaScript1const 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.log(logs.split(", "))
The output would return:
Plain text1[ 2 '1 create 09:00', 3 '2 create 10:00', 4 '1 delete 12:00', 5 '3 create 13:00', 6 '2 delete 15:00', 7 '3 delete 16:00' 8]
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.
JavaScript1function analyzeLogs(logs) { 2 let logList = logs.split(", "); // Split the log string by ', ' to separate individual events 3 4 let timeDict = {}; // Object to record the creation moment for each group in minutes 5 let lifeDict = {}; // Object to record the lifetime for each group in minutes 6 7 logList.forEach(log => { 8 let parts = log.split(" "); // Split each log into components: groupId, action, and time 9 let groupId = parseInt(parts[0]); // Convert groupId from string to number 10 let action = parts[1]; // The action can be either 'create' or 'delete' 11 let time = parts[2]; // The timestamp of the action (HH:MM format) 12 }); 13}
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 slice
method in JavaScript returns a shallow copy of a portion of an array or string into a new array or string object. A shallow copy refers to copying only the values at the first level, without copying nested structures. This means that changes to the copied object will not affect the original object unless they are changes to nested objects. With one parameter, slice(start)
, it extracts elements from the start index to the end of the array or string, while with two parameters, slice(start, end)
, it extracts elements from the start index up to, but not including, the end index. Negative indices are used to indicate an offset from the end of the array or string, for example, slice(-2)
extracts the last two elements.
Using this to parse and calculate the lifetimes, we can use the following code:
JavaScript1let time = "12:45"; 2let hour = parseInt(time.slice(0, 2)); // '12' 3let minute = parseInt(time.slice(3, 5)); // '45' 4let totalMinutes = hour * 60 + minute; 5 6console.log(totalMinutes); // Output: 765 (12 hours * 60 + 45 minutes)
Generalizing this in the analyzeLogs
function, we can parse the time and calculate the lifetimes as follows:
JavaScript1function analyzeLogs(logs) { 2 let logList = logs.split(", "); 3 4 let timeDict = {}; // Object to record the creation moment for each group in minutes 5 let lifeDict = {}; // Object to record the lifetime for each group in minutes 6 7 logList.forEach(log => { 8 let parts = log.split(" "); 9 let groupId = parseInt(parts[0]); 10 let action = parts[1]; 11 let time = parts[2]; 12 13 // Parsing the time from HH:MM format 14 let hour = parseInt(time.slice(0, 2)); 15 let minute = parseInt(time.slice(3, 5)); 16 let currentTime = hour * 60 + minute; // Time in minutes from the start of the day 17 18 if (action === "create") { 19 timeDict[groupId] = [hour, minute]; // If the group is created, log the creation time. 20 } else { 21 if (timeDict[groupId]) { 22 // If the group is deleted, calculate its entire lifetime and remove it from the records. 23 let creationTime = timeDict[groupId][0] * 60 + timeDict[groupId][1]; // Convert creation time to minutes 24 let lifetime = currentTime - creationTime; // Calculate the lifetime of the group 25 if (lifeDict[groupId]) { 26 lifeDict[groupId] += lifetime; // Add the new lifetime to the existing one 27 } else { 28 lifeDict[groupId] = lifetime; // Initialize with the first lifetime 29 } 30 delete timeDict[groupId]; // Remove group from timeDict after calculating lifetime 31 } 32 } 33 });
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.
JavaScript1function analyzeLogs(logs) { 2 let logList = logs.split(", "); 3 4 let timeDict = {}; // Object to record the creation moment for each group in minutes 5 let lifeDict = {}; // Object to record the lifetime for each group in minutes 6 7 logList.forEach(log => { 8 let parts = log.split(" "); 9 let groupId = parseInt(parts[0]); 10 let action = parts[1]; 11 let time = parts[2]; 12 13 // Parsing the time from HH:MM format 14 let hour = parseInt(time.slice(0, 2)); 15 let minute = parseInt(time.slice(3, 5)); 16 let currentTime = hour * 60 + minute; // Time in minutes from the start of the day 17 18 if (action === "create") { 19 timeDict[groupId] = [hour, minute]; // If the group is created, log the creation time. 20 } else { 21 if (timeDict[groupId]) { 22 // If the group is deleted, calculate its entire lifetime and remove it from the records. 23 let creationTime = timeDict[groupId][0] * 60 + timeDict[groupId][1]; 24 let lifetime = currentTime - creationTime; 25 if (lifeDict[groupId]) { 26 lifeDict[groupId] += lifetime; 27 } else { 28 lifeDict[groupId] = lifetime; 29 } 30 delete timeDict[groupId]; 31 } 32 } 33 }); 34 35 // Find the longest lifetime 36 let maxLife = Math.max(...Object.values(lifeDict)); 37 38 // Building the result list where each item is a string of "group ID lifetime" if it has the longest lifetime. 39 let result = []; 40 for (let groupId in lifeDict) { 41 if (lifeDict[groupId] === maxLife) { 42 let hours = Math.floor(lifeDict[groupId] / 60); 43 let minutes = lifeDict[groupId] % 60; 44 let timeString = ("0" + hours).slice(-2) + ":" + ("0" + minutes).slice(-2); 45 result.push(groupId + " " + timeString); 46 } 47 } 48 49 // Sorting the result in ascending order of the group IDs 50 return result.sort((a, b) => a.split(" ")[0] - b.split(" ")[0]); 51} 52 53// Example usage: 54let 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"; 55let result = analyzeLogs(logs); 56result.forEach(entry => { 57 console.log("Group " + entry.split(" ")[0] + " lifetime: " + entry.split(" ")[1]); 58}); 59// Outputs: 60// Group 2 lifetime: 05:00
The final return statement sorting the list will be explained below. Here is a detailed breakdown of how it works:
-
Array.sort() Method: The
sort()
method in JavaScript sorts the elements of an array in place and returns the sorted array. By default, the elements are sorted as strings in ascending lexicographical order. However, for custom sorting (e.g., by numbers or other criteria), a compare function is provided.When
sort()
is used without a compare function, JavaScript treats array elements as strings. For example,[10, 2, 30].sort()
would result in[10, 2, 30]
, not[2, 10, 30]
, because it's comparing character-by-character, like string sorting.In order to sort numerically, we need to use a compare function, as in this code snippet:
result.sort((a, b) => a.split(" ")[0] - b.split(" ")[0]);
. -
Compare Function: The arrow function
(a, b) => a.split(" ")[0] - b.split(" ")[0]
serves as the compare function. This function takes two arguments,a
andb
, which are elements from theresult
array. -
Splitting Strings: Each element in the
result
array 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.For example:
- If
a
is"2 05:00"
,a.split(" ")
results in the array["2", "05:00"]
. - Similarly, if
b
is"1 02:00"
,b.split(" ")
results in the array["1", "02:00"]
.
- If
-
Extracting Group IDs: The expression
a.split(" ")[0]
extracts the group ID froma
as a string, andb.split(" ")[0]
extracts the group ID fromb
as a string. So in the example above:a.split(" ")[0]
would yield"2"
.b.split(" ")[0]
would yield"1"
.
-
String to Number Conversion: The subtraction operation (
-
) implicitly converts these group ID strings to numbers. So"2" - "1"
is interpreted as2 - 1
, which equals1
. -
Difference Calculation: The compare function returns the difference between these numeric values:
- If the result is positive (
> 0
),a
is considered greater thanb
, andb
comes beforea
in the sorted array. - If the result is negative (
< 0
),a
is considered less thanb
, anda
comes beforeb
in the sorted array. - If the result is zero (
=== 0
), the order ofa
andb
remains unchanged.
- If the result is positive (
Given this compare 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 JavaScript. Using JavaScript's String
methods and objects 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!