9. Track Daily and Monthly Active Users from Apache Logs
1. Hello, World!
2. Rename Photos by Capture Date
3. Organize Downloads Folder by File Type
4. Delete Old Log Files Automatically
5. Find Duplicate Files Using MD5 Hashing
6. Generate Comprehensive File Inventory
7. Parse Web Server Logs for Performance Metrics
8. Extract Emails, URLs, and Phone Numbers from Text
9. Track Daily and Monthly Active Users from Apache Logs
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11. Analyze Sales Transactions and Generate Revenue Reports
12. Clean and Validate CSV Data
13. Convert JSON API Responses to CSV
14. Parse and Validate Configuration Files
15. Build a CLI Calculator with Argument Parsing
16. Parse and Display Weather Data from JSON
17. Build a Simple Inventory System with Classes
18. Generate Markdown Table from CSV Data
19. Aggregate Sales Data by Time Period
20. Recursive Directory Size Calculator with Filtering
21. Parse and Transform Server Configuration
22. Find and Replace Across Multiple Files
23. Build a Simple Template Engine
24. CSV Data Validator with Business Rules
25. Build a Multi-Format Log Analyzer

Challenge

Problem

Analytics teams track engagement metrics, product managers need DAU/MAU reports, and SaaS companies monitor usage for billing. This drill teaches you to parse Apache access logs to extract IP addresses and usernames, group activity by date, count unique users per day, and calculate 30-day active users. You'll work with complex nested hash structures and date arithmetic.

Difficulty: Intermediate

Instructions

  1. Read Apache access log file line by line
  2. Parse each line to extract: IP address, username (or '-' for anonymous), date
  3. Skip anonymous users (username = '-')
  4. Build nested structure: { date => { username => request_count } }
  5. Calculate daily unique users for each date
  6. Calculate 30-day active users (unique users across all dates)
  7. Output format:
    'Date: 2024-10-01, Active users: 5'
    'Date: 2024-10-02, Active users: 7'
    '30-day active users: 12'

Files

Editable
Read-only

Hints

Hint 1

Apache log format: IP - username [date] "request" status size

Hint 2

Use regex to extract the three parts before the bracket

Hint 3

Hash.new { |h, k| h[k] = Hash.new(0) } creates nested hash with counters

Hint 4

Date.strptime(date_str, '%d/%b/%Y') parses Apache date format

Hint 5

Use .strftime('%Y-%m-%d') to convert to standard format

Hint 6

Count unique users with hash.keys.length

Hint 7

Get all unique users across days with .flat_map(&:keys).uniq

Ruby 3.4

Provided Files (Read-only)

1. Correct daily counts

Input: 
track_active_users('apache.log')
Expected Output: 
Date: 2024-10-01, Active users: 2
Date: 2024-10-02, Active users: 3
Date: 2024-10-03, Active users: 1

30-day active users: 4

2. Skips anonymous users

Input: 
track_active_users('apache.log')
puts 'Anonymous skipped'
Expected Output: 
Date: 2024-10-01, Active users: 2
Date: 2024-10-02, Active users: 3
Date: 2024-10-03, Active users: 1

30-day active users: 4
Anonymous skipped

3. Dates sorted chronologically

Input: 
track_active_users('apache.log')
puts 'Sorted correctly'
Expected Output: 
Date: 2024-10-01, Active users: 2
Date: 2024-10-02, Active users: 3
Date: 2024-10-03, Active users: 1

30-day active users: 4
Sorted correctly
+ 2 hidden test cases