Python Backend Developer Assessment

Overview

This assessment contains 20 progressively difficult questions designed to evaluate Python programming skills and backend development capabilities. Total points: 100.

✨ NEW: Advanced Time Tracking & Analytics
Track student progress, identify learning patterns, and get comprehensive performance insights!

Structure

• questions/ - Individual question files
• tests/ - Automated test cases for each question
• time_tracker.py - Optional time tracking utility
• analytics/ - Instructor analytics tools
• requirements.txt - Required dependencies

Setup for GitHub Classroom

For Instructors:

1. Fork this repository to your GitHub Classroom organization
2. Set up autograding workflow using the provided test cases
3. Configure point allocation in GitHub Classroom settings
4. NEW: Set up analytics tracking (see INSTRUCTOR_ANALYTICS_GUIDE.md)

For Students:

1. Clone the assignment repository
2. Install dependencies: pip install -r requirements.txt
3. Complete functions in the questions/ directory
4. Optional: Use time tracker to monitor your progress
5. Run tests locally: pytest tests/
6. Push solutions to trigger autograding

Question Categories & Point Distribution

Basic Python (Questions 1-5) - 20 points

• Data types and basic operations
• Control structures
• Functions and basic algorithms

Intermediate Python (Questions 6-10) - 25 points

• Object-oriented programming
• Error handling
• File operations
• Data structures

Advanced Python (Questions 11-15) - 30 points

• Decorators and context managers
• Generators and iterators
• Concurrency basics
• Advanced data manipulation

Backend Development (Questions 16-20) - 25 points

• REST API development
• Database operations
• Authentication
• Testing and deployment concepts

🕒 Time Tracking Features

For Students (Optional)

# Track your coding sessions by category
python time_tracker.py start_basic      # Start timing Basic Python
python time_tracker.py end             # End current session
python time_tracker.py summary         # View time breakdown

Benefits:

• Learn about your coding patterns
• Identify which topics need more practice
• Track improvement over time
• Get efficiency feedback

For Instructors (Analytics)

# Generate comprehensive analytics
cd analytics/
python github_analytics.py

Get insights on:

• Student time distribution across question categories
• Work patterns (late night, weekend coding)
• Submission frequency and progression
• Class-wide performance statistics
• Academic integrity indicators

📊 Analytics Capabilities

Automatic Tracking (GitHub Classroom)

• Assignment acceptance times
• Commit timestamps and frequency
• Submission patterns
• Repository activity

Advanced Analytics (GitHub API)

• Estimated active coding time
• Commit pattern analysis
• Work schedule insights
• Performance correlations
• Efficiency metrics

Generated Reports

• Individual student time summaries
• Class performance overview
• Visual analytics charts
• CSV exports for gradebooks
• Academic integrity flags

Grading Scale

• 90-100: Excellent
• 80-89: Good
• 70-79: Satisfactory
• 60-69: Needs Improvement
• Below 60: Unsatisfactory

Time Limit

Recommended time: 3-4 hours

📁 Complete File Structure

python-backend-assessment/
├── README.md                     # This overview
├── STUDENT_GUIDE.md             # Detailed student instructions
├── INSTRUCTOR_ANALYTICS_GUIDE.md # Analytics setup and usage
├── ASSESSMENT_SUMMARY.md        # Complete question breakdown
├── requirements.txt             # Core dependencies
├── pytest.ini                  # Test configuration
├── time_tracker.py             # Student time tracking tool
│
├── .github/workflows/
│   └── autograding.yml         # GitHub Classroom autograder
│
├── questions/
│   ├── __init__.py
│   ├── basic_python.py         # Questions 1-5 (20 pts)
│   ├── intermediate_python.py  # Questions 6-10 (25 pts)
│   ├── advanced_python.py      # Questions 11-15 (30 pts)
│   └── backend_development.py  # Questions 16-20 (25 pts)
│
├── tests/
│   ├── __init__.py
│   ├── test_basic_python.py
│   ├── test_intermediate_python.py
│   ├── test_advanced_python.py
│   └── test_backend_development.py
│
└── analytics/
    ├── requirements_analytics.txt
    └── github_analytics.py     # Instructor analytics tool

🚀 Quick Start for Different Users

Students

1. Accept assignment in GitHub Classroom
2. Clone repository: git clone [YOUR_REPO_URL]
3. Install dependencies: pip install -r requirements.txt
4. Start coding: Begin with questions/basic_python.py
5. Optional tracking: Use python time_tracker.py start_basic
6. Test often: pytest tests/test_basic_python.py -v
7. Submit: git add . && git commit -m "Progress" && git push

Instructors (Setup)

1. Create template repository with all assessment files
2. Set up GitHub Classroom assignment
3. Configure autograding (automatic with included workflow)
4. Test with sample submission
5. Share assignment link with students

Instructors (Analytics)

1. Get GitHub token: https://github.com/settings/tokens
2. Set environment variables:

   export GITHUB_TOKEN="your_token"
   export GITHUB_ORG="your-org-name"

3. Install analytics tools: pip install -r analytics/requirements_analytics.txt
4. Run analytics: python analytics/github_analytics.py
5. Review reports in analytics_output/ directory

🎯 Key Features

✅ Comprehensive Assessment

• 20 carefully designed questions
• Progressive difficulty
• Real-world backend scenarios
• Complete test coverage

✅ Automated Grading

• GitHub Classroom integration
• Instant feedback for students
• Zero manual grading work
• Detailed test results

✅ Advanced Analytics

• Time tracking and analysis
• Work pattern insights
• Academic integrity tools
• Performance metrics

✅ Educational Value

• Learn about coding patterns
• Identify improvement areas
• Track skill development
• Professional-level scenarios

📈 Success Metrics

This assessment system provides insights into:

• Student Learning: Time allocation, difficulty patterns, improvement areas
• Instructor Efficiency: Automated grading, comprehensive analytics
• Academic Integrity: Unusual patterns, collaboration detection
• Course Improvement: Question difficulty analysis, time expectations

🔧 Customization Options

• Modify point allocations per question
• Add/remove questions based on course focus
• Adjust time limits in autograder
• Customize grading scale
• Add additional test cases
• Configure analytics parameters

Ready to revolutionize your Python assessment experience? 🚀