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Phase 7 ⚡ — Advanced

Topics: File I/O, exception handling, algorithms (search/sort), database basics

Write robust programs that handle errors gracefully, work with files, implement fundamental algorithms, and interact with databases.

🔄 Exercise Flow​

📚 Prerequisites​

Before starting these exercises, make sure you've read:

🔰 Starter: File Log Reader with Error Handling​

Time: 12 minutes

Build a robust log file reader that handles missing files, malformed data, and empty files gracefully.

Learning Objectives​

  • Open and read files using with statements
  • Handle FileNotFoundError, PermissionError, and generic exceptions
  • Parse structured text data line by line
  • Write cleaned data back to a new file

Starter Code​

# Starter: File Log Reader with Error Handling

import os

# Create a sample log file for testing
sample_log = """2025-01-15 10:30:00 INFO User logged in
2025-01-15 10:31:22 WARN High memory usage
2025-01-15 10:32:45 ERROR Database connection failed
INVALID LINE
2025-01-15 10:35:12 INFO User logged out"""

with open("sample.log", "w") as f:
    f.write(sample_log)

# TODO 1: Read "sample.log" with proper error handling
# TODO 2: Use try-except to handle FileNotFoundError and other exceptions
# TODO 3: Parse each line into (timestamp, level, message) — skip malformed lines
# TODO 4: Count how many lines of each level (INFO, WARN, ERROR) were found
# TODO 5: Write a cleaned version to "cleaned.log"
# TODO 6: Print a summary

# Your code here 👇

Expected Output​

=== LOG ANALYSIS ===
File: sample.log
Total lines: 5
Valid lines: 4
Skipped: 1 (malformed)

Breakdown:
  INFO:  2
  WARN:  1
  ERROR: 1

Cleaned log written to: cleaned.log

⭐ Medium: Algorithm Challenge — Search & Sort​

Time: 22 minutes

Implement classic search and sort algorithms from scratch, then benchmark them against Python's built-in implementations.

Learning Objectives​

  • Implement linear search and binary search
  • Implement bubble sort, selection sort, and merge sort
  • Compare algorithmic performance with timeit
  • Use recursion for divide-and-conquer algorithms
  • Handle edge cases (empty list, single element, duplicates)

Starter Code​

# Medium: Algorithm Challenge — Search & Sort

import time
import random

# --- Search Algorithms ---
def linear_search(arr, target):
    """Return index of target or -1 if not found."""
    # TODO: Implement linear search
    pass

def binary_search(arr, target):
    """Return index of target or -1 if not found. Assumes arr is sorted."""
    # TODO: Implement binary search (recursive or iterative)
    pass

# --- Sort Algorithms ---
def bubble_sort(arr):
    """Sort the list using bubble sort. Return new list."""
    # TODO: Implement bubble sort
    pass

def selection_sort(arr):
    """Sort the list using selection sort. Return new list."""
    # TODO: Implement selection sort
    pass

def merge_sort(arr):
    """Sort the list using merge sort. Return new list."""
    # TODO: Implement merge sort (recursive)
    pass

# --- Benchmarking ---
# TODO: Generate a random list of 1000 integers
# TODO: Time each algorithm and print results
# TODO: Verify correctness by comparing with sorted()

# Your code here 👇

Expected Output​

=== ALGORITHM BENCHMARK ===
List size: 1000 integers (random 0–999)

Search:
  Linear Search (target=500):  0.0023 ms  (found at index 482)
  Binary Search (target=500):  0.0001 ms  (found at index 501)

Sort:
  Bubble Sort:    0.0852 sec  ✓ Correct
  Selection Sort: 0.0421 sec  ✓ Correct
  Merge Sort:     0.0038 sec  ✓ Correct
  Python sort():  0.0001 sec  ✓ Correct

Performance Winner: Python's built-in sort() 🏆

🏆 Hard: Student Database Management System​

Time: 40 minutes

Build a complete student database management system using SQLite, file I/O for CSV import/export, exception handling, and algorithmic operations on the data.

Learning Objectives​

  • Connect to SQLite and execute CRUD operations
  • Import data from CSV files into a database
  • Export query results back to CSV
  • Implement algorithmic operations (search, sort, filter) on database records
  • Handle all edge cases with try-except blocks
  • Build a complete CLI application

Starter Code​

# Hard: Student Database Management System

import sqlite3
import csv
import os

# --- Database Setup ---
def init_db(db_name="students.db"):
    """Create the database and students table if it doesn't exist."""
    # TODO: Connect to SQLite database
    # TODO: Create table: students(id INTEGER PK, name TEXT, age INT, grade TEXT, marks REAL, city TEXT)
    # TODO: Return the connection
    pass

# TODO 1: Implement insert_student(conn, name, age, grade, marks, city)
# TODO 2: Implement import_from_csv(conn, csv_path) — read CSV and insert rows
# TODO 3: Implement search_students(conn, name=None, city=None, min_marks=None)
#   — allow searching by any combination of criteria
# TODO 4: Implement get_top_students(conn, n=5) — return top n by marks
# TODO 5: Implement get_average_by_city(conn) — average marks per city
# TODO 6: Implement export_to_csv(conn, csv_path) — export all records to CSV
# TODO 7: Implement delete_student(conn, student_id) — with confirmation
# TODO 8: Build a CLI menu that ties everything together
# TODO 9: Wrap ALL database operations in try-except blocks

# Your code here 👇

Expected Output​

═══════════════════════════════════════
   STUDENT DATABASE MANAGEMENT SYSTEM
═══════════════════════════════════════

1. Add Student
2. Import from CSV
3. Search Students
4. Top Students
5. Average by City
6. Export to CSV
7. Delete Student
8. Exit
───────────────────────────────────────
Choice: 3

Search Criteria (leave blank to skip):
  Name: Alice
  City:
  Min Marks: 80

Results (2 found):
  ID  Name      Age  Grade  Marks  City
  ──────────────────────────────────────
  101 Alice      17   A+     95.5   Mumbai
  105 Alice M.   16   A      88.0   Delhi
───────────────────────────────────────

Choice: 4

Top 5 Students:
  1. Bob Johnson — 98.5 ⭐
  2. Alice Smith — 95.5
  3. Charlie Lee — 92.0
  4. Diana Patel — 90.5
  5. Eva Torres — 89.0

Choice: 5

Average Marks by City:
  Mumbai:  85.3%
  Delhi:   82.1%
  Chennai: 78.9%
  Bengaluru: 80.5%
───────────────────────────────────────

💡 Tips for Success​

  • Always use with open(...) for file operations — it automatically closes the file even if an error occurs.
  • Be specific with exceptions — catch FileNotFoundError not just Exception. Catching everything hides bugs.
  • Use parameterised queries with SQLite — never use f-strings to build SQL. It prevents SQL injection attacks.
  • Close database connections — use conn.close() or a context manager to avoid locked databases.
  • Remember: Python's built-in sort() uses Timsort — O(n log n) with real-world optimisations. Your hand-crafted sorts are for learning, not production.

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