← Computer Programming I

Problem 1: The Expense Calculator

Problem Statement: You are helping a small business owner calculate their daily expenses. They have a text file called expenses.txt where every line contains a category and a dollar amount separated by a comma (e.g., Lunch,12.50).

Write a program that:

  1. Opens and reads expenses.txt.
  2. Extracts the cost from each line.
  3. Calculates the total sum of all expenses.
  4. Counts how many individual transactions (lines) there were.
  5. Prints a summary to the console.

Note: You do not need to write to a new file, just print the results.

Input Data Setup (Run this first to create the file):

data = """Lunch,12.50
Coffee,5.00
Office Supplies,23.75
Taxi,10.00
Coffee,8.25
Dinner,50.00"""

with open("expenses.txt", "w") as f:
    f.write(data)

Expected Output:

--- Expense Report ---
Total Transactions: 6
Total Spent: $109.50
Average Expense: $18.25
Problem 2: The Log Filter

Problem Statement: You have a messy server log file called server_log.txt. It contains general info messages, warnings, and critical errors mixed together. Your job is to extract only the lines containing the word “ERROR” and save them into a separate file called urgent_alerts.txt.

Write a program that:

  1. Reads server_log.txt.
  2. Checks each line to see if it contains the substring "ERROR" (case-sensitive).
  3. If it does, write that line to a new file called urgent_alerts.txt.
  4. At the end, print how many errors were found.

Input Data Setup (Run this first to create the file):

log_data = """[INFO] System started successfully
[WARNING] Memory usage high
[ERROR] Database connection failed
[INFO] User logged in
[ERROR] Payment gateway timeout
[INFO] Scheduled backup complete
[ERROR] Disk space critical"""

with open("server_log.txt", "w") as f:
    f.write(log_data)

Expected Output (Console):

Scan complete. Found 3 errors.
Please check urgent_alerts.txt.

Expected Output (File: urgent_alerts.txt):

[ERROR] Database connection failed
[ERROR] Payment gateway timeout
[ERROR] Disk space critical
Problem 3: The Inventory Restocker

Problem Statement: You manage a warehouse. You have a file called inventory.csv where each line represents a product in the format: Product Name,Current Stock,Minimum Required.

Write a program that:

  1. Reads the inventory.csv file.
  2. Identifies which items are below their minimum required level.
  3. Creates a new file called reorder_list.txt.
  4. Writes the names of the items that need to be reordered, and how many need to be bought to reach the minimum level.

Input Data Setup (Run this first):

# Format: Product, Stock, Minimum
data = """Apples,50,100
Bananas,120,100
Cherries,5,20
Dates,50,50
Eggs,10,24"""

with open("inventory.csv", "w") as f:
    f.write(data)

Expected Logic Example:

  • Apples: Have 50, need 100. (50 < 100). Order 50.
  • Bananas: Have 120, need 100. (120 >= 100). Do nothing.

Expected Output (File: reorder_list.txt):

Item: Apples | Order Amount: 50
Item: Cherries | Order Amount: 15
Item: Eggs | Order Amount: 14
Problem 4: The Formatting Fixer

Problem Statement: You have received a file raw_users.txt containing user signup data. However, the users typed their names in messy ways (weird capitalization, extra spaces) and provided their birth year instead of their age.

Data Format: Full Name - BirthYear

Write a program that:

  1. Reads the file.
  2. Formats the name to be “Title Case” (e.g., “jOhN dOE” becomes “John Doe”).
  3. Calculates their approximate age (assume the current year is 2025).
  4. Writes a clean file clean_profiles.txt in the format: Name: [Name] (Age: [Age]).

Input Data Setup (Run this first):

# Note the messy spacing and casing
data = """  john smith - 1990
SARAH CONNOR - 1984
  kylo REN - 1995
LARA croft - 1992"""

with open("raw_users.txt", "w") as f:
    f.write(data)

Expected Output (File: clean_profiles.txt):

Name: John Smith (Age: 35)
Name: Sarah Connor (Age: 41)
Name: Kylo Ren (Age: 30)
Name: Lara Croft (Age: 33)
Problem 5: The Election Auditor

Problem Statement: You are auditing an election. You have a file called votes.txt. Each line represents a ballot in the format: VoterID:CandidateName.

However, the machine that generated the file was glitchy:

  1. Some lines are incomplete (missing a name or ID).
  2. Some lines have extra whitespace.
  3. You need to count the valid votes for each candidate.

Write a program that:

  1. Reads votes.txt.
  2. Skips invalid lines (where the format isn’t ID:Name).
  3. Counts the votes for each candidate using a dictionary.
  4. Calculates the percentage of the total vote each candidate received.
  5. Writes a results.txt file that lists the candidates, their vote counts, their percentages, and declares a winner.

Input Data Setup:

data = """1001:Alice
1002:Bob
1003:Alice
ERROR_READING_LINE
1004: Charlie
1005:Alice
1006:Bob
1007:   
1008:David"""

with open("votes.txt", "w") as f:
    f.write(data)

Expected Output (File: results.txt):

OFFICIAL ELECTION RESULTS
-------------------------
Alice: 3 votes (42.9%)
Bob: 2 votes (28.6%)
Charlie: 1 votes (14.3%)
David: 1 votes (14.3%)

-------------------------
Total Valid Votes: 7
WINNER: Alice
Problem 6: The Cross-Referencing Text Analyzer

Problem Statement: You are building a tool to analyze the keyword density of a text file, but you need to ignore common “stop words” (like “the”, “is”, “at”) so they don’t clutter the results.

You have two files:

  1. stopwords.txt: A list of words to ignore (one per line).
  2. story.txt: A paragraph of text.

Write a program that:

  1. Loads the stopwords into a list.
  2. Reads the story.txt.
  3. Processes the story word-by-word. You must:
    • Convert to lowercase.
    • Remove punctuation (periods, commas).
    • Ignore the word if it is in your stopword list.
  4. Counts the frequency of the remaining “interesting” words.
  5. Writes the valid words and their counts to analysis.txt.

Input Data Setup:

# File 1: Words to ignore
stops = """the
is
at
on
a
and"""

with open("stopwords.txt", "w") as f:
    f.write(stops)

# File 2: The text to analyze
story = """The cat sat on the mat. 
The cat is a good cat. 
Is the dog on the mat? No, the dog is at the park."""

with open("story.txt", "w") as f:
    f.write(story)

Expected Output (File: analysis.txt):

WORD FREQUENCY REPORT
---------------------
cat: 3
sat: 1
mat: 2
good: 1
dog: 2
no: 1
park: 1
Problem 7: The Multi-Store Sales Consolidator

Problem Statement: You are the regional manager for a chain of three stores. Each store manager sends you a daily sales report as a separate CSV file. Your job is to consolidate all three files into a single master report.

Each store file has the format: Product,UnitsSold,PricePerUnit

Write a program that:

  1. Reads all three store files (store_a.csv, store_b.csv, store_c.csv).
  2. Consolidates the data by calculating:
    • Total Units Sold for each product across all stores.
    • Total Revenue for each product across all stores (Units × Price).
  3. Identifies which store sold the most units overall.
  4. Writes a consolidated report to regional_report.txt.

Hint: You’ll need a dictionary where keys are product names and values are another dictionary (or a list) storing totals.

Input Data Setup (Run this first to create the files):

store_a = """Laptop,5,999.99
Mouse,20,25.00
Keyboard,15,75.00
Monitor,8,300.00"""

store_b = """Laptop,3,999.99
Mouse,35,25.00
Headphones,12,150.00
Keyboard,10,75.00"""

store_c = """Mouse,25,25.00
Monitor,5,300.00
Headphones,8,150.00
Laptop,7,999.99"""

with open("store_a.csv", "w") as f:
    f.write(store_a)

with open("store_b.csv", "w") as f:
    f.write(store_b)

with open("store_c.csv", "w") as f:
    f.write(store_c)

Expected Output (File: regional_report.txt):

============================================
       REGIONAL SALES CONSOLIDATION
============================================

Product          Units Sold    Total Revenue
--------------------------------------------
Laptop           15            $14,999.85
Mouse            80            $2,000.00
Keyboard         25            $1,875.00
Monitor          13            $3,900.00
Headphones       20            $3,000.00

--------------------------------------------
GRAND TOTAL REVENUE: $25,774.85

TOP SELLING STORE: Store B (60 units sold)
============================================

Hints:

  • Create a function to process a single store file and return its data.
  • Use a nested dictionary like: {"Laptop": {"units": 0, "revenue": 0.0}, ...}
  • Track each store’s total units separately to find the top seller.
Problem 8: The Student Grade Processor with Validation

Problem Statement: You are building a grade processing system for a school. The raw input file grades_raw.txt contains student records, but the data is messy and contains various errors that must be handled gracefully.

Data Format: StudentID,Name,Assignment1,Assignment2,Assignment3,Exam

The data has these potential issues:

  • Some lines have missing fields (fewer than 6 columns).
  • Some scores are not valid numbers (typos like “eighty” or empty).
  • Some scores are out of the valid range (scores must be 0-100).
  • Some lines are completely empty.

Write a program that:

  1. Reads grades_raw.txt and validates each line.
  2. For valid students:
    • Calculates their average score (all 4 assessments weighted equally).
    • Assigns a letter grade (A: 90+, B: 80-89, C: 70-79, D: 60-69, F: below 60).
  3. For invalid lines:
    • Logs the line number, the original data, and a description of the error.
  4. Writes two output files:
    • final_grades.txt: Clean list of students with their averages and letter grades.
    • processing_errors.txt: Log of all errors encountered.
  5. Prints a summary to the console showing how many records were processed successfully vs. how many had errors.

Input Data Setup (Run this first to create the file):

data = """S001,Alice Smith,85,90,88,92
S002,Bob Jones,78,82,eighty,75
S003,Charlie Brown,95,91,89,94
S004,Diana Prince,70,65
S005,Eve Wilson,88,105,90,85
S006,Frank Miller,60,58,62,55

S007,Grace Lee,72,78,75,80
S008,Henry Ford,,85,80,78
S009,Ivy Chen,90,88,92,95
S010,Jack Black,45,50,48,52"""

with open("grades_raw.txt", "w") as f:
    f.write(data)

Expected Output (File: final_grades.txt):

FINAL GRADE REPORT
==========================================
ID      Name              Average   Grade
------------------------------------------
S001    Alice Smith       88.8      B
S003    Charlie Brown     92.2      A
S006    Frank Miller      58.8      F
S007    Grace Lee         76.2      C
S009    Ivy Chen          91.2      A
S010    Jack Black        48.8      F
==========================================
Total Students Processed: 6
Class Average: 76.0

Expected Output (File: processing_errors.txt):

PROCESSING ERROR LOG
==========================================
Line 2: S002,Bob Jones,78,82,eighty,75
  -> Error: Invalid score format (non-numeric value)

Line 4: S004,Diana Prince,70,65
  -> Error: Missing fields (expected 6, found 4)

Line 5: S005,Eve Wilson,88,105,90,85
  -> Error: Score out of range (must be 0-100)

Line 7:
  -> Error: Empty line detected

Line 9: S008,Henry Ford,,85,80,78
  -> Error: Invalid score format (empty value)

==========================================
Total Errors: 5

Expected Console Output:

Processing complete!
- Successfully processed: 6 students
- Errors encountered: 5 records
Check 'final_grades.txt' and 'processing_errors.txt' for details.

Hints:

  • Use try/except to catch conversion errors when parsing scores.
  • Check len(parts) after splitting to detect missing fields.
  • Validate each score is between 0 and 100 after successful conversion.
  • Keep track of line numbers using enumerate() or a counter variable.
  • Process the file once, writing to both output files as you go.