File Handling & Exceptions in Python: I/O, Errors & Debugging

File Handling in Python

Files store persistent data beyond program execution. Python provides built-in functions to read/write files in text mode (strings) or binary mode (raw bytes).

Key File Operations

1. Opening a File Use open() with mode flags:

   • 'r' (read), 'w' (write, overwrites), 'a' (append), 'r+' (read+write).
   • 'b' for binary (e.g., 'rb' for images).

   file = open("data.txt", "r")  # Opens in read mode
   

   Always close files with file.close() or use with (auto-closes):

   with open("data.txt", "r") as file:
       content = file.read()
   

2. Reading/Writing Data

   • read(): Reads entire file as a string.
   • readline(): Reads one line.
   • readlines(): Returns a list of lines.
   • write()/writelines(): Writes data.

   with open("output.txt", "w") as file:
       file.write("Hello, TU!\n")
   

Binary Files (Images, PDFs)

Use 'rb'/'wb' modes. Example: Copying an image:

with open("input.jpg", "rb") as src, open("output.jpg", "wb") as dst:
    dst.write(src.read())

CSV Files (Common in Data)

Use csv module for structured data:

import csv
with open("data.csv", "r") as file:
    reader = csv.reader(file)
    for row in reader:
        print(row)

Exception Handling

Errors disrupt programs. Python uses try-except blocks to handle exceptions gracefully.

Common Exceptions

Syntax

try:
    risky_operation()
except ExceptionType as e:
    handle_error(e)
else:
    runs_if_no_error()
finally:
    always_runs()

Example: Safe File Read

try:
    with open("data.txt", "r") as file:
        print(file.read())
except FileNotFoundError:
    print("File not found! Using default data.")

MERMAID: Exception Handling Flowchart

flowchart TD
    A["Start"] --> B["Try Block"]
    B -->|"Success"| C["Else Block"]
    B -->|"Error"| D["Except Block"]
    D --> E["Log Error"]
    E --> F["Continue"]
    F --> G["Finally Block"]
    C --> G

Real-World Applications

1. eSewa (Nepal) – Transaction Logs

• Idea Used: File handling ('a' mode) to append transaction records.
• How: Each successful payment writes a log entry to transactions.log:

  with open("transactions.log", "a") as log:
      log.write(f"{user_id}, {amount}, {timestamp}\n")
  

2. Daraz – Order Processing Queue

• Idea Used: File I/O to store pending orders in orders.txt.
• How: Workers read orders line-by-line:

  with open("orders.txt", "r") as file:
      for order in file:
          process_order(order)
  

3. NTC – Network Error Handling

• Idea Used: try-except to handle connection drops.
• How: Retry logic for failed data transfers:

  for _ in range(3):
      try:
          send_data()
          break
      except ConnectionError:
          print("Retrying...")
  

Exam Tip

• File Handling: Always use with to avoid resource leaks. Memorize modes ('r', 'w', 'a').
• Exceptions: Know FileNotFoundError, ValueError, and IndexError. Practice nested try-except.
• Common Pitfalls:
  • Forgetting to close files (use with).
  • Catching generic Exception (prefer specific types).
  • Not handling finally for cleanup (e.g., closing DB connections).

Worked Example: Bank Loan Calculator

Scenario: A bank stores loan data in loans.csv and calculates interest. Task: Read loans, compute interest, and save results.

import csv

def calculate_interest():
    loans = []
    with open("loans.csv", "r") as file:
        reader = csv.DictReader(file)
        for row in reader:
            loans.append({
                "id": row["id"],
                "amount": float(row["amount"]),
                "rate": float(row["rate"])
            })

    results = []
    for loan in loans:
        interest = loan["amount"] * loan["rate"] / 100
        results.append(f"{loan['id']},{interest:.2f}")

    with open("interest_results.csv", "w") as file:
        file.write("id,interest\n")
        file.writelines(f"{r}\n" for r in results)

calculate_interest()

Trace:

MERMAID: File Handling Steps for Loan Data

sequenceDiagram
    participant User
    participant Program
    participant loans_csv
    participant interest_csv

    User->>Program: Run `calculate_interest()`
    Program->>loans_csv: Open (read)
    loans_csv-->>Program: Return rows
    Program->>Program: Calculate interest
    Program->>interest_csv: Open (write)
    Program->>interest_csv: Write headers
    Program->>interest_csv: Write results
    Program->>interest_csv: Close