Chapter 7: File Handling

📁 Why File Handling?

File handling lets your programs store and retrieve data permanently. Without files, your data disappears when the program ends. With files, you can save settings, store user data, process documents, and much more!

What Can You Do with Files?

📖 Read Data

Load configuration files, read user data, process documents

💾 Save Data

Store user preferences, save game progress, create logs

📊 Process Files

Analyze CSV data, parse JSON, process text files

📝 Generate Files

Create reports, export data, generate documents

Real-World Examples

Where File Handling is Used

Examples of file handling in real applications:

1. Configuration Files
   - Storing app settings (config.json, settings.ini)
   - User preferences and customization

2. Data Storage
   - Saving user accounts and profiles
   - Game save files
   - Application state

3. Logs and Monitoring
   - Error logs (error.log)
   - Access logs (access.log)
   - Debug information

4. Data Processing
   - Reading CSV files (sales_data.csv)
   - Processing JSON APIs
   - Analyzing text documents

5. File Generation
   - Creating reports (monthly_report.pdf)
   - Exporting data (export.xlsx)
   - Generating HTML pages

🔍 How File Operations Work

When your program works with files, here's what happens:

Open: Python asks the operating system to access the file
OS Check: Operating system checks permissions and locates the file
File Descriptor: OS gives Python a "handle" to access the file
Buffering: Data is temporarily stored in memory for efficiency
Read/Write: Your program reads or writes through the buffer
Close: Buffer is flushed, file handle is released

Important: Always close files when you're done! Unclosed files can cause data loss and resource leaks.

🔓 Opening and Closing Files

Before you can read or write a file, you must open it. When you're done, you must close it!

Basic File Operations

The Basic Pattern

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⚠️ Important: The Problem with Manual Close

# What if an error happens?
file = open("data.txt", "r")
content = file.read()
# ... some code that might raise an error ...
file.close()  # This might NEVER execute if there's an error!

# Better approach (we'll learn this next!):
with open("data.txt", "r") as file:
    content = file.read()
# File automatically closes, even if there's an error!

File Paths - Where is Your File?

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📂 Understanding File Paths

Path Type	Example	Meaning
Absolute (Windows)	`C:\\Users\\name\\file.txt`	Full path from drive letter
Absolute (Mac/Linux)	`/home/user/file.txt`	Full path from root /
Relative (current)	`file.txt`	File in current directory
Relative (subfolder)	`data/file.txt`	File in data subfolder
Relative (parent)	`../file.txt`	File in parent directory

📖 Reading Files

There are several ways to read file content, each useful for different situations!

Method 1: read() - Read Entire File

Output will appear here...

💡 When to use read()

Good for: Small files, when you need all content at once

Bad for: Very large files (loads everything into memory!)

Method 2: readline() - Read One Line at a Time

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Method 3: readlines() - Read All Lines as a List

Output will appear here...

Method 4: Iterating Over File Object (Best for Large Files!)

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📊 Comparing Read Methods

Method	Returns	Use When
`read()`	Entire file as string	Small files, need all content
`readline()`	One line as string	Processing one line at a time
`readlines()`	List of lines	Need all lines in a list
`for line in file`	Each line (iteration)	Large files, memory efficient ⭐

✍️ Writing to Files

Writing to files lets you save data, create logs, generate reports, and more!

Basic Writing

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writelines() - Write Multiple Lines

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print() to Files - The Easy Way!

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🔧 File Modes - How to Open Files

The mode parameter tells Python how you want to use the file!

r

Read Mode

Read only. File must exist

open("file.txt", "r")

w

Write Mode

Write. Creates new or overwrites existing

open("file.txt", "w")

a

Append Mode

Append. Adds to end of file

open("file.txt", "a")

x

Exclusive Create

Create. Fails if file exists

open("file.txt", "x")

Understanding File Modes

# Mode: 'w' - Write (overwrites existing file!)
with open("test.txt", "w") as f:
    f.write("First write\n")

# Write again - OVERWRITES previous content!
with open("test.txt", "w") as f:
    f.write("Second write\n")

with open("test.txt", "r") as f:
    print("After 'w' mode:")
    print(f.read())  # Only shows "Second write"

# Mode: 'a' - Append (adds to existing file)
with open("test.txt", "a") as f:
    f.write("Appended line 1\n")
    f.write("Appended line 2\n")

with open("test.txt", "r") as f:
    print("\nAfter 'a' mode:")
    print(f.read())

# Mode: 'r+' - Read and Write
with open("test.txt", "r+") as f:
    content = f.read()  # Read first
    f.write("Added with r+\n")  # Then write

with open("test.txt", "r") as f:
    print("\nAfter 'r+' mode:")
    print(f.read())

# Mode: 'x' - Exclusive create (fails if exists)
try:
    with open("brand_new.txt", "x") as f:
        f.write("Created successfully!\n")
    print("\nCreated brand_new.txt")
except FileExistsError:
    print("\nFile already exists! 'x' mode prevents overwriting.")

Output will appear here...

📋 Complete File Modes Reference

Mode	Description	If File Doesn't Exist	If File Exists
`'r'`	Read only (default)	Error	Opens for reading
`'w'`	Write only	Creates new file	⚠️ Overwrites!
`'a'`	Append only	Creates new file	Appends to end
`'x'`	Exclusive create	Creates new file	Error!
`'r+'`	Read and write	Error	Opens for read/write
`'w+'`	Write and read	Creates new file	⚠️ Overwrites!
`'a+'`	Append and read	Creates new file	Appends to end

💡 Text vs Binary Mode:

't' - Text mode (default): 'r' = 'rt'
'b' - Binary mode: 'rb', 'wb' for images, audio, etc.

🔐 The 'with' Statement - Automatic Cleanup!

The 'with' statement is the Pythonic way to work with files! It automatically closes the file when you're done, even if an error occurs. This is called a context manager.

Why Use 'with'?

The Old Way vs The Better Way

# BAD: Manual open/close
# file = open("data.txt", "w")
# file.write("Some data")
# # If error happens here, file never closes!
# file.close()

# GOOD: Using 'with'
with open("data.txt", "w") as file:
    file.write("Some data")
# File automatically closes here!

print("File closed automatically!")

# Verify file is closed
with open("data.txt", "w") as file:
    print("Is file closed?", file.closed)  # False
print("Is file closed now?", file.closed)  # True!

# Multiple files with 'with'
with open("file1.txt", "w") as f1, open("file2.txt", "w") as f2:
    f1.write("Content for file 1\n")
    f2.write("Content for file 2\n")
# Both files automatically closed!

print("\nBoth files created and closed!")

# Even if an error happens, file closes!
try:
    with open("test_error.txt", "w") as file:
        file.write("Before error\n")
        # Simulate an error
        # raise Exception("Oops!")
        file.write("After error\n")
except Exception as e:
    print(f"Error occurred: {e}")
finally:
    print("File still closed properly:", file.closed)

Output will appear here...

🔍 How 'with' Works

The 'with' statement uses special methods called __enter__ and __exit__:

with open("file.txt", "w") as file:
    file.write("Hello")

# Equivalent to:
file = open("file.txt", "w")
try:
    # __enter__ method is called
    file.write("Hello")
finally:
    # __exit__ method is called (closes file)
    file.close()

# Benefits:
# 1. Automatic cleanup
# 2. Cleaner code
# 3. Exception safe
# 4. No forgetting to close!

💡 Always Use 'with' for Files!

Automatic closing: No need to remember file.close()
Exception safe: File closes even if errors occur
Cleaner code: Less boilerplate, more readable
Resource management: Prevents resource leaks

Rule of thumb: If you're not using 'with', you're probably doing it wrong!

📊 Working with CSV Files

CSV (Comma-Separated Values) is a common format for storing tabular data. Think of it like a simple spreadsheet where values are separated by commas!

Manual CSV Handling

# Writing CSV manually
with open("students.csv", "w") as file:
    # Write header
    file.write("Name,Age,Grade,City\n")
    # Write data rows
    file.write("Krishna,25,A,Mumbai\n")
    file.write("Rama,30,B,Delhi\n")
    file.write("Sita,22,A,Bangalore\n")

print("CSV file created!")

# Reading CSV manually
print("\n=== Reading CSV ===")
with open("students.csv", "r") as file:
    # Read header
    header = file.readline().strip()
    print("Header:", header)
    print()

# Read data rows
    for line in file:
        line = line.strip()
        name, age, grade, city = line.split(",")
        print(f"Name: {name}, Age: {age}, Grade: {grade}, City: {city}")

# Parse into list of dictionaries
students = []
with open("students.csv", "r") as file:
    header = file.readline().strip().split(",")

for line in file:
        values = line.strip().split(",")
        student = dict(zip(header, values))
        students.append(student)

print("\n=== As List of Dicts ===")
for student in students:
    print(student)

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Using the csv Module (Better Way!)

import csv

# Writing CSV with csv module
with open("products.csv", "w", newline='') as file:
    writer = csv.writer(file)

# Write header
    writer.writerow(["Product", "Price", "Quantity"])

# Write data rows
    writer.writerow(["Apple", 1.99, 50])
    writer.writerow(["Banana", 0.99, 100])
    writer.writerow(["Cherry", 2.99, 30])

print("CSV created with csv module!")

# Reading CSV with csv module
print("\n=== Reading with csv.reader ===")
with open("products.csv", "r") as file:
    reader = csv.reader(file)

# Read header
    header = next(reader)
    print("Header:", header)

# Read rows
    for row in reader:
        product, price, quantity = row
        print(f"{product}: ${price} (Stock: {quantity})")

# Using DictReader (even better!)
print("\n=== Reading with DictReader ===")
with open("products.csv", "r") as file:
    reader = csv.DictReader(file)

for row in reader:
        print(f"{row['Product']}: ${row['Price']} (Stock: {row['Quantity']})")

# Writing with DictWriter
data = [
    {"Name": "Alice", "Age": 28, "City": "NYC"},
    {"Name": "Bob", "Age": 34, "City": "LA"},
    {"Name": "Charlie", "Age": 22, "City": "Chicago"}
]

with open("people.csv", "w", newline='') as file:
    fieldnames = ["Name", "Age", "City"]
    writer = csv.DictWriter(file, fieldnames=fieldnames)

writer.writeheader()
    writer.writerows(data)

print("\nPeople CSV created!")

Output will appear here...

🔗 Working with JSON Files

JSON (JavaScript Object Notation) is a popular format for storing and exchanging data. It's similar to Python dictionaries and lists!

JSON Basics

import json

# Python data
student = {
    "name": "Krishna",
    "age": 25,
    "grades": [85, 90, 95],
    "is_active": True,
    "address": {
        "city": "Mumbai",
        "zip": "400001"
    }
}

# Write JSON to file
with open("student.json", "w") as file:
    json.dump(student, file, indent=4)  # indent=4 makes it readable

print("JSON file created!")

# Read JSON from file
with open("student.json", "r") as file:
    loaded_student = json.load(file)

print("\n=== Loaded from JSON ===")
print(loaded_student)
print(f"Type: {type(loaded_student)}")
print(f"Name: {loaded_student['name']}")
print(f"Grades: {loaded_student['grades']}")

# Convert to JSON string (without file)
json_string = json.dumps(student, indent=2)
print("\n=== As JSON String ===")
print(json_string)

# Convert from JSON string
parsed = json.loads(json_string)
print("\n=== Parsed from String ===")
print(parsed)

# Write list of objects to JSON
students = [
    {"name": "Krishna", "age": 25, "grade": "A"},
    {"name": "Rama", "age": 30, "grade": "B"},
    {"name": "Sita", "age": 22, "grade": "A"}
]

with open("all_students.json", "w") as file:
    json.dump(students, file, indent=2)

print("\nList of students saved to JSON!")

Output will appear here...

🔄 Python ↔ JSON Type Mapping

Python	JSON
dict	object
list, tuple	array
str	string
int, float	number
True	true
False	false
None	null

💡 JSON Methods Quick Reference

# To File
json.dump(data, file)    # Write Python object to file
json.load(file)          # Read JSON from file to Python object

# To String
json.dumps(data)         # Convert Python object to JSON string
json.loads(json_string)  # Convert JSON string to Python object

# Common parameters:
indent=4      # Pretty print with indentation
sort_keys=True  # Sort dictionary keys
ensure_ascii=False  # Allow Unicode characters

📺 Video Resources

Watch these videos to reinforce your understanding of file handling:

🤖 AI Learning Prompts

Use these prompts with AI assistants to deepen your understanding:

Understanding File Basics

I'm learning about file handling in Python. Please help me understand:

1. What happens behind the scenes when I open, read, and close a file?
2. Why is it important to close files? What happens if I don't?
3. Explain the difference between text mode and binary mode
4. What's the difference between absolute and relative file paths?
5. Show me 5 common mistakes beginners make with files

Use simple explanations and examples!

Mastering File Operations

Help me master file reading and writing:

1. When should I use read() vs readline() vs readlines() vs iteration?
2. Show me 10 different examples of reading files
3. Explain the difference between write() and writelines()
4. How do I handle large files that don't fit in memory?
5. Give me practice exercises for each reading method

Include complete working examples!

Working with Data Files

I want to learn to work with CSV and JSON files:

1. Show me how to read and write CSV files step by step
2. Explain the csv module and DictReader/DictWriter
3. How do I work with JSON data in Python?
4. When should I use CSV vs JSON?
5. Create a mini-project that reads CSV, processes it, and writes JSON

Make it practical with real-world examples!

💡 Tips for Using These Prompts:

Practice with real files: Create actual files and work with them
Handle errors: Ask about try-except with files
Build projects: Request file-based mini-projects
Learn pathlib: Ask about the modern pathlib module

✏️ Practice Exercises

File Safety Reminder:

⚠️ Be careful when writing files! Mode 'w' overwrites existing files. Always use 'x' if you don't want to overwrite, or check if file exists first.

Part 1: Guided Exercises

Guided Exercise 1: Log File Creator

What You'll Learn: How to append to files and create logs.

Time: 15 minutes

Create a Simple Logging System

Output will appear here...

Guided Exercise 2: Student Grade Manager

What You'll Learn: Working with CSV files to store structured data.

Time: 20 minutes

Create a Grade Management System

import csv

# Student data
students = [
    {"name": "Krishna", "math": 85, "science": 90, "english": 88},
    {"name": "Rama", "math": 92, "science": 88, "english": 90},
    {"name": "Sita", "math": 95, "science": 95, "english": 92}
]

# Write to CSV
with open("grades.csv", "w", newline='') as file:
    fieldnames = ["name", "math", "science", "english", "average"]
    writer = csv.DictWriter(file, fieldnames=fieldnames)

writer.writeheader()

for student in students:
        # Calculate average
        avg = (student["math"] + student["science"] + student["english"]) / 3
        student["average"] = round(avg, 2)
        writer.writerow(student)

print("Grades saved to CSV!")

# Read and display
print("\n=== Student Grades ===")
with open("grades.csv", "r") as file:
    reader = csv.DictReader(file)

print(f"{'Name':<10} {'Math':>6} {'Science':>8} {'English':>8} {'Average':>8}")
    print("=" * 52)

for row in reader:
        print(f"{row['name']:<10} {row['math']:>6} {row['science']:>8} "
              f"{row['english']:>8} {row['average']:>8}")

Output will appear here...

Part 2: Independent Practice

Challenge 1: To-Do List Manager

Difficulty: Medium | Time: 25 minutes

Task: Create a to-do list program that:

Saves tasks to a file (one task per line)
Can add new tasks
Can display all tasks
Can mark tasks as complete (delete from file)

Output will appear here...

# To-Do List Manager Solution

def add_task(task):
    """Add a new task to the file"""
    with open("todo.txt", "a") as file:
        file.write(task + "\n")
    print(f"Added: {task}")

def show_tasks():
    """Display all tasks"""
    try:
        with open("todo.txt", "r") as file:
            tasks = file.readlines()
            if tasks:
                print("\n=== To-Do List ===")
                for i, task in enumerate(tasks, 1):
                    print(f"{i}. {task.strip()}")
            else:
                print("No tasks yet!")
    except FileNotFoundError:
        print("No tasks yet!")

def complete_task(task_num):
    """Mark task as complete (remove it)"""
    try:
        with open("todo.txt", "r") as file:
            tasks = file.readlines()

        if 1 <= task_num <= len(tasks):
            completed = tasks.pop(task_num - 1)
            with open("todo.txt", "w") as file:
                file.writelines(tasks)
            print(f"Completed: {completed.strip()}")
        else:
            print("Invalid task number!")
    except FileNotFoundError:
        print("No tasks yet!")

# Test the system
add_task("Buy groceries")
add_task("Finish homework")
add_task("Call mom")
show_tasks()
complete_task(2)
show_tasks()

🎉 Congratulations!

You've completed Chapter 7 and the entire Python basics course! You now know:

How to read and write files
Different file modes and when to use them
The importance of using 'with' statement
How to work with CSV and JSON files
File path handling

You're now ready to build real Python applications! Keep practicing and building projects to solidify your skills.

🎯 Knowledge Check

Test your understanding of file handling concepts!

🎓 Congratulations on Completing This Chapter!

You've mastered file handling - a critical skill for real-world Python programming! You can now read data from files, write results to files, and work with common data formats like CSV and JSON. This opens up endless possibilities for creating practical applications!

File Handling

📁 Why File Handling?

What Can You Do with Files?

📖 Read Data

💾 Save Data

📊 Process Files

📝 Generate Files

Real-World Examples

Where File Handling is Used

🔍 How File Operations Work

🔓 Opening and Closing Files

Basic File Operations

The Basic Pattern

⚠️ Important: The Problem with Manual Close

File Paths - Where is Your File?

📂 Understanding File Paths

📖 Reading Files

Method 1: read() - Read Entire File

💡 When to use read()

Method 2: readline() - Read One Line at a Time

Method 3: readlines() - Read All Lines as a List

Method 4: Iterating Over File Object (Best for Large Files!)

📊 Comparing Read Methods

✍️ Writing to Files

Basic Writing

writelines() - Write Multiple Lines

print() to Files - The Easy Way!

🔧 File Modes - How to Open Files

Read Mode

Write Mode

Append Mode

Exclusive Create

Understanding File Modes

📋 Complete File Modes Reference

🔐 The 'with' Statement - Automatic Cleanup!

Why Use 'with'?

The Old Way vs The Better Way

🔍 How 'with' Works

💡 Always Use 'with' for Files!

📊 Working with CSV Files

Manual CSV Handling

Using the csv Module (Better Way!)

🔗 Working with JSON Files

JSON Basics

🔄 Python ↔ JSON Type Mapping

💡 JSON Methods Quick Reference

📺 Video Resources

Python File Handling

Working with CSV and JSON

Python Context Managers

🤖 AI Learning Prompts

Understanding File Basics

Mastering File Operations

Working with Data Files

💡 Tips for Using These Prompts:

✏️ Practice Exercises

File Safety Reminder:

Part 1: Guided Exercises

Guided Exercise 1: Log File Creator

Create a Simple Logging System

Guided Exercise 2: Student Grade Manager

Create a Grade Management System

Part 2: Independent Practice

Challenge 1: To-Do List Manager

🎉 Congratulations!

🎯 Knowledge Check

Quiz Results

🎓 Congratulations on Completing This Chapter!