# 🎯 File Reading Demo

# Create a sample file first
sample_text = """Welcome to Python file reading!
This file contains multiple lines.
Each line shows different concepts.
Reading files is essential for data processing.
Line 5: The end of our sample."""

# Save sample content
with open("sample.txt", "w") as file:
    file.write(sample_text)

# Method 1: Read entire file
print("📄 Reading entire file:")
with open("sample.txt", "r") as file:
    content = file.read()
    print(content)
    print(f"Total characters: {len(content)}")

# Method 2: Read line by line (memory efficient)
print("\n📝 Reading line by line:")
with open("sample.txt", "r") as file:
    for line_number, line in enumerate(file, 1):
        print(f"Line {line_number}: {line.strip()}")

# Method 3: Read all lines into a list
print("\n📋 Reading all lines:")
with open("sample.txt", "r") as file:
    lines = file.readlines()
    print(f"File has {len(lines)} lines")
    for i, line in enumerate(lines):
        word_count = len(line.strip().split())
        print(f"Line {i+1}: {word_count} words")

# 📝 Text File Processing Examples

# Create a sample diary file
diary_content = """January 15, 2024
Today I learned Python file reading.
The weather was sunny and warm.
I coded for 2 hours.

January 16, 2024
Worked on file processing project.
File handling is very useful.
Excited to learn more!"""

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

# Example 1: Count words and lines
print("📊 File Statistics:")
with open("diary.txt", "r") as file:
    content = file.read()
    words = content.split()
    lines = content.split('\n')
    
    print(f"   Total words: {len(words)}")
    print(f"   Total lines: {len(lines)}")
    print(f"   Characters: {len(content)}")

# Example 2: Find specific content
print("\n🔍 Search for dates:")
with open("diary.txt", "r") as file:
    for line_num, line in enumerate(file, 1):
        if "2024" in line:
            print(f"   Line {line_num}: {line.strip()}")

# Example 3: Process diary entries
print("\n📖 Extract entries:")
with open("diary.txt", "r") as file:
    current_entry = []
    entries = []
    
    for line in file:
        line = line.strip()
        if line and ("January" in line or "February" in line):
            if current_entry:
                entries.append(current_entry)
            current_entry = [line]
        elif line:
            current_entry.append(line)
    
    if current_entry:
        entries.append(current_entry)
    
    for i, entry in enumerate(entries, 1):
        print(f"   Entry {i}: {entry[0]}")

# 📊 CSV File Processing

# Create sample employee data
csv_content = """Name,Age,City,Job
Alice Johnson,28,New York,Engineer
Bob Smith,34,Los Angeles,Designer
Carol Davis,26,Chicago,Teacher
David Wilson,31,Houston,Analyst"""

with open("employees.csv", "w") as file:
    file.write(csv_content)

print("👥 Processing Employee Data:")
print("-" * 35)

with open("employees.csv", "r") as file:
    # Read header line
    header = file.readline().strip().split(',')
    print(f"📋 Columns: {', '.join(header)}")
    
    # Process data lines
    employees = []
    for line_num, line in enumerate(file, 2):
        if line.strip():  # Skip empty lines
            data = line.strip().split(',')
            if len(data) == len(header):
                employee = dict(zip(header, data))
                employees.append(employee)
            else:
                print(f"⚠️ Line {line_num}: Wrong number of fields")

print(f"\n✅ Loaded {len(employees)} employees:")
for emp in employees:
    print(f"   {emp['Name']} ({emp['Age']}) - {emp['Job']} in {emp['City']}")

# Simple analysis
ages = [int(emp['Age']) for emp in employees]
print(f"\n📈 Average age: {sum(ages) / len(ages):.1f} years")

# 🗂️ Memory-Efficient Large File Processing

# Create a larger sample file
print("📝 Creating sample log file...")
with open("large_log.txt", "w") as file:
    for i in range(1000):
        file.write(f"2024-01-15 10:{i:02d}:30 INFO User {i%10} logged in\n")
        file.write(f"2024-01-15 10:{i:02d}:45 DEBUG Processing request {i}\n")

print("📊 Processing large file efficiently:")

# Method 1: Memory-efficient counting
line_count = 0
error_count = 0
user_logins = {}

with open("large_log.txt", "r") as file:
    for line in file:
        line_count += 1
        
        if "ERROR" in line:
            error_count += 1
        
        if "logged in" in line:
            # Extract user number
            parts = line.split()
            if len(parts) > 4:
                user = parts[4]
                user_logins[user] = user_logins.get(user, 0) + 1

print(f"   📈 Total lines: {line_count}")
print(f"   ❌ Errors found: {error_count}")
print(f"   👤 Unique users: {len(user_logins)}")
print(f"   🔄 Most active user: {max(user_logins.items(), key=lambda x: x[1])}")

# Method 2: Process in chunks
print("\n🔍 Finding specific patterns:")
search_term = "User 5"
matches = []

with open("large_log.txt", "r") as file:
    for line_num, line in enumerate(file, 1):
        if search_term in line:
            matches.append((line_num, line.strip()))
        
        # Stop after finding 5 matches for demo
        if len(matches) >= 5:
            break

print(f"   Found {len(matches)} matches for '{search_term}':")
for line_num, content in matches:
    print(f"   Line {line_num}: {content}")

# ⚙️ Configuration File Processing

# Create a sample config file
config_text = """# My App Configuration
# Database settings
database_host = localhost
database_port = 5432
database_name = myapp

# User interface
theme = dark
language = english
max_items = 50

# Features (true/false)
debug_mode = true
auto_save = false"""

with open("app.config", "w") as file:
    file.write(config_text)

print("⚙️ Loading configuration:")

config = {}
with open("app.config", "r") as file:
    for line_num, line in enumerate(file, 1):
        line = line.strip()
        
        # Skip empty lines and comments
        if not line or line.startswith('#'):
            continue
        
        # Parse key = value pairs
        if '=' in line:
            key, value = line.split('=', 1)
            key = key.strip()
            value = value.strip()
            
            # Convert boolean strings
            if value.lower() == 'true':
                value = True
            elif value.lower() == 'false':
                value = False
            # Convert numbers
            elif value.isdigit():
                value = int(value)
            
            config[key] = value
        else:
            print(f"⚠️ Line {line_num}: Invalid format")

print("📋 Configuration loaded:")
for key, value in config.items():
    print(f"   {key}: {value} ({type(value).__name__})")

import os

# 🛡️ Safe File Reading Examples

def safe_file_reader(filename):
    """Safely read file with comprehensive error handling"""
    
    # Check if file exists
    if not os.path.exists(filename):
        print(f"❌ File '{filename}' not found")
        return None
    
    try:
        with open(filename, "r", encoding="utf-8") as file:
            content = file.read()
            print(f"✅ Successfully read '{filename}' ({len(content)} chars)")
            return content
    
    except PermissionError:
        print(f"🚫 Permission denied: '{filename}'")
    except UnicodeDecodeError:
        print(f"🔤 Encoding error: '{filename}' - try different encoding")
    except Exception as e:
        print(f"❌ Unexpected error: {e}")
    
    return None

# Test safe reading
test_files = ["sample.txt", "missing.txt", "diary.txt"]

print("🔍 Testing file reading:")
for filename in test_files:
    result = safe_file_reader(filename)
    if result:
        lines = len(result.split('\n'))
        print(f"   📊 {filename}: {lines} lines")