Practical Examples and Use Cases | File Handling: Reading from and Writing to Files | Your First Steps in Python: A Beginner to Intermediate Guide

Now that we've covered the fundamentals of reading from and writing to files in Python, let's dive into some practical examples and common use cases. These scenarios will help solidify your understanding and showcase the real-world power of file handling.

1. Reading Configuration Files

Applications often store their settings and configurations in separate files. This allows for easy modification without altering the core code. We can read these files to load parameters like database credentials, API keys, or application-specific settings.

config.ini
[database]
host = localhost
port = 5432
username = admin

with open('config.ini', 'r') as f:
    for line in f:
        if '[' not in line and '=' in line:
            key, value = line.strip().split('=', 1)
            print(f"Setting: {key}, Value: {value}")

2. Logging Application Events

Logging is crucial for debugging and monitoring applications. We can write messages to a log file, capturing events, errors, or important information as they happen. This creates a historical record of the application's activity.

import datetime

def log_event(message):
    timestamp = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
    with open('app.log', 'a') as f:
        f.write(f'{timestamp} - {message}\n')

log_event('Application started.')
# ... other application logic ...
log_event('User logged in.')

3. Processing Data from CSV Files

Comma Separated Values (CSV) files are a very common format for storing tabular data. Python's built-in csv module makes it incredibly easy to read and write this data.

data.csv
Name,Age,City
Alice,30,New York
Bob,25,Los Angeles

import csv

with open('data.csv', 'r') as f:
    reader = csv.reader(f)
    header = next(reader) # Skip header row
    for row in reader:
        name, age, city = row
        print(f"Name: {name}, Age: {age}, City: {city}")

4. Generating Reports

You can use file writing to generate reports from your application's data. This could be anything from a simple text summary to a more structured report in a format like CSV or even HTML.

sales_data = [
    {'product': 'Laptop', 'quantity': 5, 'price': 1200},
    {'product': 'Keyboard', 'quantity': 10, 'price': 75}
]

with open('sales_report.txt', 'w') as f:
    f.write('Sales Report\n')
    f.write('--------------\n')
    total_revenue = 0
    for item in sales_data:
        revenue = item['quantity'] * item['price']
        f.write(f"Product: {item['product']}, Quantity: {item['quantity']}, Revenue: ${revenue}\n")
        total_revenue += revenue
    f.write(f'\nTotal Revenue: ${total_revenue}\n')

5. Storing and Retrieving User Data

For simpler applications or prototypes, you might store user-specific data directly in text files. This could be game scores, user preferences, or progress trackers.

user_score = 1500

with open('user_progress.txt', 'w') as f:
    f.write(str(user_score))

with open('user_progress.txt', 'r') as f:
    loaded_score = int(f.read())
    print(f'Loaded score: {loaded_score}')

6. Interacting with External Data Sources

Many external services or legacy systems might provide data in simple text formats. Being able to read and parse these files allows your Python programs to interact with a wider range of data sources.

graph TD
    A[External Data Source] --> B{File Transfer}
    B --> C[Python Script]
    C -- Reads/Parses --> D[Application Logic]

These examples cover a range of common scenarios. As you become more comfortable with Python, you'll find even more innovative ways to leverage file handling in your projects.

with open('config.ini', 'r') as f: for line in f: if '[' not in line and '=' in line: key, value = line.strip().split('=', 1) print(f"Setting: {key}, Value: {value}")

import datetime def log_event(message): timestamp = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S') with open('app.log', 'a') as f: f.write(f'{timestamp} - {message}\n') log_event('Application started.') # ... other application logic ... log_event('User logged in.')

import csv with open('data.csv', 'r') as f: reader = csv.reader(f) header = next(reader) # Skip header row for row in reader: name, age, city = row print(f"Name: {name}, Age: {age}, City: {city}")

sales_data = [ {'product': 'Laptop', 'quantity': 5, 'price': 1200}, {'product': 'Keyboard', 'quantity': 10, 'price': 75} ] with open('sales_report.txt', 'w') as f: f.write('Sales Report\n') f.write('--------------\n') total_revenue = 0 for item in sales_data: revenue = item['quantity'] * item['price'] f.write(f"Product: {item['product']}, Quantity: {item['quantity']}, Revenue: ${revenue}\n") total_revenue += revenue f.write(f'\nTotal Revenue: ${total_revenue}\n')

user_score = 1500 with open('user_progress.txt', 'w') as f: f.write(str(user_score)) with open('user_progress.txt', 'r') as f: loaded_score = int(f.read()) print(f'Loaded score: {loaded_score}')