File Handling in Python

1. Reading and Writing Text Files

Text files are simple to read and write in Python. Here's how to open, read, and write text files:

Reading a Text File

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

Explanation: The with statement opens the file and automatically closes it after the block. "r" is the mode for reading.

Writing to a Text File

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

Explanation: "w" mode opens the file for writing. If the file exists, it will overwrite the content; otherwise, it creates a new file.

2. Working with CSV Files

CSV files are commonly used for data storage. Python's csv module helps with reading and writing CSV files.

Reading a CSV File

import csv

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

Explanation: csv.reader reads each row as a list of values, making it easy to process CSV data.

Writing to a CSV File

import csv

data = [["Name", "Age"], ["Alice", 30], ["Bob", 25]]

with open("data.csv", "w", newline="") as file:
    writer = csv.writer(file)
    writer.writerows(data)

Explanation: csv.writer writes data as rows in the CSV file. newline="" ensures no extra blank rows.

3. Working with JSON Files

JSON files are popular for storing structured data. Python's json module makes it easy to read and write JSON files.

Reading a JSON File

import json

with open("data.json", "r") as file:
    data = json.load(file)
    print(data)

Explanation: json.load reads and parses JSON data, converting it into Python dictionaries and lists.

Writing to a JSON File

import json

data = {"name": "Alice", "age": 30}

with open("data.json", "w") as file:
    json.dump(data, file, indent=4)

Explanation: json.dump writes Python data to a JSON file. The indent parameter formats the JSON for readability.

4. Using Context Managers

Using with statements (context managers) ensures that files are closed automatically after processing, even if errors occur. This practice is safer and more efficient.

Example

with open("example.txt", "r") as file:
    data = file.read()
    # File is automatically closed after this block

Note: This approach prevents memory leaks and avoids having to manually close files.