File Handling in Python

File handling is an essential skill for any Python programmer. It allows a program to read data from external sources and write output to files. This is crucial for building real-world applications such as log systems, data processing tools, file-based databases, and configuration managers.

In this chapter, we’ll explore Python’s file I/O capabilities in detail — including how to read from and write to files, handle different file modes, use context managers, deal with exceptions, work with CSV and JSON formats, and follow best practices.

1. Introduction to File Handling

Files are used to store data permanently. Python provides built-in functions to interact with files on disk, enabling persistent storage of data.

Common Use Cases:

• Logging application output
• Reading configurations
• Saving user input
• Importing datasets for processing
• Exporting reports

2. Opening a File

Use the built-in open() function.

Syntax:

file = open("filename", "mode")

File Modes:

Mode	Description
'r'	Read (default), file must exist
'w'	Write, creates or overwrites file
'a'	Append, creates file if not exists
'x'	Create, fails if file exists
'b'	Binary mode
't'	Text mode (default)
'r+'	Read and write

3. Reading from a File

Example:

file = open("data.txt", "r")
content = file.read()
print(content)
file.close()

Other Reading Methods:

file.readline()     # Reads one line
file.readlines()    # Returns list of all lines

Reading with Loop:

with open("data.txt") as file:
    for line in file:
        print(line.strip())

4. Writing to a File

Overwrite Mode:

file = open("output.txt", "w")
file.write("Hello, world!\n")
file.close()

Append Mode:

with open("output.txt", "a") as file:
    file.write("New line\n")

5. Using with Statement (Context Manager)

Automatically handles closing files.

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

Advantages:

• No need to call close()
• Cleaner code
• Prevents memory leaks

6. Working with Binary Files

Used for images, audio, or serialized objects.

with open("image.jpg", "rb") as file:
    data = file.read()

To write binary data:

with open("copy.jpg", "wb") as file:
    file.write(data)

7. Handling File Exceptions

Example:

try:
    with open("file.txt", "r") as f:
        data = f.read()
except FileNotFoundError:
    print("File not found.")
except IOError:
    print("Error reading file.")

Common Exceptions:

• FileNotFoundError
• PermissionError
• IsADirectoryError
• IOError

8. Working with File Paths

Use the os and pathlib modules.

import os
path = os.path.join("folder", "file.txt")

from pathlib import Path
path = Path("folder") / "file.txt"

Check existence:

os.path.exists("file.txt")

9. File Object Methods

Method	Description
.read()	Read entire file
.readline()	Read single line
.readlines()	Read all lines as list
.write()	Write string to file
.writelines()	Write list of strings to file
.seek()	Move file pointer to specific byte
.tell()	Returns current file pointer location
.close()	Closes file

10. File Pointer and seek()

Example:

file = open("data.txt", "r")
print(file.tell())     # Position = 0
file.read(5)
print(file.tell())     # Position = 5
file.seek(0)           # Go back to start
file.close()

11. Working with CSV Files

Python’s csv module simplifies working with comma-separated values.

import csv

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

Writing to CSV:

with open("output.csv", "w", newline='') as f:
    writer = csv.writer(f)
    writer.writerow(["Name", "Age"])
    writer.writerow(["Alice", 25])

Using DictReader and DictWriter:

with open("data.csv") as f:
    reader = csv.DictReader(f)
    for row in reader:
        print(row["Name"])

12. Working with JSON Files

JSON is commonly used for config files, web APIs.

import json

# Reading JSON
with open("data.json", "r") as f:
    data = json.load(f)

# Writing JSON
with open("output.json", "w") as f:
    json.dump(data, f, indent=4)

13. File Handling in Different Encodings

Specify encoding when working with non-ASCII text.

with open("data.txt", "r", encoding="utf-8") as f:
    content = f.read()

Other encodings:

• utf-16
• latin-1
• ascii

14. Real-World Applications

• Log management: Save logs for debugging
• Web scraping: Save extracted data to files
• Configuration: Read settings from JSON/YAML
• Data transformation: Process CSV files for analytics
• Data pipelines: Intermediate file-based storage

15. Best Practices

• Always use with for opening files
• Handle exceptions using try-except
• Validate file paths before opening
• Choose appropriate modes (w, a, x)
• Use newline and encoding arguments for cross-platform compatibility

16. Exercises

1. Write a script that reads a file and prints each line in uppercase.
2. Write a program to copy the contents of one file to another.
3. Parse a CSV file and print each row’s content.
4. Create and write a dictionary to a JSON file.
5. Create a log.txt file and append a new timestamped entry every time the script runs.
6. Write a program that accepts a filename from the user and checks if it exists.

17. Summary

File handling in Python empowers developers to interact with the filesystem, manage data persistently, and build practical applications. From basic file I/O to structured formats like CSV and JSON, mastering file operations is a key skill for any Python programmer.

✅ Next Chapter: Exception Handling – Learn how to gracefully manage errors and prevent crashes in Python applications.