Reading from Files

Python provides built-in functions to read from files. The most common way is using the open() function, followed by reading the file’s content.

  • Opening a File:
  file = open('filename.txt', 'r')  # 'r' for read mode
  • Reading the Entire File:
  content = file.read()
print(content)
file.close()  # Always close the file after reading
  • Reading Line by Line:
  with open('filename.txt', 'r') as file:
    for line in file:
        print(line.strip())  # .strip() removes extra whitespace
Using with open is recommended because it automatically handles file closing.

Writing to Files

You can write data to files using the write() or writelines() methods.

  • Opening a File for Writing:
  file = open('filename.txt', 'w')  # 'w' for write mode, 'a' for append
  • Writing a Single Line:
  file.write("Hello, World!\n")
file.close()
  • Writing Multiple Lines:
  with open('filename.txt', 'w') as file:
    lines = ["First line\n", "Second line\n", "Third line\n"]
    file.writelines(lines)

Working with Different File Formats

Python provides specialized modules for working with various file formats like CSV and JSON.

  • CSV Files:
  import csv

# Reading CSV
with open('data.csv', 'r') as file:
    reader = csv.reader(file)
    for row in reader:
        print(row)

# Writing CSV
with open('output.csv', 'w', newline='') as file:
    writer = csv.writer(file)
    writer.writerow(['Name', 'Age', 'City'])
    writer.writerow(['Alice', 30, 'New York'])
  • JSON Files:
  import json

# Reading JSON
with open('data.json', 'r') as file:
    data = json.load(file)
    print(data)

# Writing JSON
with open('output.json', 'w') as file:
    json.dump({'name': 'Alice', 'age': 30, 'city': 'New York'}, file, indent=4)

Let me know if you need more examples or explanations on any of these topics!

File Modes Reference

Mode Description
r Read (default)
w Write (truncates existing)
a Append
r+ Read and write
rb / wb Binary read/write

pathlib — Modern Path API 

  from pathlib import Path

data_dir = Path('data')
data_dir.mkdir(exist_ok=True)

for csv_file in data_dir.glob('*.csv'):
    print(csv_file.read_text(encoding='utf-8')[:100])

output = Path('output') / 'result.json'
output.write_text('{"status": "ok"}', encoding='utf-8')

Prefer pathlib over string concatenation for cross-platform paths.

Context Manager for Files

The with statement guarantees the file closes even if an exception occurs:

  with open('log.txt', 'a') as f:
    f.write('New entry\n')
# file automatically closed here

Reading Large Files Line by Line 

  with open('huge.log', 'r') as f:
    for line in f:
        if 'ERROR' in line:
            print(line.strip())

This uses constant memory regardless of file size.

Handling Encoding Errors 

  with open('file.txt', 'r', encoding='utf-8', errors='replace') as f:
    content = f.read()

Specify encoding='utf-8' explicitly — never rely on platform defaults.