File I/O: Reading and Writing Files - Python Mastery

Working with Files

Python makes file operations straightforward. The built-in open() function handles text and binary files. Always use the with statement — it automatically closes the file even if an error occurs.

# Basic file operations with context manager (always use 'with')
# Writing a file
with open("hello.txt", "w") as f:
    f.write("Hello, World!\n")
    f.write("Second line\n")

# Reading entire file
with open("hello.txt", "r") as f:
    content = f.read()
    print(content)

# Reading line by line (memory-efficient for large files)
with open("hello.txt", "r") as f:
    for line in f:
        print(line.strip())   # strip() removes the \n

# Reading all lines as a list
with open("hello.txt", "r") as f:
    lines = f.readlines()
    # ["Hello, World!\n", "Second line\n"]

File Modes

Mode	Meaning	Creates?	Truncates?
`"r"`	Read (default)	✗	✗
`"w"`	Write (overwrites)	✓	✓
`"a"`	Append	✓	✗
`"x"`	Exclusive create (fails if exists)	✓	N/A
`"r+"`	Read and write	✗	✗
`"b"`	Binary mode (add to any above)	-	-

# Append to file
with open("log.txt", "a") as f:
    f.write("New log entry\n")

# Binary mode — for images, PDFs, etc.
with open("image.jpg", "rb") as f:
    data = f.read()    # bytes object

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

The pathlib Module

Python 3.4+ includes pathlib for modern, object-oriented path manipulation. Prefer it over os.path.

from pathlib import Path

# Create path objects
p = Path("documents/report.txt")
home = Path.home()           # /home/user or C:\Users\user
cwd = Path.cwd()             # Current directory

# Path operations
p.name          # "report.txt"
p.stem          # "report"
p.suffix        # ".txt"
p.parent        # Path("documents")

# Build paths with / operator
data_dir = Path("data")
csv_file = data_dir / "sales" / "2024.csv"

# Read/write
path = Path("notes.txt")
path.write_text("Hello from pathlib!")
content = path.read_text()

# Check existence
path.exists()
path.is_file()
path.is_dir()

# Create directories
Path("new/nested/directory").mkdir(parents=True, exist_ok=True)

# List files
for f in Path(".").iterdir():
    print(f)

for py_file in Path(".").glob("**/*.py"):   # Recursive
    print(py_file)

# Get file info
stat = path.stat()
stat.st_size      # File size in bytes
stat.st_mtime     # Last modified timestamp

CSV and JSON Files

import csv

# Write CSV
data = [
    ["Name", "Age", "City"],
    ["Alice", 30, "NYC"],
    ["Bob", 25, "LA"],
]
with open("people.csv", "w", newline="") as f:
    writer = csv.writer(f)
    writer.writerows(data)

# Read CSV
with open("people.csv") as f:
    reader = csv.DictReader(f)
    for row in reader:
        print(row["Name"], row["Age"])

# JSON
import json

data = {"name": "Alice", "age": 30, "hobbies": ["python", "chess"]}

# Write JSON
with open("data.json", "w") as f:
    json.dump(data, f, indent=2)

# Read JSON
with open("data.json") as f:
    loaded = json.load(f)

# String conversions
json_str = json.dumps(data)          # Dict → JSON string
parsed = json.loads('{"x": 1}')     # JSON string → dict

Key Takeaways

Always use 'with' statement: auto-closes files, handles exceptions
Iterate lines directly: for line in f is memory-efficient
pathlib over os.path: modern, readable, cross-platform path handling
csv.DictReader: read CSV rows as dicts keyed by column name
json.dump/load for files, json.dumps/loads for strings

Practice Exercises

Write a script that reads a text file and prints word count, line count, and the 10 most common words.
Write a CSV reader that loads a CSV of products (name, price, quantity) and computes total inventory value.
Write a JSON-based simple contact book: save contacts to file, load on startup, add/search/delete contacts.
Use pathlib to find all Python files in a directory tree and count total lines of code.

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