File Handling Beginner¶

🐍 Core Python Track · Level 1

⏱️ ~3 days 📚 Prerequisite: Data Structures

When you'd use this

Reading, writing and managing files in Python.

Read and write files — load config, parse logs, process CSVs, or persist results to disk, using with open(...) so handles always close.

Reading files¶

Pull text from disk — whole file, all lines, or one line at a time. Prefer line-by-line iteration for large files so you never load the whole thing into memory.

# Always use 'with' — it closes the file automatically
with open("data.txt", "r") as f:
    content = f.read()          # entire file as string

with open("data.txt", "r") as f:
    lines = f.readlines()       # list of lines (with \n)

# Best: iterate line by line (memory efficient)
with open("data.txt", "r") as f:
    for line in f:
        print(line.strip())

Writing files¶

Save data to disk. Use "w" to overwrite, "a" to append (logs, journals), and writelines for a batch of lines.

# Write (overwrites existing)
with open("output.txt", "w") as f:
    f.write("Hello, World!\n")
    f.write("Second line\n")

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

# Write multiple lines
lines = ["line 1\n", "line 2\n", "line 3\n"]
with open("output.txt", "w") as f:
    f.writelines(lines)

pathlib (modern approach)¶

The object-oriented way to handle paths — join with /, read/write in one call, check existence, and glob. Prefer it over os.path string juggling in new code.

from pathlib import Path

# Create path objects
file = Path("data") / "input.txt"

# Read / write
content = file.read_text()
file.write_text("new content")

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

# List directory
for item in Path(".").iterdir():
    print(item.name)

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

Working with CSV¶

Read and write spreadsheet-style tabular data. Use DictReader/DictWriter so rows are dicts keyed by column name — far clearer than positional indexes.

import csv

# Read CSV
with open("data.csv", "r") as f:
    reader = csv.DictReader(f)
    for row in reader:
        print(row["name"], row["score"])

# Write CSV
with open("output.csv", "w", newline="") as f:
    writer = csv.DictWriter(f, fieldnames=["name", "score"])
    writer.writeheader()
    writer.writerow({"name": "Alice", "score": 95})

Working with JSON¶

Serialize Python objects to text and back — the default format for config files and web APIs. Use load/dump for files, loads/dumps for strings.

import json

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

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

# String conversion
json_str = json.dumps({"name": "Alice"})
obj      = json.loads(json_str)

Practice exercises¶

Write a program that counts the number of words in a text file.
Read a CSV file and print only rows where the score is above 80.
Create a simple note-taking app that appends notes to a file.
Write a script that finds all .py files in a directory tree using pathlib.

💬 Discussion

Have a question about this topic? Found an error? Share your thoughts below.