Python File Handling: Read, Write, JSON and CSV

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Part 10 of the Python for Everyone track. Last updated: September 2026.

File I/O in Python boils down to one rule: always use with open(...). Everything else — text vs binary, JSON, CSV, paths — builds on that.

Reading and writing text files

# Writing (overwrites existing content)
with open("notes.txt", "w") as f:
    f.write("Line one\n")
    f.write("Line two\n")

# Appending
with open("notes.txt", "a") as f:
    f.write("Line three\n")

# Reading — three flavors
with open("notes.txt") as f:
    whole = f.read()          # one big string

with open("notes.txt") as f:
    lines = f.readlines()     # list of lines

with open("notes.txt") as f:
    for line in f:            # iterate directly — memory-friendly for big files
        print(line.strip())

The with block closes the file automatically, even if an error occurs. Manual f.close() is legacy style.

Modes cheat sheet

  • "r" — read (default; errors if file missing)
  • "w" — write (creates or overwrites)
  • "a" — append (creates if missing)
  • "rb" / "wb" — binary mode for images, PDFs, etc.
  • Add encoding="utf-8" when working with non-ASCII text

Paths the modern way: pathlib

from pathlib import Path

p = Path("data") / "notes.txt"   # / joins paths — works on every OS
print(p.exists())                # True/False
print(p.name, p.suffix, p.parent)  # notes.txt .txt data
text = p.read_text()             # read whole file in one call
p.write_text("hello")            # write whole file in one call
for f in Path(".").glob("*.py"): # find files by pattern
    print(f)

Prefer pathlib over string-concatenated paths and os.path — it's cleaner and cross-platform.

JSON: Python's native data format

import json

user = {"name": "Ada", "scores": [95, 88]}

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

# Read
with open("user.json") as f:
    loaded = json.load(f)     # back to a dict

# Strings instead of files
s = json.dumps(user)          # dict → string
d = json.loads(s)             # string → dict

Mnemonic: dump/load = files, dumps/loads = strings (the "s" is for string).

CSV files

import csv

# Writing
with open("users.csv", "w", newline="") as f:
    w = csv.DictWriter(f, fieldnames=["name", "age"])
    w.writeheader()
    w.writerow({"name": "Ada", "age": 36})

# Reading
with open("users.csv") as f:
    for row in csv.DictReader(f):   # each row is a dict
        print(row["name"], row["age"])

Always pass newline="" when opening CSV files for writing — otherwise you get blank rows on Windows.

Key takeaways

  • Always with open(...) — never manage close() manually.
  • pathlib for paths; json.dump/load for JSON; csv module with newline="".
  • Iterate large files line-by-line instead of read().

Next in this series: Python Exception Handling: try/except/else/finally and raise.

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