11 - File Handling

Variables disappear when a program ends. Files let a program store information for the next run.

A simple picture

A variable is like writing on a classroom whiteboard: it is cleared when the program finishes. A file is like writing in a notebook that can be opened again tomorrow.

program -> write -> file on storage -> read during a later run

Opening a file

file = open("notes.txt", "r", encoding="utf-8")
content = file.read()
file.close()

The encoding makes text handling explicit. Calling close() matters, but the safer approach is with.

The `with` statement

with open("notes.txt", "w", encoding="utf-8") as file:
    file.write("Learn Python\n")

The file closes automatically when the block ends, even when an error occurs.

Important fact: prefer with open(...) because it closes the file automatically. A file that remains open may keep operating-system resources busy and may not finish writing buffered data when expected.

File modes

Mode	Meaning
`"r"`	read; file must exist
`"w"`	write; replaces existing content
`"a"`	append at the end
`"x"`	create; fails if file exists

Be careful with "w": it can erase existing content.

Reading methods

with open("notes.txt", encoding="utf-8") as file:
    all_text = file.read()

with open("notes.txt", encoding="utf-8") as file:
    first_line = file.readline()

with open("notes.txt", encoding="utf-8") as file:
    for line in file:
        print(line.rstrip())

rstrip() removes the line ending for display. Avoid calling .read() on a huge file when line-by-line processing is enough.

Relative paths

open("notes.txt") looks relative to the program’s current working directory, not necessarily the folder containing the .py file. Print the current directory while debugging:

The current working directory is the folder from which Python was started. A path tells Python where a file or folder is located.

from pathlib import Path
print(Path.cwd())

from pathlib import Path borrows the Path tool from Python’s standard library. Imports receive a complete explanation in Chapter 13; for now, type the line exactly as shown.

pathlib.Path is a modern way to work with paths:

from pathlib import Path
path = Path("data") / "notes.txt"
path.parent.mkdir(exist_ok=True)
path.write_text("Hello\n", encoding="utf-8")

CSV basics

CSV stores rows and columns. Use the csv module instead of manually splitting commas when data may contain commas:

CSV means comma-separated values. A CSV-aware tool understands quoted values that themselves contain commas.

import csv

with open("students.csv", newline="", encoding="utf-8") as file:
    for row in csv.DictReader(file):
        print(row["name"], row["marks"])

JSON basics

JSON represents dictionaries, lists, strings, numbers, booleans, and null values:

JSON means JavaScript Object Notation. It is a text format shared by many programming languages. JSON null becomes Python None when loaded.

import json

students = [{"name": "Meera", "marks": 86}]
with open("students.json", "w", encoding="utf-8") as file:
    json.dump(students, file, indent=2)

with open("students.json", encoding="utf-8") as file:
    loaded_students = json.load(file)

Real-world example: expenses

with open("expenses.txt", "a", encoding="utf-8") as file:
    file.write("food,250\n")

total = 0
with open("expenses.txt", encoding="utf-8") as file:
    for line in file:
        category, amount = line.strip().split(",")
        total += float(amount)
print(f"Total: {total:.2f}")

Common mistakes

Using write mode when append mode was intended.
Forgetting encoding="utf-8" for text files.
Assuming a relative path starts beside the script.
Forgetting to handle a missing file.
Storing comma-containing data by manually splitting CSV lines.

Bug Hunter

Bug 1 — write mode erased the file

with open("notes.txt", "w", encoding="utf-8") as file:
    file.write("One more note\n")

The learner wanted to keep old notes and add a new one.

Bug 2 — reading after closing

file = open("notes.txt", encoding="utf-8")
file.close()
content = file.read()

Bug 3 — wrong relative folder

with open("data/marks.txt", encoding="utf-8") as file:
    print(file.read())

The code fails when the data folder does not exist in the current working directory.

Show Bug Hunter fixes

# Bug 1: append instead of replacing.
with open("notes.txt", "a", encoding="utf-8") as file:
    file.write("One more note\n")

# Bug 2: read inside a with block.
with open("notes.txt", encoding="utf-8") as file:
    content = file.read()

# Bug 3: confirm the current folder and create the expected data folder/file.
from pathlib import Path
print(Path.cwd())

Optional deeper look: what does a Python file wrap?

The operating system gives Python a small identifier for an open file, called a file descriptor. Python adds buffering and, for text files, encoding and decoding. Buffering groups many small reads or writes for efficiency. Closing or leaving a with block releases these layers safely.

Practice

Try these problems on this page. Before coding, decide what the file should contain and which mode you need.

Problems

Write three lines to a text file.
Read and print a file line by line.
Count lines and words in a file.
Append a new expense to a file.
Copy one file into another file.
Read a CSV-style file and calculate a total column.
Save a list of students as JSON.
Load JSON and display students above a mark threshold.
Build a file-based notes application.
Build an expense tracker that saves data and calculates a total.

Show hints

Use write mode and include a newline after each line.
Iterate over the file object.
Use splitlines() and split().
Use append mode so old expenses remain.
Read the source, then write the destination.
Split each row and convert the number column.
Use the json module and json.dump().
Load the JSON into Python objects, then filter them.
Decide commands such as add, list, and exit.
Choose one record format and use it consistently.

Show solution ideas

with open(path, "w", encoding="utf-8") as file: file.write(text).
Use for line in file and line.rstrip().
Read the text and count splitlines() and split().
Open with mode "a" and write one record followed by \n.
Use a read block and a separate write block.
Parse the header, then add the numeric field from each row.
json.dump(students, file, indent=2).
students = json.load(file) followed by a loop or filter.
Keep file operations in small functions.
Store each expense with a category and amount, then read and add amounts.

Homework

Create a journal program that appends dated entries to a file and provides a command to display all previous entries.

Checkpoint

Write a program that appends one expense per line and reads the file to calculate the total.