Why use with open(...) as f?

The file is closed automatically, even on errors

Python Files – vitalstack.co.in

Programs often need to keep data after they stop: logs, settings, reports, exported spreadsheets. Python makes reading and writing files simple. In this lesson you’ll work with text files and CSV files, the format every spreadsheet program understands.

Writing a file#

with open("notes.txt", "w", encoding="utf-8") as f:
    f.write("First line\n")
    f.write("Second line\n")

print("Saved.")

open(filename, mode) opens a file and returns a file object.
Mode "w" means write: it creates the file, or erases it if it already exists.
\n adds a line break; write doesn’t add one for you.
encoding="utf-8" makes sure all characters (₹, é, Hindi, emoji) are saved correctly on every operating system.

Why `with`?#

with automatically closes the file when the block ends, even if an error happens. An unclosed file may not have all its data saved, and the operating system can run out of file handles. Always use with for files.

Reading a file#

with open("notes.txt", "w", encoding="utf-8") as f:
    f.write("First line\nSecond line\nThird line\n")

with open("notes.txt", encoding="utf-8") as f:
    content = f.read()           # the whole file as one string

print(content)

Mode "r" (read) is the default.

Line by line#

For big files, read one line at a time instead of loading everything into memory:

with open("notes.txt", "w", encoding="utf-8") as f:
    f.write("apple\nbanana\n\ncherry\n")

with open("notes.txt", encoding="utf-8") as f:
    for number, line in enumerate(f, start=1):
        line = line.strip()          # remove the \n at the end
        if not line:
            continue                 # skip empty lines
        print(number, line)

Each line includes its \n, so .strip() it. You can also get a list of lines with f.read().splitlines().

Appending#

Mode "a" adds to the end of the file without erasing it. Perfect for logs:

from datetime import datetime

def log(message):
    with open("app.log", "a", encoding="utf-8") as f:
        f.write(f"{datetime.now():%Y-%m-%d %H:%M:%S} {message}\n")

log("App started")
log("User signed in")

with open("app.log", encoding="utf-8") as f:
    print(f.read())

File modes#

Mode	Meaning
`"r"`	Read (default); error if the file doesn’t exist
`"w"`	Write; creates or overwrites
`"a"`	Append; creates or adds to the end
`"x"`	Create; error if the file already exists
`"rb"`, `"wb"`	Read/write binary data (images, PDFs)

Be careful with "w": opening an existing file in write mode deletes its contents immediately.

Handling missing files#

try:
    with open("does_not_exist.txt", encoding="utf-8") as f:
        print(f.read())
except FileNotFoundError:
    print("File not found. Check the name and folder.")

You’ll learn try/except fully in the next lesson.

pathlib: the modern way to handle paths#

from pathlib import Path

reports = Path("reports")
reports.mkdir(exist_ok=True)               # create the folder if needed

file = reports / "summary.txt"             # join paths with /
file.write_text("Sales: ₹12,400\n", encoding="utf-8")
print(file.read_text(encoding="utf-8"))

print(file.exists(), file.name, file.stem, file.suffix)
print(file.resolve())                       # the full absolute path

for txt in reports.glob("*.txt"):           # find files by pattern
    print("Found:", txt)

Path works on Windows, macOS and Linux without worrying about \ vs /. For small files, read_text and write_text are a one-line alternative to open.

Where is the file?#

Relative paths like "notes.txt" are relative to the current working directory: the folder you ran Python from, which isn’t always where the script lives. To use files next to your script:

from pathlib import Path
HERE = Path(__file__).parent
data_file = HERE / "data.txt"

CSV files#

CSV (comma-separated values) is the simplest spreadsheet format. Excel and Google Sheets can open and save it. Use the csv module rather than splitting on commas yourself, because values can contain commas inside quotes.

Writing CSV#

import csv

products = [
    {"name": "Notebook", "price": 120, "stock": 50},
    {"name": "Pen set", "price": 250, "stock": 30},
    {"name": "Backpack, large", "price": 1899, "stock": 12},
]

with open("products.csv", "w", newline="", encoding="utf-8") as f:
    writer = csv.DictWriter(f, fieldnames=["name", "price", "stock"])
    writer.writeheader()
    writer.writerows(products)

print(open("products.csv", encoding="utf-8").read())

Note newline="", which the csv module needs to avoid blank lines on Windows. “Backpack, large” is automatically quoted because it contains a comma.

Reading CSV#

import csv

with open("products.csv", "w", newline="", encoding="utf-8") as f:
    f.write("name,price,stock\nNotebook,120,50\nPen set,250,30\n\"Backpack, large\",1899,12\n")

with open("products.csv", newline="", encoding="utf-8") as f:
    reader = csv.DictReader(f)
    total_value = 0
    for row in reader:
        value = int(row["price"]) * int(row["stock"])
        total_value += value
        print(f"{row['name']:<16} ₹{value:>7,}")

print(f"Inventory value: ₹{total_value:,}")

DictReader gives each row as a dictionary keyed by the header row. All values are strings, so convert numbers with int() or float().

Reading files in other encodings#

If you get a UnicodeDecodeError, the file was saved with a different encoding. Files from older Windows programs are often "cp1252"; Excel’s “CSV UTF-8” format uses "utf-8-sig". Try open(name, encoding="utf-8-sig").

Common mistakes#

**Forgetting with**, leaving files open.
**Using "w" when you meant "a"**, erasing data.
**Forgetting \n** when writing lines.
Not stripping lines when reading, leaving \n in your data.
Treating CSV values as numbers without converting.
Wrong working directory, so the file “isn’t found” even though it exists.

Exercise#

Write a program that saves five of your favourite films to films.txt, one per line, then reads them back with numbers.
Add a “journal” function that appends today’s date and a message to journal.txt.
Count the lines, words and characters in a text file.
Write a CSV of three students with name and score, then read it and print the average score.
Use pathlib to list every .txt file in a folder with its size.

Summary#

with open(path, mode, encoding="utf-8") as f: opens files safely; they close automatically.
"r" reads, "w" overwrites, "a" appends; loop over a file to read line by line.
pathlib.Path builds paths and reads/writes small files easily.
The csv module (DictReader, DictWriter) handles spreadsheets correctly; convert values from strings.

Next, you’ll handle errors gracefully with try and except.

Python Files