Python File Handling: Read, Write & Manage Files

Python File Handling: Read, Write, and Manage Files

File handling is the process of working with files stored on a computer. Python provides simple and powerful tools for creating, reading, writing, updating, and managing files.

File handling is useful whenever a program needs to store data permanently instead of keeping it only in memory.

For example, a program can save:

• User information
• Notes
• Student records
• Application logs
• Configuration data
• CSV datasets
• JSON data
• Reports
• Backup files

Common file types include:

Why Use File Handling?

Consider this program:

pythonCopy
1name = input("Enter your name: ")
2
3print("Hello,", name)

The value is stored only while the program is running.

After the program exits, the information is lost.

A file can store the information permanently:

pythonCopy
1name = input("Enter your name: ")
2
3with open("users.txt", "a", encoding="utf-8") as file:
4    file.write(name + "\n")
5
6print("User saved successfully.")

Now the name remains in users.txt even after the program finishes.

This makes file handling an important part of building real-world Python applications.

What Is a File?

A file is a named collection of data stored on a storage device.

For example:

textCopy
1notes.txt

might contain:

textCopy
1Python is easy to learn.
2Python is powerful.
3Python is widely used.

Python can read this information, modify it, or create new files.

Python File Handling Workflow

A typical file-handling operation follows this process:

textCopy
1Open File
2   ↓
3Read / Write / Append
4   ↓
5Process Data
6   ↓
7Close File

The recommended Python approach is to use the with statement:

pythonCopy
1with open("notes.txt", "r", encoding="utf-8") as file:
2    content = file.read()

The with statement automatically closes the file when the block finishes, even if an exception occurs.

Opening a File

Python provides the built-in open() function for opening files.

Syntax:

pythonCopy
1open(file, mode)

Example:

pythonCopy
1file = open("notes.txt", "r", encoding="utf-8")

The arguments are:

• file → File name or path
• mode → How the file should be opened
• encoding → Character encoding used for text

For text files, explicitly specifying UTF-8 is a good practice:

pythonCopy
1with open("notes.txt", "r", encoding="utf-8") as file:
2    print(file.read())

File Modes in Python

Python provides several file modes.

The most commonly used modes are:

textCopy
1r → read
2w → write
3a → append
4x → create

Reading a File

Suppose notes.txt contains:

textCopy
1Python is easy.
2Python is powerful.

You can read the entire file with read():

pythonCopy
1with open("notes.txt", "r", encoding="utf-8") as file:
2    content = file.read()
3
4print(content)

Output:

textCopy
1Python is easy.
2Python is powerful.

The with block automatically closes the file.

Reading a Specific Number of Characters

The read() method can accept a number indicating how many characters to read.

pythonCopy
1with open("notes.txt", "r", encoding="utf-8") as file:
2    content = file.read(10)
3
4print(content)

For example, the output might be:

textCopy
1Python is

The exact result depends on the contents of the file.

Reading One Line

Use readline() to read one line at a time.

pythonCopy
1with open("notes.txt", "r", encoding="utf-8") as file:
2    first_line = file.readline()
3
4print(first_line)

If the file contains:

textCopy
1Python is easy.
2Python is powerful.

the result is approximately:

textCopy
1Python is easy.

The returned line may contain a trailing newline character (\n).

Reading All Lines

The readlines() method returns the lines as a list.

pythonCopy
1with open("notes.txt", "r", encoding="utf-8") as file:
2    lines = file.readlines()
3
4print(lines)

Output:

textCopy
1['Python is easy.\n', 'Python is powerful.\n']

For large files, however, reading every line into a list may consume unnecessary memory.

A better approach is often to iterate over the file:

pythonCopy
1with open("notes.txt", "r", encoding="utf-8") as file:
2    for line in file:
3        print(line.strip())

This processes the file one line at a time.

Writing to a File

The w mode writes data to a file.

pythonCopy
1with open("notes.txt", "w", encoding="utf-8") as file:
2    file.write("Welcome to Python!")

The file will contain:

textCopy
1Welcome to Python!

Be careful with w mode.

If the file already contains data, opening it with "w" normally truncates the existing content.

For example:

pythonCopy
1with open("notes.txt", "w", encoding="utf-8") as file:
2    file.write("New content")

Previous contents are replaced.

Writing Multiple Lines

You can write multiple lines using \n:

pythonCopy
1students = [
2    "Ankit",
3    "Rahul",
4    "Aman",
5]
6
7with open("students.txt", "w", encoding="utf-8") as file:
8    for student in students:
9        file.write(student + "\n")

The file becomes:

textCopy
1Ankit
2Rahul
3Aman

For larger collections of text, writelines() can also be useful:

pythonCopy
1students = [
2    "Ankit\n",
3    "Rahul\n",
4    "Aman\n",
5]
6
7with open("students.txt", "w", encoding="utf-8") as file:
8    file.writelines(students)

Appending to a File

The a mode adds new data to the end of an existing file.

pythonCopy
1with open("notes.txt", "a", encoding="utf-8") as file:
2    file.write("\nLearning Python File Handling.")

Existing content is preserved.

For example:

textCopy
1Welcome to Python!
2
3Learning Python File Handling.

Append mode is useful for:

• Notes applications
• Logs
• Activity records
• History files
• Incrementally stored data

Creating a New File with x

The x mode creates a new file.

pythonCopy
1with open("new_file.txt", "x", encoding="utf-8") as file:
2    file.write("This is a new file.")

If the file already exists, Python raises:

textCopy
1FileExistsError

You can handle this with exception handling:

pythonCopy
1try:
2    with open("new_file.txt", "x", encoding="utf-8") as file:
3        file.write("New file created.")
4except FileExistsError:
5    print("The file already exists.")

Closing a File

When using open() directly, you should close the file:

pythonCopy
1file = open("notes.txt", "r", encoding="utf-8")
2
3try:
4    print(file.read())
5finally:
6    file.close()

However, the preferred approach is:

pythonCopy
1with open("notes.txt", "r", encoding="utf-8") as file:
2    print(file.read())

The with statement handles cleanup automatically.

Why Use the with Statement?

The with statement is recommended because it ensures that the file is properly closed.

Instead of:

pythonCopy
1file = open("notes.txt", "r", encoding="utf-8")
2
3content = file.read()
4
5file.close()

use:

pythonCopy
1with open("notes.txt", "r", encoding="utf-8") as file:
2    content = file.read()

This is cleaner, safer, and easier to maintain.

Using pathlib for File Paths

Python's pathlib module provides a modern way to work with file and directory paths.

pythonCopy
1from pathlib import Path
2
3file_path = Path("notes.txt")
4
5with file_path.open("r", encoding="utf-8") as file:
6    print(file.read())

You can also use convenient methods for simple text files.

Write Text

pythonCopy
1from pathlib import Path
2
3Path("notes.txt").write_text(
4    "Python File Handling",
5    encoding="utf-8",
6)

Read Text

pythonCopy
1from pathlib import Path
2
3content = Path("notes.txt").read_text(encoding="utf-8")
4
5print(content)

Check Whether a File Exists

pythonCopy
1from pathlib import Path
2
3file_path = Path("notes.txt")
4
5if file_path.exists():
6    print("File exists.")
7else:
8    print("File does not exist.")

For modern Python applications, pathlib is often preferable to manually constructing filesystem paths with strings.

Checking Whether a File Exists

You can use pathlib:

pythonCopy
1from pathlib import Path
2
3file_path = Path("data.txt")
4
5if file_path.is_file():
6    print("File exists.")
7else:
8    print("File not found.")

You can also use os.path.exists():

pythonCopy
1import os
2
3if os.path.exists("data.txt"):
4    print("File exists.")
5else:
6    print("File not found.")

For new code, pathlib is often the cleaner option.

Handling Missing Files

If you try to read a file that doesn't exist:

pythonCopy
1with open("data.txt", "r", encoding="utf-8") as file:
2    print(file.read())

Python raises:

textCopy
1FileNotFoundError

You can handle the error:

pythonCopy
1try:
2    with open("data.txt", "r", encoding="utf-8") as file:
3        content = file.read()
4
5    print(content)
6
7except FileNotFoundError:
8    print("The file does not exist.")

This prevents the program from crashing unexpectedly.

Reading a File Safely

A reusable function can make file handling easier:

pythonCopy
1from pathlib import Path
2
3
4def read_text_file(filename):
5    path = Path(filename)
6
7    if not path.is_file():
8        return None
9
10    return path.read_text(encoding="utf-8")
11
12
13content = read_text_file("notes.txt")
14
15if content is None:
16    print("File not found.")
17else:
18    print(content)

Functions like this are useful when the same operation is needed in multiple parts of an application.

Working With CSV Files

CSV stands for Comma-Separated Values.

CSV files are commonly used for tabular data.

Example:

textCopy
1students.csv

textCopy
1Name,Marks
2Ankit,95
3Rahul,88
4Aman,91

Python provides the built-in csv module for working with CSV files.

Writing CSV Data

pythonCopy
1import csv
2
3students = [
4    ["Name", "Marks"],
5    ["Ankit", 95],
6    ["Rahul", 88],
7    ["Aman", 91],
8]
9
10with open("students.csv", "w", newline="", encoding="utf-8") as file:
11    writer = csv.writer(file)
12    writer.writerows(students)

The generated file contains:

textCopy
1Name,Marks
2Ankit,95
3Rahul,88
4Aman,91

Using csv.writer() is preferable to manually joining values with commas because CSV data can contain quoting and escaping rules.

Reading CSV Data

pythonCopy
1import csv
2
3with open("students.csv", "r", newline="", encoding="utf-8") as file:
4    reader = csv.reader(file)
5
6    for row in reader:
7        print(row)

Output:

textCopy
1['Name', 'Marks']
2['Ankit', '95']
3['Rahul', '88']
4['Aman', '91']

Notice that values read by csv.reader() are strings.

If you need marks as numbers, convert them:

pythonCopy
1import csv
2
3with open("students.csv", "r", newline="", encoding="utf-8") as file:
4    reader = csv.DictReader(file)
5
6    for row in reader:
7        name = row["Name"]
8        marks = int(row["Marks"])
9
10        print(name, marks)

Using csv.DictWriter

When CSV columns have meaningful names, DictWriter can make the code easier to understand.

pythonCopy
1import csv
2
3students = [
4    {"name": "Ankit", "marks": 95},
5    {"name": "Rahul", "marks": 88},
6    {"name": "Aman", "marks": 91},
7]
8
9with open("students.csv", "w", newline="", encoding="utf-8") as file:
10    fieldnames = ["name", "marks"]
11
12    writer = csv.DictWriter(file, fieldnames=fieldnames)
13
14    writer.writeheader()
15    writer.writerows(students)

Working With JSON Files

JSON stands for JavaScript Object Notation.

JSON is widely used for storing and exchanging structured data.

Example:

jsonCopy
1{
2    "name": "Ankit",
3    "age": 22,
4    "city": "Delhi"
5}

Python provides the built-in json module for reading and writing JSON.

Writing JSON

pythonCopy
1import json
2
3student = {
4    "name": "Ankit",
5    "age": 22,
6    "city": "Delhi",
7    "skills": ["Python", "Docker", "Git"],
8}
9
10with open("student.json", "w", encoding="utf-8") as file:
11    json.dump(student, file, indent=4)

The generated file will look like:

jsonCopy
1{
2    "name": "Ankit",
3    "age": 22,
4    "city": "Delhi",
5    "skills": [
6        "Python",
7        "Docker",
8        "Git"
9    ]
10}

The indent=4 argument makes the JSON easier for humans to read.

Reading JSON

Use json.load() to read JSON from a file.

pythonCopy
1import json
2
3with open("student.json", "r", encoding="utf-8") as file:
4    student = json.load(file)
5
6print(student["name"])
7print(student["skills"])

Output:

textCopy
1Ankit
2['Python', 'Docker', 'Git']

JSON and Python Data Types

Python automatically converts common JSON-compatible values.

For example:

pythonCopy
1data = {
2    "name": "Ankit",
3    "active": True,
4    "score": None,
5}

can be serialized to JSON.

Binary Files

Not all files contain human-readable text.

Images, PDFs, audio files, and many other formats are binary data.

Binary files should be opened with modes such as:

textCopy
1rb → read binary
2wb → write binary

Example:

pythonCopy
1with open("image.jpg", "rb") as file:
2    data = file.read()
3
4print("Bytes:", len(data))

When copying binary data:

pythonCopy
1with open("image.jpg", "rb") as source:
2    data = source.read()
3
4with open("image_copy.jpg", "wb") as destination:
5    destination.write(data)

For large files, processing data in chunks can reduce memory usage.

Practice Project 1: Notes Application

Let's create a simple command-line notes application.

The application will allow users to:

1. Add a note
2. View notes
3. Exit

pythonCopy
1from pathlib import Path
2
3NOTES_FILE = Path("notes.txt")
4
5
6def add_note():
7    note = input("Enter your note: ").strip()
8
9    if not note:
10        print("Note cannot be empty.")
11        return
12
13    with NOTES_FILE.open("a", encoding="utf-8") as file:
14        file.write(note + "\n")
15
16    print("Note saved successfully.")
17
18
19def view_notes():
20    if not NOTES_FILE.exists():
21        print("No notes found.")
22        return
23
24    content = NOTES_FILE.read_text(encoding="utf-8").strip()
25
26    if not content:
27        print("No notes found.")
28        return
29
30    print("\nYour Notes:")
31    print(content)
32
33
34def main():
35    while True:
36        print("\n1. Add Note")
37        print("2. View Notes")
38        print("3. Exit")
39
40        choice = input("Choose an option: ").strip()
41
42        if choice == "1":
43            add_note()
44        elif choice == "2":
45            view_notes()
46        elif choice == "3":
47            print("Goodbye!")
48            break
49        else:
50            print("Invalid choice. Please try again.")
51
52
53if __name__ == "__main__":
54    main()

This example combines:

• Functions
• pathlib
• File writing
• File reading
• Input validation
• The with statement
• if __name__ == "__main__"

Practice Project 2: Student Database With CSV

A CSV file can be used to store student records.

pythonCopy
1import csv
2from pathlib import Path
3
4STUDENTS_FILE = Path("students.csv")
5
6
7def add_student():
8    name = input("Student name: ").strip()
9
10    try:
11        marks = float(input("Marks: "))
12    except ValueError:
13        print("Marks must be a number.")
14        return
15
16    if not 0 <= marks <= 100:
17        print("Marks must be between 0 and 100.")
18        return
19
20    file_exists = STUDENTS_FILE.exists()
21
22    with STUDENTS_FILE.open(
23        "a",
24        newline="",
25        encoding="utf-8",
26    ) as file:
27        writer = csv.writer(file)
28
29        if not file_exists:
30            writer.writerow(["Name", "Marks"])
31
32        writer.writerow([name, marks])
33
34    print("Student saved successfully.")
35
36
37def view_students():
38    if not STUDENTS_FILE.exists():
39        print("No student records found.")
40        return
41
42    with STUDENTS_FILE.open(
43        "r",
44        newline="",
45        encoding="utf-8",
46    ) as file:
47        reader = csv.DictReader(file)
48
49        for student in reader:
50            print(
51                f"Name: {student['Name']}, "
52                f"Marks: {student['Marks']}"
53            )
54
55
56def main():
57    while True:
58        print("\n1. Add Student")
59        print("2. View Students")
60        print("3. Exit")
61
62        choice = input("Choose: ").strip()
63
64        if choice == "1":
65            add_student()
66        elif choice == "2":
67            view_students()
68        elif choice == "3":
69            break
70        else:
71            print("Invalid choice.")
72
73
74if __name__ == "__main__":
75    main()

This is a more realistic example of persistent data storage.

Practice Project 3: JSON User Profile

JSON is useful when the data has multiple fields or nested structures.

pythonCopy
1import json
2from pathlib import Path
3
4profile = {
5    "name": "Ankit",
6    "age": 22,
7    "skills": [
8        "Python",
9        "Docker",
10        "Git",
11    ],
12    "active": True,
13}
14
15file_path = Path("profile.json")
16
17file_path.write_text(
18    json.dumps(profile, indent=4),
19    encoding="utf-8",
20)
21
22print("Profile saved.")

Read the profile:

pythonCopy
1data = json.loads(
2    file_path.read_text(encoding="utf-8")
3)
4
5print("Name:", data["name"])
6print("Skills:", data["skills"])

For straightforward file-based JSON storage, json.dump() and json.load() are often the clearest choices.

Practice Project 4: File Word Counter

Create a program that counts the number of words in a text file.

pythonCopy
1from pathlib import Path
2
3file_path = Path("notes.txt")
4
5if not file_path.exists():
6    print("File not found.")
7else:
8    text = file_path.read_text(encoding="utf-8")
9    words = text.split()
10
11    print("Word count:", len(words))

The split() method separates the text into whitespace-delimited words.

Practice Project 5: Search for a Word

pythonCopy
1from pathlib import Path
2
3file_path = Path("notes.txt")
4
5word = input("Search for: ").strip()
6
7if not file_path.exists():
8    print("File not found.")
9else:
10    text = file_path.read_text(encoding="utf-8")
11
12    if word.lower() in text.lower():
13        print("Word found.")
14    else:
15        print("Word not found.")

This performs a simple case-insensitive search.

Practice Project 6: File Copy

For a small text file:

pythonCopy
1from pathlib import Path
2
3source = Path("source.txt")
4destination = Path("backup.txt")
5
6if not source.exists():
7    print("Source file not found.")
8else:
9    content = source.read_text(encoding="utf-8")
10    destination.write_text(content, encoding="utf-8")
11
12    print("File copied successfully.")

For arbitrary file types such as images, use binary mode or appropriate filesystem-copy utilities instead of treating the file as text.

Common Exceptions in File Handling

Several exceptions frequently occur when working with files.

You can handle expected errors with try and except.

Example:

pythonCopy
1from pathlib import Path
2
3try:
4    content = Path("notes.txt").read_text(encoding="utf-8")
5    print(content)
6
7except FileNotFoundError:
8    print("The file was not found.")
9
10except PermissionError:
11    print("Permission denied.")
12
13except OSError as error:
14    print("File operation failed:", error)

Avoid catching every exception with a bare except: unless you have a specific reason.

Common Mistakes

Forgetting to Close a File

Less ideal:

pythonCopy
1file = open("notes.txt", "r", encoding="utf-8")
2
3print(file.read())

Preferred:

pythonCopy
1with open("notes.txt", "r", encoding="utf-8") as file:
2    print(file.read())

Using w When You Need a

This overwrites the existing contents:

pythonCopy
1with open("notes.txt", "w", encoding="utf-8") as file:
2    file.write("New note\n")

Use append mode when you want to preserve existing content:

pythonCopy
1with open("notes.txt", "a", encoding="utf-8") as file:
2    file.write("New note\n")

Reading a Missing File

This can raise:

pythonCopy
1with open("data.txt", "r", encoding="utf-8") as file:
2    print(file.read())

If the file does not exist:

textCopy
1FileNotFoundError

Handle it when appropriate:

pythonCopy
1try:
2    with open("data.txt", "r", encoding="utf-8") as file:
3        print(file.read())
4except FileNotFoundError:
5    print("Data file not found.")

Forgetting Encoding

Instead of relying on the environment's default encoding:

pythonCopy
1open("notes.txt", "r")

prefer:

pythonCopy
1open("notes.txt", "r", encoding="utf-8")

This makes text-file behavior more predictable across different systems.

Manually Parsing CSV

Avoid doing this:

pythonCopy
1with open("students.csv", encoding="utf-8") as file:
2    for line in file:
3        name, marks = line.strip().split(",")

Real CSV files can contain commas, quotes, and escaped values.

Use Python's csv module:

pythonCopy
1import csv
2
3with open("students.csv", newline="", encoding="utf-8") as file:
4    reader = csv.reader(file)
5
6    for row in reader:
7        print(row)

File Handling Best Practices

Follow these practices when working with files in Python:

1. Prefer with open(...) for file operations.
2. Specify encoding="utf-8" for text files when appropriate.
3. Use pathlib for modern filesystem path handling.
4. Use csv for CSV files instead of manually splitting strings.
5. Use json for structured JSON data.
6. Use binary modes for binary files.
7. Validate user input before writing data.
8. Handle expected file-related exceptions.
9. Avoid accidentally using w when you need a.
10. Process very large files incrementally rather than loading everything into memory.
11. Keep file paths configurable rather than scattering hard-coded paths throughout a project.
12. Use descriptive filenames and clear directory structures.

Additional Practice Exercises

Exercise 1: Count Words

Read notes.txt and count the number of words.

Expected concept:

pythonCopy
1text.split()

Exercise 2: Count Lines

Count the number of lines in a text file.

Try processing the file line by line rather than loading the entire file into memory.

Exercise 3: Find the Longest Line

Read a text file and find the longest line.

Exercise 4: Copy a Text File

Read source.txt and create a copy named backup.txt.

Exercise 5: Search a File

Ask the user for a word and report whether it appears in notes.txt.

Exercise 6: Student CSV

Create a CSV file containing:

textCopy
1Name
2Age
3Marks

Store at least five students and display students who scored more than 80 marks.

Exercise 7: JSON Configuration

Create a config.json file containing:

jsonCopy
1{
2    "theme": "dark",
3    "language": "en",
4    "notifications": true
5}

Write a Python program that reads and displays the configuration.

Exercise 8: Log File

Create a program that records application events in a file:

textCopy
1Application started
2User logged in
3Data processed
4Application closed

Use append mode so previous log entries are preserved.

Quick File Handling Reference

Key Takeaways

After completing this module, you should understand:

• File handling allows Python programs to store and retrieve persistent data.
• open() is used to open files.
• r reads a file.
• w writes and overwrites a file.
• a appends data.
• x creates a new file.
• with automatically handles file closing.
• read() reads file content.
• readline() reads one line.
• readlines() returns lines as a list.
• Iterating directly over a file is useful for processing large text files efficiently.
• pathlib provides a modern way to work with file paths.
• csv is the recommended standard-library module for CSV data.
• json is useful for structured data.
• Binary files should be handled with binary modes such as rb and wb.
• try and except can handle expected file-related errors.
• Explicit UTF-8 encoding makes text-file handling more predictable.
• File handling is an essential skill for building real-world Python applications.

Once you understand file handling, you can move toward more advanced topics such as databases, APIs, logging, configuration management, data processing, and persistent application storage.