File Processing

What Is File Processing?

A file is a place where information is stored permanently.

Examples include:

• Text files
• CSV files
• JSON files
• Images
• PDF documents
• Log files

Python can interact with many of these files.

File
  ↓
Python opens file
  ↓
Read / Write / Modify
  ↓
Save changes
  ↓
Close file

Opening a File

Python uses the built-in open() function to open a file.

file = open("example.txt")

print(file)

If example.txt exists in the current directory, Python opens it.

However, simply opening a file is not enough. We normally need to read its contents and then close it.

Reading a File

The read() method reads the contents of the file.

file = open("example.txt")

content = file.read()

print(content)

file.close()

Suppose example.txt contains:

Hello Python
Welcome to AI.

The output will be:

Hello Python
Welcome to AI.

Using with open()

The better way to work with files is using with open().

with open("example.txt") as file:

    content = file.read()

    print(content)

Python automatically handles closing the file when the with block finishes.

This is safer and cleaner than manually calling file.close().

File Modes

The second argument of open() tells Python how you want to use the file.

"r"  → Read
"w"  → Write
"a"  → Append
"x"  → Create a new file

The default mode is "r".

with open("example.txt", "r") as file:

    content = file.read()

    print(content)

Writing to a File

Use "w" when you want to write content to a file.

with open("output.txt", "w") as file:

    file.write("Hello Python")

If output.txt does not exist, Python creates it.

If it already exists, "w" replaces its existing contents.

This is an important point:

"w" → replaces existing content

Appending to a File

Use "a" when you want to add content to the end of an existing file.

with open("output.txt", "a") as file:

    file.write("\nNew line")

Unlike "w", append mode does not remove the existing content.

Existing file

Hello Python


After append

Hello Python
New line

Reading Lines

You can read a file line by line.

with open("example.txt") as file:

    for line in file:

        print(line)

This is useful when processing large files because you don't necessarily need to load the entire file into memory at once.

You can also use readlines():

with open("example.txt") as file:

    lines = file.readlines()

print(lines)

File Paths

A file does not always exist in the same directory as your Python program.

You can provide a path.

with open("data/products.txt") as file:

    content = file.read()

    print(content)

You can also use an absolute path, although relative paths are often easier to manage inside a project.

project/
│
├── main.py
│
└── data/
    └── products.txt

File Encoding

Text files have an encoding that determines how characters are stored.

UTF-8 is a common choice for modern applications.

with open(
    "example.txt",
    "r",
    encoding="utf-8"
) as file:

    content = file.read()

    print(content)

Specifying the encoding helps avoid problems when working with different languages and special characters.

Checking if a File Exists

Before processing a file, you may need to check whether it exists.

Python provides the pathlib module for working with paths.

from pathlib import Path


file_path = Path("example.txt")


if file_path.exists():

    print("File exists")

else:

    print("File does not exist")

File exists

Using pathlib

pathlib provides a cleaner way to work with files and directories.

from pathlib import Path


file_path = Path("example.txt")

print(file_path.name)
print(file_path.suffix)
print(file_path.parent)

For example:

example.txt
.txt
.

This becomes especially useful when an AI application needs to process many uploaded files.

Working with Directories

Python can also create directories.

from pathlib import Path


folder = Path("documents")

folder.mkdir(
    exist_ok=True
)

exist_ok=True prevents an error if the directory already exists.

You can then create a file inside it:

file_path = folder / "notes.txt"

file_path.write_text(
    "Python for AI",
    encoding="utf-8"
)

Reading and Writing with pathlib

For simple text files, pathlib can make file processing very clean.

from pathlib import Path


file_path = Path("notes.txt")


file_path.write_text(
    "Learning Python",
    encoding="utf-8"
)


content = file_path.read_text(
    encoding="utf-8"
)


print(content)

Learning Python

Processing CSV Files

CSV files are commonly used for tabular data.

Python provides the built-in csv module.

Suppose products.csv contains:

name,price
Laptop,1200
Phone,800
Tablet,500

We can read it with:

import csv


with open(
    "products.csv",
    "r",
    encoding="utf-8"
) as file:

    reader = csv.DictReader(file)

    for row in reader:

        print(row["name"])
        print(row["price"])

Laptop
1200
Phone
800
Tablet
500

File Processing in AI Applications

File processing becomes much more interesting when building AI applications.

Imagine a user uploads a text document.

User uploads document
        ↓
Python receives file
        ↓
Read file
        ↓
Extract text
        ↓
Clean text
        ↓
Send text to AI model
        ↓
Generate response

For example, an AI application could read a text file containing customer feedback and then send that text to an AI model for summarization.

Processing Large Files

Loading an extremely large file completely into memory can be inefficient.

Instead, process it line by line.

with open(
    "large_file.txt",
    "r",
    encoding="utf-8"
) as file:

    for line in file:

        process(line)

This approach allows Python to process the file incrementally rather than creating one huge string containing the entire file.

Handling File Errors

Files may not exist, may be inaccessible, or may contain unexpected data.

Use try and except when appropriate.

try:

    with open(
        "example.txt",
        "r",
        encoding="utf-8"
    ) as file:

        content = file.read()

        print(content)

except FileNotFoundError:

    print("File not found")

except PermissionError:

    print("Permission denied")

This prevents the entire application from crashing unexpectedly when a file cannot be accessed.

Async and File Processing

This connects directly to the previous Async Python lesson.

Standard Python file operations are synchronous. For many simple applications, that is completely fine.

The important lesson is not to make every file operation asynchronous just because async exists.

Use async where it actually solves a waiting or concurrency problem.

Mini Project — AI Document Reader

Let's build a small document reader that reads a text file and prepares its contents for an AI application.

Create this structure:

project/
│
├── main.py
│
└── documents/
    └── article.txt

Put some text inside article.txt:

Python is a popular programming language.
It is widely used in data science and AI.

Now create main.py:

from pathlib import Path


file_path = Path(
    "documents/article.txt"
)


if not file_path.exists():

    print("Document not found")

else:

    content = file_path.read_text(
        encoding="utf-8"
    )

    print("Document loaded successfully")
    print()
    print(content)

Document loaded successfully

Python is a popular programming language.
It is widely used in data science and AI.

In a real AI application, the next step could be sending content to an AI model for summarization, classification, question answering, or information extraction.

What You Learned

• What file processing means
• How to open files
• How to read files
• How to write files
• How to append data
• How to read files line by line
• File modes
• File paths
• UTF-8 encoding
• Checking whether files exist
• Using pathlib
• Working with directories
• Processing CSV files
• Handling file errors
• Processing large files
• Using files inside AI applications