Data Management With Python, SQLite, and SQLAlchemy

In this tutorial, you’ll learn how to use:

1⃣ Flat files for data storage
🔢 SQL to improve access to persistent data
🔢 SQLite for data storage
🔢 SQLAlchemy to work with data as Python objects

Enroll Free: https://realpython.com/python-sqlite-sqlalchemy/

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Exploring pathlib for Working with Paths!
Many projects still use os.path for path operations: join, dirname, exists, and more. It works, but the code quickly becomes cluttered with string manipulations and harder to read — especially when there are many paths being actively combined.

Since Python 3.4, there's pathlib — an object-oriented API for working with files and directories.

Importing the module is simple:

from pathlib import Path

You can create a path like any regular object:

path = Path("data/users.json")

When working with Path and the / operator, the correct separators for the current OS are used automatically. This keeps the code portable between Linux, macOS, and Windows without extra checks.

If you need an absolute path, use resolve():

print(path.resolve())

Very often when working with files, you need to check if a path exists:

if path.exists():
    print("File found")

Pathlib also lets you quickly determine the type of file system object:

path.is_file()
path.is_dir()

The Path object has convenient properties for getting path parts. This eliminates manual string parsing and working with split().

print(path.name)    # users.json
print(path.stem)    # users
print(path.suffix)  # .json
print(path.parent)  # data

For joining paths, the / operator is used, which looks noticeably cleaner and is easier to read compared to os.path.join:

base = Path("logs")
file_path = base / "2026" / "app.log"

Creating directories is also compact and convenient:

Path("backup/archive").mkdir(parents=True, exist_ok=True)

Here: parents=True creates nested directories; exist_ok=True doesn't raise an error if the folder already exists.

For reading and writing text files, there are built-in methods that cover most everyday tasks:

config = Path("config.txt")

config.write_text("debug=true", encoding="utf-8")

content = config.read_text(encoding="utf-8")
print(content)

For binary data, read_bytes() and write_bytes() methods are available.

You can iterate through directory contents using iterdir():

for file in Path("logs").iterdir():
    print(file)

If you need to search for files by pattern, use glob():

for py_file in Path(".").glob("*.py"):
    print(py_file)

And for recursive directory traversal, there's rglob():

for file in Path(".").rglob("*.json"):
    print(file)

Practical example — finding logs older than a certain date. This is a more real-world task:

from pathlib import Path
from datetime import datetime

logs = Path("logs")
limit_date = datetime(2026, 1, 1)

for file in logs.glob("*.log"):
    modified = datetime.fromtimestamp(file.stat().st_mtime)

    if modified < limit_date:
        print(file.name, modified)

The stat() method lets you get file metadata: size, modification time, permissions, and other system data.

Deleting files and directories is also built directly into the Path API:

path.unlink()  # file
path.rmdir()   # empty directory

It's important to note that pathlib doesn't fully replace shutil or os. For example, for copying files, recursive directory deletion, or complex permission operations, additional modules are usually used.



🔥 pathlib makes working with the file system noticeably cleaner: less string operations, better readability, and more predictable code when working with paths and files.



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