import pathlib
import shutil

# --- Setup: Create a temporary directory and files for the demo ---
# We use a relative path './temp_docs' so it works anywhere
docs_dir = pathlib.Path("temp_docs")
if docs_dir.exists():
    shutil.rmtree(docs_dir) # Clean up from previous runs
docs_dir.mkdir()

# Create dummy files
(docs_dir / "report.txt").write_text("This is a test report.")
(docs_dir / "notes.txt").write_text("Some important notes.")
# ----------------------------------------------------------------

# 1. Create a Path object for our report file
file_path = docs_dir / "report.txt"

# 2. Inspect Path Components
print(f"File Name: {file_path.name}")
print(f"Parent Directory: {file_path.parent}")
print(f"File Stem: {file_path.stem}")
print(f"File Suffix: {file_path.suffix}")

# 3. Check Path Properties
print(f"Exists: {file_path.exists()}")
print(f"Is File: {file_path.is_file()}")
print(f"Is Directory: {file_path.is_dir()}")

# 4. Manipulate Paths and prepare for renaming/moving
archive_dir = docs_dir / "archive"
archive_dir.mkdir() # Create the 'archive' subdirectory
new_file_path = archive_dir / "old_report.txt"
print(f"New Path: {new_file_path}")

# To demonstrate renaming, let's rename the original file
file_path.rename(new_file_path)

# 5. Iterate over the original directory to find files
for found_file in sorted(docs_dir.glob("*.txt")):
    print(f"Found File: {found_file.name}")

# 6. Demonstrate a copy operation
# `pathlib` itself doesn't have a copy method, but works perfectly with `shutil`
source_file = docs_dir / "notes.txt"
destination_file = archive_dir / "notes_backup.txt"
shutil.copy(source_file, destination_file)
print("File copied successfully!")


# --- Cleanup: Remove the temporary directory ---
shutil.rmtree(docs_dir)
# -----------------------------------------------

This self-contained script first sets up a realistic file structure, then demonstrates the power and simplicity of pathlib to inspect, manipulate, and manage files and directories, cleaning up after itself when it's done.

━━━━━━━━━━━━━━━
By: @DataScience4 ✨

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🔰 For Loop In Python (10 Best Tips & Tricks)

Here are 10 tips to help you write cleaner, more efficient, and more "Pythonic" for loops.

---

1️⃣. Use enumerate() for Index and Value

Instead of using range(len(sequence)) to get an index, enumerate gives you both the index and the item elegantly.

# Less Pythonic 👎
items = ["a", "b", "c"]
for i in range(len(items)):
    print(i, items[i])

# More Pythonic 👍
for i, item in enumerate(items):
    print(i, item)

---

2️⃣. Use zip() to Iterate Over Multiple Lists

To loop through two or more lists at the same time, zip() is the perfect tool. It stops when the shortest list runs out.

names = ["Alice", "Bob", "Charlie"]
ages = [25, 30, 35]

for name, age in zip(names, ages):
    print(f"{name} is {age} years old.")

---

3️⃣. Iterate Directly Over Dictionaries with .items()

To get both the key and value from a dictionary, use the .items() method. It's much cleaner than accessing the key and then looking up the value.

# Less Pythonic 👎
config = {"host": "localhost", "port": 8080}
for key in config:
    print(key, "->", config[key])

# More Pythonic 👍
for key, value in config.items():
    print(key, "->", value)

---

4️⃣. Use List Comprehensions for Simple Loops

If your for loop just creates a new list, a list comprehension is almost always a better choice. It's more concise and often faster.

# Standard for loop
squares = []
for i in range(5):
    squares.append(i * i)
# squares -> [0, 1, 4, 9, 16]

# List comprehension 👍
squares_comp = [i * i for i in range(5)]
# squares_comp -> [0, 1, 4, 9, 16]

---

5️⃣. Use the _ Underscore for Unused Variables

If you need to loop a certain number of times but don't care about the loop variable, use _ as a placeholder by convention.

# I don't need 'i', I just want to repeat 3 times
for _ in range(3):
    print("Hello!")

---

6️⃣. Unpack Tuples Directly in the Loop

If you're iterating over a list of tuples or lists, you can unpack the values directly into named variables for better readability.

points = [(1, 2), (3, 4), (5, 6)]

# Unpacking directly into x and y
for x, y in points:
    print(f"x: {x}, y: {y}")

---

7️⃣. Use break and a for-else Block

A for loop can have an else block that runs only if the loop completes without hitting a break. This is perfect for search operations.

numbers = [1, 3, 5, 7, 9]

for num in numbers:
    if num % 2 == 0:
        print("Even number found!")
        break
else:  # This runs only if the 'break' was never hit
    print("No even numbers in the list.")

---

8️⃣. Iterate Over a Copy to Safely Modify

Never modify a list while you are iterating over it directly. This can lead to skipped items. Instead, iterate over a copy.

# This will not work correctly! 👎
numbers = [1, 2, 3, 2, 4]
for num in numbers:
    if num == 2:
        numbers.remove(num) # Skips the second '2'

# Correct way: iterate over a slice copy [:] 👍
numbers = [1, 2, 3, 2, 4]
for num in numbers[:]:
    if num == 2:
        numbers.remove(num)
print(numbers) # [1, 3, 4]

---

9️⃣. Use reversed() for Reverse Iteration

To loop over a sequence in reverse, use the built-in reversed() function. It's more readable and efficient than creating a reversed slice.

# Less readable
items = ["a", "b", "c"]
for item in items[::-1]:
    print(item)

# More readable 👍
for item in reversed(items):
    print(item)

---

🔟. Use continue to Skip the Rest of an Iteration

The continue keyword ends the current iteration and moves to the next one. It's great for skipping items that don't meet a condition, reducing nested if statements.

# Using 'if'
for i in range(10):
    if i % 2 == 0:
        print(i, "is even")

# Using 'continue' can be cleaner
for i in range(10):
    if i % 2 != 0:
        continue  # Skip odd numbers
    print(i, "is even")

━━━━━━━━━━━━━━━
By: @DataScience4 ✨

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