Top 10 Python Functions That You Aren’t Using... But Should Be
Tags: python, programming, learning
Published: 2023-06-10 05:56:35

Ahoy there, you suave Pythonistas and code-slinging pythoneers! 🎩 Ready to take your Python wrangling skills to the next level? The Python gods have bestowed upon us functions more magical than the sorting hat at Hogwarts, and it’s high time we unlocked their true potential. 🧙

So, grab a snake-sized coffee ☕, put on your best Indiana Jones hat, and let's start digging into this treasure trove of Python goodness. 🐍

## 1. The Elusive `enumerate()` 🗂
Ever felt like a marathon runner counting the number of times you’ve been lapped? Well, with `enumerate()` you won't have to, because this beauty adds a counter to your loop. Look Ma, no hands!

```python
for index, value in enumerate(["apple", "banana", "cherry"], start=1):
    print(f"The index is {index} and the value is {value}")
```

## 2. `zip()` Up Your Lists 🤐
Two lists on a date, but you're the third wheel? With `zip()`, you can zip them together and send them on their way. Talk about being a wingman!

```python
names = ["Batman", "Superman", "Wonder Woman"]
superpowers = ["Rich", "Strong", "Lasso of Truth"]

for hero, power in zip(names, superpowers):
    print(f"{hero} is really just super {power}!")
```

## 3. `collections.Counter()` — The Crowd Tamer 📊
Do you have too many elements to count? Fret not! `Counter()` will help you figure out who's the party animal in your list.

```python
from collections import Counter
party_list = ["Alice", "Bob", "Alice", "Eve", "Bob", "Eve", "Alice"]
print(Counter(party_list))
# Output: Counter({'Alice': 3, 'Bob': 2, 'Eve': 2})
```

## 4. `functools.lru_cache()` — The Time Traveler ⏱
Do your functions take longer to execute than waiting for a sloth to finish a marathon? Just add `@lru_cache` above your function to make it faster than The Flash.

```python
from functools import lru_cache

@lru_cache
def fib(n):
    if n < 2:
        return n
    return fib(n-1) + fib(n-2)
```

## 5. All Aboard the `any()` and `all()` Express 🚂
Can’t decide if you should go out tonight? Let `any()` and `all()` help you with your indecisiveness. 

```python
friends_going = [False, False, True, False]
print(any(friends_going))  # Output: True

chores_done = [True, True, True, True]
print(all(chores_done))  # Output: True
```

## 6. Get Slick with `itertools.chain()` 🚲
Link your lists like a bicycle chain with `itertools.chain()` and ride smoothly through your dataset.

```python
from itertools import chain

list1 = [1, 2, 3]
list2 = ['a', 'b', 'c']
combined = list(chain(list1, list2))
print(combined)  # Output: [1, 2, 3, 'a', 'b', 'c']
```

## 7. The Great `defaultdict()` Magician 🎩
Tired of KeyError showing up uninvited? Make it disappear with `defaultdict()`. Now, every time you try to access a key that doesn’t exist, `defaultdict()` will create it for you. Abra-ka-dabra!

```python
from collections import defaultdict

d = defaultdict(int)
print(d["new_key"])  # Output: 0, and "new_key" is now a key in the dict
```

## 8. Jazz Up with `reversed()` 🔄
Did you know that you can turn things around without taking a 180-degree U-turn? Keep your lists in check with `reversed()` without altering the original list!

```python
original_list = [1, 2, 3, 4, 5]
for item in reversed(original_list):
    print(item, end=' ')  # Output: 5 4 3 2 1
```

## 9. Don’t Get Lost, Use `pathlib.Path()` 🗺
Is navigating through files and directories driving you nuts? Put away that compass, because `pathlib.Path()` is the true north of directory navigation.

```python
from pathlib import Path

# Navigate to your home directory and create a file there.
home = Path.home()
file = home / "treasure_map.txt"
file.touch()
print(f"Your treasure map is located at: {file}")
```

## 10. The Underestimated `else` in Loops 🎢
Did you know loops have a secret sidekick called `else`? It executes when the loop has finished, like Batman showing up after the fight is over to take credit.

```python
for i in range(5):
    if i == 10:
        break
else:
    print("Loop completed without a 'break'. Batman approves.")
```

# Disclaimers 📢:
1. Be cautious while using functions like `itertools.chain()` and `collections.Counter()` on large datasets. They might consume more memory than an elephant at an all-you-can-eat buffet. 🐘
2. Don’t overuse `functools.lru_cache()`. It's like a time machine – too much messing around can have unintended consequences.
3. While `defaultdict()` is magical, make sure you really want to add a new key to your dict, or it might grow uncontrollably like Rapunzel's hair.

# Conclusion 🚀
Congratulations, you’ve now been armed with 10 Python functions that are as useful as Dumbledore's wand. Cast spells like `enumerate()` to count effortlessly, and `lru_cache()` to speed up your functions. Use them wisely, or you might find yourself in a Python jungle without a map.

But, wait! There’s more! To keep your Python journey on track and unlock more arcane secrets, subscribe to [PAIton and Crossovers](https://www.youtube.com/channel/UCzUBm8oODJRZCHYVQtArgyA?sub_confirmation=1) on YouTube. Let’s conquer the Pythonic realms together, and remember: Python is all about having fun(ctions)!

_Happy coding, fellow sorcerers!_ 🧙🔮🐍