Finding and replacing elements in a list

Multiple replacements with dictionary

When you've got several different alumni to welcome to your list's reunion, you'll want to use a dictionary:

# Note to self: These are not actual dictionary words
replacements = {1: 'One', 2: 'Two', 3: 'Three'}
my_list = [replacements.get(x, x) for x in my_list]
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replacements.get() searches for each list value as a key in replacements. If it's missing, it just allows x to resume its comfortable desk job.

Replacements with functional flair

If you want to turn your list into a functionally fabulous fashionista, use map and a lambda function:

# Lambda: The other white meat of functional programming
my_list = list(map(lambda x: new_value if x == old_value else x, my_list))
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This approach helps when your list elements come with baggage of complex conditions they can't just shed off.

Index-based replacements

When you need to fill an exact spot in a list, enumerate lets you hit that bullseye:

# Do re mi fa, so what? Let's focus on 'where'
my_list = [new_value if idx in indices_to_replace else x for idx, x in enumerate(my_list)]
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This approach keeps everything in order and only grabs the elements that you've selected for a makeover with their indices.

Visualization

Picture a Python-coded board game:

Before the move: Board 🎲: [🧙, 🧟, 🧝, 🤖]

Action: Replace the exhausted 🧟 with a high-energy 🧛.

Here goes the magic line:

board[1] = '🧛'  # Zombies make lousy co-workers, Vampires don't, well at least not during night shift
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After the move:

Board 🎲: [🧙, 🧛, 🧝, 🤖]

Even in a virtual world, new energy refreshes the game like anything. 🔄

Maintaining original lists

If you cannot touch the original list, but still fancy some replacements:

gotta_change_these = [i for i, x in enumerate(my_list) if x == old_value]
for i in gotta_change_these:
    my_list[i] = new_value
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This is the equivalent of the polite friend who never fiddles with your stuff; just makes a clean swap and leaves your list feeling honored.

The condition of being replaceable

Remember, life in dictionary world demands hashability. In simple language, stick with immutable dudes like strings, numbers, and tuples.

Efficiency across sizes

While the elegance of list comprehension is charming, embrace mapping for scaling large data sets or when the replacement rules are as tangled as a hipster's headphones.

Choosing the right tool

Not all replacements are the same:

• For uncomplicated swappings, the list comprehension is your Python's right hand.
• For a diversity of substitutions, get your hands dirty with a dictionary.
• When location matters more than personality, use enumerate to target your replacements.
• If you like functional style or face complex conditions, map() is your wrestler in the Python ring.

Whichever route you take, keep your choices mindful and your matches strict, especially if enumerate comes into play. Remember, enumerate doesn't do sloppy seconds.