Filter dict to contain only certain keys?

Extra shots of filtering syntax

Although the quick solution stated above is often what you need, filtering dictionaries in Python has deeper facets. Let's ride the Python and go beyond the basics.

Filtering with pattern-matching

Applying if statements in the dictionary comprehension enables more complex filtering scenarios:

filtered_dict = {k: v for k, v in original_dict.items() if k.startswith('b')}
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Here we filtered keys that start with 'b'. It's like playing the "startswith" game with your keys.

Large lists and efficiency rap battle

For those times when you have a massive list of keys to keep, switching it to a set is like turning a snail into a rabbit:

keys_to_keep = set(['key1', 'key2', 'key3'])  # Using a set for large lists is like using nitro boost in racing.
filtered_dict = {k: v for k, v in original_dict.items() if k in keys_to_keep}
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No comprehensions? No problems!

In case you're not a fan of dictionary comprehensions, here's an alternative that uses dict() and generator expressions:

filtered_dict = dict((k, original_dict[k]) for k in keys_to_keep if k in original_dict)
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This is like bringing a knife to a gunfight. Can it get the job done? Yes! Should you use it? Depends on the circumstances!

Advanced dictionary maneuvers

Next, let's go more in-depth and look at some advanced techniques for specific requirements or preferences.

Handling big dictionaries like a pro

When you are face-to-face with a giant of a dictionary, every operation could be the one that makes or breaks your code. Instead of checking containment, consider using set operations:

unwanted_keys = set(original_dict) - keys_to_keep

for unwanted_key in unwanted_keys:
    del original_dict[unwanted_key]
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Remember that this will permanently modify the original_dict, so use this only when you want to literally "shred some keys".

Finding allies in libraries

Sometimes, Python's built-in functions aren't enough. Time to call in the reinforcements! Libraries like funcy offer functions like project or select_keys:

from funcy import select_keys
filtered_dict = select_keys(keys_to_keep, original_dict)
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Libraries are like Swiss Army knives: they've got you covered in most situations.

Comments: the art of documentation

Even if your code is neater than a freshly made bed, comments make it sparkle. They explain your thought process to others and your future self:

# Keep only keys that start with 'config_' and have non-null values
filtered_dict = {
    k: v for k, v in original_dict.items() 
    if k.startswith('config_') and v is not None
}
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As Albert Einstein said, "If you can't explain it simply, you haven't written enough comments"... okay, he didn't say that. But you get the point!

Python 2: The return of .iteritems()

If you're living in the prehistoric ages and using Python 2.6 or before, .iteritems() would be your buddy for better memory usage:

filtered_dict = {k: original_dict[k] for k in keys_to_keep if k in original_dict.iteritems()}
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Transforming values while dancing with tuples

When filtering keys of varying types or composite keys, using tuples can work like a magic spell for efficiency:

keys_to_keep = {('compound', 'key'), ('another', 'key')}
filtered_dict = {k: v for k, v in original_dict.items() if k in keys_to_keep}
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List comprehension for hardcore value transformations

For cases where you need to twist and turn your keys or values while filtering, a list comprehension within a dict constructor can pack a punch:

# Apply transformation to the value while filtering
filtered_dict = dict(
    (k, transform_value(v)) for k, v in original_dict.items() if k in keys_to_keep
)
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Lambda: The ninja of the code world

For single-use, small operations, a lambda function can work wonders. It's like an anonymous ninja doing your bidding!

filtered_dict = dict(filter(lambda item: item[0] in keys_to_keep, original_dict.items()))
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