Create a dictionary with comprehension

Digging deeper: Mastering dict comprehensions

Understanding the nuances

• Order preservation: From Python 3.7 on, dictionaries remember the insertion order. So, the order in comprehension is the order.

• Unique keys: Beware, keys in dictionaries must be unique. If you don't pay attention, a key can overwrite another!

• Filtering: Dict comprehensions can do some spring cleaning by filtering out entries:

  # Dict, but make it clean
  {k: v for k, v in some_dict.items() if v is not None}
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Using the dict constructor and zip function

• If we have two lists and we want a dictionary out of them, the dict() constructor got us covered:

  # 'Zip' them together and they can't run away
  simple_dict = dict(zip(['one', 'two', 'three'], [1, 2, 3]))
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• But wait, it's not over yet! You can alter the values in the dict constructor:

  # No need for a gym membership, we lift +10s here
  modified_dict = dict((k, v + 10) for k, v in zip(keys, values))
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Advanced comprehension patterns in action

• You can combine advanced filtering and value modification in a comprehension to create more complex dictionaries. Who said Python wasn't a workout for your brain?

  # Putting the 'even' in 'even more fun'
  {k: v * v for k, v in zip(range(5), range(5, 10)) if v % 2 == 0}
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• Generator expressions with dict() are the way to go for creating dictionaries on the fly when handling large datasets:

  # Don't worry, it won't bite... unless you're a performance issue
  large_dict = dict((i, i**2) for i in range(1000))
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Making dictionaries in older Python versions

In Python 2.7 and below, dict comprehensions don't exist. However, worry not, there are other ways:

# Constructing a dictionary the old-fashioned way
legacy_dict = {}
for key, value in zip(keys, values):
    legacy_dict[key] = value
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Or use tuple unpacking in the dict() constructor for a more elegant solution:

# Unpacking surprises!
legacy_dict = dict((key, value) for key, value in zip(keys, values))
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Getting top performance

• Built-in functions: Use these instead of coding from scratch. Python loves efficiency!
• Nested expressions: Avoid inserting complex expressions within loops in comprehensions. They can give performance hiccups.
• Particularly for large datasets, consider the cost of memory usage and computing power.
• Overlapping keys? Dict comprehensions don't check for that. It’s not a bug, it's a feature!