Data transformation

Enables quick inversion of a mapping dictionary for reverse lookup.

Data processing: swapping keys and values of a lookup table Web development: reversing a JSON mapping to retrieve original identifiers

Python scripts, data analysis pipelines, web back‑ends, configuration management tools

inverted = {value: key for key, value in source_dict.items()}

inverted = {...: ... for ..., ... in ... .items()}

inverted: dict mapping values to keys, key: original key type, value: original value type, source_dict: dict of key→value

• .items()
• dict comprehension
• key‑value swap

• Use a for‑loop with assignment – clearer for beginners but more verbose Use zip with values and keys – `dict(zip(source_dict.values()
• source_dict.keys()))` – works only when values are unique and hashable Use `dict(map(reversed
• source_dict.items()))` – concise but less readable for novices

Omitting `.items()` and iterating over the dictionary directly – results in iterating over keys only Assuming all values are unique – duplicate values cause later keys to overwrite earlier ones Using unhashable values (e.g., lists) as new keys – raises a TypeError at runtime Swapping in place without creating a new dict – leads to runtime errors due to changing size during iteration

List comprehension – produces a list, not a mapping `dict.update()` for merging – does not invert keys and values Using `defaultdict(list)` for reverse mapping when values are not unique

Coming from JavaScript: assuming object literal inversion works the same – JavaScript objects do not preserve key order and require explicit iteration with `Object.entries` Coming from Java: expecting `Map` to allow duplicate values for reverse lookup – Python dicts will overwrite duplicates

• dict comprehension
• key‑value swap
• reverse mapping
• dict.fromkeys

Do not use when original values are not unique; you will lose data Performance is O(n) time and creates a new dict, incurring additional memory proportional to the original size All original values must be hashable; mutable types like lists cannot serve as keys in the inverted dict

Provides an efficient way to implement reverse lookups, reducing boilerplate and potential bugs in code that needs to map values back to their original identifiers.

Inverting a dictionary is like swapping name tags on a guest list so each person now wears the other's name.

If the original dictionary contains duplicate values, consider using `collections.defaultdict(list)` to collect all original keys under each value.

Use collections.defaultdict(list) to build a reverse mapping that collects all original keys for each value when values are not unique, enabling a reverse multimap.