Lists, sets, and dictionaries

The idea

Lists represent ordered sequences, sets support membership without promising a useful iteration order, and dictionaries associate keys with values while preserving insertion order. Choose the structure from the result you need. A comprehension expresses a transformation and optional filter; an explicit loop is often clearer when several branches or multiple accumulating results are involved.

Assignment creates another reference rather than copying a collection. A shallow copy creates a new outer list or dictionary but still shares nested objects. Preserve caller-owned data by constructing replacements at every level you change. When removing duplicates while retaining order, combine a set for membership with a list for output instead of relying on set iteration. Include repeated values and empty input in your examples.

seen = set()
unique = []
for label in ["api", "ui", "api"]:
    if label not in seen:
        seen.add(label)
        unique.append(label)
print(unique)

['api', 'ui']

The set answers membership questions while the output list records first occurrence order. Neither collection changes the source list.