Collections — keep order, count repetitions and build uniqueness

Concept and intended result

Lists, dictionaries and sets answer different questions. In a user-selected list of names, order and duplicates may matter. A frequency dictionary counts how often each name occurs. A unique-name list can preserve only the first appearance of each name. A plain set loses meaningful occurrence information and should not automatically replace the original list.

Runnable Python 3 exercise

Save as 06_Collections.py and run with Python 3. Predict the output before executing; every example has assertions and uses only local synthetic values.

def catalog(names):
    if not isinstance(names, list) or not all(type(x) is str and x for x in names):
        raise ValueError("list of nonempty names required")
    counts = {}
    for name in names:
        counts[name] = counts.get(name, 0) + 1
    unique_first_seen = list(dict.fromkeys(names))
    return unique_first_seen, counts
unique, counts = catalog(["Ada","Grace","Ada","Αθηνά"])
assert unique == ["Ada","Grace","Αθηνά"]
assert counts == {"Ada":2,"Grace":1,"Αθηνά":1}
assert catalog([]) == ([], {})
try: catalog(["ok",None])
except ValueError: pass
else: raise AssertionError("wrong element type accepted")
print("PASS ordered collection and frequency map")

Why this works

The code loops through the list once to build counts and uses dict.fromkeys to preserve first-seen order in supported modern Python versions. The dictionary provides expected efficient key lookup, while the list preserves display order. Unicode text such as Αθηνά works as a dictionary key. Empty input returns two empty containers without being confused with invalid elements; None is rejected by the stated schema.

Guided learner lab

Add one extra Ada and predict the count without running. Change the order of names and confirm the frequency dictionary stays the same while unique_first_seen changes. Compare set(names) with the ordered unique list; write down which requirement gets lost. Try a list containing an integer, empty string and a tuple instead of a list, and record the rejection.

Diagnosing mistakes

If KeyError occurs when counting, use counts.get(name,0) rather than assuming the key exists. If duplicates disappear unexpectedly, find where a list was converted to a set. Avoid relying on a set's iteration order to present user-facing results; preserve an explicit order when the interface needs one.