Python · Dictionaries

A dict maps keys to values. Looking up a key is fast (a hash table on average). Keys must be hashable, so ints, strings and tuples work but lists don’t.

Things I practised:

• d[k] raises KeyError if k is missing. d.get(k, default) returns the default instead.
• d.items(), d.keys() and d.values() give live views of the dict.
• Since Python 3.7, dicts keep insertion order as a language guarantee.
• d.setdefault(k, []) and collections.defaultdict make grouping easy.
• collections.Counter is a dict built for counting.
• d1 | d2 merges two dicts (Python 3.9+).

from collections import Counter, defaultdict

marks = {"maths": 88, "physics": 79}
marks["python"] = 95
print(marks)
print(marks.get("chemistry", "n/a"))

for subject, m in marks.items():
    print(f"{subject:>8}: {m}")

text = "to be or not to be"
print(Counter(text.split()).most_common(2))

by_len = defaultdict(list)
for w in text.split():
    by_len[len(w)].append(w)
print(dict(by_len))
print({"a": 1} | {"b": 2})

Output:

{'maths': 88, 'physics': 79, 'python': 95}
n/a
   maths: 88
 physics: 79
  python: 95
[('to', 2), ('be', 2)]
{2: ['to', 'be', 'or', 'to', 'be'], 3: ['not']}
{'a': 1, 'b': 2}