Learning Python

Dictionaries

Besides lists, dictionaries are perhaps the most flexible built-in data type in Python. If you think of lists as ordered collections of objects, dictionaries are unordered collections; their chief distinction is that items are stored and fetched in dictionaries by key, instead of offset. As we’ll see, built-in dictionaries can replace many of the searching algorithms and data-structures you might have to implement manually in lower-level languages. Dictionaries also sometimes do the work of records and symbol tables used in other languages. In terms of their main properties, dictionaries are:

Accessed by key, not offset

Dictionaries are sometimes called associative arrays or hashes. They associate a set of values with keys, so that you can fetch an item out of a dictionary using the key that stores it. You use the same indexing operation to get components in a dictionary, but the index takes the form of a key, not a relative offset.

Unordered collections of arbitrary objects

Unlike lists, items stored in a dictionary aren’t kept in any particular order; in fact, Python randomizes their order in order to provide quick lookup. Keys provide the symbolic (not physical) location of items in a dictionary.

Variable length, heterogeneous, arbitrarily nestable

Like lists, dictionaries can grow and shrink in place (without making a copy), they can contain objects of any type, and support nesting to any depth (they can contain lists, other dictionaries, and so on).

Of the category mutable ...