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Key

As explained in Grokking Data Structures

A key is an identifier associated with a value that determines how the value is located in an associative data structure.

A key is an identifier associated with a value. It tells a dictionary where to find that value, such as a baseball player's name identifying cards and collection details. section 12.1

Dictionary operations use keys in several practical ways:

  • Insert a value using its key, retrieve the associated value by searching for that key, and delete by key, value, or reference. section 12.3
  • A key may be extracted from a value, supplied separately as a key–value pair, or computed with a hash function. section 12.3
  • When keys are strings, extracting an integer identifier may require processing each character, adding a cost that can be treated as constant only when bounded. section 12.11

Baseball-card lookup

A collection app can use a player's name or a card photograph as a key, then retrieve the number of copies owned and related card details. A hash table converts the key into a valid array index when the array cannot hold every possible key. section 12.1 section 12.13

How Grokking Data Structures covers it

How deep it goes
Defines keys, explains extraction and hashing, and notes indexing costs, but does not fully develop hash-collision handling.
Examples
Uses baseball-player names, card photographs, string identifiers, and Python key–value pairs as examples.
What it assumes
Assumes basic familiarity with values and arrays while teaching dictionary lookup and key extraction from first principles.
What you can do after
Apply it via dictionaries and hash tables to associate, retrieve, and remove values efficiently.
How it connects
Connects keys to dictionaries, associative arrays, direct-access tables, hash functions, and hash tables.

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This explainer was generated by Manning's knowledge graph from the text of Grokking Data Structures. The section links point to the parts of the book it draws on.