Interning Strings for Efficiency
The Python interpreter works a lot with strings, and like small integers, strings can also be reused by Python through a slightly different technique called interning. When a new string is created, the Python interpreter can choose whether or not to store a cached copy of that string. This happens under certain circumstances, in particular for identifiers.
Therefore, if a string starts with a letter or an underscore and only contains letters, underscores, or numbers, Python will intern the string and create a hash for it. As most things in Python are dictionaries, Python has to do a lot of lookups for identifiers, and by interning identifier strings the lookup process can be sped up quite a bit. In other words, identifiers are stored in a table, and Python creates a hash from the string object for future lookups. Such optimization occurs during compile time, and string literals that look like identifiers will also be interned.
The Python interpreter works a lot with strings, and like small integers, strings can also be reused by Python through a slightly different technique called interning. When a new string is created, the Python interpreter can choose whether or not to store a cached copy of that string. This happens under certain circumstances, in particular for identifiers.
Therefore, if a string starts with a letter or an underscore and only contains letters, underscores, or numbers, Python will intern the string and create a hash for it. As most things in Python are dictionaries, Python has to do a lot of lookups for identifiers, and by interning identifier strings the lookup process can be sped up quite a bit. In other words, identifiers are stored in a table, and Python creates a hash from the string object for future lookups. Such optimization occurs during compile time, and string literals that look like identifiers will also be interned.
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