This package and data-structure implementation originally comes from the TQEC library: frozendefaultdict.py.

Introduction

This package introduces a new data-structure that is mix of frozendict introduced in Python 3.15 (PEP 814) and collections.defaultdict, with small changes to the API to make it more usable.

Install

You can install frozendefaultdict by using pip

python -m pip install frozendefaultdict

or any other Python package manager able to install from PyPI.

API

The frozendefaultdict class implements the same API as frozendict (see PEP 814) up to a few changes that are noted below.

Notable differences with frozendict

The constructor of frozendefaultdict has a keyword-only argument default_value that does not exist in the frozendict class.

The frozendict constructors using **kwargs (frozendict(**kwargs) and frozendict(collection, **kwargs)) are not supported for frozendefaultdict.

frozendict instances can be compared to dict. frozendefaultdict instances cannot be compared to dict (the comparison will always return False), and also cannot be compared to defaultdict due to the fact that defaultdict has a default_factory where frozendefaultdict has a default_value.

frozendefaultdict has the following additional properties and methods:

1. has_default_value that is True when the frozendefaultdict instance has a default value.
2. default_value that returns the default value of the instance or None.
3. map_keys that returns a new frozendefaultdict instance with new keys but the same values.
4. map_values that returns a new frozendefaultdict instance with new values (and default value) but the same keys.
5. map_keys_if_present that returns a new frozendefaultdict instance with new keys and (potentially a subset of) the same values.

Notable differences with defaultdict

The frozendefaultdict class takes a default value as argument instead of a callable that returns the default value. This is mainly to make frozendefaultdict hashable and comparable with other frozendefaultdict instances without relying on function identity (id()) which breaks as soon as lambdas are used.

If callables were used, the class would have no reliable way to hash or compare the provided callable (using the id() of the callable is very brittle, see below, and using the callable code from inspect would also break with a and c in the exemple below).

For example, with Python 3.10, the following code

a = lambda: 4
b = lambda: 4
c = lambda: 2 + 2
print(id(a))
print(id(b))
print(id(c))

outputs 3 different numbers, which makes the id() function a bad implementation for hash().

Examples

from frozendefaultdict import frozendefaultdict

fdd = frozendefaultdict({0: 1, 4: 2}, default_value=98)
print(fdd)
# frozendefaultdict({0: 1, 4: 2}, default_value=98)

fdd2 = fdd | {0: 3}
print(fdd2)
# frozendefaultdict({0: 3, 4: 2}, default_value=98)

fdd3 = frozendefaultdict[int, int]({}, default_value=3)
fdd4 = fdd | fdd3
print(fdd4)
# frozendefaultdict({0: 1, 4: 2}, default_value=3)

print(fdd[0])
# 1
print(fdd[-1])
# 98

print(fdd.has_default_value)
# True
print(fdd.default_value)
# 98

fdd5 = fdd.map_keys(lambda i: i + 5)
print(fdd5)
# frozendefaultdict({5: 1, 9: 2}, default_value=98)

fdd6 = fdd.map_values(lambda i: i - 5)
print(fdd6)
# frozendefaultdict({0: -4, 4: -3}, default_value=93)

fdd7 = fdd.map_keys_if_present({0: 4, 923874: 9023784})
print(fdd7)
# frozendefaultdict({4: 1}, default_value=98)

Usage of LLMs

A LLM has been used at the very beginning of the project to generate some tests. None of the tests written by an LLM are present in the code base any more. All the code you see in this repository (including the actual code, documentation and tests) have been crafted with love and passion by a human and no LLM has been involved in their development.