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Dict implementations with attribute access: ReadonlyDictProxy, FrozenDict, FrozenOrderedDict, Dict, OrderedDict

Project description

build code quality coverage pypi github license: MIT

Quick overview

  • Attribute-style item access is provided by all dictionary classes of this library.

  • 5 dictionary implementations:

    • Standard dictionaries with attribute-style item access and a smarter copy() method with update parameters:

      • Dict

      • OrderedDict

    • Immutable/hashable versions of the previous two dictionaries:

      • FrozenDict

      • FrozenOrderedDict

    • A wrapper that can be used to create a readonly view of another dictionary instance:

      • ReadonlyDictProxy


pip install dictionaries

Alternatively you can download the distribution from the following places:



After installing the library you can import the dictionary classes the following way:

from dictionaries import Dict, OrderedDict, FrozenDict, FrozenOrderedDict, ReadonlyDictProxy

Their interface is as standard as possible so I assume you know how to deal with them.

Attribute-style item access

The attribute-style dictionary item access can be really convenient in many cases but it has issues. The most obvious issue is that the attributes of the dictionary are in conflict with your item keys. For this reason attribute-style access is a little bit “stinky” (especially when you try to implement it) and to aid this problem I’ve recently come up with a different kind of attribute-style access implementation. This library provides both the usual way (discussed here and there) and also my method. (Yes, I know that providing 2 or more ways isn’t pythonic but you have to experiment to find out what works and what doesn’t…) Later I might drop one of them.

“Classic” attribute-style dict item access (as people know it)

As mentioned previously the attributes of the dictionary instance (like copy) conflict with the keys of your items. In order to be able to access dictionary methods we have to provide priority for the dictionary attributes over the item keys.

>>> from dictionaries import Dict
>>> d = Dict(copy=True, name='example')
>>> d.my_item = 5   # this is equivalent to d['my_item'] = 5
>>> d
{'my_item': 5, 'name': 'example', 'copy': True}
>>> d.my_item
>>> d.copy          # the 'copy' item conflicts with the copy method!!!
<bound method ExtendedCopyMixin.copy of {'my_item': 5, 'name': 'example', 'copy': True}>

Attribute-style item access through the items attribute of the dictionary

My recent invention aids the previous conflict between dictionary attributes and item keys. By typing a little bit more you can use attribute-style access without worrying about conflicts:

>>> from dictionaries import Dict
>>> d = Dict(copy=True, name='example')
>>> d.items.my_item = 5
>>> d
{'my_item': 5, 'name': 'example', 'copy': True}
>>> d.items.my_item
>>> d.items.copy
>>> d.items()       # using items() the good old way still works
dict_items([('my_item', 5), ('name', 'example'), ('copy', True)])

You can use the items “method” of your dictionary the old way by calling it but you can also use it as an object that provides attribute style access to your items. There are no conflicts because the only attributes of items are the keys of your dictionary items.

Besides attribute-style item access the items attribute provides a limited set of the typical dictionary interface:

  • __contains__, __iter__, __len__

  • Item assignment/retrieval/deletion with both attribute-style access and subscript notation.

This can be useful if you have to pass around the items object to be accessed elsewhere.

>>> from dictionaries import Dict
>>> d = Dict(copy=True, name='example', my_item=5)
>>> 'name' in d
>>> iter(d.items)
<dict_keyiterator object at 0x104254e08>
>>> list(d.items)
['my_item', 'name', 'copy']
>>> len(d.items)
>>> del d.items['name']
>>> del d.items.copy            # no conflict with Dict.copy :-)
>>> d
{'my_item': 5}

Dictionary classes

FrozenDict and FrozenOrderedDict

These are “frozen”/immutable like the frozenset provided by the standard library. After creation their value doesn’t change during their lifetime. Like other immutable objects, instances of these dictionaries are hashable given that all objects inside them are also hashable.

>>> from dictionaries import FrozenDict
>>> d = FrozenDict(item1=1, item2=2)
>>> d['item3'] = 3      # we shouldn't be able to modify an immutable object
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: 'FrozenDict' object does not support item assignment
>>> del d['item2']      # we shouldn't be able to modify an immutable object
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: 'FrozenDict' object does not support item deletion
>>> d
<FrozenDict {'item1': 1, 'item2': 2}>
>>> hash(d)


Sometimes you have to pass around some of your dictionaries but you want to make sure that no one modifies them. In this case what you should do is creating a ReadonlyDictProxy wrapper around your dictionary and passing around the wrapper instead of your original wrapped one. The ReadonlyDictProxy instance will delegate all requests to your original dictionary except those requests that involve data modification (like item assignment/deletion, update(), etc…). Of course if you modify the wrapped dictionary then the users of the readonly proxy will notice the changes. The proxy keeps most of the behavior provided by the wrapped dict, for example if the wrapped dict is an ordered one then the readonly proxy also behaves as ordered.

>>> from dictionaries import ReadonlyDictProxy, OrderedDict
>>> wrapped = OrderedDict.fromkeys(['item1', 'item2', 'item3'])
>>> proxy = ReadonlyDictProxy(wrapped)
>>> wrapped
OrderedDict([('item1', None), ('item2', None), ('item3', None)])
>>> proxy
<ReadonlyDictProxy OrderedDict([('item1', None), ('item2', None), ('item3', None)])>

Changes to the wrapped dict instance are reflected by the readonly proxy:

>>> del wrapped['item3']
>>> wrapped['new_item'] = 'brand new'
>>> wrapped
OrderedDict([('item1', None), ('item2', None), ('new_item', 'brand new')])
>>> proxy
<ReadonlyDictProxy OrderedDict([('item1', None), ('item2', None), ('new_item', 'brand new')])>

Trying to modify the proxy object will fail:

>>> proxy['trying hard'] = 'to assign'      # the proxy is readonly, assignment fails
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: 'ReadonlyDictProxy' object does not support item assignment
>>> del proxy['item1']                      # the proxy is readonly, deletion fails
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: 'ReadonlyDictProxy' object does not support item deletion

Copying a ReadonlyDictProxy instance with its copy method creates another ReadonlyDictProxy instance that wraps the exact same object:

>>> # Both of these statements create another wrapper/proxy around wrapped:
>>> proxy_copy = proxy.copy()
>>> proxy_copy2 = ReadonlyDictProxy(wrapped)
>>> # Now we have 3 proxy objects wrapping the same dictionary (wrapped):
>>> wrapped.clear()
>>> wrapped.items.woof = 'woof'
>>> proxy
<ReadonlyDictProxy OrderedDict([('woof', 'woof')])>
>>> proxy_copy
<ReadonlyDictProxy OrderedDict([('woof', 'woof')])>
>>> proxy_copy2
<ReadonlyDictProxy OrderedDict([('woof', 'woof')])>

Extended copy method

All dictionary classes except ReadonlyDictProxy have a copy method that receives **kwargs. These keyword arguments are treated as dictionary items and used to create a copy that is updated with them.

>>> from dictionaries import Dict
>>> d = Dict(a=0, b=1)
>>> d2 = d.copy(b=2, c=3)
>>> d
{'a': 0, 'b': 1}
>>> d2
{'a': 0, 'b': 2, 'c': 3}

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