Dictlib is a lightweight add-on for dictionaries, featuring:

Dictionary union done properly: union() (not immutably safe), union_copy() (immutably safe)

(not immutably safe), (immutably safe) "String.dot" notation for retrieval from classic dictionaries, with a string key: dig() , dig_get() , dug() . For efficiencies sake, it isn't an object. If you want dot notation more commonly used in your code, use Dict() instead.

notation for retrieval from classic dictionaries, with a string key: , , . For efficiencies sake, it isn't an object. If you want dot notation more commonly used in your code, use instead. Object.key Dictionary keys as object attributes (easy classes): Dict() (useful for rapid prototyping, just define your class as a Dict, either way:

Dictionary keys as object attributes (easy classes): (useful for rapid prototyping, just define your class as a Dict, either way: balancing features with performance: we could do more (such as supporting dictionary['this.key'] inline dot notation), but I wanted to keep it near native performance, and having an external function like dig() is similar to Ruby's method, so you can use it as needed, and if you really want dot notation, use an inline method that is efficient at runtime like Dict()

NewClass = Dict class NewClass ( Dict ): pass

If this doesn't work for you, consider other dictionary helper libraries:

Scalpl a more indepth tool that does similar to dictlib.dig() and dictlib.dug() does not include keys as object attributes -- Dict()

Addict similar to addict.Dict() and dictlib.Dict() As time allows I'll add a better comparison

Box similar to addict.Dict() and dictlib.Dict() As time allows I'll add a better comparison



union() and union_copy()

from dictlib import union , union_copy dict1 = union ( dict1 , dict2 ) dict3 = union_copy ( dict1 , dict2 )

Deep union of dict2 into dict1, where dictionary values are recursively merged. Non-dictionary elements are replaced, with preference given to dict2.

This alters dict1, which is the returned result, but it will have references to both dictionaries. If you do not want this, use union_copy(), which is less efficient but data-safe.

dig() and dig_get()

Recursively pull from a dictionary, using dot notation. dig_get behaves like dict.get() , but with dot-notated keys.

from dictlib import dig , dig_get dict1 = { "a" :{ "b" :{ "c" : 1 }, "d" :[{ "e" : 1 },{ "f" : 2 }]}} dig ( dict1 , "a.b.c" ) # 1 dig ( dict1 , "a.d[1].f" ) # 2 dig ( dict1 , "a.b.z" ) # KeyError: 'z' dig_get ( dict1 , "a.b.z" ) # None dig_get ( dict1 , "a.b.z" , 2 ) # 2

dug()

Inverse of dig() , dug() puts an item into a nested dictionary, using dot notation. This does not behave immutably, as it alters the origin dictionary.

from dictlib import dug dict1 = { "a" :{ "b" :{ "c" : 1 }}} dug ( dict1 , "a.b.c" , 200 ) # {'a': {'b': {'c': 200}}} # and it will instantiate dictionaries as values if the key doesn't exist: dug ( dict1 , "a.b.z.e" , True ) # {'a': {'b': {'c': 200, 'z': {'e': True}}}}

Note: dug() does not support pushing to lists within a dictionary, it assumes all values are dictionaries in your dot notation string. If you attempt to use a list index, it still behaves as if it were a dictionary, which may give you unexpected results:

dict1 = { "a" :{ "b" :{ "c" : 1 }}} dug ( dict1 , "a.b.d[0].e" , True ) # {'a': {'b': {'c': 1, 'd': {0: {'e': True}}}}}

(PR's to finish this feature correctly are appreciated)

Dict()

A bit of sugar to represent a dictionary in object form where keys are set as attributes on the object. Features:

it tokenizes your keys if they are not python safe ( "this-key" is .this_key ). Example:

d = Dict ({ "this key" : "value" }) d [ "this-key" ] # "value" d . this_key # "value"

Recursive -- it will walk the full depth of the dictionary

This is not python zen because it provides an alternate way to use dictionaries, and it has some challenges with names that collide with builtin methods, but it is very

But I'm okay with this, because it is handy bit of sugar.

Limitations:

raises error if there is a name conflict with reserved words

reserves the key prefix \f$\f for internal use (raises error)

because of namespace conflict problems, you must be cautious on what keys are input

Two keys exist for each non-tokenized name, such as ugly var! , which is tokenized to ugly_var_ . However, they do not point to the same data value! While both exist, if exporting to original object only the value of the tokenized name is used (see examples)

from dictlib import Dict Dict ( key1 = 1 , a = 2 ) # {'key1': 1, 'a': 2} test_dict = { "a" :{ "b" : 1 , "ugly var!" : 2 }, "c" : 3 } test_obj = Dict ( ** test_dict ) test_obj . keys () # ['a', 'c'] 'a' in test_obj # True test_obj . get ( 'c' ) # 3 test_obj [ 'c' ] # 3 test_obj . c # 3 test_obj . c = 4 test_obj . c # 4 test_obj . a . b # 1 test_obj . a . ugly_var_ # 2 test_obj . a [ 'ugly var!' ] # 2 # however, these are distinctly different values, don't be confused: test_obj . a . ugly_var_ = 0xdeadbeef test_obj . a . ugly_var_ # 3735928559 test_obj . a [ 'ugly var!' ] # 2 # how it looks -- in most cases it tries to look normal for you, but you can # use __export__ and __original__ to be assured. In some cases you can see the # mapping keys, which is confusing, and needs to be fixed (PR appreciated): test_obj = Dict ( test_dict ) test_obj # {'a': {'b': 1, 'ugly_var_': 2, 'ugly var!': 2}, 'c': 3} import json json . dumps ( test_obj ) # '{"a": {"b": 1, "ugly_var_": 2, "\\f$\\fugly_var_": "ugly var!", "ugly var!": 2}, "c": 3}' json . dumps ( test_obj . __export__ ()) # removes key mapping values, but keeps split tokenized keys # '{"a": {"b": 1, "ugly_var_": 2, "ugly var!": 2}, "c": 3}' json . dumps ( test_obj . __original__ ()) # removes key mapping values and tokenized keys # '{"a": {"b": 1, "ugly var!": 2}, "c": 3}' test_obj . __original__ () # {'a': {'b': 1, 'ugly var!': 2}, 'c': 3}

Note: Dict() was previously Obj() , which has been deprecated but is still supported.

dictlib.original() and dictlib.export()

Walk dict1 which may be mixed dict()/Dict() and export any Dict()'s to dict(), using the Dict.__original__() or Dict.__export__() method, respectively.

(useful for data conversions, such as with dict->yaml)