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https://github.com/srevenant/dictlib

python: a lightweight add-on for dictionaries, featuring deep dictionary union, dictionary keys as object attributes (in code dict.key.sub.value notation) as well as a separate string dig/dug for using strings with dot notation on native dictionaries
https://github.com/srevenant/dictlib

dict dictionaries dig dot-notation python union

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python: a lightweight add-on for dictionaries, featuring deep dictionary union, dictionary keys as object attributes (in code dict.key.sub.value notation) as well as a separate string dig/dug for using strings with dot notation on native dictionaries

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README 

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



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

  * *`Object.key` Dictionary keys as object attributes* (easy classes): `Dict()` (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()`



```python

NewClass = Dict

class NewClass(Dict):

  pass

```



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



  * [Scalpl](https://github.com/ducdetronquito/scalpl)

    - a more indepth tool that does similar to `dictlib.dig()` and `dictlib.dug()`

    - does not include keys as object attributes -- `Dict()`

  * [Addict](https://github.com/mewwts/addict) 

    - similar to `addict.Dict()` and `dictlib.Dict()`

    - As time allows I'll add a better comparison

  * [Box](https://github.com/cdgriffith/Box )

    - similar to `addict.Dict()` and `dictlib.Dict()`

    - As time allows I'll add a better comparison



union() and union_copy()

===============



```python

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.



```python

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.  



```python

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:



```python

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:

```python

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)



```python

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)

```python

import json

export(Dict({"ugly first": 1, "second": {"tres": Dict({"nachos":2})}}))

# {'ugly_first': 1, 'ugly first': 1, 'second': {'tres': {'nachos': 2}}}



json.dumps(Dict({"ugly first": 1, "second": {"tres": Dict({"nachos":2})}}))

# '{"ugly_first": 1, "\\\\f$\\\\fugly_first": "ugly first", "ugly first": 1, "second": {"tres": {"nachos": 2}}}'



json.dumps(export(Dict({"ugly first": 1, "second": {"tres": Dict({"nachos":2})}})))

# '{"ugly_first": 1, "ugly first": 1, "second": {"tres": {"nachos": 2}}}'

```