CleverDict

Overview

CleverDict is a hybrid Python data class which allows both object.attribute and dictionary['key'] notation to be used simultaneously and interchangeably. It's particularly handy when your code is mainly object-orientated but you want a 'DRY' and extensible way to import data in json/dictionary format into your objects... or vice versa... without having to write extra code just to handle the translation.

The class also optionally triggers a .save() method (which you can adapt or overwrite) which it calls whenever an attribute or dictionary value is created or changed. This is especially useful if you want your results to be automatically pickled, encoded, saved to a file or database, uploaded to the cloud etc. without having to explicitly call your update function after single operation where attributes (might) change.

Installation

No dependencies. Very lightweight:

pip install cleverdict

or to cover all bases...

python -m pip install cleverdict --upgrade --user

Quickstart

CleverDict objects behave like normal Python dictionaries, but with the convenience of immediately offering read and write access to their data (keys and values) using the object.attribute syntax, which many people find easier to type and more intuitive to read and understand:

>>> from cleverdict import CleverDict
>>> x = CleverDict({'total':6, 'usergroup': "Knights of Ni"})

>>> x.total
6
>>> x['total']
6
>>> x.usergroup
'Knights of Ni'
>>> x['usergroup']
'Knights of Ni'

You can also supply keyword arguments like this:

>>> x = CleverDict(created = "today", review = "tomorrow")

>>> x.created
'today'
>>> x['review']
'tomorrow'

Regardless of which syntax you use, new values are immediately available via both methods:

>>> x['life'] = 42
>>> x.life += 1
>>> x['life']
43

>>> del x['life']
>>> x.life
# KeyError: 'life'

You can import an existing object's data (but not its methods) directly using vars():

x = CleverDict(vars(my_existing_object))

>>> list(x.items())
[('total', 6), ('usergroup', 'Knights of Ni'), ('life', 42)]

You can set pretty much any function to run automatically whenever a CleverDict value is created or changed. There's an example function in cleverict.test_cleverdict which illustrates this option:

>>> from cleverdict.test_cleverdict import my_example_save_function
>>> CleverDict.save = my_example_save_function

>>> x = CleverDict({'total':6, 'usergroup': "Knights of Ni"})
Notional save to database: .total = 6 <class 'int'>
Notional save to database: .usergroup = Knights of Ni <class 'str'>

>>> x.life = 42
Notional save to database: .life = 42 <class 'int'>

The example function above also appends output to a file, which you might want for debugging, auditing, further analysis etc.:

>>> with open("example.log","r") as file:
...     log = file.read()

>>> log.splitlines()
["Notional save to database: .age = 10 <class 'int'>",
"Notional save to database: .total = 6 <class 'int'>",
"Notional save to database: .usergroup = Knights of Ni <class 'str'>"]

NB: The .save() method is a class method, so changing CleverDict.save will apply the new .save() method to all previously created CleverDict objects as well.

If you want to specify different .save() behaviours for different instances, consider creating sublasses that inherit from CleverDict and set a different .save() function for each subclass e.g.:

>>> class Type1(CleverDict): pass
>>> Type1.save = my_save_function1

>>> class Type2(CleverDict): pass
>>> Type2.save = my_save_function2

When writing your own .save() function, you'll need to specify three arguments as follows:

>>> def your_function(self, name: str = "", value: any = ""):
...     print("Ni!")

self
name: a valid Python .attribute name preferably, otherwise you'll only be able to access it using dictionary['key'] notation later on.
value: anything

If you want to overwrite the __str__ method with your own function, or delete it so print() and str() default to __repr__ that's easy enough too:

>>> print(x)
.total = 6 <class 'int'>
.usergroup = Knights of Ni <class 'str'>

>>> def my__str__replacement(self):
...     return str(type(self))

>>> setattr(CleverDict, "__str__", my__str__replacement)
>>> print(x)
<class 'cleverdict.cleverdict.CleverDict'>

>>> delattr(CleverDict, "__str__")
>>> print(x)
CleverDict({'total':6, 'usergroup':'Knights of Ni'})

Contributing

We'd love to see Pull Requests (and relevant tests) from other contributors, particularly if you can help with one of the following items on our wish-list:

It would be great if CleverDict behaviour could be easily 'grafted on' to existing classes using inheritance, without causing recursion or requiring a rewrite/overwrite of the original class.

For example if it were as easy as:
```
>>> class MyDatetime(datetime.datetime, CleverDict):
...     pass

>>> mdt = MyDatetime.now()
>>> mdt.hour
4
>>> mdt['hour']
4
```
Although CleverDict does accept dictionary keys such as " " and "" and strings with characters not allowed in object.attribute names, it can't create the corresponding .attributes. except if the first character is a number - it adds an underscore '_' to the attribute name).
```
>>> x = CleverDict({1: "One"})

>>> x._1
'One'
```
Is it worth creating other mappings e.g. replacing punctuation, spaces, and null strings somehow, or does that just over-complicate things when you can at least access the original keys through the dictionary?

Credits

CleverDict was developed jointly by Peter Fison, Ruud van der Ham, Loic Domaigne, and Rik Huygen who met on the friendly and excellent Pythonista Cafe forum (www.pythonistacafe.com). Peter got the ball rolling after noticing a super-convenient, but not fully-fledged feature in Pandas that allows you to (mostly) use object.attribute syntax or dictionary['key'] syntax interchangeably. Ruud, Loic and Rik then started swapping ideas for a hybrid dictionary/data class based on UserDict and the magic of __getattr__ and __setattr__, and CleverDict (originally called attr_dict - which is 'taken' on PyPi already) was born.

Akm0d / cleverdict