More Dots!
Overview
Box your JSON-like data in a Data object to get null-safe dot access. This library is a replacement for dict that is more consistent and easier to use.
See full documentation for all the features of
mo-dots
See change log to read about major changes
Create instances
Define Data using named parameters, just like you would a dict
>>> from mo_dots import Data
>>> Data(b=42, c="hello world")
Data({'b': 42, 'c': 'hello world'})
You can also box an existing dicts so they can be used like Data
>>> from mo_dots import to_data
>>> to_data({'b': 42, 'c': 'hello world'})
Data({'b': 42, 'c': 'hello world'})
Dot Access
Access properties with attribute dots: a.b == a["b"]. You have probably seen this before.
Path Access
Access properties by dot-delimited path.
>>> a = to_data({"b": {"c": 42}})
>>> a["b.c"] == 42
True
Null-Safe Access
If a property does not exist then return Null rather than raising an error.
>>> a = Data()
>>> a.b == Null
True
>>> a.b.c == Null
True
>>> a[None] == Null
True
Path assignment
No need to make intermediate dicts
>>> a = Data()
>>> a["b.c"] = 42 # same as a.b.c = 42
a == {"b": {"c": 42}}
Path accumulation
Use += to add to a property; default zero (0)
>>> a = Data()
a == {}
>>> a.b.c += 1
a == {"b": {"c": 1}}
>>> a.b.c += 42
a == {"b": {"c": 43}}
Use += with a list ([]) to append to a list; default empty list ([])
>>> a = Data()
a == {}
>>> a.b.c += [1]
a == {"b": {"c": [1]}}
>>> a.b.c += [42]
a == {"b": {"c": [1, 42]}}
Serializing to JSON
The standard Python JSON library does not recognize Data as serializable. You may overcome this by providing default=from_data; which converts the data structures in this module into Python primitives of the same.
from mo_dots import from_data, to_data
s = to_data({"a": ["b", 1]})
result = json.dumps(s, default=from_data)
Alternatively, you may consider mo-json which has a function value2json that converts a larger number of data structures into JSON.
Summary
This library is the basis for a data transformation algebra: We want a succinct way of transforming data in Python. We want operations on data to result in yet more data. We do not want data operations to raise exceptions. This library also solves Python's lack of consistency (lack of closure) under the dot (.) and slice [::] operators when operating on data objects.
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