`great_expectations.types`¶

Submodules¶

Package Contents¶

Classes¶

`ClassConfig`(class_name, module_name=None)	Defines information sufficient to identify a class to be (dynamically) loaded for a DataContext.
`DictDot`()	A convenience class for migrating away from untyped dictionaries to stronger typed objects.
`SerializableDictDot`()	A convenience class for migrating away from untyped dictionaries to stronger typed objects.

class great_expectations.types.ClassConfig(class_name, module_name=None)¶

Defines information sufficient to identify a class to be (dynamically) loaded for a DataContext.

property class_name(self)¶

property module_name(self)¶

class great_expectations.types.DictDot¶

A convenience class for migrating away from untyped dictionaries to stronger typed objects.

Can be instantiated with arguments:

my_A = MyClassA(

foo=”a string”, bar=1,

)

Can be instantiated from a dictionary:

my_A = MyClassA(

**{
“foo”: “a string”, “bar”: 1,

}

)

Can be accessed using both dictionary and dot notation

my_A.foo == “a string” my_A.bar == 1

my_A[“foo”] == “a string” my_A[“bar”] == 1

Pairs nicely with @dataclass:

@dataclass() class MyClassA(DictDot):

foo: str bar: int

Can be made immutable:

@dataclass(frozen=True) class MyClassA(DictDot):

foo: str bar: int

For more examples of usage, please see test_dataclass_serializable_dot_dict_pattern.py in the tests folder.

__getitem__(self, item)¶

__setitem__(self, key, value)¶

__delitem__(self, key)¶

__contains__(self, key)¶

__len__(self)¶

keys(self)¶

values(self)¶

items(self)¶

get(self, key, default_value=None)¶

to_dict(self)¶

Convert this object into a standard dictionary, recursively.

This is often convenient for serialization, and in cases where an untyped version of the object is required.

class great_expectations.types.SerializableDictDot¶

Bases: great_expectations.types.DictDot