great_expectations.types

Package Contents

Classes

SerializableDotDict()

Analogously to the way “SerializableDictDot” extends “DictDot” to provide JSON serialization, the present class,

ColorPalettes()

Generic enumeration.

PrimaryColors()

str(object=’’) -> str

SecondaryColors()

str(object=’’) -> str

TintsAndShades()

str(object=’’) -> str

ClassConfig(class_name, module_name=None)

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

FontFamily()

Generic enumeration.

FontFamilyURL()

Generic enumeration.

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.

Functions

safe_deep_copy(data, memo=None)

This method makes a copy of a dictionary, applying deep copy to attribute values, except for non-pickleable objects.

class great_expectations.types.SerializableDotDict

Bases: great_expectations.types.base.DotDict

Analogously to the way “SerializableDictDot” extends “DictDot” to provide JSON serialization, the present class, “SerializableDotDict” extends “DotDict” to provide JSON-serializable version of the “DotDict” class as well. Since “DotDict” is already YAML-serializable, “SerializableDotDict” is both YAML-serializable and JSON-serializable.

abstract to_json_dict(self)
class great_expectations.types.ColorPalettes

Bases: enum.Enum

Generic enumeration.

Derive from this class to define new enumerations.

CATEGORY_5
CATEGORY_7
DIVERGING_7
HEATMAP_6
ORDINAL_5
class great_expectations.types.PrimaryColors

Bases: str, enum.Enum

str(object=’’) -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to ‘strict’.

ORANGE = #FF6310
COAL_GRAY = #404041
class great_expectations.types.SecondaryColors

Bases: str, enum.Enum

str(object=’’) -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to ‘strict’.

MIDNIGHT_BLUE = #272763
ROYAL_BLUE = #223F99
TURQUOISE_BLUE = #4DC0B4
LEAF_GREEN = #B6C647
GOLD_YELLOW = #F3C62D
POMEGRANATE_PINK = #E2226B
LAVENDER_PURPLE = #BC87E6
class great_expectations.types.TintsAndShades

Bases: str, enum.Enum

str(object=’’) -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to ‘strict’.

ORANGE_100 = #803208
ORANGE_90 = #A03e0A
ORANGE_80 = #C04B0C
ORANGE_70 = #df570e
ORANGE_60 = #ff6310
ORANGE_50 = #ff7f3b
ORANGE_40 = #ff9b67
ORANGE_30 = #ffb892
ORANGE_20 = #ffd4be
ORANGE_10 = #FFF0E9
YELLOW_100 = #534207
YELLOW_90 = #7b6311
YELLOW_80 = #a3841a
YELLOW_70 = #cba524
YELLOW_60 = #f3c62d
YELLOW_50 = #f5d053
YELLOW_40 = #f7da78
YELLOW_30 = #fae59e
YELLOW_20 = #fcefc3
YELLOW_10 = #fef9e9
PINK_100 = #70062e
PINK_90 = #960f42
PINK_80 = #bc1957
PINK_70 = #e2226b
PINK_60 = #e64281
PINK_50 = #ea6396
PINK_40 = #ef83ac
PINK_30 = #f3a3c1
PINK_20 = #f7c4d6
PINK_10 = #fbe4ec
GRAY_100 = #000000
GRAY_90 = #404041
GRAY_80 = #58595B
GRAY_70 = #6d6e70
GRAY_60 = #808184
GRAY_50 = #929497
GRAY_40 = #a6a8ab
GRAY_30 = #bbbdbf
GRAY_20 = #d0d2d3
GRAY_10 = #e6e7e8
MIDNIGHT_BLUE_100 = #141432
MIDNIGHT_BLUE_90 = #1e1e48
MIDNIGHT_BLUE_80 = #272763
MIDNIGHT_BLUE_70 = #424277
MIDNIGHT_BLUE_60 = #5d5d8a
MIDNIGHT_BLUE_50 = #78789e
MIDNIGHT_BLUE_40 = #9494b1
MIDNIGHT_BLUE_30 = #afafc5
MIDNIGHT_BLUE_20 = #cacad8
MIDNIGHT_BLUE_10 = #e5e5ec
ROYAL_BLUE_100 = #091a4c
ROYAL_BLUE_90 = #0f235f
ROYAL_BLUE_80 = #162072
ROYAL_BLUE_70 = #1c3686
ROYAL_BLUE_60 = #223f99
ROYAL_BLUE_50 = #4860ab
ROYAL_BLUE_40 = #6e81bc
ROYAL_BLUE_30 = #95a3ce
ROYAL_BLUE_20 = #bbc4df
ROYAL_BLUE_10 = #e1e5f1
TURQUOISE_BLUE_100 = #144944
TURQUOISE_BLUE_90 = #226760
TURQUOISE_BLUE_80 = #31847c
TURQUOISE_BLUE_70 = #3fa298
TURQUOISE_BLUE_60 = #4dc0b4
TURQUOISE_BLUE_50 = #6ccbc1
TURQUOISE_BLUE_40 = #8bd6ce
TURQUOISE_BLUE_30 = #aae1da
TURQUOISE_BLUE_20 = #c9ece7
TURQUOISE_BLUE_10 = #e8f7f4
GREEN_100 = #454c14
GREEN_90 = #616a21
GREEN_80 = #7e892e
GREEN_70 = #9aa83a
GREEN_60 = #b6c647
GREEN_50 = #c3d067
GREEN_40 = #cfda86
GREEN_30 = #dce3a6
GREEN_20 = #e8edc5
GREEN_10 = #f5f7e5
PURPLE_100 = #3b254d
PURPLE_90 = #5b3e73
PURPLE_80 = #7c569a
PURPLE_70 = #9c6fc0
PURPLE_60 = #bc87e6
PURPLE_50 = #c79aea
PURPLE_40 = #d2adee
PURPLE_30 = #dcc1f2
PURPLE_20 = #e7d4f6
PURPLE_10 = #f2e7fa
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.FontFamily

Bases: enum.Enum

Generic enumeration.

Derive from this class to define new enumerations.

MONTSERRAT = Montserrat
ROBOTO_MONO = Roboto Mono
SOURCE_SANS_PRO = Source Sans Pro
class great_expectations.types.FontFamilyURL

Bases: enum.Enum

Generic enumeration.

Derive from this class to define new enumerations.

MONTSERRAT = https://fonts.googleapis.com/css2?family=Montserrat
ROBOTO_MONO = https://fonts.googleapis.com/css2?family=Roboto+Mono
SOURCE_SANS_PRO = https://fonts.googleapis.com/css2?family=Source+Sans+Pro
great_expectations.types.logger
great_expectations.types.pyspark
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.

include_field_names :Set[str]
exclude_field_names :Set[str]
__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_raw_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.

to_dict(self)
property_names(self, include_keys: Optional[Set[str]] = None, exclude_keys: Optional[Set[str]] = None)

Assuming that – by convention – names of private properties of an object are prefixed by “_” (a single underscore character), return these property names as public property names. To support this convention, the extending classes must implement property accessors, corresponding to the property names, return by this method.

Parameters
  • include_keys – inclusion list (“include only these properties, while excluding all the rest”)

  • exclude_keys – exclusion list (“exclude only these properties, while include all the rest”)

Returns

property names, subject to inclusion/exclusion filtering

class great_expectations.types.SerializableDictDot

Bases: 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.

abstract to_json_dict(self)

# TODO: <Alex>2/4/2022</Alex> A reference implementation can be provided, once circular import dependencies, caused by relative locations of the “great_expectations/types/__init__.py” and “great_expectations/core/util.py” modules are resolved.

great_expectations.types.safe_deep_copy(data, memo=None)

This method makes a copy of a dictionary, applying deep copy to attribute values, except for non-pickleable objects.