great_expectations.core

Package Contents

Classes

DataContextKey()

DataContextKey objects are used to uniquely identify resources used by the DataContext.

IDDict()

dict() -> new empty dictionary

DictDot()

RunIdentifier(run_name=None, run_time=None)

A RunIdentifier identifies a run (collection of validations) by run_name and run_time.

RunIdentifierSchema(*, only: types.StrSequenceOrSet = None, exclude: types.StrSequenceOrSet = (), many: bool = False, context: typing.Dict = None, load_only: types.StrSequenceOrSet = (), dump_only: types.StrSequenceOrSet = (), partial: typing.Union[bool, types.StrSequenceOrSet] = False, unknown: str = None)

Base schema class with which to define custom schemas.

ExpectationKwargs(*args, **kwargs)

dict() -> new empty dictionary

ExpectationConfiguration(expectation_type, kwargs, meta=None, success_on_last_run=None)

ExpectationConfiguration defines the parameters and name of a specific expectation.

ExpectationConfigurationSchema(*, only: types.StrSequenceOrSet = None, exclude: types.StrSequenceOrSet = (), many: bool = False, context: typing.Dict = None, load_only: types.StrSequenceOrSet = (), dump_only: types.StrSequenceOrSet = (), partial: typing.Union[bool, types.StrSequenceOrSet] = False, unknown: str = None)

Base schema class with which to define custom schemas.

ExpectationSuite(expectation_suite_name, expectations=None, evaluation_parameters=None, data_asset_type=None, meta=None)

ExpectationSuiteSchema(*, only: types.StrSequenceOrSet = None, exclude: types.StrSequenceOrSet = (), many: bool = False, context: typing.Dict = None, load_only: types.StrSequenceOrSet = (), dump_only: types.StrSequenceOrSet = (), partial: typing.Union[bool, types.StrSequenceOrSet] = False, unknown: str = None)

Base schema class with which to define custom schemas.

ExpectationValidationResult(success=None, expectation_config=None, result=None, meta=None, exception_info=None)

ExpectationValidationResultSchema(*, only: types.StrSequenceOrSet = None, exclude: types.StrSequenceOrSet = (), many: bool = False, context: typing.Dict = None, load_only: types.StrSequenceOrSet = (), dump_only: types.StrSequenceOrSet = (), partial: typing.Union[bool, types.StrSequenceOrSet] = False, unknown: str = None)

Base schema class with which to define custom schemas.

ExpectationSuiteValidationResult(success=None, results=None, evaluation_parameters=None, statistics=None, meta=None)

ExpectationSuiteValidationResultSchema(*, only: types.StrSequenceOrSet = None, exclude: types.StrSequenceOrSet = (), many: bool = False, context: typing.Dict = None, load_only: types.StrSequenceOrSet = (), dump_only: types.StrSequenceOrSet = (), partial: typing.Union[bool, types.StrSequenceOrSet] = False, unknown: str = None)

Base schema class with which to define custom schemas.

Functions

find_evaluation_parameter_dependencies(parameter_expression)

Parse a parameter expression to identify dependencies including GE URNs.

nested_update(d, u)

in_jupyter_notebook()

get_metric_kwargs_id(metric_name, metric_kwargs)

convert_to_json_serializable(data)

Helper function to convert an object to one that is json serializable

ensure_json_serializable(data)

Helper function to convert an object to one that is json serializable

_deduplicate_evaluation_parameter_dependencies(dependencies)

great_expectations.core.ge_version
class great_expectations.core.DataContextKey

Bases: object

DataContextKey objects are used to uniquely identify resources used by the DataContext.

A DataContextKey is designed to support clear naming with multiple representations including a hashable version making it suitable for use as the key in a dictionary.

abstract to_tuple(self)
classmethod from_tuple(cls, tuple_)
abstract to_fixed_length_tuple(self)
abstract classmethod from_fixed_length_tuple(cls, tuple_)
__eq__(self, other)

Return self==value.

__ne__(self, other)

Return self!=value.

__hash__(self)

Return hash(self).

__repr__(self)

Return repr(self).

great_expectations.core.find_evaluation_parameter_dependencies(parameter_expression)

Parse a parameter expression to identify dependencies including GE URNs.

Parameters

parameter_expression – the parameter to parse

Returns

  • “urns”: set of strings that are valid GE URN objects

  • ”other”: set of non-GE URN strings that are required to evaluate the parameter expression

Return type

a dictionary including

class great_expectations.core.IDDict

Bases: dict

dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object’s

(key, value) pairs

dict(iterable) -> new dictionary initialized as if via:

d = {} for k, v in iterable:

d[k] = v

dict(**kwargs) -> new dictionary initialized with the name=value pairs

in the keyword argument list. For example: dict(one=1, two=2)

_id_ignore_keys
to_id(self, id_keys=None, id_ignore_keys=None)
great_expectations.core.ge_urn
great_expectations.core.nested_update(d, u)
exception great_expectations.core.InvalidCacheValueError(result_dict)

Bases: great_expectations.exceptions.GreatExpectationsError

Common base class for all non-exit exceptions.

exception great_expectations.core.InvalidExpectationConfigurationError(message)

Bases: great_expectations.exceptions.GreatExpectationsError

Common base class for all non-exit exceptions.

exception great_expectations.core.InvalidExpectationKwargsError(message)

Bases: great_expectations.exceptions.GreatExpectationsError

Common base class for all non-exit exceptions.

exception great_expectations.core.ParserError(message)

Bases: great_expectations.exceptions.GreatExpectationsError

Common base class for all non-exit exceptions.

exception great_expectations.core.UnavailableMetricError(message)

Bases: great_expectations.exceptions.GreatExpectationsError

Common base class for all non-exit exceptions.

class great_expectations.core.DictDot

Bases: object

__getitem__(self, item)
__setitem__(self, key, value)
__delitem__(self, key)
great_expectations.core.logger
great_expectations.core.RESULT_FORMATS = ['BOOLEAN_ONLY', 'BASIC', 'COMPLETE', 'SUMMARY']
great_expectations.core.EvaluationParameterIdentifier
great_expectations.core.in_jupyter_notebook()
great_expectations.core.get_metric_kwargs_id(metric_name, metric_kwargs)
great_expectations.core.convert_to_json_serializable(data)

Helper function to convert an object to one that is json serializable

Parameters

data – an object to attempt to convert a corresponding json-serializable object

Returns

(dict) A converted test_object

Warning

test_obj may also be converted in place.

great_expectations.core.ensure_json_serializable(data)

Helper function to convert an object to one that is json serializable

Parameters

data – an object to attempt to convert a corresponding json-serializable object

Returns

(dict) A converted test_object

Warning

test_obj may also be converted in place.

class great_expectations.core.RunIdentifier(run_name=None, run_time=None)

Bases: great_expectations.core.data_context_key.DataContextKey

A RunIdentifier identifies a run (collection of validations) by run_name and run_time.

property run_name(self)
property run_time(self)
to_tuple(self)
to_fixed_length_tuple(self)
__repr__(self)

Return repr(self).

__str__(self)

Return str(self).

to_json_dict(self)
classmethod from_tuple(cls, tuple_)
classmethod from_fixed_length_tuple(cls, tuple_)
class great_expectations.core.RunIdentifierSchema(*, only: types.StrSequenceOrSet = None, exclude: types.StrSequenceOrSet = (), many: bool = False, context: typing.Dict = None, load_only: types.StrSequenceOrSet = (), dump_only: types.StrSequenceOrSet = (), partial: typing.Union[bool, types.StrSequenceOrSet] = False, unknown: str = None)

Bases: marshmallow.Schema

Base schema class with which to define custom schemas.

Example usage:

import datetime as dt
from dataclasses import dataclass

from marshmallow import Schema, fields


@dataclass
class Album:
    title: str
    release_date: dt.date


class AlbumSchema(Schema):
    title = fields.Str()
    release_date = fields.Date()


album = Album("Beggars Banquet", dt.date(1968, 12, 6))
schema = AlbumSchema()
data = schema.dump(album)
data  # {'release_date': '1968-12-06', 'title': 'Beggars Banquet'}
Parameters
  • only – Whitelist of the declared fields to select when instantiating the Schema. If None, all fields are used. Nested fields can be represented with dot delimiters.

  • exclude – Blacklist of the declared fields to exclude when instantiating the Schema. If a field appears in both only and exclude, it is not used. Nested fields can be represented with dot delimiters.

  • many – Should be set to True if obj is a collection so that the object will be serialized to a list.

  • context – Optional context passed to fields.Method and fields.Function fields.

  • load_only – Fields to skip during serialization (write-only fields)

  • dump_only – Fields to skip during deserialization (read-only fields)

  • partial – Whether to ignore missing fields and not require any fields declared. Propagates down to Nested fields as well. If its value is an iterable, only missing fields listed in that iterable will be ignored. Use dot delimiters to specify nested fields.

  • unknown – Whether to exclude, include, or raise an error for unknown fields in the data. Use EXCLUDE, INCLUDE or RAISE.

Changed in version 3.0.0: prefix parameter removed.

Changed in version 2.0.0: __validators__, __preprocessors__, and __data_handlers__ are removed in favor of marshmallow.decorators.validates_schema, marshmallow.decorators.pre_load and marshmallow.decorators.post_dump. __accessor__ and __error_handler__ are deprecated. Implement the handle_error and get_attribute methods instead.

run_name
run_time
make_run_identifier(self, data, **kwargs)
class great_expectations.core.ExpectationKwargs(*args, **kwargs)

Bases: dict

dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object’s

(key, value) pairs

dict(iterable) -> new dictionary initialized as if via:

d = {} for k, v in iterable:

d[k] = v

dict(**kwargs) -> new dictionary initialized with the name=value pairs

in the keyword argument list. For example: dict(one=1, two=2)

ignored_keys = ['result_format', 'include_config', 'catch_exceptions']

ExpectationKwargs store information necessary to evaluate an expectation.

isEquivalentTo(self, other)
__repr__(self)

Return repr(self).

__str__(self)

Return str(self).

to_json_dict(self)
great_expectations.core._deduplicate_evaluation_parameter_dependencies(dependencies)
class great_expectations.core.ExpectationConfiguration(expectation_type, kwargs, meta=None, success_on_last_run=None)

Bases: great_expectations.types.DictDot

ExpectationConfiguration defines the parameters and name of a specific expectation.

property expectation_type(self)
property kwargs(self)
isEquivalentTo(self, other)

ExpectationConfiguration equivalence does not include meta, and relies on equivalence of kwargs.

__eq__(self, other)

ExpectationConfiguration equality does include meta, but ignores instance identity.

__ne__(self, other)

Return self!=value.

__repr__(self)

Return repr(self).

__str__(self)

Return str(self).

to_json_dict(self)
get_evaluation_parameter_dependencies(self)
class great_expectations.core.ExpectationConfigurationSchema(*, only: types.StrSequenceOrSet = None, exclude: types.StrSequenceOrSet = (), many: bool = False, context: typing.Dict = None, load_only: types.StrSequenceOrSet = (), dump_only: types.StrSequenceOrSet = (), partial: typing.Union[bool, types.StrSequenceOrSet] = False, unknown: str = None)

Bases: marshmallow.Schema

Base schema class with which to define custom schemas.

Example usage:

import datetime as dt
from dataclasses import dataclass

from marshmallow import Schema, fields


@dataclass
class Album:
    title: str
    release_date: dt.date


class AlbumSchema(Schema):
    title = fields.Str()
    release_date = fields.Date()


album = Album("Beggars Banquet", dt.date(1968, 12, 6))
schema = AlbumSchema()
data = schema.dump(album)
data  # {'release_date': '1968-12-06', 'title': 'Beggars Banquet'}
Parameters
  • only – Whitelist of the declared fields to select when instantiating the Schema. If None, all fields are used. Nested fields can be represented with dot delimiters.

  • exclude – Blacklist of the declared fields to exclude when instantiating the Schema. If a field appears in both only and exclude, it is not used. Nested fields can be represented with dot delimiters.

  • many – Should be set to True if obj is a collection so that the object will be serialized to a list.

  • context – Optional context passed to fields.Method and fields.Function fields.

  • load_only – Fields to skip during serialization (write-only fields)

  • dump_only – Fields to skip during deserialization (read-only fields)

  • partial – Whether to ignore missing fields and not require any fields declared. Propagates down to Nested fields as well. If its value is an iterable, only missing fields listed in that iterable will be ignored. Use dot delimiters to specify nested fields.

  • unknown – Whether to exclude, include, or raise an error for unknown fields in the data. Use EXCLUDE, INCLUDE or RAISE.

Changed in version 3.0.0: prefix parameter removed.

Changed in version 2.0.0: __validators__, __preprocessors__, and __data_handlers__ are removed in favor of marshmallow.decorators.validates_schema, marshmallow.decorators.pre_load and marshmallow.decorators.post_dump. __accessor__ and __error_handler__ are deprecated. Implement the handle_error and get_attribute methods instead.

expectation_type
kwargs
meta
make_expectation_configuration(self, data, **kwargs)
class great_expectations.core.ExpectationSuite(expectation_suite_name, expectations=None, evaluation_parameters=None, data_asset_type=None, meta=None)

Bases: object

add_citation(self, comment, batch_kwargs=None, batch_markers=None, batch_parameters=None, citation_date=None)
isEquivalentTo(self, other)

ExpectationSuite equivalence relies only on expectations and evaluation parameters. It does not include: - data_asset_name - expectation_suite_name - meta - data_asset_type

__eq__(self, other)

ExpectationSuite equality ignores instance identity, relying only on properties.

__ne__(self, other)

Return self!=value.

__repr__(self)

Return repr(self).

__str__(self)

Return str(self).

to_json_dict(self)
get_evaluation_parameter_dependencies(self)
get_citations(self, sort=True, require_batch_kwargs=False)
get_table_expectations(self)

Return a list of table expectations.

get_column_expectations(self)

Return a list of column map expectations.

static _filter_citations(citations, filter_key)
static _sort_citations(citations)
_copy_and_clean_up_expectation(self, expectation, discard_result_format_kwargs=True, discard_include_config_kwargs=True, discard_catch_exceptions_kwargs=True)

Returns copy of expectation without success_on_last_run and other specified key-value pairs removed

Returns a copy of specified expectation will not have success_on_last_run key-value. The other key-value pairs will be removed by default but will remain in the copy if specified.

Parameters
  • expectation (json) – The expectation to copy and clean.

  • discard_result_format_kwargs (boolean) – if True, will remove the kwarg output_format key-value pair from the copied expectation.

  • discard_include_config_kwargs (boolean) – if True, will remove the kwarg include_config key-value pair from the copied expectation.

  • discard_catch_exceptions_kwargs (boolean) – if True, will remove the kwarg catch_exceptions key-value pair from the copied expectation.

Returns

A copy of the provided expectation with success_on_last_run and other specified key-value pairs removed

Note

This method may move to ExpectationConfiguration, minus the “copy” part.

_copy_and_clean_up_expectations_from_indexes(self, match_indexes, discard_result_format_kwargs=True, discard_include_config_kwargs=True, discard_catch_exceptions_kwargs=True)

Copies and cleans all expectations provided by their index in DataAsset._expectation_suite.expectations.

Applies the _copy_and_clean_up_expectation method to multiple expectations, provided by their index in DataAsset,_expectation_suite.expectations. Returns a list of the copied and cleaned expectations.

Parameters
  • match_indexes (List) – Index numbers of the expectations from expectation_config.expectations to be copied and cleaned.

  • discard_result_format_kwargs (boolean) – if True, will remove the kwarg output_format key-value pair from the copied expectation.

  • discard_include_config_kwargs (boolean) – if True, will remove the kwarg include_config key-value pair from the copied expectation.

  • discard_catch_exceptions_kwargs (boolean) – if True, will remove the kwarg catch_exceptions key-value pair from the copied expectation.

Returns

A list of the copied expectations with success_on_last_run and other specified key-value pairs removed.

See also

_copy_and_clean_expectation

append_expectation(self, expectation_config)

Appends an expectation.

Parameters

expectation_config (ExpectationConfiguration) – The expectation to be added to the list.

Notes

May want to add type-checking in the future.

find_expectation_indexes(self, expectation_type=None, column=None, expectation_kwargs=None)

Find matching expectations and return their indexes. :param expectation_type=None: The name of the expectation type to be matched. :param column=None: The name of the column to be matched. :param expectation_kwargs=None: A dictionary of kwargs to match against.

Returns

A list of indexes for matching expectation objects. If there are no matches, the list will be empty.

find_expectations(self, expectation_type=None, column=None, expectation_kwargs=None, discard_result_format_kwargs=True, discard_include_config_kwargs=True, discard_catch_exceptions_kwargs=True)

Find matching expectations and return them. :param expectation_type=None: The name of the expectation type to be matched. :param column=None: The name of the column to be matched. :param expectation_kwargs=None: A dictionary of kwargs to match against. :param discard_result_format_kwargs=True: In returned expectation object(s), suppress the result_format parameter. :param discard_include_config_kwargs=True: In returned expectation object(s), suppress the include_config parameter. :param discard_catch_exceptions_kwargs=True: In returned expectation object(s), suppress the catch_exceptions parameter.

Returns

A list of matching expectation objects. If there are no matches, the list will be empty.

remove_expectation(self, expectation_type=None, column=None, expectation_kwargs=None, remove_multiple_matches=False, dry_run=False)

Remove matching expectation(s). :param expectation_type=None: The name of the expectation type to be matched. :param column=None: The name of the column to be matched. :param expectation_kwargs=None: A dictionary of kwargs to match against. :param remove_multiple_matches=False: Match multiple expectations :param dry_run=False: Return a list of matching expectations without removing

Returns

None, unless dry_run=True. If dry_run=True and remove_multiple_matches=False then return the expectation that would be removed. If dry_run=True and remove_multiple_matches=True then return a list of expectations that would be removed.

Note

If remove_expectation doesn’t find any matches, it raises a ValueError. If remove_expectation finds more than one matches and remove_multiple_matches!=True, it raises a ValueError. If dry_run=True, then remove_expectation acts as a thin layer to find_expectations, with the default values for discard_result_format_kwargs, discard_include_config_kwargs, and discard_catch_exceptions_kwargs

class great_expectations.core.ExpectationSuiteSchema(*, only: types.StrSequenceOrSet = None, exclude: types.StrSequenceOrSet = (), many: bool = False, context: typing.Dict = None, load_only: types.StrSequenceOrSet = (), dump_only: types.StrSequenceOrSet = (), partial: typing.Union[bool, types.StrSequenceOrSet] = False, unknown: str = None)

Bases: marshmallow.Schema

Base schema class with which to define custom schemas.

Example usage:

import datetime as dt
from dataclasses import dataclass

from marshmallow import Schema, fields


@dataclass
class Album:
    title: str
    release_date: dt.date


class AlbumSchema(Schema):
    title = fields.Str()
    release_date = fields.Date()


album = Album("Beggars Banquet", dt.date(1968, 12, 6))
schema = AlbumSchema()
data = schema.dump(album)
data  # {'release_date': '1968-12-06', 'title': 'Beggars Banquet'}
Parameters
  • only – Whitelist of the declared fields to select when instantiating the Schema. If None, all fields are used. Nested fields can be represented with dot delimiters.

  • exclude – Blacklist of the declared fields to exclude when instantiating the Schema. If a field appears in both only and exclude, it is not used. Nested fields can be represented with dot delimiters.

  • many – Should be set to True if obj is a collection so that the object will be serialized to a list.

  • context – Optional context passed to fields.Method and fields.Function fields.

  • load_only – Fields to skip during serialization (write-only fields)

  • dump_only – Fields to skip during deserialization (read-only fields)

  • partial – Whether to ignore missing fields and not require any fields declared. Propagates down to Nested fields as well. If its value is an iterable, only missing fields listed in that iterable will be ignored. Use dot delimiters to specify nested fields.

  • unknown – Whether to exclude, include, or raise an error for unknown fields in the data. Use EXCLUDE, INCLUDE or RAISE.

Changed in version 3.0.0: prefix parameter removed.

Changed in version 2.0.0: __validators__, __preprocessors__, and __data_handlers__ are removed in favor of marshmallow.decorators.validates_schema, marshmallow.decorators.pre_load and marshmallow.decorators.post_dump. __accessor__ and __error_handler__ are deprecated. Implement the handle_error and get_attribute methods instead.

expectation_suite_name
expectations
evaluation_parameters
data_asset_type
meta
clean_empty(self, data)
prepare_dump(self, data, **kwargs)
make_expectation_suite(self, data, **kwargs)
class great_expectations.core.ExpectationValidationResult(success=None, expectation_config=None, result=None, meta=None, exception_info=None)

Bases: object

__eq__(self, other)

ExpectationValidationResult equality ignores instance identity, relying only on properties.

__repr__(self)

Return repr(self).

__str__(self)

Return str(self).

validate_result_dict(self, result)
to_json_dict(self)
get_metric(self, metric_name, **kwargs)
class great_expectations.core.ExpectationValidationResultSchema(*, only: types.StrSequenceOrSet = None, exclude: types.StrSequenceOrSet = (), many: bool = False, context: typing.Dict = None, load_only: types.StrSequenceOrSet = (), dump_only: types.StrSequenceOrSet = (), partial: typing.Union[bool, types.StrSequenceOrSet] = False, unknown: str = None)

Bases: marshmallow.Schema

Base schema class with which to define custom schemas.

Example usage:

import datetime as dt
from dataclasses import dataclass

from marshmallow import Schema, fields


@dataclass
class Album:
    title: str
    release_date: dt.date


class AlbumSchema(Schema):
    title = fields.Str()
    release_date = fields.Date()


album = Album("Beggars Banquet", dt.date(1968, 12, 6))
schema = AlbumSchema()
data = schema.dump(album)
data  # {'release_date': '1968-12-06', 'title': 'Beggars Banquet'}
Parameters
  • only – Whitelist of the declared fields to select when instantiating the Schema. If None, all fields are used. Nested fields can be represented with dot delimiters.

  • exclude – Blacklist of the declared fields to exclude when instantiating the Schema. If a field appears in both only and exclude, it is not used. Nested fields can be represented with dot delimiters.

  • many – Should be set to True if obj is a collection so that the object will be serialized to a list.

  • context – Optional context passed to fields.Method and fields.Function fields.

  • load_only – Fields to skip during serialization (write-only fields)

  • dump_only – Fields to skip during deserialization (read-only fields)

  • partial – Whether to ignore missing fields and not require any fields declared. Propagates down to Nested fields as well. If its value is an iterable, only missing fields listed in that iterable will be ignored. Use dot delimiters to specify nested fields.

  • unknown – Whether to exclude, include, or raise an error for unknown fields in the data. Use EXCLUDE, INCLUDE or RAISE.

Changed in version 3.0.0: prefix parameter removed.

Changed in version 2.0.0: __validators__, __preprocessors__, and __data_handlers__ are removed in favor of marshmallow.decorators.validates_schema, marshmallow.decorators.pre_load and marshmallow.decorators.post_dump. __accessor__ and __error_handler__ are deprecated. Implement the handle_error and get_attribute methods instead.

success
expectation_config
result
meta
exception_info
convert_result_to_serializable(self, data, **kwargs)
make_expectation_validation_result(self, data, **kwargs)
class great_expectations.core.ExpectationSuiteValidationResult(success=None, results=None, evaluation_parameters=None, statistics=None, meta=None)

Bases: great_expectations.types.DictDot

__eq__(self, other)

ExpectationSuiteValidationResult equality ignores instance identity, relying only on properties.

__repr__(self)

Return repr(self).

__str__(self)

Return str(self).

to_json_dict(self)
get_metric(self, metric_name, **kwargs)
class great_expectations.core.ExpectationSuiteValidationResultSchema(*, only: types.StrSequenceOrSet = None, exclude: types.StrSequenceOrSet = (), many: bool = False, context: typing.Dict = None, load_only: types.StrSequenceOrSet = (), dump_only: types.StrSequenceOrSet = (), partial: typing.Union[bool, types.StrSequenceOrSet] = False, unknown: str = None)

Bases: marshmallow.Schema

Base schema class with which to define custom schemas.

Example usage:

import datetime as dt
from dataclasses import dataclass

from marshmallow import Schema, fields


@dataclass
class Album:
    title: str
    release_date: dt.date


class AlbumSchema(Schema):
    title = fields.Str()
    release_date = fields.Date()


album = Album("Beggars Banquet", dt.date(1968, 12, 6))
schema = AlbumSchema()
data = schema.dump(album)
data  # {'release_date': '1968-12-06', 'title': 'Beggars Banquet'}
Parameters
  • only – Whitelist of the declared fields to select when instantiating the Schema. If None, all fields are used. Nested fields can be represented with dot delimiters.

  • exclude – Blacklist of the declared fields to exclude when instantiating the Schema. If a field appears in both only and exclude, it is not used. Nested fields can be represented with dot delimiters.

  • many – Should be set to True if obj is a collection so that the object will be serialized to a list.

  • context – Optional context passed to fields.Method and fields.Function fields.

  • load_only – Fields to skip during serialization (write-only fields)

  • dump_only – Fields to skip during deserialization (read-only fields)

  • partial – Whether to ignore missing fields and not require any fields declared. Propagates down to Nested fields as well. If its value is an iterable, only missing fields listed in that iterable will be ignored. Use dot delimiters to specify nested fields.

  • unknown – Whether to exclude, include, or raise an error for unknown fields in the data. Use EXCLUDE, INCLUDE or RAISE.

Changed in version 3.0.0: prefix parameter removed.

Changed in version 2.0.0: __validators__, __preprocessors__, and __data_handlers__ are removed in favor of marshmallow.decorators.validates_schema, marshmallow.decorators.pre_load and marshmallow.decorators.post_dump. __accessor__ and __error_handler__ are deprecated. Implement the handle_error and get_attribute methods instead.

success
results
evaluation_parameters
statistics
meta
prepare_dump(self, data, **kwargs)
make_expectation_suite_validation_result(self, data, **kwargs)
great_expectations.core.expectationConfigurationSchema
great_expectations.core.expectationSuiteSchema
great_expectations.core.expectationValidationResultSchema
great_expectations.core.expectationSuiteValidationResultSchema
great_expectations.core.runIdentifierSchema