great_expectations.data_context.types.resource_identifiers

Module Contents

Classes

ExpectationSuiteIdentifier(expectation_suite_name: str)

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

ExpectationSuiteIdentifierSchema(*, 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.

BatchIdentifier(batch_identifier: Union[BatchKwargs, dict, str], data_asset_name: str = None)

A BatchIdentifier tracks

BatchIdentifierSchema(*, 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.

ValidationResultIdentifier(expectation_suite_identifier, run_id, batch_identifier)

A ValidationResultIdentifier identifies a validation result by the fully-qualified expectation_suite_identifier

GeCloudIdentifier(resource_type: str, ge_cloud_id: Optional[str] = None)

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

ValidationResultIdentifierSchema(*, 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.

SiteSectionIdentifier(site_section_name, resource_identifier)

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

ConfigurationIdentifier(configuration_key: Union[str, UUID])

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

ConfigurationIdentifierSchema(*, 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.
great_expectations.data_context.types.resource_identifiers.logger
class great_expectations.data_context.types.resource_identifiers.ExpectationSuiteIdentifier(expectation_suite_name: str)

Bases: great_expectations.core.data_context_key.DataContextKey

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.

property expectation_suite_name(self)
to_tuple(self)
to_fixed_length_tuple(self)
classmethod from_tuple(cls, tuple_)
classmethod from_fixed_length_tuple(cls, tuple_)
__repr__(self)

Return repr(self).

class great_expectations.data_context.types.resource_identifiers.ExpectationSuiteIdentifierSchema(*, 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: great_expectations.marshmallow__shade.Schema

Base schema class with which to define custom schemas.

Example usage:

import datetime as dt
from dataclasses import dataclass

from great_expectations.marshmallow__shade 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
make_expectation_suite_identifier(self, data, **kwargs)
class great_expectations.data_context.types.resource_identifiers.BatchIdentifier(batch_identifier: Union[BatchKwargs, dict, str], data_asset_name: str = None)

Bases: great_expectations.core.data_context_key.DataContextKey

A BatchIdentifier tracks

property batch_identifier(self)
property data_asset_name(self)
to_tuple(self)
classmethod from_tuple(cls, tuple_)
class great_expectations.data_context.types.resource_identifiers.BatchIdentifierSchema(*, 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: great_expectations.marshmallow__shade.Schema

Base schema class with which to define custom schemas.

Example usage:

import datetime as dt
from dataclasses import dataclass

from great_expectations.marshmallow__shade 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.

batch_identifier
data_asset_name
make_batch_identifier(self, data, **kwargs)
class great_expectations.data_context.types.resource_identifiers.ValidationResultIdentifier(expectation_suite_identifier, run_id, batch_identifier)

Bases: great_expectations.core.data_context_key.DataContextKey

A ValidationResultIdentifier identifies a validation result by the fully-qualified expectation_suite_identifier and run_id.

property expectation_suite_identifier(self)
property run_id(self)
property batch_identifier(self)
to_tuple(self)
to_fixed_length_tuple(self)
classmethod from_tuple(cls, tuple_)
classmethod from_fixed_length_tuple(cls, tuple_)
classmethod from_object(cls, validation_result)
class great_expectations.data_context.types.resource_identifiers.GeCloudIdentifier(resource_type: str, ge_cloud_id: Optional[str] = None)

Bases: great_expectations.core.data_context_key.DataContextKey

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.

property resource_type(self)
property ge_cloud_id(self)
to_tuple(self)
to_fixed_length_tuple(self)
classmethod from_tuple(cls, tuple_)
classmethod from_fixed_length_tuple(cls, tuple_)
__repr__(self)

Return repr(self).

class great_expectations.data_context.types.resource_identifiers.ValidationResultIdentifierSchema(*, 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: great_expectations.marshmallow__shade.Schema

Base schema class with which to define custom schemas.

Example usage:

import datetime as dt
from dataclasses import dataclass

from great_expectations.marshmallow__shade 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_identifier
run_id
batch_identifier
make_validation_result_identifier(self, data, **kwargs)
class great_expectations.data_context.types.resource_identifiers.SiteSectionIdentifier(site_section_name, resource_identifier)

Bases: great_expectations.core.data_context_key.DataContextKey

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.

property site_section_name(self)
property resource_identifier(self)
to_tuple(self)
classmethod from_tuple(cls, tuple_)
class great_expectations.data_context.types.resource_identifiers.ConfigurationIdentifier(configuration_key: Union[str, UUID])

Bases: great_expectations.core.data_context_key.DataContextKey

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.

property configuration_key(self)
to_tuple(self)
to_fixed_length_tuple(self)
classmethod from_tuple(cls, tuple_)
classmethod from_fixed_length_tuple(cls, tuple_)
__repr__(self)

Return repr(self).

class great_expectations.data_context.types.resource_identifiers.ConfigurationIdentifierSchema(*, 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: great_expectations.marshmallow__shade.Schema

Base schema class with which to define custom schemas.

Example usage:

import datetime as dt
from dataclasses import dataclass

from great_expectations.marshmallow__shade 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.

configuration_key
make_configuration_identifier(self, data, **kwargs)
great_expectations.data_context.types.resource_identifiers.expectationSuiteIdentifierSchema
great_expectations.data_context.types.resource_identifiers.validationResultIdentifierSchema
great_expectations.data_context.types.resource_identifiers.runIdentifierSchema
great_expectations.data_context.types.resource_identifiers.batchIdentifierSchema
great_expectations.data_context.types.resource_identifiers.configurationIdentifierSchema