CloudWatch Logs (logs)

Primary Models

Primary models are models that you can act on directly. They are the models that represent resources in the AWS service, and are acted on by the managers.

pydantic model botocraft.services.logs.LogGroup

Bases: TagsDictMixin, PrimaryBoto3Model

Represents a log group.

Show JSON schema

{
   "title": "LogGroup",
   "description": "Represents a log group.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "arn": {
         "default": null,
         "title": "Arn",
         "type": "string"
      },
      "logGroupName": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Loggroupname"
      },
      "creationTime": {
         "default": null,
         "title": "Creationtime",
         "type": "integer"
      },
      "retentionInDays": {
         "default": null,
         "title": "Retentionindays",
         "type": "integer"
      },
      "metricFilterCount": {
         "default": null,
         "title": "Metricfiltercount",
         "type": "integer"
      },
      "storedBytes": {
         "default": null,
         "title": "Storedbytes",
         "type": "integer"
      },
      "kmsKeyId": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Kmskeyid"
      },
      "dataProtectionStatus": {
         "default": null,
         "enum": [
            "ACTIVATED",
            "DELETED",
            "ARCHIVED",
            "DISABLED"
         ],
         "title": "Dataprotectionstatus",
         "type": "string"
      },
      "inheritedProperties": {
         "items": {
            "const": "ACCOUNT_DATA_PROTECTION",
            "type": "string"
         },
         "title": "Inheritedproperties",
         "type": "array"
      },
      "logGroupClass": {
         "anyOf": [
            {
               "enum": [
                  "STANDARD",
                  "INFREQUENT_ACCESS",
                  "DELIVERY"
               ],
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Loggroupclass"
      },
      "logGroupArn": {
         "default": null,
         "title": "Loggrouparn",
         "type": "string"
      },
      "deletionProtectionEnabled": {
         "anyOf": [
            {
               "type": "boolean"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Deletionprotectionenabled"
      },
      "bearerTokenAuthenticationEnabled": {
         "default": null,
         "title": "Bearertokenauthenticationenabled",
         "type": "boolean"
      },
      "Tags": {
         "anyOf": [
            {
               "items": {
                  "$ref": "#/$defs/Tag"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Tags"
      }
   },
   "$defs": {
      "Tag": {
         "description": "The metadata that you apply to a resource to help you categorize and\norganize them. Each tag consists of a key and an optional value. You define\nthem.\n\nThe following basic restrictions apply to tags:\n\n* Maximum number of tags per resource - 50\n* For each resource, each tag key must be unique, and each tag key can have\n  only one value.\n* Maximum key length - 128 Unicode characters in UTF-8\n* Maximum value length - 256 Unicode characters in UTF-8\n* If your tagging schema is used across multiple services and resources,\n  remember that other services may have restrictions on allowed characters.\n  Generally allowed characters are: letters, numbers, and spaces representable in\n  UTF-8, and the following characters: + - = . _ : / @.\n* Tag keys and values are case-sensitive.\n* Do not use ``aws:``, ``AWS:``, or any upper or lowercase combination of such\n  as a prefix for either keys or values as it is reserved for Amazon Web Services\n  use. You cannot edit or delete tag keys or values with this prefix. Tags with\n  this prefix do not count against your tags per resource limit.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Key": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Key"
            },
            "Value": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Value"
            }
         },
         "title": "Tag",
         "type": "object"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• Arn (str)

• Tags (list[botocraft.services.common.Tag] | None)

• bearerTokenAuthenticationEnabled (bool)

• creationTime (int)

• dataProtectionStatus (Literal['ACTIVATED', 'DELETED', 'ARCHIVED', 'DISABLED'])

• deletionProtectionEnabled (bool | None)

• inheritedProperties (list[typing.Literal['ACCOUNT_DATA_PROTECTION']])

• kmsKeyId (str | None)

• logGroupArn (str)

• logGroupClass (Literal['STANDARD', 'INFREQUENT_ACCESS', 'DELIVERY'] | None)

• logGroupName (str | None)

• metricFilterCount (int)

• retentionInDays (int)

• session (Any | None)

• storedBytes (int)

field Arn: str = None (alias 'arn')

The Amazon Resource Name (ARN) of the log group.

This version of the ARN includes a trailing :* after the log group name.

field Tags: builtins.list[Tag] | None [Optional]

The tags associated with the log group.

field bearerTokenAuthenticationEnabled: bool = None

Indicates whether bearer token authentication is enabled for this log group.

When enabled, bearer token authentication is allowed on operations until it is explicitly disabled.

field creationTime: int = None

The creation time of the log group, expressed as the number of milliseconds after Jan 1, 1970 00:00:00 UTC.

field dataProtectionStatus: Literal['ACTIVATED', 'DELETED', 'ARCHIVED', 'DISABLED'] = None

Displays whether this log group has a protection policy, or whether it had one in the past.

For more information, see P utDataProtectionPolicy.

field deletionProtectionEnabled: bool | None = None

Indicates whether deletion protection is enabled for this log group.

When enabled, deletion protection blocks all deletion operations until it is explicitly disabled.

field inheritedProperties: builtins.list[Literal['ACCOUNT_DATA_PROTECTION']] [Optional]

Displays all the properties that this log group has inherited from account-level settings.

field kmsKeyId: str | None = None

The Amazon Resource Name (ARN) of the KMS key to use when encrypting log data.

field logGroupArn: str = None

The Amazon Resource Name (ARN) of the log group.

This version of the ARN doesn’t include a trailing :* after the log group name.

field logGroupClass: Literal['STANDARD', 'INFREQUENT_ACCESS', 'DELIVERY'] | None = None

This specifies the log group class for this log group.

There are three classes:

field logGroupName: str | None = None

The name of the log group.

field metricFilterCount: int = None

The number of metric filters.

field retentionInDays: int = None

The number of days to retain the log events in the specified log group.

Possible values are: 1, 3, 5, 7, 14, 30, 60, 90, 120, 150, 180, 365, 400, 545, 731, 1096, 1827, 2192, 2557, 2922, 3288, and 3653.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

field storedBytes: int = None

The number of bytes stored.

manager_class

alias of LogGroupManager

tag_class

alias of Tag

delete()

Delete the model.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

save(**kwargs)

Save the model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

property arn: str | None

Return the ARN of the model. This is the value of the Arn attribute.

Returns:

The ARN of the model instance.

property name: str | None

Return the name of the model. This is the value of the logGroupName attribute.

Returns:

The name of the model instance.

objects: ClassVar[classproperty]

Get the manager for this model, and set it as a class property

property pk: str | None

Return the primary key of the model. This is the value of the Arn attribute.

Returns:

The primary key of the model instance.

property tags: TagsDict

Get the tags for the model instance.

Returns:

The tags for the model instance.

Managers

Managers work with the primary models to provide a high-level interface to the AWS service. They are responsible for creating, updating, and deleting the resources in the service, as well as any additional operations that are available for those models.

class botocraft.services.logs.LogGroupManager

Bases: LogGroupManagerMixin, Boto3ModelManager

create(model: LogGroup, tags: dict[str, str] | None = None) → None

Creates a log group with the specified name. You can create up to 1,000,000 log groups per Region per account.

Parameters:

model – The LogGroup to create.

Keyword Arguments:

tags – The key-value pairs to use for the tags.

delete(logGroupName: str) → None

Deletes the specified log group and permanently deletes all the archived log events associated with the log group.

Parameters:

logGroupName – The name of the log group.

get(logGroupIdentifier: str, *, accountIdentifiers: list[str] | None = None, logGroupNamePattern: str | None = None, limit: int | None = None, includeLinkedAccounts: bool | None = None) → LogGroup | None

Returns information about log groups, including data sources that ingest into each log group. You can return all your log groups or filter the results by prefix. The results are ASCII-sorted by log group name.

Parameters:

logGroupIdentifier – The identifier of the log group to get. If this is in the same account you are querying, you can use the log group name, if you also set ``includeLinkedAccounts`` to ``true``, you must use the log group ARN.

Keyword Arguments:

• accountIdentifiers – When includeLinkedAccounts is set to true, use this parameter to specify the list of accounts to search. You can specify as many as 20 account IDs in the array.

• logGroupNamePattern – If you specify a string for this parameter, the operation returns only log groups that have names that match the string based on a case-sensitive substring search. For example, if you specify DataLogs, log groups named DataLogs, aws/DataLogs, and GroupDataLogs would match, but datalogs, Data/log/s and Groupdata would not match.

• limit – The maximum number of items returned. If you don’t specify a value, the default is up to 50 items.

• includeLinkedAccounts – If you are using a monitoring account, set this to true to have the operation return log groups in the accounts listed in accountIdentifiers.

get_fields(*, logGroupName: str | None = None, time: int | None = None, logGroupIdentifier: str | None = None) → list[botocraft.services.logs.LogGroupField]

Returns a list of the fields that are included in log events in the specified log group. Includes the percentage of log events that contain each field. The search is limited to a time period that you specify.

Keyword Arguments:

• logGroupName – The name of the log group to search.

• time – The time to set as the center of the query. If you specify time, the 8 minutes before and 8 minutes after this time are searched. If you omit time, the most recent 15 minutes up to the current time are searched.

• logGroupIdentifier – Specify either the name or ARN of the log group to view. If the log group is in a source account and you are using a monitoring account, you must specify the ARN.

list(*, accountIdentifiers: list[str] | None = None, logGroupNamePrefix: str | None = None, logGroupNamePattern: str | None = None, limit: int | None = None, includeLinkedAccounts: bool | None = None, logGroupClass: Literal['STANDARD', 'INFREQUENT_ACCESS', 'DELIVERY'] | None = None, logGroupIdentifiers: list[str] | None = None) → PrimaryBoto3ModelQuerySet

Returns information about log groups, including data sources that ingest into each log group. You can return all your log groups or filter the results by prefix. The results are ASCII-sorted by log group name.

Keyword Arguments:

• accountIdentifiers – When includeLinkedAccounts is set to true, use this parameter to specify the list of accounts to search. You can specify as many as 20 account IDs in the array.

• logGroupNamePrefix – The prefix to match.

• logGroupNamePattern – If you specify a string for this parameter, the operation returns only log groups that have names that match the string based on a case-sensitive substring search. For example, if you specify DataLogs, log groups named DataLogs, aws/DataLogs, and GroupDataLogs would match, but datalogs, Data/log/s and Groupdata would not match.

• limit – The maximum number of items returned. If you don’t specify a value, the default is up to 50 items.

• includeLinkedAccounts – If you are using a monitoring account, set this to true to have the operation return log groups in the accounts listed in accountIdentifiers.

• logGroupClass – Use this parameter to limit the results to only those log groups in the specified log group class. If you omit this parameter, log groups of all classes can be returned.

• logGroupIdentifiers – Use this array to filter the list of log groups returned. If you specify this parameter, the only other filter that you can choose to specify is includeLinkedAccounts.

service_name: str = 'logs'

ec2, s3, etc.

Type:

The name of the boto3 service. Example

Secondary Models

Secondary models are models that are used by the primary models to organize their data. They are not acted on directly, but are used to describe the structure of the fields in the primary models or other secondary models.

Request/Response Models

Request/response models are models that are used to describe the structure of the data that is sent to and received from the AWS service. They are used by the managers to send requests to the service and to parse the responses that are received.

You will not often use them directly – typically they are used by the managers internally to send requests and parse responses – but they are included here for completeness, and because occasionally we return them directly to you because they have some useful additional information.

pydantic model botocraft.services.logs.DescribeLogGroupsResponse

Bases: Boto3Model

Show JSON schema

{
   "title": "DescribeLogGroupsResponse",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "logGroups": {
         "anyOf": [
            {
               "items": {
                  "$ref": "#/$defs/LogGroup"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Loggroups"
      },
      "nextToken": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Nexttoken"
      }
   },
   "$defs": {
      "LogGroup": {
         "description": "Represents a log group.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "arn": {
               "default": null,
               "title": "Arn",
               "type": "string"
            },
            "logGroupName": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Loggroupname"
            },
            "creationTime": {
               "default": null,
               "title": "Creationtime",
               "type": "integer"
            },
            "retentionInDays": {
               "default": null,
               "title": "Retentionindays",
               "type": "integer"
            },
            "metricFilterCount": {
               "default": null,
               "title": "Metricfiltercount",
               "type": "integer"
            },
            "storedBytes": {
               "default": null,
               "title": "Storedbytes",
               "type": "integer"
            },
            "kmsKeyId": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Kmskeyid"
            },
            "dataProtectionStatus": {
               "default": null,
               "enum": [
                  "ACTIVATED",
                  "DELETED",
                  "ARCHIVED",
                  "DISABLED"
               ],
               "title": "Dataprotectionstatus",
               "type": "string"
            },
            "inheritedProperties": {
               "items": {
                  "const": "ACCOUNT_DATA_PROTECTION",
                  "type": "string"
               },
               "title": "Inheritedproperties",
               "type": "array"
            },
            "logGroupClass": {
               "anyOf": [
                  {
                     "enum": [
                        "STANDARD",
                        "INFREQUENT_ACCESS",
                        "DELIVERY"
                     ],
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Loggroupclass"
            },
            "logGroupArn": {
               "default": null,
               "title": "Loggrouparn",
               "type": "string"
            },
            "deletionProtectionEnabled": {
               "anyOf": [
                  {
                     "type": "boolean"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Deletionprotectionenabled"
            },
            "bearerTokenAuthenticationEnabled": {
               "default": null,
               "title": "Bearertokenauthenticationenabled",
               "type": "boolean"
            },
            "Tags": {
               "anyOf": [
                  {
                     "items": {
                        "$ref": "#/$defs/Tag"
                     },
                     "type": "array"
                  },
                  {
                     "type": "null"
                  }
               ],
               "title": "Tags"
            }
         },
         "title": "LogGroup",
         "type": "object"
      },
      "Tag": {
         "description": "The metadata that you apply to a resource to help you categorize and\norganize them. Each tag consists of a key and an optional value. You define\nthem.\n\nThe following basic restrictions apply to tags:\n\n* Maximum number of tags per resource - 50\n* For each resource, each tag key must be unique, and each tag key can have\n  only one value.\n* Maximum key length - 128 Unicode characters in UTF-8\n* Maximum value length - 256 Unicode characters in UTF-8\n* If your tagging schema is used across multiple services and resources,\n  remember that other services may have restrictions on allowed characters.\n  Generally allowed characters are: letters, numbers, and spaces representable in\n  UTF-8, and the following characters: + - = . _ : / @.\n* Tag keys and values are case-sensitive.\n* Do not use ``aws:``, ``AWS:``, or any upper or lowercase combination of such\n  as a prefix for either keys or values as it is reserved for Amazon Web Services\n  use. You cannot edit or delete tag keys or values with this prefix. Tags with\n  this prefix do not count against your tags per resource limit.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "Key": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Key"
            },
            "Value": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Value"
            }
         },
         "title": "Tag",
         "type": "object"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• logGroups (list[botocraft.services.logs.LogGroup] | None)

• nextToken (str | None)

• session (Any | None)

field logGroups: builtins.list[LogGroup] | None [Optional]

An array of structures, where each structure contains the information about one log group.

field nextToken: str | None = None

The token for the next set of items to return.

The token expires after 24 hours.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.logs.GetLogGroupFieldsResponse

Bases: Boto3Model

Show JSON schema

{
   "title": "GetLogGroupFieldsResponse",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "logGroupFields": {
         "anyOf": [
            {
               "items": {
                  "$ref": "#/$defs/LogGroupField"
               },
               "type": "array"
            },
            {
               "type": "null"
            }
         ],
         "title": "Loggroupfields"
      }
   },
   "$defs": {
      "LogGroupField": {
         "description": "The fields contained in log events found by a ``GetLogGroupFields`` operation, along\nwith the percentage of queried log events in which each field appears.",
         "properties": {
            "session": {
               "anyOf": [
                  {},
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Session"
            },
            "name": {
               "anyOf": [
                  {
                     "type": "string"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Name"
            },
            "percent": {
               "anyOf": [
                  {
                     "type": "integer"
                  },
                  {
                     "type": "null"
                  }
               ],
               "default": null,
               "title": "Percent"
            }
         },
         "title": "LogGroupField",
         "type": "object"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• logGroupFields (list[botocraft.services.logs.LogGroupField] | None)

• session (Any | None)

field logGroupFields: builtins.list[LogGroupField] | None [Optional]

The array of fields found in the query.

Each object in the array contains the name of the field, along with the percentage of time it appeared in the log events that were queried.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.

pydantic model botocraft.services.logs.LogGroupField

Bases: Boto3Model

The fields contained in log events found by a GetLogGroupFields operation, along with the percentage of queried log events in which each field appears.

Show JSON schema

{
   "title": "LogGroupField",
   "description": "The fields contained in log events found by a ``GetLogGroupFields`` operation, along\nwith the percentage of queried log events in which each field appears.",
   "type": "object",
   "properties": {
      "session": {
         "anyOf": [
            {},
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Session"
      },
      "name": {
         "anyOf": [
            {
               "type": "string"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Name"
      },
      "percent": {
         "anyOf": [
            {
               "type": "integer"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "title": "Percent"
      }
   }
}

Config:

• validate_assignment: bool = True

• arbitrary_types_allowed: bool = True

Fields:

• name (str | None)

• percent (int | None)

• session (Any | None)

field name: str | None = None

The name of a log field.

field percent: int | None = None

The percentage of log events queried that contained the field.

field session: Any | None = None

The boto3 session to use for this model. This is set by the manager, and is used in relationships. We have to use Any here because we pydantic complains vociferously if we use boto3.session.Session. We exclude it from the model dump because it’s not something that should be serialized.

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → Self

Creates a new instance of the Model class with validated data.

Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.

!!! note

model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.

Parameters:

• _fields_set – A set of field names that were originally explicitly set during instantiation. If provided, this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.

• values – Trusted or pre-validated data dictionary.

Returns:

A new instance of the Model class with validated data.

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → Self

Validate the given object with string data against the Pydantic model.

Parameters:

• obj – The object containing string data to validate.

• strict – Whether to enforce types strictly.

• context – Extra variables to pass to the validator.

• by_alias – Whether to use the field’s alias when validating against the provided input data.

• by_name – Whether to use the field’s name when validating against the provided input data.

Returns:

The validated Pydantic model.

set_session(session: Session) → None

Set the boto3 session for this model.

Parameters:

session – The boto3 session to use.

Returns:

The model instance.

transform(attribute: str, transformer: str | None) → Any

Transform an attribute using a regular expression into something else before it is returned.

Important

This only makes sense for attributes that are strings.

transformer is a regular expression that will be used to transform the value of the attribute.

• If the attribute is None, it will be returned verbatim.

• If transformer is None, the attribute will be returned verbatim.

• If transformer has no named groups, the attribute will be replaced with the value of the first group.

• If transformer has named groups, the attribute will be replaced with a dictionary of the named groups.

Raises:

• ValueError – If the attribute does not exist on the model.

• RuntimeError – If the transformer fails to match the attribute value.

Parameters:

• attribute – The attribute to transform.

• transformer – The regular expression to use to transform the attribute.

Returns:

The transformed attribute.