Module `lum.odinson.rest.requests`

Expand source code

from __future__ import annotations
import typing
from pydantic import BaseModel, ConfigDict


__all__ = ["GrammarRequest", "SimplePatternsRequest"]


class GrammarRequest(BaseModel):
    grammar: str
    metadataQuery: typing.Optional[str] = None
    maxDocs: typing.Optional[int] = None
    allowTriggerOverlaps: typing.Optional[bool] = None
    pretty: typing.Optional[bool] = None

    def model_dump(self, by_alias=True, **kwargs):
        return super().model_dump(by_alias=by_alias, **kwargs)

    def model_dump_json(self, by_alias=True, **kwargs):
        return super().model_dump_json(by_alias=by_alias, **kwargs)

    def dict(self, **kwargs):
        return self.model_dump(**kwargs)

    def json(self, **kwargs):
        return self.model_dump_json(**kwargs)


class SimplePatternsRequest(BaseModel):
    patterns: list[str]
    metadataQuery: typing.Optional[str] = None
    prevDoc: typing.Optional[int] = None
    prevScore: typing.Optional[float] = None
    enriched: typing.Optional[bool] = None
    pretty: typing.Optional[bool] = None

    def model_dump(self, by_alias=True, **kwargs):
        return super().model_dump(by_alias=by_alias, **kwargs)

    def model_dump_json(self, by_alias=True, **kwargs):
        return super().model_dump_json(by_alias=by_alias, **kwargs)

    def dict(self, **kwargs):
        return self.model_dump(**kwargs)

    def json(self, **kwargs):
        return self.model_dump_json(**kwargs)

Classes

class GrammarRequest (**data: Any)

A base model class for creating Pydantic models.

Attributes

model_config: Configuration settings for the model.
model_fields: Metadata about the fields defined on the model. This replaces Model.__fields__ from Pydantic V1.
__class_vars__: The names of classvars defined on the model.
__private_attributes__: Metadata about the private attributes of the model.
__signature__: The signature for instantiating the model.
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.
__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.
__pydantic_custom_init__: Whether the model has a custom __init__ function.
__pydantic_decorators__: Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.
__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to args, origin, parameters in typing-module generics. May eventually be replaced by these.
__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.
__pydantic_post_init__: The name of the post-init method for the model, if defined.
__pydantic_root_model__: Whether the model is a RootModel.
__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.
__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.
__pydantic_extra__: An instance attribute with the values of extra fields from validation when model_config['extra'] == 'allow'.
__pydantic_fields_set__: An instance attribute with the names of fields explicitly specified during validation.
__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

Uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Expand source code

class GrammarRequest(BaseModel):
    grammar: str
    metadataQuery: typing.Optional[str] = None
    maxDocs: typing.Optional[int] = None
    allowTriggerOverlaps: typing.Optional[bool] = None
    pretty: typing.Optional[bool] = None

    def model_dump(self, by_alias=True, **kwargs):
        return super().model_dump(by_alias=by_alias, **kwargs)

    def model_dump_json(self, by_alias=True, **kwargs):
        return super().model_dump_json(by_alias=by_alias, **kwargs)

    def dict(self, **kwargs):
        return self.model_dump(**kwargs)

    def json(self, **kwargs):
        return self.model_dump_json(**kwargs)

Ancestors

pydantic.main.BaseModel

Class variables

var allowTriggerOverlaps : Optional[bool]
var grammar : str
var maxDocs : Optional[int]
var metadataQuery : Optional[str]
var model_config
var model_fields
var pretty : Optional[bool]

Methods

def dict(self, **kwargs)

Expand source code

def dict(self, **kwargs):
    return self.model_dump(**kwargs)

def json(self, **kwargs)

Expand source code

def json(self, **kwargs):
    return self.model_dump_json(**kwargs)

def model_dump(self, by_alias=True, **kwargs)

Usage docs: https://docs.pydantic.dev/dev-v2/usage/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Args

mode: The mode in which to_python should run. If mode is 'json', the dictionary will only contain JSON serializable types. If mode is 'python', the dictionary may contain any Python objects.
include: A list of fields to include in the output.
exclude: A list of fields to exclude from the output.
by_alias: Whether to use the field's alias in the dictionary key if defined.
exclude_unset: Whether to exclude fields that are unset or None from the output.
exclude_defaults: Whether to exclude fields that are set to their default value from the output.
exclude_none: Whether to exclude fields that have a value of None from the output.
round_trip: Whether to enable serialization and deserialization round-trip support.
warnings: Whether to log warnings when invalid fields are encountered.

Returns

A dictionary representation of the model.

Expand source code

def model_dump(self, by_alias=True, **kwargs):
    return super().model_dump(by_alias=by_alias, **kwargs)

def model_dump_json(self, by_alias=True, **kwargs)

Usage docs: https://docs.pydantic.dev/dev-v2/usage/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic's to_json method.

Args

indent: Indentation to use in the JSON output. If None is passed, the output will be compact.
include: Field(s) to include in the JSON output. Can take either a string or set of strings.
exclude: Field(s) to exclude from the JSON output. Can take either a string or set of strings.
by_alias: Whether to serialize using field aliases.
exclude_unset: Whether to exclude fields that have not been explicitly set.
exclude_defaults: Whether to exclude fields that have the default value.
exclude_none: Whether to exclude fields that have a value of None.
round_trip: Whether to use serialization/deserialization between JSON and class instance.
warnings: Whether to show any warnings that occurred during serialization.

Returns

A JSON string representation of the model.

Expand source code

def model_dump_json(self, by_alias=True, **kwargs):
    return super().model_dump_json(by_alias=by_alias, **kwargs)

class SimplePatternsRequest (**data: Any)

A base model class for creating Pydantic models.

Attributes

model_config: Configuration settings for the model.
model_fields: Metadata about the fields defined on the model. This replaces Model.__fields__ from Pydantic V1.
__class_vars__: The names of classvars defined on the model.
__private_attributes__: Metadata about the private attributes of the model.
__signature__: The signature for instantiating the model.
__pydantic_complete__: Whether model building is completed, or if there are still undefined fields.
__pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer.
__pydantic_custom_init__: Whether the model has a custom __init__ function.
__pydantic_decorators__: Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.
__pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to args, origin, parameters in typing-module generics. May eventually be replaced by these.
__pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.
__pydantic_post_init__: The name of the post-init method for the model, if defined.
__pydantic_root_model__: Whether the model is a RootModel.
__pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model.
__pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model.
__pydantic_extra__: An instance attribute with the values of extra fields from validation when model_config['extra'] == 'allow'.
__pydantic_fields_set__: An instance attribute with the names of fields explicitly specified during validation.
__pydantic_private__: Instance attribute with the values of private attributes set on the model instance.

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

Uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Expand source code

class SimplePatternsRequest(BaseModel):
    patterns: list[str]
    metadataQuery: typing.Optional[str] = None
    prevDoc: typing.Optional[int] = None
    prevScore: typing.Optional[float] = None
    enriched: typing.Optional[bool] = None
    pretty: typing.Optional[bool] = None

    def model_dump(self, by_alias=True, **kwargs):
        return super().model_dump(by_alias=by_alias, **kwargs)

    def model_dump_json(self, by_alias=True, **kwargs):
        return super().model_dump_json(by_alias=by_alias, **kwargs)

    def dict(self, **kwargs):
        return self.model_dump(**kwargs)

    def json(self, **kwargs):
        return self.model_dump_json(**kwargs)

Ancestors

pydantic.main.BaseModel

Class variables

var enriched : Optional[bool]
var metadataQuery : Optional[str]
var model_config
var model_fields
var patterns : list[str]
var pretty : Optional[bool]
var prevDoc : Optional[int]
var prevScore : Optional[float]

Methods

def dict(self, **kwargs)

Expand source code

def dict(self, **kwargs):
    return self.model_dump(**kwargs)

def json(self, **kwargs)

Expand source code

def json(self, **kwargs):
    return self.model_dump_json(**kwargs)

def model_dump(self, by_alias=True, **kwargs)

Usage docs: https://docs.pydantic.dev/dev-v2/usage/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Args

mode: The mode in which to_python should run. If mode is 'json', the dictionary will only contain JSON serializable types. If mode is 'python', the dictionary may contain any Python objects.
include: A list of fields to include in the output.
exclude: A list of fields to exclude from the output.
by_alias: Whether to use the field's alias in the dictionary key if defined.
exclude_unset: Whether to exclude fields that are unset or None from the output.
exclude_defaults: Whether to exclude fields that are set to their default value from the output.
exclude_none: Whether to exclude fields that have a value of None from the output.
round_trip: Whether to enable serialization and deserialization round-trip support.
warnings: Whether to log warnings when invalid fields are encountered.

Returns

A dictionary representation of the model.

Expand source code

def model_dump(self, by_alias=True, **kwargs):
    return super().model_dump(by_alias=by_alias, **kwargs)

def model_dump_json(self, by_alias=True, **kwargs)

Usage docs: https://docs.pydantic.dev/dev-v2/usage/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic's to_json method.

Args

indent: Indentation to use in the JSON output. If None is passed, the output will be compact.
include: Field(s) to include in the JSON output. Can take either a string or set of strings.
exclude: Field(s) to exclude from the JSON output. Can take either a string or set of strings.
by_alias: Whether to serialize using field aliases.
exclude_unset: Whether to exclude fields that have not been explicitly set.
exclude_defaults: Whether to exclude fields that have the default value.
exclude_none: Whether to exclude fields that have a value of None.
round_trip: Whether to use serialization/deserialization between JSON and class instance.
warnings: Whether to show any warnings that occurred during serialization.

Returns

A JSON string representation of the model.

Expand source code

def model_dump_json(self, by_alias=True, **kwargs):
    return super().model_dump_json(by_alias=by_alias, **kwargs)