pixano.app.models.base_schema

BaseSchemaModel(created_at=None, updated_at=None, **data)

Bases: BaseModel, Generic[T]

Base schema model.

This class is a base class for all schema models. It provides methods to convert a row to a model and vice versa.

Attributes:

Name	Type	Description
id	str	Unique identifier of the row.
created_at	datetime	The creation date of the row.
updated_at	datetime	The last modification date of the row.
table_info	TableInfo	Information about the table to which the row belongs.
data	dict[str, Any]	Dumped data from the Pixano backend row except the id.

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

self is explicitly positional-only to allow self as a field name.

Parameters:

Name	Type	Description	Default
created_at	datetime | None	The creation date of the object.	None
updated_at	datetime | None	The last modification date of the object.	None
data	Any	The data of the object validated by Pydantic.	{}

Source code in pixano/app/models/base_schema.py

def __init__(self, /, created_at: datetime | None = None, updated_at: datetime | None = None, **data: Any):
    """Create a new model by parsing and validating input data from keyword arguments.

    Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
    validated to form a valid model.

    `self` is explicitly positional-only to allow `self` as a field name.

    Args:
        created_at: The creation date of the object.
        updated_at: The last modification date of the object.
        data: The data of the object validated by Pydantic.
    """
    created_at, updated_at = validate_and_init_create_at_and_update_at(created_at, updated_at)
    data.update({"created_at": created_at, "updated_at": updated_at})
    super().__init__(**data)

from_row(row, table_info) classmethod

Create a model from a row.

Parameters:

Name	Type	Description	Default
row	T	The row to create the model from.	required
table_info	TableInfo	The table info of the row.	required

Returns:

Type	Description
Self	The created model.

Source code in pixano/app/models/base_schema.py

@classmethod
def from_row(cls, row: T, table_info: TableInfo) -> Self:
    """Create a model from a row.

    Args:
        row: The row to create the model from.
        table_info: The table info of the row.

    Returns:
        The created model.
    """
    model_dict = {}
    data = {}
    for key, value in row.model_dump().items():
        if key in ["id", "created_at", "updated_at"]:
            model_dict[key] = value
            continue
        data[key] = value
    model_dict["data"] = data
    model_dict["table_info"] = table_info

    return cls.model_validate(model_dict)

from_rows(rows, table_info) classmethod

Create a list of models from a list of schemas.

Parameters:

Name	Type	Description	Default
rows	list[T]	The rows to create the models from.	required
table_info	TableInfo	The table info of the rows.	required

Returns:

Type	Description
list[Self]	The list of created models.

Source code in pixano/app/models/base_schema.py

@classmethod
def from_rows(cls, rows: list[T], table_info: TableInfo) -> list[Self]:
    """Create a list of models from a list of schemas.

    Args:
        rows: The rows to create the models from.
        table_info: The table info of the rows.

    Returns:
        The list of created models.
    """
    return [cls.from_row(row, table_info) for row in rows]

model_dump(exclude_timestamps=False, **kwargs)

Dump the model to a dictionary.

Parameters:

Name	Type	Description	Default
exclude_timestamps	bool	Exclude timestamps "created_at" and "updated_at" from the model dump. Useful for comparing models without timestamps.	False
kwargs	Any	Arguments for pydantic BaseModel.model_dump().	{}

Returns:

Type	Description
dict[str, Any]	The model dump.

Source code in pixano/app/models/base_schema.py

def model_dump(self, exclude_timestamps: bool = False, **kwargs: Any) -> dict[str, Any]:
    """Dump the model to a dictionary.

    Args:
        exclude_timestamps: Exclude timestamps "created_at" and "updated_at" from the model dump. Useful for
            comparing models without timestamps.
        kwargs: Arguments for pydantic `BaseModel.model_dump()`.

    Returns:
        The model dump.
    """
    model_dump = super().model_dump(**kwargs)
    if exclude_timestamps:
        model_dump.pop("created_at", None)
        model_dump.pop("updated_at", None)
    return model_dump

to_row(dataset)

Create a row from the model.

Parameters:

Name	Type	Description	Default
dataset	Dataset	The dataset of the row.	required

Returns:

Type	Description
T	The created row.

Source code in pixano/app/models/base_schema.py

def to_row(self, dataset: Dataset) -> T:
    """Create a row from the model.

    Args:
        dataset: The dataset of the row.

    Returns:
        The created row.
    """
    schema_dict = self.model_dump()
    schema = dataset.schema.schemas[self.table_info.name]
    row = schema.model_validate(
        {
            "id": schema_dict["id"],
            "created_at": schema_dict["created_at"],
            "updated_at": schema_dict["updated_at"],
            **schema_dict["data"],
        }
    )
    row.dataset = dataset
    row.table_name = self.table_info.name
    return row

to_rows(models, dataset) staticmethod

Create a list of rows from a list of models.

Parameters:

Name	Type	Description	Default
models	list[BaseSchemaModel]	The models to create the rows from.	required
dataset	Dataset	The dataset of the row.	required

Returns:

Type	Description
list[T]	The list of created rows.

Source code in pixano/app/models/base_schema.py

@staticmethod
def to_rows(models: list["BaseSchemaModel"], dataset: Dataset) -> list[T]:
    """Create a list of rows from a list of models.

    Args:
        models: The models to create the rows from.
        dataset: The dataset of the row.

    Returns:
        The list of created rows.
    """
    return [model.to_row(dataset) for model in models]