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Module tifeatures.dbmodel

tifeatures.dbmodel: database events.

Variables

Database

Functions

get_table_index

def get_table_index(
    db_pool: buildpg.asyncpg.BuildPgPool,
    schemas: Union[List[str], NoneType] = ['public'],
    tables: Union[List[str], NoneType] = None,
    spatial: bool = True
) -> Dict[str, Dict[str, Any]]

Fetch Table index.

Classes

Column

class Column(
    __pydantic_self__,
    **data: Any
)

Model for database Column.

Ancestors (in MRO)

  • pydantic.main.BaseModel
  • pydantic.utils.Representation

Descendants

  • tifeatures.dbmodel.GeometryColumn
  • tifeatures.dbmodel.DatetimeColumn

Class variables

Config

Static methods

construct

def construct(
    _fields_set: Union[ForwardRef('SetStr'), NoneType] = None,
    **values: Any
) -> 'Model'

Creates a new model setting dict and fields_set from trusted or pre-validated data.

Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

from_orm

def from_orm(
    obj: Any
) -> 'Model'

parse_file

def parse_file(
    path: Union[str, pathlib.Path],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: Any
) -> 'Model'

parse_raw

def parse_raw(
    b: Union[str, bytes],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

schema

def schema(
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}'
) -> 'DictStrAny'

schema_json

def schema_json(
    *,
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}',
    **dumps_kwargs: Any
) -> 'unicode'

update_forward_refs

def update_forward_refs(
    **localns: Any
) -> None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate

def validate(
    value: Any
) -> 'Model'

Instance variables

json_type

Return JSON field type.

Methods

copy

def copy(
    self: 'Model',
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    update: Union[ForwardRef('DictStrAny'), NoneType] = None,
    deep: bool = False
) -> 'Model'

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

Name Type Description Default
include None fields to include in new model None
exclude None fields to exclude from new model, as with values this takes precedence over include None
update None values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
None
deep None set to True to make a deep copy of the model None

Returns:

Type Description
None new model instance

dict

def dict(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    by_alias: bool = False,
    skip_defaults: Union[bool, NoneType] = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False
) -> 'DictStrAny'

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

json

def json(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    by_alias: bool = False,
    skip_defaults: Union[bool, NoneType] = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    encoder: Union[Callable[[Any], Any], NoneType] = None,
    models_as_dict: bool = True,
    **dumps_kwargs: Any
) -> 'unicode'

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

DatetimeColumn

class DatetimeColumn(
    __pydantic_self__,
    **data: Any
)

Model for PostGIS geometry/geography column.

Ancestors (in MRO)

  • tifeatures.dbmodel.Column
  • pydantic.main.BaseModel
  • pydantic.utils.Representation

Class variables

Config

Static methods

construct

def construct(
    _fields_set: Union[ForwardRef('SetStr'), NoneType] = None,
    **values: Any
) -> 'Model'

Creates a new model setting dict and fields_set from trusted or pre-validated data.

Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

from_orm

def from_orm(
    obj: Any
) -> 'Model'

parse_file

def parse_file(
    path: Union[str, pathlib.Path],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: Any
) -> 'Model'

parse_raw

def parse_raw(
    b: Union[str, bytes],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

schema

def schema(
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}'
) -> 'DictStrAny'

schema_json

def schema_json(
    *,
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}',
    **dumps_kwargs: Any
) -> 'unicode'

update_forward_refs

def update_forward_refs(
    **localns: Any
) -> None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate

def validate(
    value: Any
) -> 'Model'

Instance variables

json_type

Return JSON field type.

Methods

copy

def copy(
    self: 'Model',
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    update: Union[ForwardRef('DictStrAny'), NoneType] = None,
    deep: bool = False
) -> 'Model'

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

Name Type Description Default
include None fields to include in new model None
exclude None fields to exclude from new model, as with values this takes precedence over include None
update None values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
None
deep None set to True to make a deep copy of the model None

Returns:

Type Description
None new model instance

dict

def dict(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    by_alias: bool = False,
    skip_defaults: Union[bool, NoneType] = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False
) -> 'DictStrAny'

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

json

def json(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    by_alias: bool = False,
    skip_defaults: Union[bool, NoneType] = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    encoder: Union[Callable[[Any], Any], NoneType] = None,
    models_as_dict: bool = True,
    **dumps_kwargs: Any
) -> 'unicode'

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

GeometryColumn

class GeometryColumn(
    __pydantic_self__,
    **data: Any
)

Model for PostGIS geometry/geography column.

Ancestors (in MRO)

  • tifeatures.dbmodel.Column
  • pydantic.main.BaseModel
  • pydantic.utils.Representation

Class variables

Config

Static methods

construct

def construct(
    _fields_set: Union[ForwardRef('SetStr'), NoneType] = None,
    **values: Any
) -> 'Model'

Creates a new model setting dict and fields_set from trusted or pre-validated data.

Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

from_orm

def from_orm(
    obj: Any
) -> 'Model'

parse_file

def parse_file(
    path: Union[str, pathlib.Path],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: Any
) -> 'Model'

parse_raw

def parse_raw(
    b: Union[str, bytes],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

schema

def schema(
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}'
) -> 'DictStrAny'

schema_json

def schema_json(
    *,
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}',
    **dumps_kwargs: Any
) -> 'unicode'

update_forward_refs

def update_forward_refs(
    **localns: Any
) -> None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate

def validate(
    value: Any
) -> 'Model'

Instance variables

json_type

Return JSON field type.

Methods

copy

def copy(
    self: 'Model',
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    update: Union[ForwardRef('DictStrAny'), NoneType] = None,
    deep: bool = False
) -> 'Model'

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

Name Type Description Default
include None fields to include in new model None
exclude None fields to exclude from new model, as with values this takes precedence over include None
update None values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
None
deep None set to True to make a deep copy of the model None

Returns:

Type Description
None new model instance

dict

def dict(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    by_alias: bool = False,
    skip_defaults: Union[bool, NoneType] = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False
) -> 'DictStrAny'

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

json

def json(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    by_alias: bool = False,
    skip_defaults: Union[bool, NoneType] = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    encoder: Union[Callable[[Any], Any], NoneType] = None,
    models_as_dict: bool = True,
    **dumps_kwargs: Any
) -> 'unicode'

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

Table

class Table(
    __pydantic_self__,
    **data: Any
)

Model for DB Table.

Ancestors (in MRO)

  • pydantic.main.BaseModel
  • pydantic.utils.Representation

Descendants

  • tifeatures.layer.Table

Class variables

Config

Static methods

construct

def construct(
    _fields_set: Union[ForwardRef('SetStr'), NoneType] = None,
    **values: Any
) -> 'Model'

Creates a new model setting dict and fields_set from trusted or pre-validated data.

Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

from_orm

def from_orm(
    obj: Any
) -> 'Model'

parse_file

def parse_file(
    path: Union[str, pathlib.Path],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: Any
) -> 'Model'

parse_raw

def parse_raw(
    b: Union[str, bytes],
    *,
    content_type: 'unicode' = None,
    encoding: 'unicode' = 'utf8',
    proto: pydantic.parse.Protocol = None,
    allow_pickle: bool = False
) -> 'Model'

schema

def schema(
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}'
) -> 'DictStrAny'

schema_json

def schema_json(
    *,
    by_alias: bool = True,
    ref_template: 'unicode' = '#/definitions/{model}',
    **dumps_kwargs: Any
) -> 'unicode'

update_forward_refs

def update_forward_refs(
    **localns: Any
) -> None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate

def validate(
    value: Any
) -> 'Model'

Instance variables

id_column_info

Return Column for a unique identifier.

Methods

columns

def columns(
    self,
    properties: Union[List[str], NoneType] = None
) -> List[str]

Return table columns optionally filtered to only include columns from properties.

copy

def copy(
    self: 'Model',
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    update: Union[ForwardRef('DictStrAny'), NoneType] = None,
    deep: bool = False
) -> 'Model'

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

Name Type Description Default
include None fields to include in new model None
exclude None fields to exclude from new model, as with values this takes precedence over include None
update None values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
None
deep None set to True to make a deep copy of the model None

Returns:

Type Description
None new model instance

dict

def dict(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    by_alias: bool = False,
    skip_defaults: Union[bool, NoneType] = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False
) -> 'DictStrAny'

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

get_column

def get_column(
    self,
    property_name: str
) -> Union[tifeatures.dbmodel.Column, NoneType]

Return column info.

get_datetime_column

def get_datetime_column(
    self,
    name: Union[str, NoneType] = None
) -> Union[tifeatures.dbmodel.Column, NoneType]

Return the Column for either the passed in tstz column or the first tstz column.

get_geometry_column

def get_geometry_column(
    self,
    name: Union[str, NoneType] = None
) -> Union[tifeatures.dbmodel.GeometryColumn, NoneType]

Return the name of the first geometry column.

json

def json(
    self,
    *,
    include: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    exclude: Union[ForwardRef('AbstractSetIntStr'), ForwardRef('MappingIntStrAny'), NoneType] = None,
    by_alias: bool = False,
    skip_defaults: Union[bool, NoneType] = None,
    exclude_unset: bool = False,
    exclude_defaults: bool = False,
    exclude_none: bool = False,
    encoder: Union[Callable[[Any], Any], NoneType] = None,
    models_as_dict: bool = True,
    **dumps_kwargs: Any
) -> 'unicode'

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().