pyiem.models package

Submodules

pyiem.models.cwa module

Data Model for CWA.

class pyiem.models.cwa.CWAModel(*, center: str, expire: datetime, geom: Polygon, issue: datetime, is_corrected: bool, narrative: str, num: int)

Bases: BaseModel

A Center Weather Advisory.

center: str

expire: datetime

geom: Polygon

is_corrected: bool

issue: datetime

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

narrative: str

num: int

pyiem.models.gairmet module

Data Model for GAIRMET.

class pyiem.models.gairmet.AIRMETRecord(*, gml_id: str, label: str, status: str, hazard_type: str, valid_at: datetime, weather_conditions: List[str], geom: Polygon)

Bases: BaseModel

A single AIRMET Record.

geom: Polygon

gml_id: str

hazard_type: str

label: str

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

status: str

valid_at: datetime

weather_conditions: List[str]

class pyiem.models.gairmet.FreezingLevelRecord(*, gml_id: str, valid_at: datetime, geom: MultiLineString, level: int | None = None, lower_level: int, upper_level: int)

Bases: BaseModel

A single FreezingLevel Record.

geom: MultiLineString

gml_id: str

level: int | None

lower_level: int

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

upper_level: int

valid_at: datetime

class pyiem.models.gairmet.GAIRMETModel(*, valid_from: ~datetime.datetime, valid_to: ~datetime.datetime, issuetime: ~datetime.datetime, airmets: ~typing.List[~pyiem.models.gairmet.AIRMETRecord] = <factory>, freezing_levels: ~typing.List[~pyiem.models.gairmet.FreezingLevelRecord] = <factory>)

Bases: BaseModel

A G-AIRMET.

airmets: List[AIRMETRecord]

freezing_levels: List[FreezingLevelRecord]

issuetime: datetime

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

valid_from: datetime

valid_to: datetime

pyiem.models.sel module

Pydantic data model for SPC Watch (SEL).

class pyiem.models.sel.SELModel(*, typ: str, num: int)

Bases: BaseModel

SPC Watch Probability.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

num: int

typ: str

pyiem.models.shef module

SHEF Data Model.

class pyiem.models.shef.SHEFElement(*, station: str, basevalid: datetime, valid: datetime, dv_interval: timedelta | None = None, physical_element: str | None = None, duration: str | None = None, type: str = 'R', source: str = 'Z', extremum: str = 'Z', probability: str = 'Z', str_value: str = '', num_value: float | None = None, data_created: datetime | None = None, depth: Annotated[int | None, Ge(ge=0), Le(le=32767)] = None, unit_convention: str = 'E', qualifier: str | None = None, comment: str | None = None, narrative: str | None = None, raw: str | None = None)

Bases: BaseModel

A PEDTSEP Element.

basevalid: datetime

comment: str | None

consume_code(text: str) → None

Fill out element based on provided text.

data_created: datetime | None

depth: int | None

duration: str | None

dv_interval: timedelta | None

extremum: str

lonlat() → tuple[float | None, float | None]

For ‘Stranger Locations’, return longitude and latitude.

model_config: ClassVar[ConfigDict] = {'validate_assignment': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

narrative: str | None

num_value: float | None

physical_element: str | None

probability: str

qualifier: str | None

raw: str | None

source: str

station: str

str_value: str

to_english() → float

Return an English value representation.

Implementation Note: In the case of wind direction (UH, UR), this returns the un-scaled value.

type: str

unit_convention: str

valid: datetime

varname() → str | None

Return the Full SHEF Code.

pyiem.models.taf module

TAF Data Model.

class pyiem.models.taf.SkyCondition(*, amount: str, level: Annotated[int | None, Ge(ge=0), Le(le=100000)] = None)

Bases: BaseModel

The Sky condition.

amount: str

level: int | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class pyiem.models.taf.TAFForecast(*, valid: ~datetime.datetime, raw: str, ftype: ~typing.Annotated[int, ~annotated_types.Ge(ge=0), ~annotated_types.Le(le=5)], end_valid: ~datetime.datetime | None = None, sknt: ~typing.Annotated[int | None, ~annotated_types.Ge(ge=0), ~annotated_types.Le(le=199)] = None, drct: ~typing.Annotated[int | None, ~annotated_types.Ge(ge=0), ~annotated_types.Le(le=360)] = None, gust: ~typing.Annotated[int | None, ~annotated_types.Ge(ge=0), ~annotated_types.Le(le=199)] = None, visibility: ~typing.Annotated[float | None, ~annotated_types.Ge(ge=0), ~annotated_types.Le(le=6)] = None, presentwx: ~typing.List[str] = <factory>, sky: ~typing.List[~pyiem.models.taf.SkyCondition] = <factory>, shear: ~pyiem.models.taf.WindShear | None = None)

Bases: BaseModel

A TAF forecast.

drct: int | None

end_valid: datetime | None

ftype: int

gust: int | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

presentwx: List[str]

raw: str

shear: WindShear | None

sknt: int | None

sky: List[SkyCondition]

valid: datetime

visibility: float | None

class pyiem.models.taf.TAFReport(*, station: ~typing.Annotated[str, ~annotated_types.MinLen(min_length=4), ~annotated_types.MaxLen(max_length=4)], valid: ~datetime.datetime, product_id: ~typing.Annotated[str, ~annotated_types.MinLen(min_length=28), ~annotated_types.MaxLen(max_length=35)], observation: ~pyiem.models.taf.TAFForecast, forecasts: ~typing.List[~pyiem.models.taf.TAFForecast] = <factory>)

Bases: BaseModel

A TAF Report consisting of forecasts.

forecasts: List[TAFForecast]

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

observation: TAFForecast

product_id: str

station: str

valid: datetime

class pyiem.models.taf.WindShear(*, level: Annotated[int, Ge(ge=0), Le(le=100000)], drct: Annotated[int, Ge(ge=0), Le(le=360)], sknt: Annotated[int, Ge(ge=0), Le(le=199)])

Bases: BaseModel

A Wind Shear Value.

drct: int

level: int

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

sknt: int

pyiem.models.wwp module

Pydantic data model for SPC Watch Probabilities (WWP).

class pyiem.models.wwp.WWPModel(*, typ: str, num: int, tornadoes_2m: int | None = None, tornadoes_1m_strong: int | None = None, wind_10m: int | None = None, wind_1m_65kt: int | None = None, hail_10m: int | None = None, hail_1m_2inch: int | None = None, hail_wind_6m: int | None = None, max_hail_size: float | None = None, max_wind_gust_knots: int | None = None, max_tops_feet: int | None = None, storm_motion_drct: int | None = None, storm_motion_sknt: int | None = None, is_pds: bool)

Bases: BaseModel

SPC Watch Probability.

hail_10m: int | None

hail_1m_2inch: int | None

hail_wind_6m: int | None

is_pds: bool

max_hail_size: float | None

max_tops_feet: int | None

max_wind_gust_knots: int | None

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

num: int

storm_motion_drct: int | None

storm_motion_sknt: int | None

tornadoes_1m_strong: int | None

tornadoes_2m: int | None

typ: str

wind_10m: int | None

wind_1m_65kt: int | None

Module contents

pyiem data models.