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"""
Module provides tools to deal with Windy's point forecast API.
"""
from dataclasses import dataclass
from datetime import datetime
from enum import Enum
import numpy as np
def _json(value):
try:
return value.json()
except AttributeError:
return value
def _convert_notation(unit):
return unit.replace("-1", "^-1")
class _StrEnum(Enum):
def __init__(self, value):
self._index = len(self.__class__.__members__)
def __lt__(self, other):
if self.__class__ is other.__class__:
return self._index < other._index
return NotImplemented
def __le__(self, other):
if self.__class__ is other.__class__:
return self._index <= other._index
return NotImplemented
def __gt__(self, other):
if self.__class__ is other.__class__:
return self._index > other._index
return NotImplemented
def __ge__(self, other):
if self.__class__ is other.__class__:
return self._index >= other._index
return NotImplemented
def __str__(self):
return self.value
def json(self):
return self.value
class Model(_StrEnum):
"""
Numerical models available for use with point forecast API.
"""
AROME = "arome"
GEOS5 = "geos5"
GFS = "gfs"
GFSWAVE = "gfsWave"
ICONEU = "iconEu"
NAMALASKA = "namAlaska"
NAMCONUS = "namConus"
NAMHAWAII = "namHawaii"
class Level(_StrEnum):
"""
Selectable levels for some of the input parameters that support them.
"""
SURFACE = "surface"
H1000 = "1000h"
H950 = "950h"
H925 = "925h"
H900 = "900h"
H850 = "850h"
H800 = "800h"
H700 = "700h"
H600 = "600h"
H500 = "500h"
H400 = "400h"
H300 = "300h"
H200 = "200h"
H150 = "150h"
def pressure(self):
if self is Level.SURFACE:
raise ValueError
return float(self.value[:-1])
@dataclass
class Request:
"""
Wraps raw JSON request expected by Windy's API.
"""
key: str
lat: float
lon: float
model: Model
parameters: list = None
levels: list = None
def json(self):
body = {
'key': self.key,
'lat': self.lat,
'lon': self.lon,
'model': _json(self.model),
'parameters': self.parameters or [],
}
if self.levels:
body['levels'] = [_json(x) for x in self.levels]
return body
class Prediction:
"""
Predicted values for each of the requested parameters along with their associated time point.
"""
def __init__(self, response, index=0):
self._response = response
self._index = index
@property
def timestamp(self) -> datetime:
return self._response.timestamps[self._index]
@property
def parameters(self) -> tuple:
return self._response.parameters
@property
def levels(self) -> tuple:
return self._response.levels
def __iter__(self):
return iter(self.parameters)
def __getitem__(self, key):
return self._response.values[key][self._index]
class Response:
"""
Wraps raw JSON response from the Windy's API to allow for easier access, converts all values to pint's
Quantities, and converts all timestamps into datetime objects.
Can be used in a for-loop to access all samples via Prediction:
>>> for prediction in response:
>>> print(prediction.timestamp, prediction['temp'])
Otherwise, timestamps list and samples dictionary are available for direct access.
"""
_INTERNAL_FIELDS = ('ts', 'units', 'warning')
def __init__(self, registry, raw):
self.timestamps = [datetime.fromtimestamp(x // 1000) for x in raw['ts']]
count = len(self.timestamps)
split = [tuple(x.split("-")) for x in raw if x not in self._INTERNAL_FIELDS]
self.parameters = tuple({x for x, _ in split})
self.levels = tuple(sorted({Level(x) for _, x in split}))
if 'pressure' in self.parameters:
for level in self.levels:
if level is Level.SURFACE:
continue
raw[f'pressure-{level}'] = [level.pressure() for _ in range(len(self.timestamps))]
units = {x: registry(_convert_notation(raw['units'][f'{x}-surface'])) for x in self.parameters} # Don't guess surface
self.values = {p: [[raw[f'{p}-{l}'][i] for l in self.levels] * units[p] for i in range(count)] for p in self.parameters}
def __len__(self):
return len(self.timestamps)
def predictions(self) -> Prediction:
"""
Yields Prediction for each time point available in this Response.
"""
for index in range(len(self.timestamps)):
yield Prediction(self, index)
def __iter__(self):
return self.predictions()
@dataclass
class PointForecast:
"""
Represents the point forecast endpoint bound to *path*. Once created it can be called with Request object or
with the same arguments that would be used to initialize the Request. The request is made using the passed
*ctx*, which is usually a Windy instance.
"""
path: str
def __call__(self, ctx, *args, **kwargs):
try:
body = args[0].json()
except (IndexError, AttributeError):
body = Request(*args, **kwargs).json()
response = ctx.session.post(ctx.api + self.path, json=body)
response.raise_for_status()
return Response(ctx.registry, response.json())
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