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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
def _json(value):
try:
return value.json()
except AttributeError:
return value
def _convert_notation(unit):
return unit.replace("-1", "^-1")
class _StrEnum(Enum):
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"
@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 EntryView:
"""
Allows to iterate over samples in Response in a zip-like manner, where all parameters for a given time point are
available via item access.
"""
def __init__(self, response, index=0):
self._response = response
self._index = index
def __iter__(self):
return self
def __next__(self):
self._index += 1
if not self:
raise StopIteration
return self
def __bool__(self):
return self._index < len(self)
def __len__(self):
return len(self._response)
@property
def timestamp(self):
"""
Datetime object representing timestamp of the current entry.
"""
return self._response.timestamps[self._index]
def __getitem__(self, key):
return self._response.samples[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 EntryView:
>>> for entry in response:
>>> print(entry.timestamp, entry['temp-surface'])
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']]
self.samples = {}
parameters = ((x, raw['units'][x]) for x in raw if x not in self._INTERNAL_FIELDS)
for parameter, unit in parameters:
self.samples[parameter] = [x * registry(_convert_notation(unit)) for x in raw[parameter]]
def __len__(self):
return len(self.timestamps)
def parameters(self) -> tuple:
"""
All of the available output parameters.
"""
return tuple(self.samples.keys())
def entries(self) -> EntryView:
"""
Helper iterator to go over all of the samples in a zip-like manner.
"""
return EntryView(self)
def __iter__(self):
return self.entries()
@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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