mirror of
https://github.com/jdejaegh/python-irceline.git
synced 2025-06-27 03:35:56 +02:00
Handle daily mean values from WFS as well
This commit is contained in:
parent
7248caed49
commit
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GPG key ID:
99D6D184CA66933A
4 changed files with 300 additions and 16 deletions
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@ -1,6 +1,6 @@
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import asyncio
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import socket
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from datetime import datetime, timedelta
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from datetime import datetime, timedelta, date
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from typing import Tuple, List, Dict
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import aiohttp
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@ -40,29 +40,35 @@ class IrcelineClient:
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return round(result[0]), round(result[1])
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async def get_rio_value(self,
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timestamp: datetime,
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timestamp: datetime | date,
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features: List[RioFeature],
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position: Tuple[float, float]
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) -> Dict[RioFeature, FeatureValue]:
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"""
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Call the WFS API to get the interpolated level of RioFeature
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Call the WFS API to get the interpolated level of RioFeature. Raises exception upon API error
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:param timestamp: datetime for which to get the data for
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:param features: list of RioFeature to fetch from the API
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:param position: decimal degrees pair of coordinates
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:return: dict with the response (key is RioFeature, value is FeatureValue with actual value and timestamp)
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"""
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# Remove one hour from timestamp to handle case where the hour just passed but the data is not yet there
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# Remove one hour/day from timestamp to handle case where the hour just passed but the data is not yet there
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# (e.g. 5.01 PM, but the most recent data is for 4.00 PM)
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timestamp = timestamp.replace(microsecond=0, second=0, minute=0) - timedelta(hours=1)
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if isinstance(timestamp, datetime):
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timestamp = timestamp.replace(microsecond=0, second=0, minute=0) - timedelta(hours=1)
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elif isinstance(timestamp, date):
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timestamp = timestamp - timedelta(days=1)
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coord = self.epsg_transform(position)
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querystring = {"service": "WFS",
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"version": "1.3.0",
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"request": "GetFeature",
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"outputFormat": "application/json",
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"typeName": ",".join(features),
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"cql_filter": f"timestamp>='{timestamp.isoformat()}' AND "
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f"INTERSECTS(the_geom, POINT ({coord[0]} {coord[1]}))"}
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"cql_filter":
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f"{'timestamp' if isinstance(timestamp, datetime) else 'date'}>='{timestamp.isoformat()}'"
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f" AND "
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f"INTERSECTS(the_geom, POINT ({coord[0]} {coord[1]}))"}
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r: ClientResponse = await self._api_wrapper(rio_wfs_base_url, querystring)
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return self.format_result('rio', await r.json(), features)
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@ -82,14 +88,21 @@ class IrcelineClient:
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features_api = data.get('features', [])
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result = dict()
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for f in features_api:
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props = f.get('properties', {})
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if (f.get('id', None) is None or
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f.get('properties', {}).get('value', None) is None or
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f.get('properties', {}).get('timestamp', None) is None):
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props.get('value', None) is None):
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continue
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if (props.get('timestamp', None) is None and
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props.get('date', None) is None):
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continue
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try:
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timestamp = datetime.fromisoformat(f.get('properties', {}).get('timestamp'))
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value = float(f.get('properties', {}).get('value'))
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if 'timestamp' in props.keys():
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timestamp = datetime.fromisoformat(props.get('timestamp'))
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else:
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# Cut last character as the date is written '2024-06-15Z' which is not ISO compliant
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timestamp = date.fromisoformat(props.get('date')[:-1])
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value = float(props.get('value'))
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except (TypeError, ValueError):
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continue
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@ -1,6 +1,6 @@
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from enum import StrEnum
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from typing import TypedDict
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from datetime import datetime
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from datetime import datetime, date
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class RioFeature(StrEnum):
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@ -23,5 +23,5 @@ class RioFeature(StrEnum):
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class FeatureValue(TypedDict):
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timestamp: datetime | None
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timestamp: datetime | date
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value: int | float | None
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243
tests/fixtures/rio_wfs_dmean.json
vendored
Normal file
243
tests/fixtures/rio_wfs_dmean.json
vendored
Normal file
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@ -0,0 +1,243 @@
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{
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"type": "FeatureCollection",
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"features": [
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{
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"type": "Feature",
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"id": "bc_dmean.fid-280be381_1901d555556_494e",
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"geometry": {
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"type": "Polygon",
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"coordinates": [
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[
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[
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182000,
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128000
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],
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[
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182000,
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132000
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],
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[
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186000,
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132000
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],
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[
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186000,
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128000
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],
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[
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182000,
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128000
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]
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]
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]
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},
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"geometry_name": "the_geom",
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"properties": {
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"id": 1102,
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"date": "2024-06-14Z",
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"value": 0.2,
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"network": "Wallonia"
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}
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},
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{
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"type": "Feature",
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"id": "bc_dmean.fid-280be381_1901d555556_494f",
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"geometry": {
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"type": "Polygon",
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"coordinates": [
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[
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[
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182000,
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128000
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],
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[
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182000,
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132000
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],
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[
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186000,
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132000
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],
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[
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186000,
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128000
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],
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[
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182000,
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128000
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]
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]
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]
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},
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"geometry_name": "the_geom",
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"properties": {
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"id": 1102,
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"date": "2024-06-15Z",
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"value": 0.1,
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"network": "Wallonia"
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}
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},
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{
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"type": "Feature",
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"id": "pm10_dmean.fid-280be381_1901d555556_4950",
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"geometry": {
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"type": "Polygon",
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"coordinates": [
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[
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[
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182000,
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128000
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],
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[
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182000,
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132000
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],
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[
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186000,
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132000
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],
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[
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186000,
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128000
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],
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[
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182000,
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128000
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]
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]
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]
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},
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"geometry_name": "the_geom",
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"properties": {
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"id": 1102,
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"date": "2024-06-14Z",
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"value": 4.8,
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"network": "Wallonia"
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}
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},
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{
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"type": "Feature",
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"id": "pm10_dmean.fid-280be381_1901d555556_4951",
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"geometry": {
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"type": "Polygon",
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"coordinates": [
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[
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[
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182000,
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128000
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],
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[
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182000,
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132000
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],
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[
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186000,
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132000
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],
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[
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186000,
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128000
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],
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[
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182000,
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128000
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]
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]
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]
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},
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"geometry_name": "the_geom",
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"properties": {
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"id": 1102,
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"date": "2024-06-15Z",
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"value": 5.9,
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"network": "Wallonia"
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}
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},
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{
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"type": "Feature",
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"id": "pm25_dmean.fid-280be381_1901d555556_4952",
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"geometry": {
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"type": "Polygon",
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"coordinates": [
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[
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[
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182000,
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128000
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],
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[
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182000,
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132000
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],
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[
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186000,
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132000
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],
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[
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186000,
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128000
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],
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[
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182000,
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128000
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]
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]
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]
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},
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"geometry_name": "the_geom",
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"properties": {
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"id": 1102,
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"date": "2024-06-14Z",
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"value": 1.3,
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"network": "Wallonia"
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}
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},
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{
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"type": "Feature",
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"id": "pm25_dmean.fid-280be381_1901d555556_4953",
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"geometry": {
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"type": "Polygon",
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"coordinates": [
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[
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[
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182000,
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128000
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],
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[
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182000,
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132000
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],
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[
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186000,
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132000
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],
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[
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186000,
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128000
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],
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[
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182000,
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128000
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]
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]
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]
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},
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"geometry_name": "the_geom",
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"properties": {
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"id": 1102,
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"date": "2024-06-15Z",
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"value": 1.1,
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"network": "Wallonia"
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}
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}
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],
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"totalFeatures": 6,
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"numberMatched": 6,
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"numberReturned": 6,
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"timeStamp": "2024-06-15T19:30:09.581Z",
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"crs": {
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"type": "name",
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"properties": {
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"name": "urn:ogc:def:crs:EPSG::31370"
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}
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}
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}
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@ -1,12 +1,15 @@
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from datetime import datetime, date
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from aiohttp import ClientSession
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from freezegun import freeze_time
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from src.open_irceline.api import IrcelineClient
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from src.open_irceline.data import RioFeature, FeatureValue
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from tests.conftest import get_api_data
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from datetime import datetime
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from freezegun import freeze_time
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@freeze_time(datetime.fromisoformat("2024-06-15T16:55:03.419Z"))
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async def test_format_result():
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async def test_format_result_hmean():
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data = get_api_data('rio_wfs.json')
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result = IrcelineClient.format_result('rio', data, [RioFeature.NO2_HMEAN, RioFeature.O3_HMEAN])
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@ -22,3 +25,28 @@ async def test_format_result():
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}
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assert result == expected
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@freeze_time(datetime.fromisoformat("2024-06-15T19:30:09.581Z"))
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async def test_format_result_dmean():
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data = get_api_data('rio_wfs_dmean.json')
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result = IrcelineClient.format_result('rio', data,
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[RioFeature.BC_DMEAN, RioFeature.PM10_DMEAN, RioFeature.PM25_DMEAN])
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expected = {
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str(RioFeature.BC_DMEAN): FeatureValue(timestamp=date(2024, 6, 15), value=0.1),
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str(RioFeature.PM10_DMEAN): FeatureValue(timestamp=date(2024, 6, 15), value=5.9),
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str(RioFeature.PM25_DMEAN): FeatureValue(timestamp=date(2024, 6, 15), value=1.1),
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}
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assert result == expected
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async def test_run():
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async with ClientSession() as session:
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api = IrcelineClient(session)
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r = await api.get_rio_value(
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date.today(),
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[RioFeature.BC_DMEAN, RioFeature.PM10_DMEAN, RioFeature.PM25_DMEAN],
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(4.8637, 50.4656))
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print(r)
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