Merge pull request #45 from MET-OM/fix-override-syntax

Fix override syntax + test + dependencies

environment.yml

@@ -14,3 +14,4 @@ dependencies:
   - pytest-cov
   - cdsapi
   - cartopy
+  - setuptools

metocean_api/ts/internal/ec/ec_products.py

@@ -1,5 +1,5 @@
 from __future__ import annotations
-from typing import TYPE_CHECKING, override, Tuple, List
+from typing import TYPE_CHECKING, Tuple, List
 import os
 import subprocess
 import pandas as pd
@@ -24,7 +24,6 @@ def find_product(name: str) -> Product:
 
 class ERA5(Product):
 
-    @override
     def import_data(self, ts: TimeSeries, save_csv=True, save_nc=False, use_cache=False):
         """
         Extract times series of  the nearest gird point (lon,lat) from
@@ -152,7 +151,6 @@ def download_temporary_files(self, ts: TimeSeries, use_cache: bool = False) -> T
 
 class GTSM(Product):
 
-    @override
     def import_data(self, ts: TimeSeries, save_csv=True, save_nc=False, use_cache=False):
         """
         Extract times series of the nearest grid point (lon, lat) from

metocean_api/ts/internal/metno/met_product.py

@@ -1,5 +1,5 @@
 from __future__ import annotations
-from typing import TYPE_CHECKING, override, Tuple, List
+from typing import TYPE_CHECKING, Tuple, List
 import os
 from abc import abstractmethod
 from tqdm import tqdm
@@ -35,12 +35,10 @@ def _get_near_coord(self, url: str, lon: float, lat: float):
     def get_dates(self, start_date, end_date):
         raise NotImplementedError(f"Not implemented for {self.name}")
 
-    @override
     def import_data(self, ts: TimeSeries, save_csv=True, save_nc=False, use_cache=False):
         tempfiles, lon_near, lat_near = self.download_temporary_files(ts, use_cache)
         return self._combine_temporary_files(ts, save_csv, save_nc, use_cache, tempfiles, lon_near, lat_near, height=ts.height, depth=ts.depth)
 
-    @override
     def download_temporary_files(self, ts: TimeSeries, use_cache: bool = False) -> Tuple[List[str], float, float]:
         if ts.variable == [] or ts.variable is None:
             ts.variable = self.get_default_variables()

metocean_api/ts/internal/metno/met_products.py

@@ -1,5 +1,5 @@
 from __future__ import annotations
-from typing import TYPE_CHECKING, override, Tuple,List
+from typing import TYPE_CHECKING, Tuple,List
 import os
 from datetime import datetime
 import xarray as xr
@@ -52,7 +52,6 @@ def find_product(name: str) -> Product:
 
 class Nora3Wave(MetProduct):
 
-    @override
     def get_default_variables(self):
         return [
             "hs",
@@ -71,7 +70,6 @@ def get_default_variables(self):
             "thq_swell",
         ]
 
-    @override
     def get_dates(self, start_date, end_date):
         return pd.date_range(start=start_date, end=end_date, freq="D")
 
@@ -99,7 +97,6 @@ def _drop_variables(self):
 
 class Nora3WaveSub(Nora3Wave):
 
-    @override
     def get_dates(self, start_date, end_date):
         return pd.date_range(
             start=datetime.strptime(start_date, "%Y-%m-%d").strftime("%Y-%m"),
@@ -113,31 +110,26 @@ def _get_url_info(self, date: str):
 
 class NORA3WindSub(MetProduct):
 
-    @override
     def get_default_variables(self):
         return ["wind_speed", "wind_direction"]
 
-    @override
     def get_dates(self, start_date, end_date):
         return pd.date_range(
             start=datetime.strptime(start_date, "%Y-%m-%d").strftime("%Y-%m"),
             end=datetime.strptime(end_date, "%Y-%m-%d").strftime("%Y-%m"),
             freq="MS",
         )
 
-    @override
     def _get_url_info(self, date: str):
         return "https://thredds.met.no/thredds/dodsC/nora3_subset_atmos/wind_hourly/arome3kmwind_1hr_" + date.strftime("%Y%m") + ".nc"
 
-    @override
     def _get_near_coord(self, url: str, lon: float, lat: float):
         with xr.open_dataset(url) as ds:
             x, y = aux_funcs.find_nearest_cart_coord(ds.longitude, ds.latitude, lon, lat)
             lon_near = ds.longitude.sel(y=y, x=x).values[0][0]
             lat_near = ds.latitude.sel(y=y, x=x).values[0][0]
             return {"x": x.values[0], "y": y.values[0]}, lon_near, lat_near
 
-    @override
     def _alter_temporary_dataset_if_needed(self, dataset: xr.Dataset):
         for var_name in dataset.variables:
             # The encoding of the fill value is not always correct in the netcdf files on the server
@@ -146,7 +138,6 @@ def _alter_temporary_dataset_if_needed(self, dataset: xr.Dataset):
                 var.encoding["_FillValue"] = var.attrs["fill_value"]
         return dataset
 
-    @override
     def _flatten_data_structure(self, ds: xr.Dataset, **flatten_dims):
         variables_to_flatten = ["wind_speed", "wind_direction"]
         height = self._get_values_for_dimension(ds, flatten_dims, "height")
@@ -161,23 +152,18 @@ def _flatten_data_structure(self, ds: xr.Dataset, **flatten_dims):
 
 class NORA3WindWaveCombined(MetProduct):
 
-    @override
     def get_default_variables(self):
         raise NotImplementedError("This method should not be called")
 
-    @override
     def _get_url_info(self, date: str):
         raise NotImplementedError("This method should not be called")
 
-    @override
     def _get_near_coord(self, url: str, lon: float, lat: float):
         raise NotImplementedError("This method should not be called")
 
-    @override
     def get_dates(self, start_date, end_date):
         raise NotImplementedError("This method should not be called")
-
-    @override
+
     def import_data(self, ts: TimeSeries, save_csv=True, save_nc=False, use_cache=False):
         product = ts.product
 
@@ -240,8 +226,7 @@ def import_data(self, ts: TimeSeries, save_csv=True, save_nc=False, use_cache=Fa
             self._clean_cache(tempfiles)
 
         return df
-
-    @override
+
     def download_temporary_files(self, ts: TimeSeries, use_cache: bool = False) -> Tuple[List[str], float, float]:
         raise NotImplementedError(f"Not implemented for product {self.name}")
 
@@ -266,19 +251,16 @@ def get_default_variables(self):
             "pdir1",
         ]
 
-    @override
     def get_dates(self, start_date, end_date):
         return pd.date_range(
             start=datetime.strptime(start_date, "%Y-%m-%d").strftime("%Y-%m"),
             end=datetime.strptime(end_date, "%Y-%m-%d").strftime("%Y-%m"),
             freq="MS",
         )
 
-    @override
     def _get_url_info(self, date: str):
         return "https://thredds.met.no/thredds/dodsC/norac_wave/field/ww3." + date.strftime("%Y%m") + ".nc"
 
-    @override
     def _get_near_coord(self, url: str, lon: float, lat: float):
         with xr.open_dataset(url) as ds:
             node_id = aux_funcs.distance_2points(ds.latitude.values, ds.longitude.values, lat, lon).argmin()
@@ -289,7 +271,6 @@ def _get_near_coord(self, url: str, lon: float, lat: float):
 
 class NORA3AtmSub(MetProduct):
 
-    @override
     def get_default_variables(self):
         return [
             "air_pressure_at_sea_level",
@@ -301,7 +282,6 @@ def get_default_variables(self):
             "fog",
         ]
 
-    @override
     def get_dates(self, start_date, end_date):
         return pd.date_range(
             start=datetime.strptime(start_date, "%Y-%m-%d").strftime("%Y-%m"),
@@ -325,7 +305,6 @@ def _drop_variables(self):
 
 class NORA3Atm3hrSub(MetProduct):
 
-    @override
     def get_default_variables(self):
         return [
             "wind_speed",
@@ -336,7 +315,6 @@ def get_default_variables(self):
             "tke",
         ]
 
-    @override
     def get_dates(self, start_date, end_date):
         return pd.date_range(
             start=datetime.strptime(start_date, "%Y-%m-%d").strftime("%Y-%m"),
@@ -368,11 +346,9 @@ def _flatten_data_structure(self, ds: xr.Dataset, **flatten_dims):
 
 class NORA3StormSurge(MetProduct):
 
-    @override
     def get_default_variables(self):
         return ["zeta"]
 
-    @override
     def get_dates(self, start_date, end_date):
         return pd.date_range(start=start_date, end=end_date, freq="YS")
 
@@ -390,7 +366,6 @@ def _alter_temporary_dataset_if_needed(self, dataset: xr.Dataset):
         dataset = dataset.rename_dims({"ocean_time": "time"})
         return dataset.rename_vars({"ocean_time": "time"})
 
-    @override
     def import_data(self, ts: TimeSeries, save_csv=False, save_nc=False, use_cache=False):
         """
         Extract times series of  the nearest gird point (lon,lat) from
@@ -433,11 +408,9 @@ def _drop_variables(self):
 
 class Norkyst800(MetProduct):
 
-    @override
     def get_default_variables(self):
         return ["salinity", "temperature", "u", "v", "zeta"]
 
-    @override
     def get_dates(self, start_date, end_date):
         return pd.date_range(start=start_date, end=end_date, freq="D")
 
@@ -489,6 +462,9 @@ def import_data(self, ts: TimeSeries, save_csv=True, save_nc=False, use_cache=Fa
                     dataset = dataset[ts.variable]
                     dataset = dataset.sel(selection).squeeze(drop=True)
                     dataset.to_netcdf(tempfiles[i])
+
+        ts.lat_data = lat_near
+        ts.lon_data = lon_near
 
         return self._combine_temporary_files(ts, save_csv, save_nc, use_cache, tempfiles, lon_near, lat_near, height=ts.height)
 
@@ -570,7 +546,6 @@ def _get_near_coord(self, url: str, lon: float, lat: float):
             lat_near = ds.lat.sel(y=y, x=x).values[0][0]
             return {"x": x.values[0], "y": y.values[0]}, lon_near, lat_near
 
-    @override
     def _flatten_data_structure(self, ds: xr.Dataset, **flatten_dims):
         depth = self._get_values_for_dimension(ds, flatten_dims, "depth")
         variables_to_flatten = ["u", "v", "temp", "salt", "AKs"]
@@ -598,11 +573,9 @@ def _flatten_data_structure(self, ds: xr.Dataset, **flatten_dims):
 
 class NORA3WaveSpectrum(MetProduct):
 
-    @override
     def get_default_variables(self):
         return ["SPEC"]
 
-    @override
     def get_dates(self, start_date, end_date):
         return pd.date_range(start=start_date, end=end_date, freq="D")
 
@@ -626,7 +599,6 @@ def _get_near_coord(self, url: str, lon: float, lat: float):
             station += 1  # station labels are 1-indexed
             return {"x": station}, lon_near, lat_near
 
-    @override
     def import_data(self, ts: TimeSeries, save_csv=True, save_nc=False, use_cache=False):
         """
         Extract NORA3 wave spectra timeseries.
@@ -669,11 +641,9 @@ def import_data(self, ts: TimeSeries, save_csv=True, save_nc=False, use_cache=Fa
 
 class NORACWaveSpectrum(MetProduct):
 
-    @override
     def get_default_variables(self):
         return ["efth"]
 
-    @override
     def get_dates(self, start_date, end_date):
         return pd.date_range(
             start=datetime.strptime(start_date, "%Y-%m-%d").strftime("%Y-%m"),
@@ -733,11 +703,9 @@ def import_data(self, ts: TimeSeries, save_csv=True, save_nc=False, use_cache=Fa
 
 class E39Observations(MetProduct):
 
-    @override
     def get_default_variables(self):
         return ["Hm0"]
 
-    @override
     def get_dates(self, start_date, end_date):
         return pd.date_range(start=start_date, end=end_date, freq="MS")
 

metocean_api/ts/internal/tudelft/tudelft_products.py

@@ -1,6 +1,6 @@
 from __future__ import annotations
 import os
-from typing import TYPE_CHECKING,override
+from typing import TYPE_CHECKING
 from datetime import datetime
 import pandas as pd
 import xarray as xr
@@ -20,7 +20,6 @@ def find_product(name: str) -> Product:
 
 class EchoWave(Product):
 
-    @override
     def import_data(self, ts: TimeSeries, save_csv=True, save_nc=False, use_cache=False):
         """
         Extract times series of  the nearest gird point (lon,lat) from
@@ -52,7 +51,6 @@ def import_data(self, ts: TimeSeries, save_csv=True, save_nc=False, use_cache=Fa
             self.__clean_cache(tempfiles)
         return df
 
-    @override
     def download_temporary_files(self, ts: TimeSeries, use_cache: bool = False):
         ts.variable = [ 'ucur', 'vcur', 'uwnd', 'vwnd', 'wlv', 'ice', 'hs', 'lm', 't02', 't01', 'fp', 'dir', 'spr', 'dp', 'phs0', 'phs1', 'phs2', 'ptp0', 'ptp1', 'ptp2', 'pdir0', 'pdir1']
         dates = self.__get_dates(start_date=ts.start_time, end_date=ts.end_time)

setup.py

@@ -22,7 +22,7 @@
         'dask',
         'pip',
         'netcdf4',
-        'cdsapi',
+        'cartopy',
     ],
     packages = setuptools.find_packages(),
     include_package_data = True,