use new join class to load data in data preparation, data directory is excluded from git tracking

src/data_preparation.py

@@ -6,11 +6,12 @@ import xarray as xr
 import pandas as pd
 import logging
 import os
+from src import join
 
 
 class DataPrep:
 
-    def __init__(self, path, network, stations, variables, **kwargs):
+    def __init__(self, path: str, network: str, stations, variables, **kwargs):
         self.path = path
         self.network = network
         self.stations = stations
@@ -19,26 +20,29 @@ class DataPrep:
         if self.statistics_per_var is not None:
             self.load_data()
         else:
-            self.data, self.meta = Fkf.read_hourly_data_from_csv_to_xarray(self.path, self.network, self.stations,
-                                                                           self.variables, **kwargs)
+            raise NotImplementedError
+            # self.data, self.meta = Fkf.read_hourly_data_from_csv_to_xarray(self.path, self.network, self.stations,
+            #                                                               self.variables, **kwargs)
         self.mean = None
         self.std = None
         self.df = None
         self.history = None
         self.label = None
         self.kwargs = kwargs
+        self.data = None
+        self.meta = None
 
     def load_data(self):
         self.check_path_and_create(self.path)
-        file_name = "{}{}_{}.nc".format(self.path, ''.join(self.stations), '_'.join(sorted(self.variables)))
-        meta_file = "{}{}_{}_meta.csv".format(self.path, ''.join(self.stations), '_'.join(sorted(self.variables)))
+        file_name = self._set_file_name()
+        meta_file = self._set_meta_file_name()
         try:
             self.data = xr.open_dataarray(file_name)
             self.meta = pd.read_csv(meta_file, index_col=0)
-        except FileExistsError as e:
+        except FileNotFoundError as e:
             logging.warning(e)
             df_all = {}
-            df, self.meta = Fkf.download_join(station_name=self.stations, statvar=self.statistics_per_var)
+            df, self.meta = join.download_join(station_name=self.stations, statvar=self.statistics_per_var)
             df_all[self.stations[0]] = df
             # convert df_all to xarray
             xarr = {k: xr.DataArray(v, dims=['datetime', 'variables']) for k, v in df_all.items()}
@@ -48,18 +52,18 @@ class DataPrep:
             xarr.to_netcdf(path=file_name)
             self.meta.to_csv(meta_file)
 
+    def _set_file_name(self):
+        return f"{self.path}{''.join(self.stations)}_{'_'.join(sorted(self.variables))}.nc"
+
+    def _set_meta_file_name(self):
+        return f"{self.path}{''.join(self.stations)}_{'_'.join(sorted(self.variables))}_meta.csv"
+
     def __repr__(self):
-        return "DataPrep(path='{}', network='{}', stations={}, variables={}, **{}".format(self.path, self.network,
-                                                                                          self.stations, self.variables,
-                                                                                          self.kwargs)
+        return f"Dataprep(path='{self.path}', network='{self.network}', stations={self.stations}, " \
+               f"variables={self.variables}, **{self.kwargs}"
 
     @staticmethod
     def check_path_and_create(path):
-        """
-
-        :param path:
-        :return:
-        """
         try:
             os.makedirs(path)
             logging.info("Created path: {}".format(path))
@@ -91,3 +95,8 @@ class DataPrep:
     def create_indexarray(index_name, index_values):
         raise NotImplementedError
 
+
+if __name__ == "__main__":
+
+    dp = DataPrep('data/', 'dummy', 'DEBW107', ['o3', 'temp'], statistics_per_var={'o3': 'dma8eu', 'temp': 'maximum'})
+    print(dp)