Merge pull request #26 from paul-florentin-charles/dev

Dev

.github/workflows/coveragepy.yml

@@ -7,7 +7,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.8", "3.9", "3.10"]
+        python-version: ["3.9", "3.10"]
     steps:
     - uses: actions/checkout@v3
     - name: Set up Python ${{ matrix.python-version }}

.github/workflows/pylint.yml

@@ -7,7 +7,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.8", "3.9", "3.10"]
+        python-version: ["3.9", "3.10"]
     steps:
     - uses: actions/checkout@v3
     - name: Set up Python ${{ matrix.python-version }}

src/config.py

@@ -6,8 +6,6 @@
 from yaml import safe_load
 
 CONFIG_FNAME: str = 'config.yaml'
-UTF_8: str = 'utf-8'
-MODE: str = 'rt'
 
 
 class Config:
@@ -19,7 +17,7 @@ class Config:
 
     def __init__(self, path: Optional[str] = CONFIG_FNAME):
         self.path: str = path
-        with open(self.path, mode=MODE, encoding=UTF_8) as stream:
+        with open(self.path, mode='rt', encoding='utf-8') as stream:
             self.yaml_config: dict = safe_load(stream)
 
     def get_dataset_url(self) -> str:

src/core/models/all_rainfall.py

@@ -1,10 +1,12 @@
 """
-Provides a costly to instantiate all-in-one class
-to manipulate rainfall data for every timeframes.
+Provides an all-in-one class to manipulate rainfall data for every timeframe.
+At a yearly, monthly and seasonal level.
 """
 
 from typing import Optional
 
+import pandas as pd
+
 from src.core.models.monthly_rainfall import MonthlyRainfall
 from src.core.models.seasonal_rainfall import SeasonalRainfall
 from src.core.models.yearly_rainfall import YearlyRainfall
@@ -20,7 +22,7 @@ class AllRainfall:
     - MonthlyRainfall data for all months
     - SeasonalRainfall data for all seasons
 
-    Costly to instantiate but contains all necessary data.
+    A bit costly to instantiate but contains all necessary data.
     """
 
     def __init__(self,
@@ -30,18 +32,19 @@ def __init__(self,
         self.dataset_url: str = dataset_url
         self.starting_year: int = start_year
         self.round_precision: int = round_precision
-        self.yearly_rainfall: YearlyRainfall = YearlyRainfall(dataset_url,
+        self.raw_data: pd.DataFrame = pd.read_csv(dataset_url)
+        self.yearly_rainfall: YearlyRainfall = YearlyRainfall(self.raw_data,
                                                               start_year,
                                                               round_precision)
         self.monthly_rainfalls: list = []
         for month in Month:
-            self.monthly_rainfalls.append(MonthlyRainfall(dataset_url,
+            self.monthly_rainfalls.append(MonthlyRainfall(self.raw_data,
                                                           month,
                                                           start_year,
                                                           round_precision))
         self.seasonal_rainfalls: list = []
         for season in Season:
-            self.seasonal_rainfalls.append(SeasonalRainfall(dataset_url,
+            self.seasonal_rainfalls.append(SeasonalRainfall(self.raw_data,
                                                             season,
                                                             start_year,
                                                             round_precision))

src/core/models/monthly_rainfall.py

@@ -16,12 +16,12 @@ class MonthlyRainfall(YearlyRainfall):
     """
 
     def __init__(self,
-                 dataset_url: str,
+                 raw_data: pd.DataFrame,
                  month: Month,
                  start_year: Optional[int] = 1970,
                  round_precision: Optional[int] = 2):
         self.month: Month = month
-        super().__init__(dataset_url, start_year, round_precision)
+        super().__init__(raw_data, start_year, round_precision)
 
     def load_yearly_rainfall(self) -> pd.DataFrame:
         """

src/core/models/seasonal_rainfall.py

@@ -16,12 +16,12 @@ class SeasonalRainfall(YearlyRainfall):
     """
 
     def __init__(self,
-                 dataset_url: str,
+                 raw_data: pd.DataFrame,
                  season: Season,
                  start_year: Optional[int] = 1970,
                  round_precision: Optional[int] = 2):
         self.season: Season = season
-        super().__init__(dataset_url, start_year, round_precision)
+        super().__init__(raw_data, start_year, round_precision)
 
     def load_yearly_rainfall(self) -> pd.DataFrame:
         """

src/core/models/yearly_rainfall.py

@@ -25,10 +25,10 @@ class YearlyRainfall:
     """
 
     def __init__(self,
-                 dataset_url: str,
+                 raw_data: pd.DataFrame,
                  start_year: Optional[int] = 1970,
                  round_precision: Optional[int] = 2):
-        self.dataset_url: str = dataset_url
+        self.raw_data = raw_data
         self.starting_year: int = start_year
         self.round_precision: int = round_precision
         self.data: pd.DataFrame = self.load_yearly_rainfall()
@@ -49,7 +49,7 @@ def load_rainfall(self,
                       start_month: int,
                       end_month: Optional[int] = None) -> pd.DataFrame:
         """
-        Generic function to load Yearly Rainfall data into pandas DataFrame.
+        Generic function to load Yearly Rainfall data from raw data stored in pandas DataFrame.
 
         :param start_month: An integer representing the month
         to start getting our rainfall values (compulsory)
@@ -58,7 +58,7 @@ def load_rainfall(self,
         :return: A pandas DataFrame displaying rainfall data (in mm) according to year.
         """
 
-        return df_opr.retrieve_rainfall_data_with_constraints(pd.read_csv(self.dataset_url),
+        return df_opr.retrieve_rainfall_data_with_constraints(self.raw_data,
                                                               self.starting_year,
                                                               self.round_precision,
                                                               start_month,

tst/functions/test_dataframe_operations.py

@@ -1,6 +1,7 @@
 # pylint: disable=missing-docstring
 
 from datetime import datetime
+
 import pandas as pd
 
 import src.core.utils.functions.dataframe_operations as df_opr