Add app.py and update .gitignore for Ruff and Pytest

.gitignore

@@ -15,4 +15,7 @@ dist/
 .pytest_cache/
 
 # Logs
-*.log
+*.log
+
+# Ruff Cache
+.ruff_cache/

app.py

@@ -0,0 +1,99 @@
+"""
+Main Script to Fetch, Format, and Save NESO Solar Forecast Data
+
+This script orchestrates the following steps:
+1. Fetches solar forecast data using the `fetch_data` function from `fetch_data.py`.
+2. Formats the forecast data (currently a placeholder for future enhancements).
+3. Saves the forecast data (currently a placeholder for future enhancements).
+
+Each step is modularized into functions to allow for testing and future extension.
+
+Functions:
+    - get_forecast: Fetches raw solar forecast data.
+    - format_forecast: Processes the forecast data for a specific format (placeholder for now).
+    - save_forecast: Saves the formatted forecast data (placeholder for now).
+"""
+
+from fetch_data import fetch_data
+
+
+def get_forecast():
+    """
+    Fetch solar forecast data from NESO API.
+
+    This function retrieves the solar forecast data from the NESO API and processes
+    it into a Pandas DataFrame using the `fetch_data` function.
+
+    Returns:
+        pd.DataFrame: A DataFrame containing solar forecast data with the following columns:
+                      - `start_utc`: Start time of the forecast (UTC).
+                      - `end_utc`: End time of the forecast (UTC).
+                      - `solar_forecast_kw`: Forecasted solar energy in kW.
+    """
+    resource_id = "example_resource_id"  # Replace with the actual resource ID.
+    limit = 100  # Number of records to fetch.
+    columns = ["DATE_GMT", "TIME_GMT", "EMBEDDED_SOLAR_FORECAST"]  # Relevant columns to extract.
+    rename_columns = {
+        "DATE_GMT": "start_utc",
+        "TIME_GMT": "end_utc",
+        "EMBEDDED_SOLAR_FORECAST": "solar_forecast_kw",
+    }
+
+    # Fetch and return data as a DataFrame.
+    return fetch_data(resource_id, limit, columns, rename_columns)
+
+
+def format_forecast(data):
+    """
+    Format solar forecast data.
+
+    Placeholder function for future enhancements. In its current form, it simply logs
+    a message and returns the input data unmodified.
+
+    Parameters:
+        data (pd.DataFrame): The raw forecast data fetched from the NESO API.
+
+    Returns:
+        pd.DataFrame: The formatted forecast data (currently identical to input data).
+    """
+    print("Formatting forecast data...")
+    return data  # Currently, no modifications are applied.
+
+
+def save_forecast(data):
+    """
+    Save solar forecast data.
+
+    Placeholder function for future enhancements. In its current form, it logs
+    a message but does not persist data.
+
+    Parameters:
+        data (pd.DataFrame): The formatted forecast data to be saved.
+
+    Returns:
+        None
+    """
+    print("Saving forecast data...")
+    # Future implementation will save data to a database or file.
+
+
+if __name__ == "__main__":
+    """
+    Orchestrates the following steps:
+        1. Fetch forecast data.
+        2. Format forecast data.
+        3. Save forecast data.
+    """
+    # Step 1: Get forecast data
+    print("Fetching forecast data...")
+    forecast_data = get_forecast()
+
+    # Step 2: Format forecast data
+    print("Formatting forecast data...")
+    formatted_data = format_forecast(forecast_data)
+
+    # Step 3: Save forecast data
+    print("Saving forecast data...")
+    save_forecast(formatted_data)
+
+    print("Process completed successfully!")