Add fetching of NOAA 3-day forecast

solarconditionsproviders/noaa3dayforecast.py

@@ -0,0 +1,97 @@
+import logging
+import re
+from datetime import datetime, timezone
+
+from solarconditionsproviders.http_solar_conditions_provider import HTTPSolarConditionsProvider
+
+POLL_INTERVAL = 3600  # 1 hour
+URL = "https://services.swpc.noaa.gov/text/3-day-forecast.txt"
+
+
+class NOAA3dayForecast(HTTPSolarConditionsProvider):
+    """Solar conditions provider using the NOAA 3-day forecast text file. Parses the NOAA forecast and populates
+    corresponding fields in the solar conditions object.."""
+
+    def __init__(self, provider_config):
+        super().__init__(provider_config, URL, POLL_INTERVAL)
+
+    def _http_response_to_solar_conditions(self, http_response):
+        if http_response.status_code != 200:
+            logging.warning("NOAA K-index forecast API returned HTTP " + str(http_response.status_code))
+            return None
+
+        lines = http_response.text.splitlines()
+
+        # Find the "NOAA Kp index breakdown" section header
+        start_idx = None
+        for i, line in enumerate(lines):
+            if "NOAA Kp index breakdown" in line:
+                start_idx = i
+                break
+
+        if start_idx is None:
+            logging.warning("NOAA K-index forecast: could not find 'NOAA Kp index breakdown' section")
+            return None
+
+        # Extract the year from the header line, e.g. "NOAA Kp index breakdown Apr 2-Apr 4, 2026"
+        header_line = lines[start_idx]
+        year_match = re.search(r'\b(\d{4})\b', header_line)
+        if not year_match:
+            logging.warning("NOAA K-index forecast: could not extract year from: " + header_line)
+            return None
+        year = int(year_match.group(1))
+
+        # Parse the column date headers on the next line, e.g. "              Apr 02     Apr 03     Apr 04"
+        if start_idx + 1 >= len(lines):
+            logging.warning("NOAA K-index forecast: missing date header line")
+            return None
+
+        date_header_line = lines[start_idx + 2]
+        date_matches = re.findall(r'([A-Za-z]{3})\s+(\d{2})', date_header_line)
+        if not date_matches:
+            logging.warning("NOAA K-index forecast: could not parse date headers from: " + date_header_line)
+            return None
+
+        column_dates = []
+        for month_str, day_str in date_matches:
+            try:
+                column_dates.append(datetime.strptime(f"{day_str} {month_str} {year}", "%d %b %Y").date())
+            except ValueError:
+                logging.warning(f"NOAA K-index forecast: could not parse date: {month_str} {day_str} {year}")
+                return None
+
+        # Parse each data row, e.g. "00-03UT          2.00          3.00          2.00"
+        k_index_forecast = {}
+        for line in lines[start_idx + 3:]:
+            time_match = re.match(r'^(\d{2})-(\d{2})UT\s+(.*)', line.strip())
+            if not time_match:
+                if k_index_forecast:
+                    break
+                continue
+
+            start_hour = int(time_match.group(1))
+            raw_values = time_match.group(3).split()
+
+            for i, val in enumerate(raw_values):
+                if i >= len(column_dates):
+                    break
+                # Discard bracketed values
+                if val.startswith('(') and val.endswith(')'):
+                    continue
+                try:
+                    kp = float(val)
+                except ValueError:
+                    continue
+
+                date = column_dates[i]
+                start_dt = datetime(date.year, date.month, date.day, start_hour, 0, 0, tzinfo=timezone.utc)
+
+                # Key the data dict by start time
+                key = start_dt.timestamp()
+                k_index_forecast[key] = kp
+
+        if not k_index_forecast:
+            logging.warning("NOAA K-index forecast: no data rows parsed")
+            return None
+
+        return {"k_index_forecast": k_index_forecast}