Refactor of caching & data storage part 9 #118

providers/solarconditions/noaa3dayforecast.py

@@ -0,0 +1,174 @@
+import logging
+import re
+from datetime import datetime, timezone
+
+from providers.solarconditions.http_solar_conditions_provider import HTTPSolarConditionsProvider
+
+POLL_INTERVAL = 10800  # Every 3 hours
+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__("NOAA 3-day Forecast", provider_config, URL, POLL_INTERVAL)
+
+    @staticmethod
+    def _parse_percentage_table(lines, section_header, year):
+        """Find and parse a forecast table using percentages, identified by section_header. This is common to the lookup
+        of the solar storm and radio blackout forecast parsing."""
+
+        start_idx = None
+        for i, line in enumerate(lines):
+            if section_header in line:
+                start_idx = i
+                break
+        if start_idx is None:
+            logging.warning(f"NOAA 3-day forecast: could not find '{section_header}' section")
+            return None
+
+        # Find the date header line by scanning the next few lines for month & day patterns
+        date_header_idx = None
+        for j in range(start_idx + 1, min(start_idx + 6, len(lines))):
+            if re.search(r'[A-Za-z]{3}\s+\d{2}', lines[j]):
+                date_header_idx = j
+                break
+        if date_header_idx is None:
+            logging.warning(f"NOAA 3-day forecast: could not find date header after '{section_header}'")
+            return None
+        date_matches = re.findall(r'([A-Za-z]{3})\s+(\d{2})', lines[date_header_idx])
+        if not date_matches:
+            logging.warning(f"NOAA 3-day forecast: no dates in header: {lines[date_header_idx]}")
+            return None
+
+        # Figure out the date based on the line found
+        column_timestamps = []
+        for month_str, day_str in date_matches:
+            try:
+                dt = datetime.strptime(f"{day_str} {month_str} {year}", "%d %b %Y").replace(tzinfo=timezone.utc)
+                column_timestamps.append(dt.timestamp())
+            except ValueError:
+                logging.warning(f"NOAA 3-day forecast: could not parse date: {month_str} {day_str} {year}")
+                return None
+
+        # Parse data rows. Each non-empty line should have a text label followed by percentage values
+        result = {}
+        for line in lines[date_header_idx + 1:]:
+            line_stripped = line.strip()
+            if not line_stripped:
+                if result:
+                    break
+                continue
+            pct_matches = list(re.finditer(r'\b(\d+)%', line_stripped))
+            if not pct_matches:
+                if result:
+                    break
+                continue
+
+            # Row label is everything before the first percentage value
+            row_label = line_stripped[:line_stripped.index(pct_matches[0].group())].strip()
+            row_data = {}
+            for j, match in enumerate(pct_matches):
+                if j >= len(column_timestamps):
+                    break
+                row_data[column_timestamps[j]] = int(match.group(1))
+            if row_data:
+                result[row_label] = row_data
+
+        return result if result else None
+
+    def _http_response_to_solar_conditions(self, http_response):
+        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))
+            # Split on 2 or more spaces so that e.g. "5.67 (G2)" stays as one token per column
+            raw_values = re.split(r' {2,}', time_match.group(3).strip())
+
+            for i, val in enumerate(raw_values):
+                if i >= len(column_dates):
+                    break
+                # Take only the leading numeric part, discarding any bracketed section
+                try:
+                    kp = float(val.split()[0])
+                except (ValueError, IndexError):
+                    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
+
+        # Parse Solar Radiation Storm Forecast (single row: "S1 or greater")
+        solar_storm_forecast = None
+        radiation_table = self._parse_percentage_table(lines, "Solar Radiation Storm Forecast", year)
+        if radiation_table:
+            solar_storm_forecast = radiation_table.get("S1 or greater")
+
+        # Parse Radio Blackout Forecast (two rows: "R1-R2" and "R3 or greater")
+        blackout_forecast_r1r2 = None
+        blackout_forecast_r3_or_greater = None
+        blackout_table = self._parse_percentage_table(lines, "Radio Blackout Forecast", year)
+        if blackout_table:
+            blackout_forecast_r1r2 = blackout_table.get("R1-R2")
+            blackout_forecast_r3_or_greater = blackout_table.get("R3 or greater")
+
+        return {
+            "k_index_forecast": k_index_forecast,
+            "solar_storm_forecast": solar_storm_forecast,
+            "blackout_forecast_r1r2": blackout_forecast_r1r2,
+            "blackout_forecast_r3_or_greater": blackout_forecast_r3_or_greater,
+        }