# -*- coding: utf-8 -*- from flask import Flask, jsonify, request, Response, send_file, render_template_string from pathlib import Path from datetime import datetime, timedelta from openpyxl import Workbook from openpyxl.styles import Font, PatternFill, Alignment from openpyxl.utils import get_column_letter import csv import glob import io import json import math import os import re import sqlite3 import threading import time # ============================================================ # CONFIGURACIÓN GENERAL # ============================================================ BASE_DIR = Path(__file__).resolve().parent # ============================================================ WEATHERLINK_FILE = r"C:\WeatherLink\WallEDav\download.txt" DATABASE_FILE = str(BASE_DIR / "meteorologia_uca.db") LOGO_FILE = str(BASE_DIR / "uca_logo.png") SITE_TITLE = "Centro de Meteorología UCA" UNIVERSITY_NAME = ( 'Universidad Centroamericana "José Simeón Cañas"' ) DEPARTMENT_NAME = ( "CEF: Departamento de Ciencias Energéticas y Fluídicas" ) STATION_NAME = "Estación Meteorológica UCA - CEF" STATION_MODEL = "Davis Vantage Pro2" # Coordenadas de la estación. # Las podemos cambiar después si fuese necesario. STATION_LAT = 13.67968 STATION_LON = -89.23559 # Cada cuánto revisará Python si WeatherLink modificó download.txt IMPORT_CHECK_SECONDS = 30 # Si el último dato tiene más de 30 minutos, # la web indicará que los datos están retrasados. ONLINE_THRESHOLD_MINUTES = 30 PORT = 5000 # ============================================================ # LOS 38 CAMPOS DEL ARCHIVO WEATHERLINK # ============================================================ COLUMNS = [ { "key": "record_date", "label": "Fecha", "unit": "", "type": "TEXT", "group": "Tiempo" }, { "key": "record_time", "label": "Hora", "unit": "", "type": "TEXT", "group": "Tiempo" }, { "key": "temp_out", "label": "Temperatura exterior", "unit": "°C", "type": "REAL", "group": "Temperatura" }, { "key": "hi_temp", "label": "Temperatura máxima", "unit": "°C", "type": "REAL", "group": "Temperatura" }, { "key": "low_temp", "label": "Temperatura mínima", "unit": "°C", "type": "REAL", "group": "Temperatura" }, { "key": "out_hum", "label": "Humedad exterior", "unit": "%", "type": "REAL", "group": "Humedad" }, { "key": "dew_pt", "label": "Punto de rocío exterior", "unit": "°C", "type": "REAL", "group": "Temperatura" }, { "key": "wind_speed", "label": "Velocidad del viento", "unit": "m/s", "type": "REAL", "group": "Viento" }, { "key": "wind_dir", "label": "Dirección del viento", "unit": "", "type": "TEXT", "group": "Viento" }, { "key": "wind_run", "label": "Recorrido del viento", "unit": "km", "type": "REAL", "group": "Viento" }, { "key": "hi_speed", "label": "Ráfaga máxima", "unit": "m/s", "type": "REAL", "group": "Viento" }, { "key": "hi_dir", "label": "Dirección de ráfaga máxima", "unit": "", "type": "TEXT", "group": "Viento" }, { "key": "wind_chill", "label": "Sensación térmica", "unit": "°C", "type": "REAL", "group": "Confort térmico" }, { "key": "heat_index", "label": "Índice de calor", "unit": "°C", "type": "REAL", "group": "Confort térmico" }, { "key": "thw_index", "label": "Índice THW", "unit": "°C", "type": "REAL", "group": "Confort térmico" }, { "key": "thsw_index", "label": "Índice THSW", "unit": "°C", "type": "REAL", "group": "Confort térmico" }, { "key": "bar", "label": "Presión barométrica", "unit": "hPa", "type": "REAL", "group": "Atmósfera" }, { "key": "rain", "label": "Precipitación", "unit": "mm", "type": "REAL", "group": "Precipitación" }, { "key": "rain_rate", "label": "Intensidad de lluvia", "unit": "mm/h", "type": "REAL", "group": "Precipitación" }, { "key": "solar_rad", "label": "Radiación solar", "unit": "W/m²", "type": "REAL", "group": "Radiación" }, { "key": "solar_energy", "label": "Energía solar", "unit": "Ly", "type": "REAL", "group": "Radiación" }, { "key": "hi_solar_rad", "label": "Radiación solar máxima", "unit": "W/m²", "type": "REAL", "group": "Radiación" }, { "key": "uv_index", "label": "Índice UV", "unit": "", "type": "REAL", "group": "Radiación UV" }, { "key": "uv_dose", "label": "Dosis UV", "unit": "", "type": "REAL", "group": "Radiación UV" }, { "key": "hi_uv", "label": "Índice UV máximo", "unit": "", "type": "REAL", "group": "Radiación UV" }, { "key": "heat_dd", "label": "Grados-día calefacción", "unit": "°D", "type": "REAL", "group": "Grados-día" }, { "key": "cool_dd", "label": "Grados-día refrigeración", "unit": "°D", "type": "REAL", "group": "Grados-día" }, { "key": "in_temp", "label": "Temperatura interior", "unit": "°C", "type": "REAL", "group": "Interior" }, { "key": "in_hum", "label": "Humedad interior", "unit": "%", "type": "REAL", "group": "Interior" }, { "key": "in_dew", "label": "Punto de rocío interior", "unit": "°C", "type": "REAL", "group": "Interior" }, { "key": "in_heat", "label": "Índice de calor interior", "unit": "°C", "type": "REAL", "group": "Interior" }, { "key": "in_emc", "label": "EMC interior", "unit": "%", "type": "REAL", "group": "Interior" }, { "key": "in_air_density", "label": "Densidad del aire interior", "unit": "kg/m³", "type": "REAL", "group": "Interior" }, { "key": "et", "label": "Evapotranspiración", "unit": "mm", "type": "REAL", "group": "Precipitación" }, { "key": "wind_samp", "label": "Muestras de viento", "unit": "", "type": "REAL", "group": "Diagnóstico" }, { "key": "wind_tx", "label": "Transmisor", "unit": "", "type": "REAL", "group": "Diagnóstico" }, { "key": "iss_recept", "label": "Recepción ISS", "unit": "%", "type": "REAL", "group": "Diagnóstico" }, { "key": "arc_int", "label": "Intervalo de archivo", "unit": "min", "type": "REAL", "group": "Diagnóstico" }, ] COLUMN_KEYS = [column["key"] for column in COLUMNS] NUMERIC_KEYS = { column["key"] for column in COLUMNS if column["type"] == "REAL" } # ============================================================ # VARIABLES PARA LAS GRÁFICAS # ============================================================ CHART_METRICS = { "temp_out": { "label": "Temperatura exterior", "unit": "°C" }, "hi_temp": { "label": "Temperatura máxima", "unit": "°C" }, "low_temp": { "label": "Temperatura mínima", "unit": "°C" }, "out_hum": { "label": "Humedad exterior", "unit": "%" }, "dew_pt": { "label": "Punto de rocío", "unit": "°C" }, "wind_speed": { "label": "Velocidad del viento", "unit": "m/s" }, "hi_speed": { "label": "Ráfaga máxima", "unit": "m/s" }, "wind_run": { "label": "Recorrido del viento", "unit": "km" }, "wind_chill": { "label": "Sensación térmica", "unit": "°C" }, "heat_index": { "label": "Índice de calor", "unit": "°C" }, "thw_index": { "label": "Índice THW", "unit": "°C" }, "thsw_index": { "label": "Índice THSW", "unit": "°C" }, "bar": { "label": "Presión barométrica", "unit": "hPa" }, "rain": { "label": "Precipitación", "unit": "mm" }, "rain_rate": { "label": "Intensidad de lluvia", "unit": "mm/h" }, "solar_rad": { "label": "Radiación solar", "unit": "W/m²" }, "solar_energy": { "label": "Energía solar", "unit": "Ly" }, "hi_solar_rad": { "label": "Radiación solar máxima", "unit": "W/m²" }, "uv_index": { "label": "Índice UV", "unit": "" }, "uv_dose": { "label": "Dosis UV", "unit": "" }, "hi_uv": { "label": "Índice UV máximo", "unit": "" }, "in_temp": { "label": "Temperatura interior", "unit": "°C" }, "in_hum": { "label": "Humedad interior", "unit": "%" }, "in_dew": { "label": "Punto de rocío interior", "unit": "°C" }, "in_heat": { "label": "Índice de calor interior", "unit": "°C" }, "in_emc": { "label": "EMC interior", "unit": "%" }, "in_air_density": { "label": "Densidad del aire", "unit": "kg/m³" }, "et": { "label": "Evapotranspiración", "unit": "mm" }, "iss_recept": { "label": "Recepción ISS", "unit": "%" }, } # ============================================================ # BASE DE DATOS SQLITE # ============================================================ def db_connect(): connection = sqlite3.connect( DATABASE_FILE, timeout=30 ) connection.row_factory = sqlite3.Row return connection def init_database(): definitions = [] for column in COLUMNS: definitions.append( f'"{column["key"]}" {column["type"]}' ) sql = f""" CREATE TABLE IF NOT EXISTS observations ( timestamp TEXT PRIMARY KEY, {", ".join(definitions)}, imported_at TEXT NOT NULL ) """ with db_connect() as connection: connection.execute(sql) connection.execute( """ CREATE INDEX IF NOT EXISTS idx_observations_timestamp ON observations(timestamp) """ ) connection.commit() # ============================================================ # LOCALIZAR DOWNLOAD.TXT # ============================================================ def resolve_weatherlink_file(): if WEATHERLINK_FILE.strip(): return os.path.expandvars( WEATHERLINK_FILE.strip() ) candidates = glob.glob( r"C:\weatherlink\**\download.txt", recursive=True ) if not candidates: return "" candidates.sort( key=lambda path: os.path.getmtime(path), reverse=True ) return candidates[0] # ============================================================ # CONVERSIÓN DE DATOS # ============================================================ def to_number(value): if value is None: return None value = value.strip() if value in { "", "--", "---", "N/A" }: return None try: return float(value) except ValueError: return None DATA_LINE_PATTERN = re.compile( r"^\s*\d{1,2}/\d{1,2}/\d{2}\s+\d{1,2}:\d{2}\s+" ) # ============================================================ # LEER UNA FILA DE WEATHERLINK # ============================================================ def parse_weatherlink_line(line): parts = line.strip().split() if len(parts) < len(COLUMNS): return None parts = parts[:len(COLUMNS)] record = {} for index, column in enumerate(COLUMNS): raw_value = parts[index] if column["key"] in NUMERIC_KEYS: record[column["key"]] = to_number( raw_value ) else: record[column["key"]] = raw_value try: date_time = datetime.strptime( ( record["record_date"] + " " + record["record_time"] ), "%d/%m/%y %H:%M" ) except ValueError: return None record["timestamp"] = date_time.strftime( "%Y-%m-%d %H:%M:%S" ) return record # ============================================================ # LEER DOWNLOAD.TXT # ============================================================ def read_weatherlink_records(path): encodings = [ "utf-8-sig", "cp1252", "latin-1" ] text = None for encoding in encodings: try: with open( path, "r", encoding=encoding ) as file: text = file.read() break except UnicodeDecodeError: continue if text is None: raise RuntimeError( "No se pudo leer download.txt" ) records = [] for line in text.splitlines(): if not DATA_LINE_PATTERN.match(line): continue record = parse_weatherlink_line(line) if record: records.append(record) return records # ============================================================ # IMPORTACIÓN A SQLITE # ============================================================ LAST_IMPORT = { "ok": False, "message": "Todavía no se ha importado.", "source": "", "records": 0, "last_run": None } IMPORT_LOCK = threading.Lock() def import_weatherlink(): global LAST_IMPORT with IMPORT_LOCK: path = resolve_weatherlink_file() current_time = datetime.now().strftime( "%Y-%m-%d %H:%M:%S" ) if not path: LAST_IMPORT = { "ok": False, "message": "No se encontró download.txt.", "source": "", "records": 0, "last_run": current_time } return LAST_IMPORT if not os.path.isfile(path): LAST_IMPORT = { "ok": False, "message": "La ruta de download.txt no existe.", "source": path, "records": 0, "last_run": current_time } return LAST_IMPORT try: records = read_weatherlink_records( path ) if not records: LAST_IMPORT = { "ok": False, "message": "No se encontraron registros válidos.", "source": path, "records": 0, "last_run": current_time } return LAST_IMPORT database_columns = ( ["timestamp"] + COLUMN_KEYS + ["imported_at"] ) placeholders = ",".join( ["?"] * len(database_columns) ) column_names = ",".join( f'"{column}"' for column in database_columns ) sql = f""" INSERT OR REPLACE INTO observations ({column_names}) VALUES ({placeholders}) """ rows = [] for record in records: values = [ record["timestamp"] ] values.extend( record.get(key) for key in COLUMN_KEYS ) values.append(current_time) rows.append(values) with db_connect() as connection: connection.executemany( sql, rows ) connection.commit() LAST_IMPORT = { "ok": True, "message": "Datos importados correctamente.", "source": path, "records": len(records), "last_run": current_time } return LAST_IMPORT except PermissionError: LAST_IMPORT = { "ok": False, "message": "WeatherLink está escribiendo el archivo. " "Se volverá a intentar.", "source": path, "records": 0, "last_run": current_time } return LAST_IMPORT except Exception as error: LAST_IMPORT = { "ok": False, "message": str(error), "source": path, "records": 0, "last_run": current_time } return LAST_IMPORT # ============================================================ # IMPORTADOR AUTOMÁTICO # ============================================================ def automatic_import_loop(): while True: import_weatherlink() time.sleep( IMPORT_CHECK_SECONDS ) # ============================================================ # OBTENER ÚLTIMO REGISTRO # ============================================================ def get_latest(): with db_connect() as connection: row = connection.execute( """ SELECT * FROM observations ORDER BY timestamp DESC LIMIT 1 """ ).fetchone() if row is None: return None data = dict(row) if data["wind_speed"] is not None: data["wind_speed_kmh"] = round( data["wind_speed"] * 3.6, 1 ) else: data["wind_speed_kmh"] = None if data["hi_speed"] is not None: data["hi_speed_kmh"] = round( data["hi_speed"] * 3.6, 1 ) else: data["hi_speed_kmh"] = None try: record_time = datetime.strptime( data["timestamp"], "%Y-%m-%d %H:%M:%S" ) age = ( datetime.now() - record_time ).total_seconds() / 60 data["age_minutes"] = round( age, 1 ) data["online"] = ( age <= ONLINE_THRESHOLD_MINUTES ) except Exception: data["online"] = False return data # ============================================================ # RESUMEN DEL DÍA # ============================================================ def get_summary(): latest = get_latest() if not latest: return {} date = latest["timestamp"][0:10] month = latest["timestamp"][0:7] year = latest["timestamp"][0:4] with db_connect() as connection: day = connection.execute( """ SELECT MAX(hi_temp) AS temp_max, MIN(low_temp) AS temp_min, AVG(out_hum) AS humidity_avg, MAX(hi_speed) AS gust_max, MAX(hi_uv) AS uv_max, MAX(hi_solar_rad) AS solar_max, SUM(COALESCE(rain, 0)) AS rain_day, SUM(COALESCE(et, 0)) AS et_day FROM observations WHERE substr(timestamp,1,10) = ? """, (date,) ).fetchone() rain_month = connection.execute( """ SELECT SUM(COALESCE(rain,0)) FROM observations WHERE substr(timestamp,1,7) = ? """, (month,) ).fetchone()[0] rain_year = connection.execute( """ SELECT SUM(COALESCE(rain,0)) FROM observations WHERE substr(timestamp,1,4) = ? """, (year,) ).fetchone()[0] total_records = connection.execute( """ SELECT COUNT(*) FROM observations """ ).fetchone()[0] result = dict(day) result["rain_month"] = ( rain_month or 0 ) result["rain_year"] = ( rain_year or 0 ) result["total_records"] = ( total_records ) if result["gust_max"] is not None: result["gust_max_kmh"] = round( result["gust_max"] * 3.6, 1 ) else: result["gust_max_kmh"] = None return result # ============================================================ # FILTROS DE FECHA # ============================================================ def build_date_filter( start_date, end_date ): clauses = [] params = [] if start_date: clauses.append( "timestamp >= ?" ) params.append( start_date + " 00:00:00" ) if end_date: clauses.append( "timestamp <= ?" ) params.append( end_date + " 23:59:59" ) if clauses: return ( " WHERE " + " AND ".join(clauses), params ) return "", [] # ============================================================ # FLASK # ============================================================ app = Flask(__name__) # ============================================================ # API - ÚLTIMO REGISTRO # ============================================================ @app.route("/api/latest") def api_latest(): data = get_latest() if not data: return jsonify({ "ok": False, "message": "Todavía no existen datos." }), 404 return jsonify({ "ok": True, "data": data }) # ============================================================ # API - RESUMEN # ============================================================ @app.route("/api/summary") def api_summary(): return jsonify({ "ok": True, "data": get_summary() }) # ============================================================ # API - ESTADO # ============================================================ @app.route("/api/status") def api_status(): with db_connect() as connection: count = connection.execute( """ SELECT COUNT(*) FROM observations """ ).fetchone()[0] first = connection.execute( """ SELECT MIN(timestamp) FROM observations """ ).fetchone()[0] last = connection.execute( """ SELECT MAX(timestamp) FROM observations """ ).fetchone()[0] return jsonify({ "ok": True, "import": LAST_IMPORT, "database": { "records": count, "first": first, "last": last } }) # ============================================================ # API - GRÁFICAS # ============================================================ @app.route("/api/history") def api_history(): metric = request.args.get( "metric", "temp_out" ) span = request.args.get( "span", "24h" ) if metric not in CHART_METRICS: return jsonify({ "ok": False, "message": "Variable no permitida." }), 400 latest = get_latest() if not latest: return jsonify({ "ok": True, "points": [], "meta": CHART_METRICS[metric] }) end = datetime.strptime( latest["timestamp"], "%Y-%m-%d %H:%M:%S" ) if span == "7d": start = end - timedelta( days=7 ) elif span == "30d": start = end - timedelta( days=30 ) elif span == "365d": start = end - timedelta( days=365 ) else: start = end - timedelta( hours=24 ) sql = f""" SELECT timestamp, "{metric}" AS value FROM observations WHERE timestamp >= ? AND timestamp <= ? AND "{metric}" IS NOT NULL ORDER BY timestamp ASC """ with db_connect() as connection: rows = connection.execute( sql, ( start.strftime( "%Y-%m-%d %H:%M:%S" ), end.strftime( "%Y-%m-%d %H:%M:%S" ) ) ).fetchall() points = [ { "timestamp": row["timestamp"], "value": row["value"] } for row in rows ] # Evita mandar demasiados puntos al navegador. if len(points) > 1500: step = math.ceil( len(points) / 1500 ) points = points[::step] return jsonify({ "ok": True, "meta": CHART_METRICS[metric], "points": points }) # ============================================================ # API - TABLA # ============================================================ @app.route("/api/records") def api_records(): try: page = max( 1, int( request.args.get( "page", 1 ) ) ) except ValueError: page = 1 try: per_page = int( request.args.get( "per_page", 100 ) ) except ValueError: per_page = 100 per_page = min( max(per_page, 10), 300 ) start_date = request.args.get( "desde" ) end_date = request.args.get( "hasta" ) where, params = build_date_filter( start_date, end_date ) offset = ( page - 1 ) * per_page with db_connect() as connection: total = connection.execute( """ SELECT COUNT(*) FROM observations """ + where, params ).fetchone()[0] rows = connection.execute( """ SELECT * FROM observations """ + where + """ ORDER BY timestamp DESC LIMIT ? OFFSET ? """, params + [ per_page, offset ] ).fetchall() total_pages = ( math.ceil(total / per_page) if total else 1 ) return jsonify({ "ok": True, "page": page, "pages": total_pages, "total": total, "records": [ dict(row) for row in rows ] }) # ============================================================ # EXPORTACIÓN # ============================================================ def export_rows(): start_date = request.args.get( "desde" ) end_date = request.args.get( "hasta" ) where, params = build_date_filter( start_date, end_date ) with db_connect() as connection: rows = connection.execute( """ SELECT * FROM observations """ + where + """ ORDER BY timestamp ASC """, params ).fetchall() return [ dict(row) for row in rows ] # ============================================================ # DESCARGAR EXCEL # ============================================================ @app.route("/descargar.xlsx") def download_excel(): rows = export_rows() workbook = Workbook() sheet = workbook.active sheet.title = ( "Datos meteorológicos" ) headers = ( ["Fecha y hora"] + [ column["label"] for column in COLUMNS ] ) units = ( [""] + [ column["unit"] for column in COLUMNS ] ) sheet.append(headers) sheet.append(units) blue_fill = PatternFill( "solid", fgColor="173A56" ) secondary_fill = PatternFill( "solid", fgColor="E7EDF1" ) white_font = Font( color="FFFFFF", bold=True ) for cell in sheet[1]: cell.fill = blue_fill cell.font = white_font cell.alignment = Alignment( horizontal="center" ) for cell in sheet[2]: cell.fill = secondary_fill cell.font = Font( italic=True ) for row in rows: values = [ row["timestamp"] ] values.extend( row.get(column["key"]) for column in COLUMNS ) sheet.append(values) sheet.freeze_panes = "A3" sheet.auto_filter.ref = ( f"A1:" f"{get_column_letter(len(headers))}" f"{sheet.max_row}" ) for index, header in enumerate( headers, start=1 ): sheet.column_dimensions[ get_column_letter(index) ].width = min( max(len(header) + 2, 12), 30 ) # ======================================================== # HOJA DE METADATOS # ======================================================== metadata = workbook.create_sheet( "Metadatos" ) metadata.append([ "Centro", SITE_TITLE ]) metadata.append([ "Universidad", UNIVERSITY_NAME ]) metadata.append([ "Departamento", DEPARTMENT_NAME ]) metadata.append([ "Estación", STATION_NAME ]) metadata.append([ "Modelo", STATION_MODEL ]) metadata.append([ "Latitud", STATION_LAT ]) metadata.append([ "Longitud", STATION_LON ]) metadata.append([]) metadata.append([ "Variable", "Unidad", "Grupo", "Nombre interno" ]) for column in COLUMNS: metadata.append([ column["label"], column["unit"], column["group"], column["key"] ]) for cell in metadata[9]: cell.fill = blue_fill cell.font = white_font output = io.BytesIO() workbook.save(output) output.seek(0) filename = ( "meteorologia_uca_" + datetime.now().strftime( "%Y%m%d_%H%M" ) + ".xlsx" ) return send_file( output, as_attachment=True, download_name=filename, mimetype=( "application/vnd.openxmlformats-" "officedocument.spreadsheetml.sheet" ) ) # ============================================================ # DESCARGAR CSV # ============================================================ @app.route("/descargar.csv") def download_csv(): rows = export_rows() output = io.StringIO() writer = csv.writer( output, delimiter=";" ) writer.writerow( ["Fecha y hora"] + [ column["label"] for column in COLUMNS ] ) for row in rows: writer.writerow( [row["timestamp"]] + [ row.get( column["key"] ) for column in COLUMNS ] ) content = ( "\ufeff" + output.getvalue() ).encode("utf-8") filename = ( "meteorologia_uca_" + datetime.now().strftime( "%Y%m%d_%H%M" ) + ".csv" ) return Response( content, mimetype=( "text/csv; charset=utf-8" ), headers={ "Content-Disposition": f'attachment; filename="{filename}"' } ) # ============================================================ # LOGO # ============================================================ @app.route("/logo") def logo(): if os.path.isfile( LOGO_FILE ): return send_file( LOGO_FILE ) # Logo temporal si todavía # no has colocado uca_logo.png. svg = """ UCA Centro de Meteorología """ return Response( svg, mimetype="image/svg+xml" ) # ============================================================ # INTERFAZ WEB # ============================================================ HTML = """ {{ site_title }}

{{ site_title }}

{{ university_name }}
{{ department_name }}
Comprobando estación
Último dato: --
{{ station_name }} | {{ station_model }}
WeatherLink 6.0.5

Boletín meteorológico

Condiciones registradas por la estación meteorológica del Departamento de Ciencias Energéticas y Fluídicas.

Estado de la estación
Operativa
Temperatura exterior
-- °C
Humedad exterior
-- %
Recepción ISS
-- %
Temperatura máxima
--
Temperatura mínima
--
Precipitación del día
--
Precipitación del mes
--
Índice UV máximo
--
Ráfaga máxima
--
Temperatura
Weather Station
-- °C
Máxima del intervalo --
Mínima del intervalo --
Punto de rocío --
Índice de calor --
Humedad exterior
Estación meteorológica
-- %
Promedio del día --
Punto de rocío --
Presión barométrica
Consola
-- hPa
Variable atmosférica Presión reducida
Unidad WeatherLink hPa
Velocidad del viento
Weather Station
-- m/s
Equivalente --
Ráfaga --
Dirección de ráfaga --
Recorrido del viento --
Dirección del viento
Weather Station
N S E O
--
Radiación solar
Weather Station
-- W/m²
Máxima del intervalo --
Energía solar --
Radiación ultravioleta
Weather Station
-- Índice UV
Índice UV máximo --
Dosis UV --
Precipitación
Weather Station
-- mm
Intensidad de lluvia --
Evapotranspiración --

Evolución durante las últimas 24 horas

Temperatura exterior
Histórico de 24 horas
Radiación solar
Histórico de 24 horas

Variables meteorológicas avanzadas

Índices térmicos
Weather Station
Sensación térmica --
Índice de calor --
Índice THW --
Índice THSW --
Grados-día calefacción --
Grados-día refrigeración --
Condiciones interiores
Console
Temperatura interior --
Humedad interior --
Punto de rocío interior --
Índice de calor interior --
EMC interior --
Densidad del aire --
Diagnóstico y estado de la estación
Sistema de adquisición
Recepción ISS --
Muestras de viento --
Transmisor --
Intervalo de archivo --

Gráficas meteorológicas

Explore el comportamiento histórico de las variables registradas por la estación.

Serie meteorológica

Datos registrados

Consulta completa de los registros archivados por WeatherLink y almacenados en la base histórica.

Página 1

Ubicación de la estación

Localización geográfica de la estación meteorológica del Departamento de Ciencias Energéticas y Fluídicas.

Descarga de datos

Acceso a los registros meteorológicos para fines académicos, científicos y de investigación.

Base de datos meteorológica

Seleccione un rango de fechas para obtener los registros almacenados por el Centro de Meteorología UCA. El archivo Excel contiene todas las variables disponibles en la exportación de WeatherLink, además de una hoja de metadatos que identifica las unidades y variables utilizadas.

Los registros se almacenan de manera histórica en la base de datos local del sistema. La exportación puede realizarse para todo el período disponible o para un intervalo seleccionado.
Información del conjunto de datos
Institución
{{ university_name }}
Departamento
{{ department_name }}
Estación
{{ station_name }}
Equipo
{{ station_model }}
Fuente de adquisición
WeatherLink 6.0.5
Registros disponibles
--
""" # ============================================================ # PÁGINA PRINCIPAL # ============================================================ @app.route("/") def home(): return render_template_string( HTML, site_title= SITE_TITLE, university_name= UNIVERSITY_NAME, department_name= DEPARTMENT_NAME, station_name= STATION_NAME, station_model= STATION_MODEL, station_lat= STATION_LAT, station_lon= STATION_LON, station_name_json= json.dumps( STATION_NAME, ensure_ascii=False ), columns_json= json.dumps( COLUMNS, ensure_ascii=False ), metrics_json= json.dumps( CHART_METRICS, ensure_ascii=False ) ) # ============================================================ # ARRANQUE # ============================================================ init_database() # Primera importación import_weatherlink() # Hilo que revisará WeatherLink cada 30 segundos thread = threading.Thread( target= automatic_import_loop, daemon=True ) thread.start() if __name__ == "__main__": print() print("=" * 70) print( "CENTRO DE METEOROLOGÍA UCA" ) print("=" * 70) print( "Archivo WeatherLink:" ) print( resolve_weatherlink_file() or "NO ENCONTRADO" ) print() print( "Base de datos:" ) print( DATABASE_FILE ) print() print( "Página local:" ) print( f"http://127.0.0.1:{PORT}" ) print() print("=" * 70) app.run( host= "0.0.0.0", port= PORT, debug= False, use_reloader= False, threaded= True )