Petites améliorations du graphe + préparation d'autre amélioration

Ajout téléchargement des données en JSON

raspberry/python/cameteo.py

@@ -41,9 +41,9 @@ db = SQLAlchemy(app)
 
 class SensorModel(db.Model):
     """SensorModel : classe des modèles de capteur"""
-    
+
     __tablename__= 'sensor_model'
-    
+
     name=db.Column(db.String(20), primary_key=True)
     brand=db.Column(db.String(20), nullable=False)
     description=db.Column(db.String(1000))
@@ -56,30 +56,33 @@ class SensorModel(db.Model):
 
 class Sensor(db.Model):
     """Sensor : classe des capteurs"""
-    
+
     __tablename__= 'sensors'
-    
+
     name = db.Column(db.String(20), primary_key=True)
     model_id = db.Column(db.String(20), nullable=False)
     description = db.Column(db.String(1000))
-    
+
     def __repr__(self):
         return "<Sensor(name='%s', model='%s', description='%s')>" % (self.name, self.model, self.description)
 
     def __str__(self):
-        return """%s : 
+        return """%s :
  - Modèle : \t%s
  - Description: \t%s""" % (self.name, self.model, self.description)
 
 class DataType(db.Model):
     """DataType : classe des types de données"""
-    
+
     __tablename__ = 'data_type'
-    
+
     type_id = db.Column(db.String(4), primary_key=True)
-    name = db.Column(db.String(20), nullable=False)
+    name = db.Column(db.String(20), nullable=False)       #Short name
-    description = db.Column(db.String(1000))
+    plot_mini = db.Column(db.Float, nullable=True)        #y minimum for plotting
-    
+    plot_maxi = db.Column(db.Float, nullable=True)        #y maximum for plotting
+    unit_si = db.Column(db.String(10), nullable=True)     #Unit in SI
+    description = db.Column(db.String(1000))              #Long description
+
     def __repr__(self):
         return "<DataType(name='%s', ID='%s', description='%s')>" % (self.name, self.type_id, self.description)
 
@@ -88,9 +91,9 @@ class DataType(db.Model):
 
 class Data(db.Model):
     """Data : classe des données"""
-    
+
     __tablename__ = 'data'
-    
+
     data_id = db.Column(db.BigInteger, primary_key=True, autoincrement="auto")
     dbdate = db.Column(db.DateTime, nullable=False)
     valdate = db.Column(db.DateTime, nullable=True)
@@ -98,29 +101,29 @@ class Data(db.Model):
     unit = db.Column(db.String(20), nullable=True)
     type_id = db.Column(db.String(4), nullable=True)
     sensor_id = db.Column(db.String(20), nullable=True)
-    
+
     def __repr__(self):
         return "<Data(value='%0.2f', type='%s', date='%s', sensor ID='%s', id='%s')>" % (self.value, self.type_id, self.valdate.utc, self.sensor_id, self.data_id)
 
     def __str__(self):
-        try:        
+        try:
             val = "{:8.2f} {:8s}".format(self.value, self.unit)
         except:
             val = "  'NULL'         "
         return "{} : {:4s}= {} (capteur: {:s})".format(self.valdate, self.type_id, val, self.sensor_id)
-        
+
 class Photo(db.Model):
     """DataType : classe des types de données"""
-    
+
     __tablename__ = 'photos'
-    
+
     photo_id = db.Column(db.BigInteger, primary_key=True, autoincrement="auto")
     file_name = db.Column(db.String(32), unique = True, index = True, nullable=False)
     file_date = db.Column(db.DateTime, nullable=False)
     image_type = db.Column(db.String(4), nullable=False)
-    
+
     def __repr__(self):
         return "<Photo(name='%s', date='%s', ID='%s')>" % (self.file_name, self.photo_id, self.description)
 
     def __str__(self):
-        return "%s" % (self.file_name)
+        return "%s" % (self.file_name)

raspberry/python/templates/data_graph.html.j2

@@ -1,5 +1,5 @@
 {% extends "base.html.j2" %}
-{% block title %}Camétéo{% endblock %}
+{% block title %}Camétéo - {{ data_type }}{% endblock %}
 
 {% block styles %}
   {{super()}}
@@ -13,6 +13,10 @@
 
     {{ plot_div|safe }}
 
+    <div id="json">
+      <a href="/json_type_id={{ data_type }}">Télécharger les données (JSON)</a>
+    </div>
+
     {{ render_pagination(dat) }}
 
     <div class="table-responsive">

raspberry/python/web_app.py

@@ -81,9 +81,10 @@ def by_data_type(dt):
     date_deb = datetime.now()-timedelta(hours=1)
     #Récupération des données à afficher
     q = Data.query.filter(Data.type_id == dt).filter(Data.dbdate >= date_deb).order_by(Data.valdate)
+    #q = Data.query.filter(Data.type_id == dt).order_by(Data.valdate)
     res = pd.read_sql(q.selectable, db.engine)
 
-    plot_data = ColumnDataSource(data=dict(x = res['data_valdate'], y = res['data_value']))
+    plot_data = ColumnDataSource(data=dict(dates = res['data_valdate'], values = res['data_value']))
 
     #Préparation du graphique
     data_plot = figure(tools        = "hover,pan,reset,save,wheel_zoom",
@@ -94,15 +95,17 @@ def by_data_type(dt):
                        plot_height  = 400,
                        plot_width   = 1140,
                        )
-    data_plot.line('x', 'y', source=plot_data, line_width=2)
+    data_plot.line('dates', 'values', source=plot_data, line_width=2)
 
     script, div = components(data_plot)
 
-    return render_template('data_graph.html.j2', dat=q.order_by(Data.dbdate.desc()).paginate(per_page=15),
+    return render_template('data_graph.html.j2',
-                           plot_script=script,
+                            data_type = dt,
-                           plot_div=div,
+                            dat=q.order_by(Data.dbdate.desc()).paginate(per_page=15),
-                           js_resources=js_resources,
+                            plot_script=script,
-                           css_resources=css_resources,
+                            plot_div=div,
+                            js_resources=js_resources,
+                            css_resources=css_resources,
                            )
 
 @app.route('/sensor_id=<sens>')
@@ -121,5 +124,15 @@ def config_page():
 
     return render_template('config_page.html.j2')
 
+@app.route('/json_type_id=<dt>')
+def json_by_data_type(dt):
+    date_deb = datetime.now()-timedelta(hours=1)
+    #Récupération des données à afficher
+    q = Data.query.filter(Data.type_id == dt).filter(Data.dbdate >= date_deb).order_by(Data.valdate)
+    #q = Data.query.filter(Data.type_id == dt).order_by(Data.valdate)
+    res = pd.read_sql(q.selectable, db.engine)
+
+    return res.to_json()
+
 if __name__=="__main__":
     app.run(host="0.0.0.0")