creating plot of last 3h values with pandas and matplotlib

backend/flask/app/graph.py

@@ -0,0 +1,90 @@
+""" makes the nice plots """
+
+from datetime import datetime
+
+from matplotlib import pyplot as plt
+import numpy as np
+import pandas as pd
+import psycopg2
+
+from app.db_connect import db_connect, db_close
+
+
+def create_current(config):
+    """ recreate current graph """
+    # last three hours
+    now = datetime.now()
+    now_human = now.strftime('%c')
+    now_epoch = int(now.strftime('%s'))
+    last_3h = now_epoch - 3 * 60 * 60
+    last_3h_limit = int(60 * 3)
+    # connect
+    conn, cur = db_connect(config)
+    # get data
+    cur.execute(
+        "SELECT epoch_time, aqi_value FROM aqi \
+        WHERE epoch_time > " + str(last_3h) + " ORDER BY epoch_time DESC \
+        LIMIT " + str(last_3h_limit) + ";")
+    rows = cur.fetchall()
+    # close db
+    db_close(conn, cur)
+    # parse rows
+    x, y, plt_title = build_plt(rows, now)
+    # calc x_ticks
+    x_ticks = []
+    for num, i in enumerate(x):
+        minute = int(i.split(':')[1])
+        if minute % 15 == 0:
+            x_ticks.append(num)
+    # write plt
+    write_plt(x, y, plt_title, x_ticks)
+    message = f'recreated current graph: {now_human}'
+    print(message)
+
+
+def build_plt(rows, now):
+    """ parse rows returns axis"""
+    # build x y
+    x_timeline = [datetime.fromtimestamp(i[0]) for i in rows]
+    y_aqi_values = [int(i[1]) for i in rows]
+    # build dataframe
+    data = {'timestamp': x_timeline, 'aqi': y_aqi_values}
+    df = pd.DataFrame(data)
+    # reindex as timeseries
+    indexed = df.set_index('timestamp')
+    indexed.sort_values(by=['timestamp'], inplace=True)
+    mean = indexed.resample('3min').mean()
+    mean.reset_index(level=0, inplace=True)
+    mean['timestamp'] = mean['timestamp'].dt.strftime('%H:%M')
+    mean['aqi'] = mean['aqi'].round()
+    # set axis
+    x = mean['timestamp']
+    y = mean['aqi']
+    # build title
+    data_from = now.strftime("%Y-%m-%d")
+    time_from = x_timeline[-1].strftime('%H:%M')
+    time_until = x_timeline[0].strftime('%H:%M')
+    plt_title = f'AQI values from: {data_from} {time_from} - {time_until}'
+    return x, y, plt_title
+
+
+def write_plt(x, y, plt_title, x_ticks):
+    """ save plot to file """
+    # calc ticks
+    y_max = np.ceil(y.max()/50)*50 + 50
+    # setup plot
+    plt.style.use('seaborn')
+    plt.plot(x, y, color='#313131',)
+    plt.fill_between(x, y, y2=0, where=(y > 0), color='#85a762', interpolate=True)              # good
+    plt.fill_between(x, y, y2=50, where=(y > 50), color='#d4b93c', interpolate=True)            # moderate
+    plt.fill_between(x, y, y2=100, where=(y > 100), color='#e96843', interpolate=True)          # ufsg
+    plt.fill_between(x, y, y2=150, where=(y > 150), color='#d03f3b', interpolate=True)          # unhealthy
+    plt.fill_between(x, y, y2=200, where=(y > 200), color='#be4173', interpolate=True)          # vunhealthy
+    plt.fill_between(x, y, y2=300, where=(y > 300), color='#714261', interpolate=True)          # hazardous
+    plt.fill_between(x, y, y2=0, where=(y > 0), color='#ffffff', alpha=0.1, interpolate=True)   # soft
+    plt.xticks(x_ticks)
+    plt.yticks(np.arange(0, y_max, step=50))
+    plt.title(plt_title)
+    plt.tight_layout()
+    plt.savefig('dyn/current.png', dpi = 300)
+    plt.figure()

backend/flask/app/views.py

@@ -9,9 +9,8 @@ from apscheduler.schedulers.background import BackgroundScheduler
 from app import app
 from app import aqi_parser
 from app import weather
-from app import db_insert
-
-auth = HTTPBasicAuth()
+from app import graph
+from app.db_connect import db_insert
 
 
 def get_config():
@@ -35,8 +34,10 @@ def get_config():
 
 
 # start up
+auth = HTTPBasicAuth()
 config = get_config()
 weather.handle_weather(config)
+graph.create_current(config)
 # build username / pw dict for basic auth
 USER_DATA = {}
 USER_DATA[config['authUsername']] = config['authPassword']
@@ -44,10 +45,13 @@ USER_DATA[config['authUsername']] = config['authPassword']
 
 # start scheduler
 scheduler = BackgroundScheduler()
-scheduler.start()
 scheduler.add_job(
     weather.handle_weather, args=[config], trigger="interval", name='weather_api', seconds=900
 )
+scheduler.add_job(
+    graph.create_current, args=[config], trigger="cron", minute='*/5', name='current_graph'
+)
+scheduler.start()
 
 
 @auth.verify_password
@@ -70,7 +74,7 @@ def ingest():
             print(json_dict)
         else:
             # save to db
-            time_stamp = db_insert.db_connect(config, json_dict)
+            time_stamp = db_insert(config, json_dict)
             print(f'db insert done at {time_stamp}')
             # save to webserver
             data = json.dumps(json_dict)

backend/flask/requirements.txt

@@ -1,7 +1,9 @@
 apscheduler
 Flask
 Flask-HTTPAuth
+matplotlib
 numpy
+pandas
 psycopg2-binary
 requests
 uWSGI