Compare commits
12 Commits
Author | SHA1 | Date | |
---|---|---|---|
73b55b05c4
|
|||
aa74c02498 | |||
6fd2bd0863 | |||
2c78fba3a6 | |||
86b883569f | |||
ba86a08632 | |||
0b61a18eb1 | |||
1418603007 | |||
9926c89ef2 | |||
fc6f407a52 | |||
0e9cb0a7f8 | |||
e3b2ea704d |
116
src/run.py
116
src/run.py
@ -7,6 +7,7 @@ import redis
|
||||
import json
|
||||
import os
|
||||
import plotly.express as px
|
||||
import plotly.graph_objects as po
|
||||
import pandas as pd
|
||||
import psycopg
|
||||
import sqlalchemy
|
||||
@ -52,13 +53,15 @@ def index():
|
||||
dbh = psycopg.connect()
|
||||
engine = sqlalchemy.create_engine("postgresql+psycopg://", creator=lambda: dbh)
|
||||
|
||||
step0 = time.time()
|
||||
step0_time = time.time()
|
||||
df = pd.read_sql("SELECT month, cast(year AS varchar), current_energy AS value FROM pv_energy_by_month", con=engine)
|
||||
step1_time = time.time()
|
||||
duration1 = step1_time - step0_time
|
||||
logger.info(f"{duration1=}")
|
||||
fig_1 = px.bar(df, x='month', y='value', color='year', barmode='group')
|
||||
step2_time = time.time()
|
||||
duration2 = step2_time - step1_time
|
||||
logger.info(f"{duration2=}")
|
||||
fig_1.update_layout(
|
||||
title=f"Jahreswerte Exportierte Energie {duration1:.3f}, {duration2:.3f}",
|
||||
xaxis_title="",
|
||||
@ -71,39 +74,44 @@ def index():
|
||||
),
|
||||
yaxis=dict(ticksuffix=" kWh")
|
||||
)
|
||||
graph_html_1 = fig_1.to_html(full_html=False, default_height='33%')
|
||||
graph_html_1 = fig_1.to_html(full_html=False, default_height='30%')
|
||||
|
||||
step3_time = time.time()
|
||||
df = pd.read_sql("SELECT time_bucket('5 minutes', time) AS bucket, AVG(power) AS avg_power FROM pv_power_v WHERE time >= date_trunc('day', now()) - '1 day'::interval AND time < date_trunc('day', now()) GROUP BY bucket ORDER BY bucket", con=engine)
|
||||
step4_time = time.time()
|
||||
duration1 = step4_time - step3_time
|
||||
duration3 = step4_time - step3_time
|
||||
logger.info(f"{duration3=}")
|
||||
fig_2 = px.line(df, x='bucket', y='avg_power')
|
||||
step5_time = time.time()
|
||||
duration2 = step5_time - step4_time
|
||||
duration4 = step5_time - step4_time
|
||||
logger.info(f"{duration4=}")
|
||||
fig_2.update_layout(
|
||||
xaxis_title="",
|
||||
yaxis_title="",
|
||||
title=f"Export gestern {duration1:.3f}, {duration2:.3f}",
|
||||
title=f"Export gestern {duration3:.3f}, {duration4:.3f}",
|
||||
yaxis=dict(ticksuffix=" W")
|
||||
)
|
||||
graph_html_2 = fig_2.to_html(full_html=False, default_height='33%')
|
||||
graph_html_2 = fig_2.to_html(full_html=False, default_height='30%')
|
||||
|
||||
step6_time = time.time()
|
||||
df = pd.read_sql("SELECT time_bucket('5 minutes', time) AS bucket, AVG(power) AS avg_power FROM pv_power_v WHERE time >= date_trunc('day', now()) AND time < date_trunc('day', now()) + '1 day'::interval GROUP BY bucket ORDER BY bucket", con=engine)
|
||||
step7_time = time.time()
|
||||
duration1 = step7_time - step6_time
|
||||
duration5 = step7_time - step6_time
|
||||
logger.info(f"{duration5=}")
|
||||
fig_3 = px.line(df, x='bucket', y='avg_power')
|
||||
step8_time = time.time()
|
||||
duration2 = step8_time - step7_time
|
||||
duration6 = step8_time - step7_time
|
||||
logger.info(f"{duration6=}")
|
||||
fig_3.update_layout(
|
||||
xaxis_title="",
|
||||
yaxis_title="",
|
||||
title=f"Export heute {duration1:.3f}, {duration2:.3f}",
|
||||
title=f"Export heute {duration5:.3f}, {duration6:.3f}",
|
||||
yaxis=dict(ticksuffix=" W")
|
||||
)
|
||||
graph_html_3 = fig_3.to_html(full_html=False, default_height='33%')
|
||||
graph_html_3 = fig_3.to_html(full_html=False, default_height='30%')
|
||||
stepZ_time = time.time()
|
||||
duration = stepZ_time - stepX_time
|
||||
duration7 = stepZ_time - stepX_time
|
||||
logger.info(f"{duration7=}")
|
||||
|
||||
return render_template_string(f"""
|
||||
<html>
|
||||
@ -114,9 +122,23 @@ def index():
|
||||
{graph_html_1}
|
||||
{graph_html_2}
|
||||
{graph_html_3}
|
||||
<p>
|
||||
{duration:.3f}
|
||||
</p>
|
||||
<div style="height:9vh; background-color:lightgrey; font-family: Courier, Consolas, monospace;">
|
||||
<table style="border-collapse: collapse;">
|
||||
<style>
|
||||
td.smallsep {{ padding-right: 10px }}
|
||||
td.largesep {{ padding-right: 30px }}
|
||||
</style>
|
||||
<tr>
|
||||
<td class="smallsep">Query 1:</td><td class="largesep"> {duration1:.3f} s</td><td class="smallsep">Graph 1:</td><td> {duration2:.3f} s</td>
|
||||
</tr><tr>
|
||||
<td class="smallsep">Query 2:</td><td class="largesep"> {duration3:.3f} s</td><td class="smallsep">Graph 2:</td><td> {duration4:.3f} s</td>
|
||||
</tr><tr>
|
||||
<td class="smallsep">Query 3:</td><td class="largesep"> {duration5:.3f} s</td><td class="smallsep">Graph 3:</td><td> {duration6:.3f} s</td>
|
||||
</tr><tr>
|
||||
<td class="smallsep">Total:</td><td> {duration7:.3f} s</td><td></td><td></td>
|
||||
</tr>
|
||||
</table>
|
||||
</div>
|
||||
</body>
|
||||
</html>
|
||||
""")
|
||||
@ -127,6 +149,72 @@ def index():
|
||||
dbh.close()
|
||||
|
||||
|
||||
@app.route('/ntpserver')
|
||||
def ntpserver():
|
||||
try:
|
||||
dbh = psycopg.connect()
|
||||
engine = sqlalchemy.create_engine("postgresql+psycopg://", creator=lambda: dbh)
|
||||
|
||||
query = """
|
||||
select time_bucket('5 minutes', time) as bucket,
|
||||
device,
|
||||
avg(cast(values->'rootdisp'->>'value' as float)) as rootdisp,
|
||||
avg(cast(values->'stratum'->>'value' as int)) as stratum
|
||||
from measurements
|
||||
where time >= date_trunc('day', now()) AND time < date_trunc('day', now()) + '1 day'::interval and
|
||||
application = 'TSM' and attributes->>'Label' = 'david'
|
||||
group by bucket, device
|
||||
order by bucket, device
|
||||
"""
|
||||
|
||||
df = pd.read_sql(query, con=engine)
|
||||
|
||||
fig = po.Figure()
|
||||
fig.add_trace(po.Scatter(x=df['bucket'], y=df['rootdisp'], mode='lines', name='Root Dispersion', yaxis='y1', line=dict(color='red')))
|
||||
fig.add_trace(po.Scatter(x=df['bucket'], y=df['stratum'], mode='lines', name='Stratum', yaxis='y2', line=dict(color='blue')))
|
||||
|
||||
fig.update_layout(
|
||||
title='NTP Server Numbers',
|
||||
|
||||
# Linke Y-Achse
|
||||
yaxis=dict(
|
||||
title='Root Dispersion'
|
||||
),
|
||||
|
||||
# Rechte Y-Achse
|
||||
yaxis2=dict(
|
||||
title='Stratum',
|
||||
overlaying='y', # Legt die zweite Y-Achse über die erste
|
||||
side='right', # Setzt sie auf die rechte Seite
|
||||
tickmode='linear', # Stellt sicher, dass die Ticks in festen Intervallen sind
|
||||
dtick=1, # Zeigt nur ganzzahlige Ticks
|
||||
),
|
||||
|
||||
legend=dict(x=0.05, y=1) # Position der Legende
|
||||
)
|
||||
|
||||
|
||||
graph_html = fig.to_html(full_html=False, default_height='30%')
|
||||
|
||||
return render_template_string(f"""
|
||||
<html>
|
||||
<head>
|
||||
<title>NTP Server Numbers</title>
|
||||
</head>
|
||||
<body>
|
||||
{graph_html}
|
||||
</body>
|
||||
</html>
|
||||
""")
|
||||
except Exception as e:
|
||||
raise Exception(f"Error when querying NTP server values: {e}")
|
||||
finally:
|
||||
if dbh is not None:
|
||||
dbh.close()
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
|
Reference in New Issue
Block a user