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0e9cb0a7f8 timing
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2025-01-30 14:16:01 +01:00
e3b2ea704d timing
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2025-01-30 13:35:08 +01:00

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@ -52,7 +52,7 @@ def index():
dbh = psycopg.connect() dbh = psycopg.connect()
engine = sqlalchemy.create_engine("postgresql+psycopg://", creator=lambda: dbh) 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) 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() step1_time = time.time()
duration1 = step1_time - step0_time duration1 = step1_time - step0_time
@ -71,7 +71,7 @@ def index():
), ),
yaxis=dict(ticksuffix=" kWh") 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() 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) 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)
@ -86,7 +86,7 @@ def index():
title=f"Export gestern {duration1:.3f}, {duration2:.3f}", title=f"Export gestern {duration1:.3f}, {duration2:.3f}",
yaxis=dict(ticksuffix=" W") 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() 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) 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)
@ -101,7 +101,7 @@ def index():
title=f"Export heute {duration1:.3f}, {duration2:.3f}", title=f"Export heute {duration1:.3f}, {duration2:.3f}",
yaxis=dict(ticksuffix=" W") 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() stepZ_time = time.time()
duration = stepZ_time - stepX_time duration = stepZ_time - stepX_time
@ -114,9 +114,9 @@ def index():
{graph_html_1} {graph_html_1}
{graph_html_2} {graph_html_2}
{graph_html_3} {graph_html_3}
<p> <div style="height:9vh; background-color:lightgrey;">
{duration:.3f} {duration:.3f}
</p> </div>
</body> </body>
</html> </html>
""") """)