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Author SHA1 Message Date
37c4a373b7 timing
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ci/woodpecker/push/woodpecker Pipeline was successful
ci/woodpecker/tag/woodpecker Pipeline was successful
2025-01-30 10:25:56 +01:00
408cff442c timing
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ci/woodpecker/push/woodpecker Pipeline was successful
ci/woodpecker/tag/woodpecker Pipeline was successful
2025-01-30 10:19:07 +01:00

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@ -53,10 +53,13 @@ def index():
start_time = time.time() start_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)
duration = time.time() - start_time step1_time = time.time()
duration1 = step1_time - start_time
fig_1 = px.bar(df, x='month', y='value', color='year', barmode='group') fig_1 = px.bar(df, x='month', y='value', color='year', barmode='group')
step2_time = time.time()
duration2 = step2_time - start_time
fig_1.update_layout( fig_1.update_layout(
title=f"Jahreswerte Exportierte Energie {duration}", title=f"Jahreswerte Exportierte Energie {duration1:.3f}, {duration2:.3f}",
xaxis_title="", xaxis_title="",
yaxis_title="", yaxis_title="",
legend_title="Jahr", legend_title="Jahr",
@ -71,24 +74,30 @@ def index():
start_time = time.time() start_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)
duration = time.time() - start_time step1_time = time.time()
duration1 = step1_time - start_time
fig_2 = px.line(df, x='bucket', y='avg_power') fig_2 = px.line(df, x='bucket', y='avg_power')
step2_time = time.time()
duration2 = step2_time - start_time
fig_2.update_layout( fig_2.update_layout(
xaxis_title="", xaxis_title="",
yaxis_title="", yaxis_title="",
title=f"Export gestern {duration}", 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='33%')
start_time = time.time() start_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)
duration = time.time() - start_time step1_time = time.time()
duration1 = step1_time - start_time
fig_3 = px.line(df, x='bucket', y='avg_power') fig_3 = px.line(df, x='bucket', y='avg_power')
step2_time = time.time()
duration2 = step2_time - start_time
fig_3.update_layout( fig_3.update_layout(
xaxis_title="", xaxis_title="",
yaxis_title="", yaxis_title="",
title=f"Export heute {duration}", 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='33%')