jitcache¶
jitcache is a just-in-time key-value cache that is thread/process safe. jitcache also prevents repeated computation when multiple workers request the same value.
jitcache was designed to improve the performance of Plot.ly Dash apps by caching results and reducing CPU load.
Documentation¶
Examples and specific information on classes and methods are below.
Basic Usage¶
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | from jitcache import Cache
import time
cache = Cache()
@cache.memoize
def slow_fn(input_1, input_2, input_3=10):
print("Slow Function Called")
time.sleep(1)
return input_1 * input_2 * input_3
print(slow_fn(10, 2))
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Plot.ly Dash Usage¶
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | import dash
import dash_html_components as html
from jitcache import Cache
import dash_core_components as dcc
cache = Cache()
app = dash.Dash(__name__)
server = app.server
app.layout = html.Div(
children=[
html.Div(id="output-container-dropdown1", children=[]),
html.Div(id="output-container-dropdown2", children=[]),
dcc.Dropdown(
options=[
{"label": "New York City", "value": "NYC"},
{"label": "Montréal", "value": "MTL"},
{"label": "San Francisco", "value": "SF"},
],
value="MTL",
id="dropdown",
),
]
)
@app.callback(
dash.dependencies.Output("output-container-dropdown1", "children"),
[dash.dependencies.Input("dropdown", "value")],
)
@cache.memoize
def update_output1(input_dropdown):
print("run1")
return input_dropdown
@app.callback(
dash.dependencies.Output("output-container-dropdown2", "children"),
[dash.dependencies.Input("dropdown", "value")],
)
@cache.memoize
def update_output2(input_dropdown):
print("run2")
return input_dropdown
if __name__ == "__main__":
app.run_server(debug=True)
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