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.

Installation

Install via pip:

$ pip install jitcache

Documentation

Full documentation available here https://jitcache.readthedocs.io/

Basic Usage

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))

Output:

Slow Function Called
40

Plot.ly Dash Usage

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)