Shared parameter?

For a project I am working on, I have a param.Dataframe that can be updated and modified, or even replaced (through syncing with a database). I would then have multiple different Parameterized instances that draw data from this dataframe. Is there a way that I can sync this base dataframe across all those objects? i.e. can they all share a single instance of the dataframe? Or is the only way to use options?

I asked a similar question before here: Can a paramterized class react to parameters outside of itself?

You can pass parameterized classes (like a dataframe) into other parameterized classes (some random component) and react to them.

import param
import numpy as np
import pandas as pd

class Data(param.Parameterized):
    df = param.DataFrame(df)

class Component1(param.Parameterized):
    data = param.Parameterized()

    def view(self):
class Component2(param.Parameterized):
    data = param.Parameterized()

    def view(self):
        return len(
data = Data(df = pd.DataFrame(np.random.rand(10,10)))
# Have components that take the dataframe as a parameter
c1 = Component1(data=data)
c2 = Component2(data=data)

# Components have access to dataframe
print(c1.view(), c2.view())

#Update dataframe
data.df = pd.DataFrame(np.random.rand(100,100))

# Have it show up in all other components
print(c1.view(), c2.view())
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Cool, this makes sense and is really helpful! I’m also wondering if there’s a way to set it so it’s possible to call @param.depends(‘data’) rather than @param.depends(‘data.df’)?

Not as far as I know. param.depends reacts to parameters, not parameterized classes. You have to specify which parameters you want to depend on when using param.depends.

Interestingly, you can just omit the param.depends entirely from your methods, and each one will react all parameters declared in the class without having to specify which. Refer to: What is the purpose of @param.depends in a parameterized class?

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Actually, this may not be true. By setting param.depends('data') I seem to get the same functionality.