import streamlit as st

@st.cache_resource
def get_database_session(url):
    # Create a database session object that points to the URL.
    return session

s1 = get_database_session(SESSION_URL_1)
# Actually executes the function, since this is the first time it was
# encountered.

s2 = get_database_session(SESSION_URL_1)
# Does not execute the function. Instead, returns its previously computed
# value. This means that now the connection object in s1 is the same as in s2.

s3 = get_database_session(SESSION_URL_2)
# This is a different URL, so the function executes.

By default, all parameters to a cache_resource function must be hashable. Any parameter whose name begins with _ will not be hashed. You can use this as an "escape hatch" for parameters that are not hashable:

import streamlit as st

@st.cache_resource
def get_database_session(_sessionmaker, url):
    # Create a database connection object that points to the URL.
    return connection

s1 = get_database_session(create_sessionmaker(), DATA_URL_1)
# Actually executes the function, since this is the first time it was
# encountered.

s2 = get_database_session(create_sessionmaker(), DATA_URL_1)
# Does not execute the function. Instead, returns its previously computed
# value - even though the _sessionmaker parameter was different
# in both calls.

A cache_resource function's cache can be procedurally cleared:

import streamlit as st

@st.cache_resource
def get_database_session(_sessionmaker, url):
    # Create a database connection object that points to the URL.
    return connection

get_database_session.clear()
# Clear all cached entries for this function.

To override the default hashing behavior, pass a custom hash function. You can do that by mapping a type (e.g. Person) to a hash function (str) like this:

import streamlit as st
from pydantic import BaseModel

class Person(BaseModel):
    name: str

@st.cache_resource(hash_funcs={Person: str})
def get_person_name(person: Person):
    return person.name

Alternatively, you can map the type's fully-qualified name (e.g. "__main__.Person") to the hash function instead:

import streamlit as st
from pydantic import BaseModel

class Person(BaseModel):
    name: str

@st.cache_resource(hash_funcs={"__main__.Person": str})
def get_person_name(person: Person):
    return person.name