Demo#
Here is a demo code to perform simple operation on the data from the Blocks. The code also shows the implementation of the loading the saved schemas and the activation-deactivation of the compute_engine
.
Demo code#
from barfi import st_barfi, barfi_schemas, Block
import streamlit as st
from barfi import Block
feed = Block(name='Feed')
feed.add_output()
def feed_func(self):
self.set_interface(name='Output 1', value=4)
feed.add_compute(feed_func)
splitter = Block(name='Splitter')
splitter.add_input()
splitter.add_output()
splitter.add_output()
def splitter_func(self):
in_1 = self.get_interface(name='Input 1')
value = (in_1/2)
self.set_interface(name='Output 1', value=value)
self.set_interface(name='Output 2', value=value)
splitter.add_compute(splitter_func)
mixer = Block(name='Mixer')
mixer.add_input()
mixer.add_input()
mixer.add_output()
def mixer_func(self):
in_1 = self.get_interface(name='Input 1')
in_2 = self.get_interface(name='Input 2')
value = (in_1 + in_2)
self.set_interface(name='Output 1', value=value)
mixer.add_compute(mixer_func)
result = Block(name='Result')
result.add_input()
def result_func(self):
in_1 = self.get_interface(name='Input 1')
result.add_compute(result_func)
load_schema = st.selectbox('Select a saved schema:', barfi_schemas())
compute_engine = st.checkbox('Activate barfi compute engine', value=False)
barfi_result = st_barfi(base_blocks=[feed, result, mixer, splitter],
compute_engine=compute_engine, load_schema=load_schema)
if barfi_result:
st.write(barfi_result)