How do I use updatable displays on colab? - ipython

On the Jupyter Notebook I can create named outputs that are able to be updated like this:
from IPython.display import HTML, display
import time
def progress(value, max=100):
return HTML("""
<progress
value='{value}'
max='{max}',
style='width: 100%'
>
{value}
</progress>
""".format(value=value, max=max))
out = display(progress(0, 100), display_id=True)
for ii in range(101):
time.sleep(0.02)
out.update(progress(ii, 100))
Whereas in colab it doesn't update the progress bar.
How do you do this in colab?


Good news! This now works in Colab. :)
(Previously, we didn't support update_display_data messages.)
Pasting the code for anyone with sharing issues:
from IPython.display import HTML, display
import time
def progress(value, max=100):
return HTML("""
<progress
value='{value}'
max='{max}',
style='width: 100%'
>
{value}
</progress>
""".format(value=value, max=max))
out = display(progress(0, 100), display_id=True)
for ii in range(101):
time.sleep(0.02)
out.update(progress(ii, 100))

Related

How to use echarts-gl with echarts

I am learning to use echarts.js for my project.
I would like to know to use the extension echarts-gl (for 3D graphics) with ES modules. The documentation is very succinct and I am just a noobie.
In fact, I am trying to use echarts-gl together with the echarts-for-vue, anyone have tried it?
My main.js looks like this:
import Vue from 'vue';
import App from './App.vue';
import { plugin } from 'echarts-for-vue';
import * as echarts from 'echarts/esm/echarts';
import 'echarts/esm/chart/line';
import 'echarts/esm/chart/bar';
import 'echarts/esm/component/title';
import 'echarts/esm/component/tooltip';
import 'echarts/esm/component/legend';
import 'echarts/esm/component/toolbox';
import 'echarts/esm/component/polar';
import 'echarts/esm/component/visualMap';
// require('echarts-gl/lib/echarts-gl');
// import '../assets/echarts-gl.js';
// import 'echarts-gl/lib/component/grid3D';
// import 'echarts-gl/lib/chart/surface';
Vue.config.productionTip = false;
Vue.use(plugin, { echarts });
new Vue({
render: (h) => h(App),
}).$mount('#app');
I don't know where or how to include the imports for echarts-gl. Do I need webpack configuration?
Sorry about my lack of expertise.
Thanks!

For me it worked when I just imported it like this:
import 'echarts';
import 'echarts-gl';
Also make sure to use a compatible version of echarts-gl with echarts.
(
"echarts": "4.9.0",
"echarts-gl": "1.1.2",
"vue-echarts": "4.1.0",
)

how to shortcut the imports from styled-components

i have file of many styled components vars
export {NavHeader, MainNav, Logo, LogoContainer, NavBarUl, SubUl, Li, SubLi, NavLink, HamburgerContainer}
now i need to import it to the componenets and its very huge
import {
NavHeader,
MainNav,
Logo,
LogoContainer,
NavBarUl,
SubUl,
Li,
SubLi,
NavLink,
HamburgerContainer,
A,
} from "../styles/Header";
there is a way to handle this? and import * or something?

import * as Header from '../styles/Header';
then you can use
<Header.NavHeader />

How can I hide code and rerun all cells in JupyterLab?

I'd like to do exacly what has been asked and answered in the post How can I hide code and rerun all cells in a jupyter notebook? but in JupyterLab. A while back, this just didn't seem to be possible. But after the release of v0.33 I believe it should be possible since:
Javascript execution in notebook cells has been re-enabled
But If i try to run the script below, the only thing that happens in JupyterLab is that this output is produced:
Output:
Button(description='Refresh', style=ButtonStyle())
Code:
from IPython.display import HTML
HTML('''<script>
function code_toggle() {
if (code_shown){
$('div.input').hide('500');
$('#toggleButton').val('Show code')
} else {
$('div.input').show('500');
$('#toggleButton').val('Hide code')
}
code_shown = !code_shown
}
$( document ).ready(function(){
code_shown=false;
$('div.input').hide()
});
</script>
<form action="javascript:code_toggle()"><input type="submit" id="toggleButton" value="Show code"></form>''')
from IPython.display import Javascript, display
from ipywidgets import widgets
def run_all(ev):
display(Javascript('IPython.notebook.execute_cells_below()'))
button = widgets.Button(description="Refresh")
button.on_click(run_all)
display(button)
So, does anyone know if this should be possible in JupyterLab?

Deploy Bokeh Document to Server

I am following the example code I've attached below. It currently displays the plot and associated slider embedded in the doc returned by the "modify_doc" function in the notebook. However, I'd like to deploy it into it's own server to make a GUI, while still maintaining it's ability to run the callback when the slider is changed and update the plot. However when I try to use Panel Pyviz to deploy it, it just displays the message "< bokeh.document.document.Document object at 0x00000193EC5FFE80 >" on the server that pops up. How do I deploy the doc in a way that will display the image?
import numpy as np
import holoviews as hv
from bokeh.io import show, curdoc
from bokeh.layouts import layout
from bokeh.models import Slider, Button
renderer = hv.renderer('bokeh').instance(mode='server')
# Create the holoviews app again
def sine(phase):
xs = np.linspace(0, np.pi*4)
return hv.Curve((xs, np.sin(xs+phase))).opts(width=800)
stream = hv.streams.Stream.define('Phase', phase=0.)()
dmap = hv.DynamicMap(sine, streams=[stream])
# Define valid function for FunctionHandler
# when deploying as script, simply attach to curdoc
def modify_doc(doc):
# Create HoloViews plot and attach the document
hvplot = renderer.get_plot(dmap, doc)
# Create a slider
def slider_update(attrname, old, new):
# Notify the HoloViews stream of the slider update
stream.event(phase=new)
start, end = 0, np.pi*2
slider = Slider(start=start, end=end, value=start, step=0.2, title="Phase")
slider.on_change('value', slider_update)
# Combine the holoviews plot and widgets in a layout
plot = layout([
[hvplot.state],
[slider]], sizing_mode='fixed')
doc.add_root(plot)
return doc
# To display in the notebook
show(modify_doc, notebook_url='localhost:8888')
# To display in a script
doc = modify_doc(curdoc())
# To deploy to separate server using Panel (attempt, doesn't work. Just displays #"<bokeh.document.document.Document object at 0x00000193EC5FFE80>":
graph = pn.Row (doc)
graph.show()

There is some mixing of very different APIs going on in your example. Panel is meant to simplify some of Bokeh's APIs so a lot of what you're doing here isn't necessary. That said I'll provide a few versions which are either using only Panel components or combining Panel and bokeh components.
To start with this is how I might write this example using just Panel:
import numpy as np
import panel as pn
import holoviews as hv
pn.extension()
start, end = 0, np.pi*2
slider = pn.widgets.FloatSlider(start=start, end=end, value=start, step=0.2, name="Phase")
#pn.depends(phase=slider.param.value)
def sine(phase):
xs = np.linspace(0, np.pi*4)
return hv.Curve((xs, np.sin(xs+phase))).opts(width=800)
dmap = hv.DynamicMap(sine)
row = pn.Row(dmap, slider)
# Show in notebook
row.app('localhost:8888')
# Open a server
row.show()
# To deploy this using `panel serve` or `bokeh serve`
row.servable()
In your example you instead use various bokeh components, this is also possible and might be desirable if you've already got bokeh code.
import numpy as np
import holoviews as hv
import panel as pn
from bokeh.models import Slider, Button
# Create the holoviews app again
def sine(phase):
xs = np.linspace(0, np.pi*4)
return hv.Curve((xs, np.sin(xs+phase))).opts(width=800)
stream = hv.streams.Stream.define('Phase', phase=0.)()
dmap = hv.DynamicMap(sine, streams=[stream])
def slider_update(attrname, old, new):
# Notify the HoloViews stream of the slider update
stream.event(phase=new)
start, end = 0, np.pi*2
slider = Slider(start=start, end=end, value=start, step=0.2, title="Phase")
slider.on_change('value', slider_update)
graph = pn.Row(dmap, slider)
# Show in notebook
row.app('localhost:8888')
# Open a server
row.show()
# To deploy this using `panel serve` or `bokeh serve`
row.servable()
If you want to serve these apps to multiple people I'd definitely recommend using panel serve but if you really want to make a script you can run with python script.py you should do this:
def app():
start, end = 0, np.pi*2
slider = pn.widgets.FloatSlider(start=start, end=end, value=start, step=0.2, name="Phase")
#pn.depends(phase=slider.param.value)
def sine(phase):
xs = np.linspace(0, np.pi*4)
return hv.Curve((xs, np.sin(xs+phase))).opts(width=800)
dmap = hv.DynamicMap(sine)
return pn.Row(dmap, slider)
pn.serve({'/': app})
This requires latest Panel, but ensures that even if you run the app as a script that each user gets a new instance of the app which does not share state with all others.

How to align widget buttons in IPython notebook

I have the following peace of code
from ipywidgets import widgets
from IPython.display import display
import numpy as np
class Test(object):
def __init__(self, arraylen):
self.a = np.random.randn(arraylen)
self.button = widgets.Button(description = 'Show')
self.button.on_click(self.show)
display(self.button)
self.button1 = widgets.Button(description = 'Show1')
self.button1.on_click(self.show)
display(self.button1)
def show(self, ev = None):
np.savetxt('test',self.a)
self.button.disabled = True
test = Test(10)
The output is two buttons in a column as shown here:
Would it also be possible, to embed the buttons in a HTML table (where I could choose them to be in a row), or any other organization scheme? Maybe it could look like this:

You could use (a very basic example):
from IPython.display import display
from ipywidgets import widgets
button1 = widgets.Button(description = 'Button1')
button2 = widgets.Button(description = 'Button2')
display(widgets.HBox((button1, button2)))
Here you can find basic and more complete examples about the use of the widgets. If you are using Jupyter you should adapt some info (from ipywidgets import widgets instead from IPython.html import widgets,...).