The following code looks like it's a combination of both plotly dash and Jupyter dash and it was run via jupyter notebook. Can someone explain why both jupyter dash and plotly dash need to be used together?
from jupyter_dash import JupyterDash
from dash import Dash, dcc, html, Input, Output, no_update
import plotly.graph_objects as go
import pandas as pd
app = JupyterDash(__name__)
fig = go.Figure(data=[
go.Scatter(
x=df['x_lv'], #x_px and y_px for pixel data
y=df['y_lv'],
mode='markers',
marker=dict(color=df['color']), showlegend=True
)
])
# turn off native plotly.js hover effects - make sure to use
# hoverinfo="none" rather than "skip" which also halts events.
fig.update_traces(hoverinfo="none", hovertemplate=None)
server = app.server
app.layout = html.Div([
dcc.Graph(id="graph-basic-2", figure=fig, clear_on_unhover=True),
dcc.Tooltip(id="graph-tooltip"), html.Div(id="debug"),
])
#app.callback(
Output("graph-tooltip", "show"),
Output("graph-tooltip", "bbox"),
Output("graph-tooltip", "children"),
Input("graph-basic-2", "hoverData"),
)
def display_hover(hoverData):
if hoverData is None:
return False, no_update, no_update
# demo only shows the first point, but other points may also be available
pt = hoverData["points"][0]
bbox = pt["bbox"]
num = pt["pointNumber"]
app.run_server(mode="inline", host="localhost",port=8052)
The code you posted uses a JupyterDash app, identifiable from the line app = JupyterDash(__name__). However, it uses Dash components as part of the app, because JupyterDash (which is by the way developed by plotly, as is the "original" Dash) is basically the same thing as Dash, but tailored to run from within a Jupyter notebook. So a JupyterDash app can be built just like a Dash app, but will provide extra features for a smooth user experience in a Jupyter notebook.
For more details, I suggest reading the announcement of JupyterDash from plotly.
Related
Sorry if the question is not entirely clear. Will add details if unclear.
PrintPlugin is a class from another python file I have imported. I used to get clickable links on this on VS code. Meaning, if I cmd+click on PrintPlugin it would go to that class on the source Python file.
My bottom bar used to look like this when it was working.
Now it looks like this
The difference is that I was having the Python 3.9.5 64-bit ('base':conda) earlier.
Everything else works fine. I am on my virtual environment too. I am not sure what else could be causing this. Will add any details required.
Edit:
I have added some reproducible code. This differs from the original image because the original was work related and I can't post it here. But I'm still running this in the same folder and in the same virtual environment, so it has the same problem (that I cannot cmd+click on Multiply() in process.py and go to the class on plugin.py)
File process.py
import numpy as np
from plugin import Multiply
a = np.array([[2,3],
[3,4]])
b = np.array([[5,6],
[7,8]])
result = Multiply()
print(result.multiply(a,b))
File plugin.py
import numpy as np
class Multiply():
def __init__(
self,
a = np.array([[1,1],
[1,1]]),
b = np.array([[1,1],
[1,1]])
):
return
def multiply(self,a,b):
c = a # b
return c
Output when I do python process.py
>>> [[31 36]
[43 50]]
I'm trying to figure out how to activate CodeMirror syntax highlighting for a CodeMirror-supported language (cypher) within a cell for a custom Jupyter cell magic (%%mymagic). The magic isn't associated with a special kernel - it just runs Python commands that process the string entered into the cell that I want to highlight. From what I can tell, this ostensibly can be done using something like
from notebook.services.config.manager import ConfigManager
cm = ConfigManager()
cm.update('notebook', {'CodeCell': {'highlight_modes': {'magic_cypher': {'reg': '^%%mymagic'}}}})
within the class that implements the magic.
I can't seem to get this to work, however; no change in highlighting occurs when I enter stuff in a cell that starts with %%mymagic. Is the above approach accurate? Does 'magic_cypher' need to have a specific format? Does the magic need to somehow specify the MIME type CodeMirror associates with the desired highlighting language? I'm using notebook 5.0.0, jupyter_core 4.3.0, and python 2.7.13.
The following code works for SQL when placed in ~/.jupyter/custom/custom.js with notebook 5.x:
require(['notebook/js/codecell'], function(codecell) {
codecell.CodeCell.options_default.highlight_modes['magic_text/x-mssql'] = {'reg':[/^%%sql/]} ;
Jupyter.notebook.events.one('kernel_ready.Kernel', function(){
Jupyter.notebook.get_cells().map(function(cell){
if (cell.cell_type == 'code'){ cell.auto_highlight(); } }) ;
});
});
Credit goes to Thomas K for this info!
The case where I've been successful doing this was in adding SQL highlighting for the %%sql magic. I did this by adding the following to ~/.jupyter/custom/custom.js. The first line adds the mode to the Codemirror configuration, the rest apply the style to any existing cells in the workbook that need it (later cells will get styled appropriately as they are created). I haven't been successful in having it happen when the magic is installed, although I expect that it is possible.
IPython.CodeCell.config_defaults.highlight_modes['magic_text/x-mssql'] = {'reg':[/^%%sql/]} ;
IPython.notebook.events.one('kernel_ready.Kernel', function(){
IPython.notebook.get_cells().map(function(cell){
if (cell.cell_type == 'code'){ cell.auto_highlight(); } }) ;
});
I'm surprised to not find a previous question about this, but I did give an honest try before posting.
I've created a ui with Qt Creator which contains quite a few QtWidgets of type QLineEdit, QTextEdit, and QCheckbox. I've used pyuic5 to convert to a .py file for use in a small python app. I've successfully got the form connected and working, but this is my first time using python with forms.
I'm searching to see if there is a built-in function or object that would allow me to pull the ObjectNames and Values of all widgets contained within the GUI form and store them in a dictionary with associated keys:values, because I need to send off the information for post-processing.
I guess something like this would work manually:
...
dict = []
dict['checkboxName1'] = self.checkboxName1.isChecked()
dict['checkboxName2'] = self.checkboxName2.isChecked()
dict['checkboxName3'] = self.checkboxName3.isChecked()
dict['checkboxName4'] = self.checkboxName4.isChecked()
dict['lineEditName1'] = self.lineEditName1.text()
... and on and on
But is there a way to grab all the objects and loop through them, even if each different type (i.e. checkboxes, lineedits, etc) needs to be done separately?
I hope I've explained that clearly.
Thank you.
Finally got it working. Couldn't find a python specific example anywhere, so through trial and error this worked perfectly. I'm including the entire working code of a .py file that can generate a list of all QCheckBox objectNames on a properly referenced form.
I named my form main_form.ui from within Qt Creator. I then converted it into a .py file with pyuic5
pyuic5 main_form.ui -o main_form.py
This is the contents of a sandbox.py file:
from PyQt5 import QtCore, QtGui, QtWidgets
import sys
import main_form
# the name of my Qt Creator .ui form converted to main_form.py with pyuic5
# pyuic5 original_form_name_in_creator.ui -o main_form.py
class MainApp(QtWidgets.QMainWindow, main_form.Ui_MainWindow):
def __init__(self):
super(self.__class__, self).__init__()
self.setupUi(self)
# Push button object on main_form named btn_test
self.btn_test.clicked.connect(self.runTest)
def runTest(self):
# I believe this creates a List of all QCheckBox objects on entire UI page
c = self.findChildren(QtWidgets.QCheckBox)
# This is just to show how to access objectName property as an example
for box in c:
print(box.objectName())
def main():
app = QtWidgets.QApplication(sys.argv) # A new instance of QApplication
form = MainApp() # We set the form to be our ExampleApp (design)
form.show() # Show the form
app.exec_() # and execute the app
if __name__ == '__main__': # if we're running file directly and not importing it
main() # run the main function
See QObject::findChildren()
In C++ the template argument would allow one to specify which type of widget to retrieve, e.g. to just retrieve the QLineEdit objects, but I don't know if or how that is mapped into Python.
Might need to retrieve all types and then switch handling while iterating over the resulting list.
This code contains the following tidbit:
from theano.tensor.nnet import conv2d
...
# convolve input feature maps with filters
conv_out = conv2d(
input=input,
filters=self.W,
filter_shape=filter_shape,
input_shape=image_shape
)
which raises an exception due to 'input_shape' not being found, despite being mentioned in the documentation where it says that:
"image_shape ... – Deprecated alias for input_shape"
Looking at conv.py both locally and in the source I found:
def conv2d(input, filters, image_shape=None, filter_shape=None,
border_mode='valid', subsample=(1, 1), **kargs):
Needless to say, there is no trace of input_shape.
If one modifies the code above as follows
# convolve input feature maps with filters
conv_out = conv2d(
input=input,
filters=self.W,
filter_shape=filter_shape,
image_shape=image_shape
)
, the exception disappears and the code runs fine.
What am I missing? If image_shape is deprecated, how come it works while input_shape does not?
Is the theano version at the repository obsolete?
PS: I would have liked to ask directly the folks at http://deeplearning.net, but I could not find how.
Are you sure you have the latest version installed?
conv.py contains the deprecated implementation of conv2d. The new implementation can be found in __init__.py
Make sure you are using the import statement
from theano.tensor.nnet import conv2d
and not
from theano.tensor.nnet.conv import conv2d
since the second one is going to import the deprecated implementation
I want to duplicate ipython notebook capability in Emacs / Pymacs; and I need some direction for a simple code that can 1) send python / "magics" code to a ipython kernel 2) receive the display output, as a string. I found this comment by minrk, the "ipython kernel" example did not work, it gave "ImportError: No module named zmq.blockingkernelmanager".
I had better luck with one his other pointers, finally I landed at ipython-1.1.0/IPython/kernel/inprocess/tests/test_kernel.py, I ripped out a minimal part, and coded an Emacs extension called pytexipy-notebook. It's on Github
goo.gl/kQzJW1
If anyone knows of better examples, such as connecting to an existing (out of process), I'd like to hear about these.
Thanks in advance,
Here is a sample for ipython 3.0.
from IPython.testing.globalipapp import get_ipython
from IPython.utils.io import capture_output
ip = get_ipython()
def run_cell(cmd):
with capture_output() as io:
res = ip.run_cell(content)
print 'suc', res.success
print 'res', res.result
res_out = io.stdout
print 'res out', res_out
content = "print (111+222)"
run_cell(content)
content = "alsdkjflajksf"
run_cell(content)
I will soon update
https://github.com/burakbayramli/emacs-ipython