Jupyter OSBot-Commands

bokeh.py

#https://bokeh.pydata.org/
#http://bokeh.pydata.org/en/latest/docs/installation.html
#https://nbviewer.jupyter.org/github/bokeh/bokeh-notebooks/blob/master/quickstart/quickstart.ipynb

!pip install bokeh
from bokeh.plotting import figure 
from bokeh.io import output_notebook, show
output_notebook()
from numpy import cos, linspace
x = linspace(-6, 60, 1200)
y = cos(x)
p = figure(width=500, height=500)
p.circle(x, y, size=7, color="firebrick", alpha=0.5)
show(p)

# Reall cool example 

from bokeh.sampledata.autompg import autompg

grouped = autompg.groupby("yr")

mpg = grouped.mpg
avg, std = mpg.mean(), mpg.std()
years = list(grouped.groups)
american = autompg[autompg["origin"]==1]
japanese = autompg[autompg["origin"]==3]

p = figure(title="MPG by Year (Japan and US)")

p.vbar(x=years, bottom=avg-std, top=avg+std, width=0.8, 
       fill_alpha=0.2, line_color=None, legend="MPG 1 stddev")

p.circle(x=japanese["yr"], y=japanese["mpg"], size=10, alpha=0.5,
         color="red", legend="Japanese")

p.triangle(x=american["yr"], y=american["mpg"], size=10, alpha=0.3,
           color="blue", legend="American")

p.legend.location = "top_right"
show(p)

cells-python.py

#---- get issue
from osbot_jira.api.jira_server.API_Jira import API_Jira
api_jira = API_Jira()

#---- take screenshot
from osbot_aws.apis.Lambda import Lambda
lambda_name    = 'osbot_browser.lambdas.lambda_browser'
lambda_browser = Lambda(lambda_name)
payload        = {"params": ['screenshot','https://news.bbc.co.uk']}
png_data = lambda_browser.invoke(payload)
from IPython.display import display_html
html = '<img style="margin:0" align="left" src="data:image/png;base64,{}"/>'.format(png_data)
display_html(html, raw=True)

cells_with-bash.sh

# install dependencies
!pip install osbot_aws boto3 pbx_gs_python_utils osbot_jira jira

# list current servers
!jupyter notebook list

# stop server at 8888
!jupyter notebook stop 8888

chrome-in-code-build.py

#bash commands
apt-get install -y libnss3 libgconf-2-4
pip install nest_asyncio
pip install syncer, pyppeteer
pip install osbot_browser osbot_aws pbx_gs_python_utils boto3


# cell code (first version)
import nest_asyncio
nest_asyncio.apply()

import os
from osbot_browser.browser.Browser_Lamdba_Helper import Browser_Lamdba_Helper
url     = 'https://www.google.com/asd'
#url     = 'http://localhost:8888'

print(os.getenv('AWS_REGION'))

browser = Browser_Lamdba_Helper().setup().api_browser

browser.sync__open(url)
#print(browser.sync__url())
png_data  = browser.sync__screenshot_base64(url)
from IPython.display import display_html
html = '<img style="margin:0" align="left" src="data:image/png;base64,{}"/>'.format(png_data)
display_html(html, raw=True)

### Better version

import nest_asyncio
import os
from IPython.display import display_html
from osbot_browser.browser.Browser_Lamdba_Helper import Browser_Lamdba_Helper

nest_asyncio.apply()

def open_url(url):
    browser = Browser_Lamdba_Helper().setup().api_browser
    browser.sync__open(url)
    png_data  = browser.sync__screenshot_base64(url)
    html = '<img style="margin:0" align="left" src="data:image/png;base64,{}"/>'.format(png_data)
    display_html(html, raw=True)

open_url('https://www.google.com/asd')   

copy-page-images.js

%%javascript
document.onpaste = function(event) {
  var items = event.clipboardData.items;
  console.log(JSON.stringify(items)); // will give you the mime types
  var blob = items[0].getAsFile();
  var reader = new FileReader();
  reader.onload = function(event){
      console.log(event.target.result)
      Jupyter.notebook.cells_to_markdown()
      Jupyter.notebook.get_selected_cell().set_text('<img style="border:1px solid black" align="left" src="'
                                                  +event.target.result +
                                                 '"/>')
      Jupyter.notebook.get_selected_cell().execute()
      };
  reader.readAsDataURL(blob);
}

inside-jupuyter.js

//--- execute code in cell
code = Jupyter.notebook.get_selected_cell()
code.set_text('40+3') ; code.execute() ;
code.output_area.element.find('.output_result').text() // after execution, this is where the answer will be

//--- other commands

Jupyter.notebook.cells_to_markdown() // change in ui the current cell to markdown
Jupyter.notebook.cells_to_code() // change in ui the current cell to markdown
Jupyter.notebook.delete_cell()
Jupyter.notebook.get_cells()

Jupyter.notebook.insert_cell_below();
Jupyter.notebook.select_next(true);
Jupyter.notebook.focus_cell();
Jupyter.notebook.get_selected_cell().set_text('40+3')
Jupyter.notebook.get_selected_cell().execute();


//--- UI changes

Jupyter.toolbar.add_buttons_group([
        {
             'label'   : 'alert me',
             'icon'    : 'fa-terminal', // select your icon from
                                          // http://fontawesome.io/icons/
             'callback': function(){alert(42)}
        }
        // add more button here if needed.
        ]);

lightning.py

#!pip install lightning-python
from lightning import Lightning

from numpy import random
lgn = Lightning(ipython=True, local=True)
#series = random.randn(10, 50)
#lgn.line(series)

# x = random.randn(1000)
# y = random.randn(1000)
# v = random.randn(1000)

# lgn.scatter(x, y, alpha=0.5, values=v, colormap='Reds')
mat = random.rand(100,100)
mat[mat<0.97] = 0

lgn.force(mat)

other-jupyter.py

#https://jupyter-notebook.readthedocs.io/en/stable/examples/Notebook/JavaScript%20Notebook%20Extensions.html
from jupyter_core.paths import jupyter_config_dir
jupyter_dir = jupyter_config_dir()
jupyter_dir


# ---- Create notebook from notebook

import nbformat as nbf
nb = nbf.v4.new_notebook()
text = """\
# My first automatic Jupyter Notebook
This is an auto-generated notebook."""

code = """\
%pylab inline
hist(normal(size=2000), bins=50);"""

nb['cells'] = [nbf.v4.new_markdown_cell(text),
               nbf.v4.new_code_cell(code) ]
nbf.write(nb, 'test.ipynb')

qgrid.py

import numpy as np
import pandas as pd
import qgrid
randn = np.random.randn
df_types = pd.DataFrame({
    'A' : pd.Series(['2013-01-01', '2013-01-02', '2013-01-03', '2013-01-04',
               '2013-01-05', '2013-01-06', '2013-01-07', '2013-01-08', '2013-01-09'],index=list(range(9)),dtype='datetime64[ns]'),
    'B' : pd.Series(randn(9),index=list(range(9)),dtype='float32'),
    'C' : pd.Categorical(["washington", "adams", "washington", "madison", "lincoln","jefferson", "hamilton", "roosevelt", "kennedy"]),
    'D' : ["test 123", "bar", "buzz", "bippity","boppity", "foo", "foo", "bar", "zoo"] })
df_types['E'] = df_types['D'] == 'foo'
qgrid_widget = qgrid.show_grid(df_types, show_toolbar=True)
qgrid_widget

resources.md

good links

Jupyter notebook tests https://github.com/jupyter/notebook/blob/master/notebook/tests/selenium/utils.py