rothnic

import logging
logger = logging.getLogger(__name__)

import time
import json
import paho.mqtt.client as mqtt
import pandas as pd
import random

from src.backend.data import datatodf, roverdata, mapdata

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{
  "remote_browsers": {
    "chrome_remote_desktop_headless": {
      "goog:chromeOptions": {
        "args": ["--headless", "--disable-gpu", "--window-size=1366,768"]
      },
      "platform": "ANY",
      "browserName": "chrome"
    },
    "chrome_remote_mobile_headless": {

rothnic

master:
  image: jupyter/pyspark-notebook
  command: bash -c "/usr/local/spark/bin/spark-class org.apache.spark.deploy.master.Master -h master && \
           start-notebook.sh"
  hostname: master
  environment:
    MASTER: spark://master:7077
    SPARK_CONF_DIR: /conf
    SPARK_PUBLIC_DNS: localhost
  expose:

rothnic

→ conda list
# packages in environment at /Users/nroth/anaconda/envs/dask:
#
appnope                   0.1.0                    py36_0    defaults
bokeh                     0.12.4                   py36_0    defaults
boto3                     1.4.3                    py36_0    defaults
botocore                  1.4.90                   py36_0    defaults
chest                     0.2.3                    py36_0    defaults
cloudpickle               0.2.2                    py36_0    defaults
cycler                    0.10.0                   py36_0    defaults

rothnic

__author__ = 'Nick'

import os

from openmdao.main.api import Component
from openmdao.lib.datatypes.api import Float
import pandas as pd

from calc_uncertainties import Distribution
from Common.AttributeTools.io import get_outputs

rothnic

from bokeh.models import GlyphRenderer, ColumnDataSource
from bokeh.models.plots import Plot
from bokeh.models import Circle, Range1d, LinearAxis, CategoricalAxis, Axis, FactorRange
from bokeh.models.widgets import HBox, VBoxForm, Select

from bokeh.io import curdoc

data = {'a': [1, 2, 3, 4],
        'b': [3, 5, 4, 5],
        'c': ['foo', 'bar', 'foo', 'bar']}

rothnic

from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from time import sleep
import os
import subprocess
from watchdog.observers import Observer
from watchdog.events import PatternMatchingEventHandler


CHARTS = {

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from bokeh.models.widgets import HBox, VBoxForm, Select
from bokeh.charts import Bar
from bokeh.io import curdoc

data = {'a': [1, 2, 3, 4],
        'b': [3, 5, 4, 5],
        'c': ['foo', 'bar', 'foo', 'bar']}

col_names = list(data.keys())

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from bokeh.charts import Line, show, output_file, color

# build a dataset where multiple columns measure the same thing
data = dict(python=[2, 3, 7, 5, 26, 221, 44, 233, 254, 265, 266, 267, 120, 111],
            pypy=[12, 33, 47, 15, 126, 121, 144, 233, 254, 225, 226, 267, 110, 130],
            jython=[22, 43, 10, 25, 26, 101, 114, 203, 194, 215, 201, 227, 139, 160],
            test=['foo', 'bar', 'foo', 'bar', 'foo', 'bar', 'foo', 'bar', 'foo', 'bar',
                  'foo', 'bar', 'foo', 'bar']
            )

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from bokeh.models import Plot, ColumnDataSource, GlyphRenderer
from bokeh.properties import Instance, Dict, String, Any
from bokeh.server.app import bokeh_app
from bokeh.server.utils.plugins import object_page
from bokeh.models.widgets import HBox, TextInput, VBoxForm, Select
from bokeh.charts import Bar


class ChartApp(HBox):
    """An example of a browser-based, interactive plot with column selection controls."""