from graph_fmt import *

# Connect to Aerospike Graph
g = traversal().withRemote(DriverRemoteConnection('ws://0.0.0.0:8182/gremlin','g'))

#"ME-799370", "ME-094592"
g.V("ME-094592")\
 .outE("used_ip","used_device","used_mailing_address","used_browser_agent").as_('e1')\
 .select('e1').values().sum_().is_(P.lt(2.0).or_(eq(2.0))).toList()

g.E().id_().toList()

import pandas as pd
from ipywidgets import widgets, interact, interactive, fixed, interact_manual, Layout, AppLayout, HBox, VBox
from IPython.display import display

df = pd.DataFrame([1,2,3])

def f(x, df):
    df
    df['Kosten A'] = x
    y = x*x
    print(df, y)

interact(f, x=(10,50,5), df = fixed(df))

al = widgets.IntText(
    value=0,
    description='AVG Latency (ms):',
    style={'description_width': 'initial'},
    disabled=False,
    layout=Layout(width='20%')
)

tp = widgets.IntText(
    value=0,
    description='Trafic Proportion',
    style={'description_width': 'initial'},
    disabled=False,
    layout=Layout(width='20%')
)

qps = widgets.IntText(
    value=0,
    description='Trafic Proportion',
    style={'description_width': 'initial'},
    disabled=False,
    layout=Layout(width='20%')
)

HBox(al, tp, qps)

from ipywidgets import interact, HBox, VBox, Output, HTML, Dropdown, Button, Layout, Label
from IPython.display import display, clear_output
import pandas as pd
import matplotlib.pyplot as plt
import datetime as dt
class demo():
    def __init__(self):
        self.df = pd.DataFrame({'A':[23,45,26,43,67], 'B':[25,65,85,74,56], 'C':[23,65,87,89,65]})
        
        style="""
            <style>
                /* enlarges the default jupyter cell outputs, can revert by Cell->Current Outputs->Clear */
                .container { width:1020 !important; } 
                
                /* styles for output widgets */
                .o2 {width:400px; border:1px solid #ddd}
                .o3 {width:400px; border:1px solid #ddd}
                .o4 {width:400px; border:1px solid #ddd}
                .o5 {width:800px; }
                .o5 span {color:red !important}
                
                /* custom styles for testing */
                .style_A {background-color:#fafaaa}
                .style_B {background-color:#faaafa}
                .style_C {background-color:#aafafa}
            </style>
        """
        display(HTML(style))
        self.o1 = Output(layout=Layout(width='400px'))
        
        self.o2 = Output() 
        self.o2.add_class('o2')
        self.o3 = Output()
        self.o3.add_class('o3')
        self.o4 = Output()
        self.o4.add_class('o4')
        self.o5 = Output()
        self.o5.add_class('o5')
        # create a scene for displaying the outputs, 
        # Output1 on the top row, 2,3, and 4 stacked horizontally in the second row
        scene = VBox([self.o1,
                      HBox([self.o2, self.o3, self.o4]),
                      self.o5
                     ])
        display(scene)
    
        with self.o1:
            display(HTML('<h2>Demo</h2>'))
            
        with self.o2:
            self.dd_filter = Dropdown(description='Select Filter', options=['', 'A','B','C'])
            self.dd_filter.observe(self.fill_values)
            
            self.dd_values = Dropdown(description='Select Value')
            
            self.btn = Button(description='Run')
            self.btn.on_click(self.display_results)
            
            display(self.dd_filter, self.dd_values, self.btn)
            
            
    def fill_values(self,x):
        if x['type'] == 'change' and x['name'] == 'value':
            filter_by = x['owner'].value
            
            if filter_by=='':
                filter_values = []
            else:
                filter_values = self.df[filter_by].values
            self.dd_values.options = filter_values
        
    def display_results(self, x):
        filter_by = self.dd_filter.value
        filter_val = self.dd_values.value
        
        if filter_by=='':
            with self.o3:
                clear_output()
                print('Please select filter')
            return
        
        df_filtered = self.df[self.df[filter_by]>=filter_val]
        
        with self.o3:
            clear_output()
            lbl = Label(value=f'Filter by {filter_by}, with {filter_val}, found {df_filtered.shape[0]} observation(s)')
            lbl.add_class(f'style_{filter_by}')
            display(lbl)
            display(df_filtered)
            
        with self.o4:
            clear_output()
            df_filtered.plot(kind='bar')
            plt.show()
            
        with self.o5:
            clear_output()
            display(Label(value= f'Code last run {dt.datetime.now().strftime("%Y-%m-%d %H:%M:%S")}' ))
            
        
d = demo()

from ipywidgets import interact, HBox, VBox, Output
import pandas as pd
import matplotlib.pyplot as plt
@interact
def chart_and_table(filterby=['A','B','C']):
    df = pd.DataFrame({'A':[23,45,26,43,67], 'B':[25,65,85,74,56], 'C':[23,65,87,89,65]})
    
    o1, o2 = Output(), Output()
    scene = HBox([o1,o2])
    display(scene)
    
    with o1:
        df[[filterby]].plot(kind='bar')
        plt.show()
    with o2:
        display(df[[filterby]])

from ipywidgets import interact, HBox, VBox, Output, HTML, Layout
import pandas as pd
import matplotlib.pyplot as plt
@interact
def chart_and_table(filterby=['A','B','C']):
    df = pd.DataFrame({'A':[23,45,26,43,67], 'B':[25,65,85,74,56], 'C':[23,65,87,89,65]})
    
    style="""
        <style>
            .style_a {background-color:#fafaaa}
            .style_b {background-color:#faaafa}
            .style_c {background-color:#aafafa}
        </style>
    """
    display(HTML(style))
    
    o1 = Output(layout=Layout(width='400px'))
    o2 = Output(layout=Layout(width='200px')) 
    o3 = Output()
    o4 = Output()
    scene = HBox([o1,
                  o2,
                  VBox([o3, o4])
                 ])
    display(scene)
    
    with o1:
        df[[filterby]].plot(kind='bar')
        plt.show()
    with o2:
        display(df[[filterby]])
    with o3:
        if filterby=='A':
            o3.add_class('style_a')
        elif filterby=='B':
            o3.add_class('style_b')
        elif filterby=='C':
            o3.add_class('style_c')
        print('The selected filter is :', filterby)
    with o4:
        display(df)