app = dash.Dash(__name__,external_stylesheets=[dbc.themes.CYBORG])
server = app.server
# style={'display':'inline-block', 'verticalAlign':'top', 'width':'30%'}
# In[ ]:
app.layout = html.Div(children=[
html.Title("Tweet Analyzer"),
html.Img(src="https://help.twitter.com/content/dam/help-twitter/twitter-logo.png",style={'display':'inline-block', 'verticalAlign':'middle','height':'10%', 'width':'10%','margin-left': '45%'}),
html.H1("Tweet Analyzer 🔥",
style={
'textAlign': 'center',
'color': '#7FDBFF'
}),
html.H3("Analyze Tweets Of Specific Account on Twitter",
style={
'textAlign': 'center',
'color': '#7FDBFF'
}),
dcc.Input(id='id1',placeholder='Enter the exact twitter handle of the User (without @)',type='text', style={'display':'inline-block','verticalAlign':'middle', 'width':'50%','margin-left': '25%'}),
html.Br(),
html.Br(),
html.H6("Select Action To Perform",
)
from refresh import update
from pages.functions import indiadata, worlddata
external_stylesheets = ["https://codepen.io/theajit/pen/vYYxVLb.css"]
# external JavaScript files
external_scripts = [
"https://codepen.io/theajit/pen/JjdLvZE.js",
]
app.title = "Track Corona India | USA | China | Online Live "
app.layout = html.Div([
dcc.Location(id="url", refresh=False),
html.Title("Track Corona India"),
html.Img(src=app.get_asset_url("track_corona_online_logo.png"),
title="Track Corona Logo",
style={
"height": "80px",
"textAlign": "center",
"display": "inline-block",
"margin-left": "1.5%",
"margin-top": "0.5%"
}),
html.Div(
[
html.Ul([
html.Li([dcc.Link("Home ", href="/")]),
html.Li([
dcc.Link("India", href="#"),
def tab_general():
global history
clan, history, clanWar, dateWar = cr.getJsonWithCache(
apiToken, playerId, clanId)
currentDate = datetime.now().strftime('%d-%m-%Y %H:%M:%S')
maxDonationValue = 0
minDonationValue = 6000
# get min and max donatin values
for hist in history:
if hist[2] > maxDonationValue:
maxDonationValue = hist[2]
if hist[2] < minDonationValue:
minDonationValue = hist[2]
limiteClanDonation = conf.K_CLANLIMITE
if maxDonationValue < limiteClanDonation:
limiteClanDonation = maxDonationValue
if minDonationValue > limiteClanDonation:
limiteClanDonation = minDonationValue
marks = []
if minDonationValue > 100:
minMark = minDonationValue + (100 - (minDonationValue % 100))
else:
minMark = 0
if maxDonationValue > 100:
maxMark = maxDonationValue + (100 - (maxDonationValue % 100))
else:
maxMark = 100
for mark in range(minMark, maxMark, 100):
marks.append(mark)
marks.append(maxMark)
return html.Div(children=[
html.Title('Clan ' + clan[conf.F_NAME]),
html.H1(children=u'Statistiques du clan "' + clan[conf.F_NAME] + '"'),
html.Div('Last update: ' + currentDate),
html.Div(children=[
dcc.Graph(id='graph-dons'),
]),
html.Div(children=[
dcc.RangeSlider(
id='graph-dons-slider',
min=minDonationValue,
max=maxDonationValue,
marks={i: str(i)
for i in marks},
value=[0, limiteClanDonation],
)
]),
html.Br(),
html.Div(children=[
dcc.Graph(id='graph-war',
figure={
'data': [
{
'x': clanWar[0],
'y': clanWar[1],
'type': 'bar',
'name': u'Préparations'
},
{
'x': clanWar[0],
'y': clanWar[2],
'type': 'bar',
'name': u'Guerre finale'
},
],
'layout': {
'title': u'Rapport de guerre du ' + dateWar
}
})
])
])
def serve_layout():
attributes = get_attributes()
return html.Div(
[
# page title
html.Title(["Euronext Technology Companies"]),
# page header
html.Div([html.H1("Technological Companies Stocks Dashboard")]),
# summary
html.Div([
html.H2("Summary", className="summary-title"),
html.P(summary_1, className="summary-text"),
html.P(summary_2, className="summary-text"),
html.A(
"Please visit my GitHub!",
href="https://github.com/jschnab/finance-scraping.git",
className="summary-text",
),
],
className="summary"),
# timeseries
html.Div([html.H2("Timeseries Analysis")]),
# dropdown grid
html.Div(
[
# select y axis dropdown
html.Div(
[
html.Div("Select y-axis", className="label"),
html.Div(
dcc.Dropdown(
id="y_var",
options=attributes,
value="last_quote",
className="dropdown",
)),
],
className="subcontainer-dropdown",
),
# select companies dropdown
html.Div(
[
html.Div("Select companies", className="label"),
html.Div(
dcc.Dropdown(
id="companies",
options=get_companies(),
value=[
"Capgemini SE",
"Ubisoft Entertainment",
"Dassault Systemes SE",
],
multi=True,
className="dropdown",
)),
],
className="subcontainer-dropdown",
),
# date picker
html.Div(
[
html.Div("Select date range", className="label"),
html.Div(
dcc.DatePickerRange(
id="date_range",
min_date_allowed=get_min_date(),
max_date_allowed=get_max_date(),
className="datepicker",
)),
],
className="subcontainer-dropdown",
),
],
className="container-dropdown",
),
# graph grid
html.Div(
[html.Div([dcc.Graph(id="timeseries")])],
className="timeseries-container",
),
html.Div(html.H2("Company rankings")),
# tables container
html.Div(
[
# single table
html.Div(
[
html.H3("Top 10 values", className="top-values"),
# table top 10 values dropdown
html.Div([
html.Div("Table attribute", className="label"),
html.Div(
dcc.Dropdown(
id="drop-top-values",
options=attributes,
value="capital",
className="dropdown",
)),
]),
# table top 10 values
html.Table(id="top-ten-values"),
],
className="container-one-table",
),
# single table
html.Div(
[
html.H3("Bottom 10 values",
className="top-values"),
# table bottom 10 values dropdown
html.Div([
html.Div("Table attribute", className="label"),
html.Div(
dcc.Dropdown(
id="drop-bottom-values",
options=attributes,
value="capital",
className="dropdown",
)),
]),
# table bottom 10 values
html.Table(id="bottom-ten-values"),
],
className="container-one-table",
),
# single table
html.Div(
[
html.H3("Top 10 movers", className="top-values"),
# table top 10 progressions dropdown
html.Div([
html.Div("Table attribute", className="label"),
html.Div(
dcc.Dropdown(
id="drop-top-prog",
options=attributes,
value="capital",
className="dropdown",
)),
]),
# table top 10 progressions
html.Table(id="top-ten-prog"),
],
className="container-one-table",
),
# single table
html.Div(
[
html.H3("Bottom 10 movers",
className="top-values"),
# table top 10 progressions dropdown
html.Div([
html.Div("Table attribute", className="label"),
html.Div(
dcc.Dropdown(
id="drop-bottom-prog",
options=attributes,
value="capital",
className="dropdown",
)),
]),
# table bottom 10 progressions
html.Table(id="bottom-ten-prog"),
],
className="container-one-table",
)
],
className="container-tables",
),
],
className="main",
)
def create_app_ui():
main_layout = html.Div([
html.H1(id="heading", children='Terrorism analysis'),
dcc.Tabs(id="Tabs",
value="Map",
children=[
dcc.Tab(label="Map Tool",
id="Map tool",
value="Map",
children=[
dcc.Tabs(id="subtabs",
value="WorldMap",
children=[
dcc.Tab(label="World Map Tool",
id="World",
value="WorldMap"),
dcc.Tab(label="India Map Tool",
id="India",
value="IndiaMap")
]),
dcc.Dropdown(
id="month_drop",
options=month_list,
multi=True,
placeholder='Select Month',
),
dcc.Dropdown(
id="date_drop",
options=date_list,
multi=True,
placeholder='Select date',
),
dcc.Dropdown(
id="day_drop",
value=1,
options=date_list,
multi=True,
placeholder='Select Day',
),
dcc.Dropdown(
id="region_drop",
options=region_list,
multi=True,
placeholder='Select Region',
),
dcc.Dropdown(
id="country_drop",
options=country_list,
multi=True,
placeholder='Select Country',
),
dcc.Dropdown(
id="state_drop",
options=state_list,
multi=True,
placeholder='Select Sate',
),
dcc.Dropdown(
id="city_drop",
options=city_list,
multi=True,
placeholder='Select City',
),
dcc.Dropdown(
id="attack_drop",
options=attack_type_list,
multi=True,
placeholder='Select Attack-type',
),
html.Title(children="Select the year range"),
dcc.RangeSlider(
id="range-slider",
min=min(year_list),
max=max(year_list),
value=[min(year_list),
max(year_list)],
marks=year_dict,
step=None),
html.Br(),
]),
dcc.Tab(label="Chart Tool",
id="chart tool",
value="Chart",
children=[
dcc.Tabs(id="subtabs2",
value="WorldChart",
children=[
dcc.Tab(label="World Chart tool",
id="WorldC",
value="WorldChart"),
dcc.Tab(label="India Chart tool",
id="IndiaC",
value="IndiaChart")
]),
dcc.Dropdown(id="Chart_drop",
options=chart_dropdown_values,
placeholder="Select option",
value="region_txt"),
html.Br(),
html.Br(),
html.Hr(),
dcc.Input(id="search",
placeholder="Search Filter"),
html.Hr(),
html.Br(),
dcc.RangeSlider(
id='cyear_slider',
min=min(year_list),
max=max(year_list),
value=[min(year_list),
max(year_list)],
marks=year_dict,
step=None),
html.Br()
]),
]),
html.Div(id="graph-object", children="space for graph"),
])
return main_layout
return [
dcc.Dropdown(id='words-dd',
options=return_list,
className='round-dropdown',
value=Utils.list_of_found_words,
multi=True,
clearable=False)
]
#######################
# FRONTEND
#######################
app.layout = \
html.Div(className="big_container", children=[
html.Title("uRank"),
html.Div(className="bookmark_history", children=[
html.Div(className="bookmark", children=[
html.H1('Choose a topic', className='center-header'),
# html.Br(),
dcc.Dropdown(
id='topic-dropdown',
options=select_themas(),
className='round-dropdown'
),
]),
html.Div(id="words_search", className="history", children=[
html.H1('Type in words', className='center-header'),
dcc.Input(
gmm = GaussianMixture(n_components=5)
gmm.fit(cDf.values)
km = KMeans(n_clusters=5,
init='random',
n_init=30,
max_iter=300,
random_state=0)
km.fit(cDf.values)
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.layout = html.Div([
html.Title("View, Inc. Dashboard"),
html.H1("View, Inc."),
html.Div([
html.H3("Statistics table"),
html.Br(),
"Select date range",
html.Br(),
dcc.DatePickerRange(id='my-date-picker-range',
min_date_allowed=df.index.min().date(),
max_date_allowed=df.index.max().date(),
initial_visible_month=df.index.min().date(),
start_date=str(df.index.min().date()),
end_date=str(df.index.min().date()),
minimum_nights=0),
html.Div(id='output-container-date-picker-single'),
]),
#My first Dash app, displaying the US States by 'Voting Opportunity'.
#This will include how many eligible voters didn't vote, and other relevant slices.
# -*- coding: utf-8 -*-
import dash
import dash_html_components as html
import dash_core_components as dcc
app = dash.Dash()
app.layout = html.Div(children=[
html.Title('''Voting Opportunity'''),
html.H1(children=[
'''Intro'''
]),
html.P(children=[
'''100 million americans did not vote in the 2016 presidential election.
The election was decided by a collective 78,000 votes.
This elections displays the opportunity for increased voter turnout, by voting district, in the United States.
'''
]),
dcc.Graph(
id='example-graph',
figure={
def GetMainSite(dashApp, dbRef, days):
""" Returns the layout for the website. Documentation on dash.plotly.com """
dates = GetInitialDates(dbRef, days)
mainSite = html.Div([
html.Title("jolyu | Dashboard"),
# empty Div to trigger javascript file for graph resizing
html.Div(id="output-clientside"),
dcc.Store(id="dbDates"),
# Header Div
html.Div(
[
html.Div(
[
html.Img(
src=dashApp.get_asset_url("jolyu.svg"),
style={
"height": "8em",
"width": "auto",
},
)
],
id="jolyu-logo",
className="one-third column",
),
html.Div(
[
html.Div([
html.H3(
"Bird Statictics",
style={"margin-bottom": "0px"},
),
html.H5("System overview",
style={"margin-top": "0em"}),
])
],
className="one-half column",
id="title",
),
html.Div(
[
html.A(
html.Button("Learn More", id="learn-more-button"),
href=
"https://glados.no/files/ntnu/v20/ttt4270/jolyu_fremtidens_fugletitter_elsys_v2020.pdf",
target="_blank",
)
],
className="one-third column",
id="button",
),
],
id="header",
className="row flex-display",
style={"margin-bottom": "0em"},
),
# Div for main site
html.Div([
html.Div(
[
dcc.DatePickerRange(
id="dbDatePicker",
display_format="YYYY-MM-DD",
start_date_placeholder_text='YYYY-MM-DD',
end_date_placeholder_text='YYYY-MM-DD',
start_date=dates[0],
end_date=dates[1],
first_day_of_week=1,
),
html.Button("Fetch DB", id="fetchDbButton"),
html.A(html.Button("Download Dataset",
id="downloadDbButton"),
id="downloadBut",
download="rawdata.csv",
href="",
target="_blank"),
],
className="pretty_container six columns",
),
html.Div(
[
html.P(id="dbResponse"),
],
className="pretty_container six columns",
),
],
id="quick-facts",
className="row flex-display"),
html.Div(
[
html.Div(
[
html.Div(
[
dcc.Graph(id="mainGraph"),
],
id="mainGraphContainer",
className="pretty_container",
)
],
className="twelve columns",
)
],
id="mainGraphDiv",
className="row flex-display",
),
html.Div(
[
html.Div(
[
html.Div(
[
dcc.Graph(id="secondGraph"),
html.H5("Show:"),
dcc.Checklist(
labelStyle={'display': 'inline-block'},
id="checklistShow",
)
],
id="secondaryGraphContainer",
className="pretty_container",
)
],
className="twelve columns",
)
],
id="second_graph_div",
className="row flex-display",
)
])
return mainSite
color="primary",
className='mr-1',
outline=False,
style={
'margin': '20px',
'border-radius': '5px'
}),
],
style={'text-align': 'center'})
display_page = html.Div([dcc.Graph(id="graph", figure=fig)])
no_display = html.Div([])
app.layout = html.Div([
html.Title("Transportation Topography"),
dcc.Location(id='url', refresh=False), main_page,
html.Div(id='visual-content', style={'text-align': 'center'})
],
style={'background-color': 'MintCream'})
@app.callback([
dash.dependencies.Output('visual-content', 'children'),
dash.dependencies.Output('nbhd', 'active'),
dash.dependencies.Output('district', 'active'),
dash.dependencies.Output('city', 'active'),
dash.dependencies.Output('region', 'active')
], [dash.dependencies.Input('go_button', 'n_clicks')],
[dash.dependencies.State('nbhd', 'n_clicks_timestamp')],
[dash.dependencies.State('district', 'n_clicks_timestamp')],
style={
"color": "white",
'font-weight': 'bold'
})
],
vertical=True,
pills=True,
), footer
],
style=SIDEBAR_STYLE,
)
# Permet de mettre le style du contenu pour chaque page
content = html.Div(id="page-content", style=CONTENT_STYLE)
# Le titre de notre page
titleDash = html.Title(id="title",
children=[html.Title(children="DataScience")])
# Notre header présent sur toutes les pages
header = html.Header(
id="header", children=[html.H1(children='Projet DATA SCIENCE'),
html.Hr()])
# Toute notre application
app.layout = html.Div([dcc.Location(id="url"), sidebar, content])
# Presentation dans la rubrique Home
cardPresentationUs = dbc.Card(
dbc.CardBody([
html.H6('A propos', className='card-title'),
html.P(
'Dans le cadre de notre projet Data Science à l\'école d\'ingénieur Polytech Montpellier, nous avons '
'réalisé ce site interactif afin de présenter les étapes de notre travail et nos résultats. ',
if len(sc) != 2:
continue
electoral_votes = int(line[1])
margin = abs(int(line[2]) - int(line[3]))
voter_opp = (non_voters_map[sc] / float(margin)) * (electoral_votes / TOTAL_ELECTORAL_VOTES)
voter_opp_map[sc] = voter_opp
with open('voter_opp.csv', 'w') as voter_opp_file:
voter_opp_file.write('State, Voter Turnout Opportunity\n')
voter_opp_file.write('string, number\n')
for k,v in sorted(voter_opp_map.items(), key=lambda x: x[1], reverse=True):
voter_opp_file.write(k + "," + ("%.3f" % v) + '\n')
app.layout = html.Div([
html.Title("Voting opportunity"),
dcc.Graph(
id='voting-opportunity',
figure={
'data': [
go.Bar(
x=list(voter_opp_map.keys()),
y=list(voter_opp_map.values()),
)
],
'layout': go.Layout(
xaxis={'title': 'State'},
yaxis={'title': 'Turnout opportunity'},
title="Voter turnout opportunity by state for the 2016 presidential election"
)
}
def server_layout(mode=None):
#return the layout of the GUI
session_id = str(uuid.uuid4())
#variable, distribution selection panel
selection_panel = html.Div(id='selection-panel',children=[
html.Div(id='selected-column-panel',children=[
html.Div(id='selected-column-sec1-panel',children=[
drc.NamedDropdown(
name='Select series',
id='selected-series',
searchable=False,
clearable=False
),
dcc.Checklist(
id='apply-log-transform',
options=[{'label':' Apply log transform','value':'logtransform'}
]),
]),
drc.NamedTextarea(
id='series-characteristics',
name='Series characteristics',
cols='50',
rows='2',
readOnly='readOnly'
),
]),
html.Div(id='apply-panel',children=[
html.Div(id='apply-sec1-panel',children=[
drc.NamedDropdown(
id='fitted-distributions',
name='Fitted distribution',
options=[
{'label': ' '+ v[0], 'value': k}
for k,v in dist_par_template.items() if k != 'native' and v[2]
],
value='normal',
searchable=False,
clearable=False
),
]),
# html.Div(id='apply-sec1b-panel',children=[
# drc.NamedDropdown(
# id='plotting-distributions',
# name='Probability scale',
# options=[
# {'label': ' '+ v[0], 'value': k}
# for k,v in dist_par_template.items() if v[2]
# ],
# value='native',
# searchable=False,
# clearable=False
# ),
# ]),
html.Div(id='apply-sec2a-panel',children=[
html.Button('Fit',id='fit-button',n_clicks=0),
]),
#dcc.Checklist(
# id='show-y-log',
# options=[{'label':' Show y-axis in log scale','value':'true'}
#]),
]),
html.Label(id='graph-refresh'),
dcc.Store(
id='graph-refresh-hidden',
data=0
),
html.Div(id='message-panel',children=[""]),
])
#variable, distribution selection panel
par_panel = html.Div(id='fitted-panel',children=[
html.Div(id='fitted-sec1-panel',children=[
drc.NamedTextarea(
id='fitted-par',
name='Estimated distribution parameters',
readOnly='readOnly',
cols= 40,
rows= 3
),
drc.NamedTextarea(
id='estimated-quantiles',
name='Estimated quantiles',
readOnly='readOnly',
cols= 40,
rows= 3
),
])
])
upload_panel = html.Div(id='last-card',children=[
dcc.Upload(
id='upload-data',
children=html.Div([
'Drag and Drop or ',
html.A('Select File')
]),
style={
'lineHeight': '60px',
'borderWidth': '1px',
'borderStyle': 'dashed',
'borderRadius': '5px',
'textAlign': 'center',
}
),
html.Label('''File upload limited to < %0.0f Kb, containing no more than %d rows and %d columns'''%(configs['max_file_size']/1024,configs['max_file_rows'],configs['max_file_cols'])),
html.Label('',id='data-filename'),
html.Label('',id='data-description'),
html.Div(id='table-panel',children=[
dash_table.DataTable(
id='attribute-table',
columns=[],
row_selectable='multi',
editable=False,
style_header={
'textAlign': 'center',
'fontWeight': 'bold',
'color': 'black',
},
style_cell={
'padding': '2px',
'--selected-background': 'grey',
'color': 'black',
},
style_data_conditional=[
{
'if': {'row_index': 'odd'},
'backgroundColor': 'rgb(248, 248, 248)'
}
],
#locale_format= '0.3',
)
],style={'visibility':'none','display':'none'}),
])
chart_panel = html.Div(id='chart-panel',children=[
dcc.Loading(id = "loading-icon", children=[
dcc.Graph(
id='graph',
figure={
},
responsive=True,
config=graph_config,
style={'display':'none'}
)
]),
],
style={'visibility':'none'})
layout = html.Div(
id="body",
className="container scalable",
children=[
visdcc.Run_js(id = 'chart-updated-js'),
visdcc.Run_js(id = 'chart-unupdated-js'),
visdcc.Run_js(id = 'error-display-js'),
dcc.Store(id='error-display',data=''),
html.Title(title=configs['title']),
#hidden session id
#row 1 for title
html.Div(id='top-panel',children=[
html.H5(id='app-title',children=
'''Distribution Fitting and Analysis Tool.
This tool is only for demostration porpuses''',
style={"margin-bottom": "0px"},
),
],className="row flex-display"),
#second row layout
html.Div(id='main-panel',children=[
html.Div(id='left-panel',children=[
upload_panel
]),
html.Div(id='output-panel',children=[
selection_panel,
par_panel,
chart_panel
],style={'visibility':'none','display':'none'}),
]),
#row 4 is the footer
html.Div(id='footer-panel',children=[
'''
A web application built on top of Dash (v%s) (framework for Python) by
Exequiel Sepúlveda and Dmitri Kavetski.'''%(dash.__version__)
]),
],
)
return layout
s = Store(location=location, keys=sl.sl._keys)
return dbc.Alert(value + " created!"), s.tables()
@app.callback(Output("content", "children"),
[dash.dependencies.Input('location-drop-down', 'value')])
def update_output(value):
print("selector says:", value)
location.set(value)
return PageStatus(location=location, sl=sl).get_layout()
from .pages.navbar import navbar
app.layout = html.Div(children=[
html.Title("Roomba"),
navbar(),
html.Div(id="selector",
children=dbc.Row([
dbc.Col(dbc.Select(
options=[{
"label": x,
"value": x
} for x in Store(keys=[]).tables()],
value=location.get(),
id="location-drop-down",
),
width=4),
dbc.Col(dbc.Button("new",
outline=True,
id="new-location-button",
"position": "fixed",
"top": 0,
"left": 0,
"bottom": 0,
"width": "16rem",
"padding": "2rem 1rem",
"background-color": "#f8f9fa",
}
# 主要内容的样式将其放置在侧边栏的右侧，然后添加一些填充
CONTENT_STYLE = {
"margin-left": "18rem",
"margin-right": "2rem",
"padding": "2rem 1rem",
}
header = html.Header(html.Title('校校招'))
sidebar = html.Div(
[
html.H2("校校招", className="display-4", title='校校招，连接高校与企业的平台'),
html.P("校校招轻量级分析平台", className="lead"),
html.Hr(),
dbc.Nav(
[
dbc.NavItem(dbc.NavLink("首页", href="/", active="exact")),
html.H3('用户端数据概览', className='lead', style={}), # 导航
dbc.NavItem(
dbc.NavLink(
"每日数据概览",
href="/per/report",
active="exact",
if len(response) == 0:
break
for item in response:
category_id = item['id']
category_title = item['title']
if category_id is not None and category_title is not None:
if db.session.query(JeopardyTable).filter(JeopardyTable.category_id == category_id).count() == 0:
data = JeopardyTable(category_title, category_id)
db.session.add(data)
db.session.commit()
offset += 100
# Layout for web app
app.layout = html.Div(children=[
html.Title("Test"),
dcc.Tabs(id="tabs", children=[
dcc.Tab(label='Search for Jeopardy Questions', children=[
html.Div(children=[
html.Div([
html.Br(),
html.H2(children="Jeopardy Trivia Search Engine", style={
'textAlign': 'center',
}),
html.Br(),
html.Div(id='search', children=[
html.Div([
html.Div(children=[
html.H6(children="Search for a category by key word/phrase (required)", style={
'margin-left': '1em'
})
import dash
import dash_html_components as html
app = dash.Dash()
server = app.server
app.config.suppress_callback_exceptions = True
app.scripts.config.serve_locally=True
app.head = [
html.Title('Cards Acquisition')
]
app.css.append_css({
'external_url': 'https://stackpath.bootstrapcdn.com/bootstrap/4.1.1/css/bootstrap.min.css'
})
# app.css.append_css({
# "external_url": "https://codepen.io/chriddyp/pen/dZVMbK.css"
# })
import dash_html_components as html
header = [
html.Title("xsplot.com material cross section plotting"),
html.Iframe(
src="https://ghbtns.com/github-btn.html?user=openmc-data-storage&repo=material_xs_plotter&type=star&count=true&size=large",
width="170",
height="30",
title="GitHub",
style={"border": 0, "scrolling": "0"},
),
html.H1(
"XSPlot - Neutron cross section plotter for materials",
# TODO find a nicer font
# style={'font-family': 'Times New Roman, Times, serif'},
# style={'font-family': 'Georgia, serif'},
style={"text-align": "center"},
),
html.Div(
html.Iframe(
src="https://www.youtube.com/embed/Rhb0Oqm29B8",
width="560",
height="315",
title="Tutorial video",
# style={},
style={"text-align": "center", "border": 0, "scrolling": "0"},
),
style={"text-align": "center"},
),
]
def title(self, page_title: str) -> html.Title:
"""Return a HTML title component which includes `page_title` and
includes additional text to be included in all page titles.
"""
return html.Title(f'{page_title} - {APP_NAME}')
# amount of records per table page
PAGE_SIZE = 15
# application object
app = dash.Dash(__name__, server=server, static_folder='static')
# init configuration, second param allow to make dynamic callbacks
app.css.config.serve_locally = True
app.scripts.config.serve_locally = True
app.config['suppress_callback_exceptions'] = True
# static layout
app.layout = html.Div(
[
html.Link(href='/static/undo-redo.css', rel='stylesheet'),
html.Title("PricesCC trading web-interface"),
html.H5("Pairs from prices RPC call:"),
dcc.Dropdown(id='my-dropdown', options=options_arg, value='BTC_USD'),
html.H5("User custom prices:"),
dcc.Dropdown(id='user-dropdown', options=user_args,
value=user_args[0]),
dcc.Input(placeholder='Input synthetic for custom graph...',
type='text',
value='',
id='graph_synthetic',
style={
'marginBottom': 15,
'marginTop': 10
}),
html.Button('Build custom price',
id='graph_build_button',
fig1.update_traces(marker=dict(color='#6D6194'))
######################## Update Scheduling ########################
# Define scheduler and add jobs for data refresh
scheduler = BackgroundScheduler()
# Cron style scheduling set to every day for S3 and every minute for DynamoDB as default
scheduler.add_job(func=read_s3_data, trigger='cron', day='1')
scheduler.add_job(func=read_dynamodb_data, trigger='cron', minute=1)
# Start scheduling
scheduler.start()
######################## App Head ########################
app.head = [html.Title('MTT Current Monitoring Dashboard')]
######################## App Layout ########################
app.layout = html.Div(
id="big-app-container",
children=[
# Banner with logo creation
html.Div(
id="banner",
className="banner",
children=[
html.Div(
id="banner-text",
children=[
html.H5("Machine Tool Technologies"),
stacked_complete_df = pd.concat([stacked_cases_df, stacked_deaths_df])
# Get information for sliders/radio buttons/etc.
available_indicators_cases = stacked_cases_df['indicator'].unique()
available_indicators_deaths = stacked_deaths_df['indicator'].unique()
days = stacked_complete_df.Days.unique()
continents = stacked_complete_df.Continent.unique()
app.layout = html.Div(children=[
# Titles Div
html.Div(
[
html.Title(['Corona-virus Dashboard']),
# Dashboard heading
html.H1(children='Corona-virus Dashboard',
style={
'textAlign': 'center',
}),
# Dashboard sub-heading
html.Div(
children=
f'A dashboard for visualising my analyses of the Johns Hopkins Univerisity\'s (JHUs)'
f' corona-virus dataset.',
style={
'textAlign': 'center',
}),
import dash
import pandas as pd
import numpy as np
import plotly.offline as plt
import plotly.graph_objs as go
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
import plotly.graph_objs as go
import plotly.figure_factory as ff
pd.set_option('display.max_columns', 10)
app = dash.Dash()
app.layout = html.Div([
html.Title(children='KMC'),
html.Div([
html.H1(children="K Mean Clustering",
style={
'text-align': 'center',
'color': '#7FDBFF'
}),
html.P(children='Seleccione el numero de cluster'),
dcc.Input(id="opcion",
type="number",
placeholder="Ingrese",
value=7,
min=1),
dcc.Graph(id='feature-graphic')
])
])
def create_dashboard(server):
dash_app = dash.Dash(routes_pathname_prefix='/',
external_stylesheets=[dbc.themes.SLATE],
server=server)
dash_app.index_string = '''
<!DOCTYPE html>
<html>
<head>
{%metas%}
<title>{%title%}</title>
{%favicon%}
{%css%}
<!-- Global site tag (gtag.js) - Google Analytics -->
<script async src="https://www.googletagmanager.com/gtag/js?id=UA-11302591-2"></script>
<script>
window.dataLayer = window.dataLayer || [];
function gtag(){dataLayer.push(arguments);}
gtag('js', new Date());
gtag('config', 'UA-11302591-2');
</script>
</head>
<body>
{%app_entry%}
<footer>
{%config%}
{%scripts%}
{%renderer%}
</footer>
</body>
</html>
'''
dash_app.title = 'Pi-chart.com'
dash_app.layout = dbc.Container(
[
html.Title("Pi-chart.com"),
dcc.Store(id="localstorage", storage_type="local"),
html.Div(id='tab-content'),
html.Div(id='tabs'),
dcc.Interval(
id='interval-component',
interval=1 * 60000, # in millisecond
n_intervals=0)
],
fluid=True)
@dash_app.callback(Output('localstorage', 'data'),
[Input('interval-component', 'n_intervals')])
def create_figure(n):
graphs = {}
brackets = {}
marketData = []
fetch_tables = ps.fetch_tables()
tables = list(fetch_tables)
count = 0
for market in tables:
fig = go.Figure()
data = ps.query_bracket(market)
graphs[market] = data
return graphs
@dash_app.callback(
Output("tab-content", "children"),
[Input("localstorage", "data")],
)
def create_layout(graphs):
figures = {}
markets = graphs.keys()
for market in markets:
brackets = graphs[market].keys()
fig = go.Figure()
for bracket in brackets:
prices = graphs[market][bracket][0]
timeStamp = graphs[market][bracket][1]
figure = fig.add_trace(
go.Scattergl(
x=timeStamp,
y=prices,
name=bracket,
hovertemplate='<b>Bracket: ' + bracket +
'</b>.<br>Price: %{y:$.2f}<extra></extra><br>' +
'%{x}<br>'))
figures.update({market: fig})
template = 'plotly_dark'
fig.update_layout(
template=template,
xaxis=dict(
autorange=True,
showgrid=False,
mirror=True,
ticks='outside',
showline=True,
linecolor='#FFFFFF',
rangeslider=dict(visible=True, thickness=0.08),
),
yaxis=dict(showgrid=False),
#height=768,
#width=1070,
title_text=market,
showlegend=True,
margin=dict(l=100, t=100, r=20, b=20),
uirevision="uirevisionstring")
fig.update_xaxes(tickformatstops=[
dict(dtickrange=[None, 1000], value='%-I:%M:%S%.%L%p ms'),
dict(dtickrange=[1000, 60000], value='%-I:%M:%S%p s'),
dict(dtickrange=[60000, 3600000], value='%-I:%M%p'),
dict(dtickrange=[3600000, 86400000], value='%-a %-I:%M%p'),
dict(dtickrange=[86400000, 604800000], value='%e. %b d'),
dict(dtickrange=[604800000, 'M1'], value='%e. %b w'),
dict(dtickrange=['M1', 'M12'], value="%b '%y M"),
dict(dtickrange=['M12', None], value='%Y Y'),
])
graphs.update({market: fig})
tabscontent = []
for key in figures:
tabscontent.append(dbc.Col(dcc.Graph(figure=figures[key])))
notice = "Dear tweets degens... We may have to move on, but we don't have to give up."
return html.Div([
dbc.Row(
dbc.Col([
dbc.NavbarSimple([
dbc.NavItem(
dbc.NavLink(
"Tweet Markets",
href=
"https://www.predictit.org/markets/search?query=poll",
target="_blank"))
],
brand="Pi-Chart",
color="primary",
dark=True,
fluid=True)
])),
dbc.Row(tabscontent, no_gutters=True),
html.Div([
html.P(notice),
html.P([
dcc.Link("Don't let this be the end. Join us on discord.",
href='https://discord.gg/V7wmfd',
target="_blank")
])
])
])
return dash_app.server
from PIL import Image
from PIL import ImageDraw
from PIL import ImageFont
import textwrap
df = pd.read_csv('all_tweets.csv')
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
from app import app
# app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
# server = app.server
# app.title='FAKENEWS'
layout = html.Div([
html.Title("HELLO", id='tit'),
dcc.Graph(id='score_map'),
html.Img(id='tweet'),
html.Button('Real', id='btn-nclicks-1', n_clicks=0),
html.Button('Fake Good/Funny', id='btn-nclicks-3', n_clicks=0),
html.Button('Fake Bad', id='btn-nclicks-2', n_clicks=0),
html.Button('Fake ok but fix end', id='btn-nclicks-4', n_clicks=0),
html.Div(id='container-button-timestamp'),
dcc.Store(id='idx', storage_type='session'),
dcc.Store(id='local', storage_type='session')
#Output('intermediate-value', 'children')
])
@app.callback(Output('score_map', 'figure'),
Input('local', 'modified_timestamp'), State('local', 'data'))
'name': 'SF'
}],
'layout': {
'plot_bgcolor': colors['background'],
'paper_bgcolor': colors['background'],
'font': {
'color': colors['text']
}
}
}
app.title = 'Reddit scraper'
app.layout = html.Div(children=[
html.Title(children="Reddit Scraper"),
html.Nav(className='navbar navbar-default'),
html.H1(children='Welcome to a basic reddit scraper!'),
html.Br(),
html.Div(children='''
Hello there! This is a simple graphing applet that will graph for you the words that are most frequently
appearing on a reddit post. All you have to do is enter the ID of the reddit post. THE ID is a 6 digit string
in the URL of any reddit post. For example, in "https://www.reddit.com/r/aww/comments/7j44o0/just_two_best_friends/", the id is 7j44o0.
''',
className='container'),
html.Br(),
dcc.Input(id='id-state', type='text', value=''),
html.P(),
html.Button(id='submit-button',
n_clicks=0,
children='Submit post ID',
import dash_table
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Output, Input, State
from dash.exceptions import PreventUpdate
import plotly.express as px
import numpy as np
import pandas as pd
import flask
server = flask.Flask(__name__)
app = dash.Dash(__name__, server=server)
app.layout = html.Div([
html.Title('Phebi数据分析'),
html.Header(html.Meta(name="referrer", content="no-referrer")),
html.Div(
id='row_1',
style={'display': 'flex'},
children=[
html.Div(
id='上传数据',
className='left_bar',
children=[
html.Div(
id='数据上传区域',
children=[
html.H6('数据源'),
dcc.Upload(id='stock_file',
children=html.Div([html.A('选择库存文件')]),
# Dash init end
# Read DataFrame, generate plot
df = pd.read_csv('https://gist.githubusercontent.com/chriddyp/c78bf172206ce24f77d6363a2d754b59/raw/c353e8ef842413cae56ae3920b8fd78468aa4cb2/usa-agricultural-exports-2011.csv',
index_col=0)
# Read, generated plot end
md_intro = '''
## US states' agricultural exports
You can filter which states are displayed using the first drop-down.
You can also control the type of plot using the second dropdown.
'''
# Generate app layout
app.layout = html.Div(style={'backgroundColor': colors['background']}, children=[
html.Title(children=['US agricultural exports']),
dcc.Markdown(children=md_intro),
html.Div(children=[
html.Label('Select state(s):'),
dcc.Dropdown(
id='state-selector',
options=[
{'label': i, 'value': i} for i in df.state.unique()
],
value=['All'],
multi=True
),
html.Label('Select plot type:'),
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
from importlib import reload
from app import app, server
from apps import QKD_settings, QKD_status, detector_settings
from navbar import Navbar
app.layout = html.Div([
Navbar(),
html.Title(id='dummy'),
dcc.Location(id='url', refresh=False),
html.Div(id='page-content')
])
@app.callback(Output('page-content', 'children'), [Input('url', 'pathname')])
def display_page(pathname):
# print(pathname)
if pathname == '/apps/QKD_settings':
return QKD_settings.serve_layout()
elif pathname == '/apps/QKD_status':
return QKD_status.serve_layout()
elif pathname == '/apps/detector_settings':
return detector_settings.serve_layout()
else:
return QKD_status.serve_layout()
if __name__ == '__main__':
