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app.py
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app.py
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import urllib.request
import json
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import plotly
import plotly.plotly as py
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
from plotly.graph_objs import *
import datetime
from operator import itemgetter
with open('config.json') as f:
credentials = json.load(f)
mapbox_access_token = credentials["mapbox_access_token"]
username = credentials["username"]
api_key = credentials["api_key"]
plotly.tools.set_credentials_file(username='abachant', api_key='WWLZwB7VhIf7pkNRG9Kr')
app = dash.Dash('RIPTA-App')
def get_data(url):
"""Retreive data from RIPTA's API"""
response = urllib.request.urlopen(url).read()
response = json.loads(response)
return response
def get_trip_updates():
url = "http://realtime.ripta.com:81/api/tripupdates?format=json"
return get_data(url)
def get_vehicle_positions():
url = "http://realtime.ripta.com:81/api/vehiclepositions?format=json"
return get_data(url)
def get_service_alerts():
url = "http://realtime.ripta.com:81/api/servicealerts?format=json"
return get_data(url)
def position_data_to_dataframe(d):
"""Get relevant data and postion it to a pandas dataframe"""
vehicle_id = []
trip_id = []
start_time = []
start_date = []
schedule_relationship = []
route_id = []
latitude = []
longitude = []
bearing = []
odometer = []
speed = []
current_stop_sequence = []
current_status = []
timestamp = []
congestion_level = []
stop_id = []
for entity_item in d["entity"]:
vehicle_id.append(entity_item["vehicle"]["vehicle"]["id"])
trip_id.append(entity_item["vehicle"]["trip"]["trip_id"])
start_time.append(entity_item["vehicle"]["trip"]["start_time"])
start_date.append(entity_item["vehicle"]["trip"]["start_date"])
schedule_relationship.append(entity_item["vehicle"]["trip"]["schedule_relationship"])
route_id.append(entity_item["vehicle"]["trip"]["route_id"])
latitude.append(entity_item["vehicle"]["position"]["latitude"])
longitude.append(entity_item["vehicle"]["position"]["longitude"])
bearing.append(entity_item["vehicle"]["position"]["bearing"])
odometer.append(entity_item["vehicle"]["position"]["odometer"])
speed.append(entity_item["vehicle"]["position"]["speed"])
current_stop_sequence.append(entity_item["vehicle"]["current_stop_sequence"])
current_status.append(entity_item["vehicle"]["current_status"])
timestamp.append(entity_item["vehicle"]["timestamp"])
congestion_level.append(entity_item["vehicle"]["congestion_level"])
stop_id.append(entity_item["vehicle"]["stop_id"])
df = pd.DataFrame()
df["vehicle_id"] = vehicle_id
df["trip_id"] = trip_id
df["start_time"] = start_time
df["start_date"] = start_date
df["schedule_relationship"] = schedule_relationship
df["route_id"] = route_id
df.route_id = df.route_id.astype(int)
df["latitude"] = latitude
df["longitude"] = longitude
df["bearing"] = bearing
df["odometer"] = odometer
df["speed"] = speed
df.speed = round(df.speed, 1)
df["current_stop_sequence"] = current_stop_sequence
df["current_status"] = current_status
df["timestamp"] = timestamp
df["congestion_level"] = congestion_level
df["stop_id"] = stop_id
return df
def make_data_frame():
d = get_vehicle_positions()
df = position_data_to_dataframe(d)
return df
df = make_data_frame()
data = Data([
Scattermapbox(
lat=df['latitude'],
lon=df['longitude'],
mode='markers',
marker=Marker(
size=9
),
text="test",
)
])
layout = Layout(
autosize=True,
hovermode='closest',
mapbox=dict(
accesstoken=mapbox_access_token,
bearing=0,
center=dict(
lat=41.83,
lon=-71.41
),
pitch=0,
zoom=10
),
)
available_routes = [{'label': 'All', 'value': 'All'}]
available_routes_numeric = []
working_route_list = list(df.route_id)
def search_active_routes(routes, term):
"""Find which bus routes are currently active"""
is_in=False
for i in routes:
if term in i.values():
is_in=True
break
else:
pass
return is_in
def all_active_routes():
"""Organize all active routes"""
for i in working_route_list:
if i==11 and search_active_routes(available_routes, i) == False:
available_routes.append({'label': 'R/L', 'value': i})
elif search_active_routes(available_routes_numeric, i) == False:
available_routes_numeric.append({'label': i, 'value': i})
else:
pass
all_active_routes()
available_routes_numeric = sorted(available_routes_numeric, key=itemgetter('value'))
available_routes = available_routes + available_routes_numeric
fig = dict(data=data, layout=layout)
app.layout = html.Div(children=[
html.H1(children='Realtime RIPTA Locations'),
html.Div(children='''
A Dashboard for all RIPTA vehicles and routes.
'''),
html.Hr(),
html.Label('Choose which bus routes to view'),
dcc.Dropdown(
id='route-dropdown',
options=available_routes,
value='All',
),
dcc.Graph(
figure=Figure(fig),
style={'height': 800},
id='live-update-graph',
# 'animate=True' here would make for smoother callbacks but it is still in beta and breaks our ability to maintain camera's position and zoom
),
dcc.Interval(
id='interval-component',
interval=1 * 5000, # reload time in milliseconds
n_intervals=0
),
dcc.Markdown("Source: Transit API(http://realtime.ripta.com:81/)",
className="source"),
])
@app.callback(Output('live-update-graph', 'figure'),
[Input('interval-component', 'n_intervals'),
Input('route-dropdown', 'value')],
[State('live-update-graph', 'figure')])
def update_graph_live(n, value, fig):
"""Updates the data being plotted at every n_interval"""
d = get_vehicle_positions()
df = position_data_to_dataframe(d)
try:
value = int(value)
except ValueError:
pass
if value in df.route_id:
df = df[df.route_id == value]
data = Data([
Scattermapbox(
lat=(df['latitude']),
lon=(df['longitude']),
mode='markers',
marker=Marker(
size=9
),
hovertext=("Line: " + df.route_id.astype(str) + ", ID: " + df.vehicle_id.astype(str) + ", Speed: " + df.speed.astype(str) + " mph"),
)
])
fig["data"] = data
return fig
external_css = ["https://cdnjs.cloudflare.com/ajax/libs/skeleton/2.0.4/skeleton.min.css",
"//fonts.googleapis.com/css?family=Raleway:400,300,600",
"//fonts.googleapis.com/css?family=Dosis:Medium",
"https://cdn.rawgit.com/plotly/dash-app-stylesheets/62f0eb4f1fadbefea64b2404493079bf848974e8/dash-uber-ride-demo.css",
"https://maxcdn.bootstrapcdn.com/font-awesome/4.7.0/css/font-awesome.min.css"]
for css in external_css:
app.css.append_css({"external_url": css})
if __name__ == "__main__":
app.run_server(debug=True)