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app.py
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app.py
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import dash
from dash import dcc, html, Input, Output
from flask_caching import Cache
import dash_bootstrap_components as dbc
import json
import pandas as pd
import uuid
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from get_data import GetData
from make_features import MakeFeatures
features = MakeFeatures()
gd = GetData()
dash_app = dash.Dash(__name__,
external_stylesheets=[dbc.themes.SPACELAB,
dbc.icons.FONT_AWESOME])
dash_app.title = 'Agrihub Vessels'
cache = Cache(dash_app.server, config={
'CACHE_TYPE': 'redis',
# Note that filesystem cache doesn't work on systems with ephemeral
# filesystems like Heroku.
'CACHE_TYPE': 'filesystem',
'CACHE_DIR': 'cache-directory',
# should be equal to maximum number of users on the app at a single time
# higher numbers will store more data in the filesystem / redis cache
'CACHE_THRESHOLD': 200
})
app = dash_app.server
def get_dataframe(session_id):
@cache.memoize()
def query_and_serialize_data(session_id):
# expensive or user/session-unique data processing step goes here
df = gd.get_vessel_commodity()
return df.to_json()
return pd.read_json(query_and_serialize_data(session_id))
########################################################################
# Define dashboard aspects
########################################################################
# Select commodity card
commdodity_select_card = dbc.Card(
[dbc.CardHeader("Select Commodity"),
dbc.CardBody(dcc.Dropdown(
[], 'ALL', clearable=False, id='commodity-dropdown')),
], className="mt-4",
)
# Select vessel card
vessel_select_card = dbc.Card(
[dbc.CardHeader("Select Vessel"),
dbc.CardBody(dcc.Dropdown(
[], 'ALL', clearable=False, id='vessel-dropdown')),
], className="mt-4",
)
# Map card for geolocation of vessels
map_card = dbc.Card(
[
html.Div(id='map-vis', className="mb-2"),
],
className="mt-4",
)
# Next port table card
next_port_card = dbc.Card(
[
dbc.CardHeader("Next port information"),
dbc.CardBody(
html.Div(id='vessel-table'),
),
],
className="mt-4",
)
# Commodity summary card
commodity_card = dbc.Card(
[
dbc.CardHeader("Commodity information"),
dbc.CardBody(
html.Div(id='commodity-table'),
),
],
className="mt-4",
)
# Footer card
footer = html.Div(
dcc.Markdown(
"""
Agrihub 2022-2023
"""
),
className="p-2 mt-5 bg-primary text-white small",
)
########################################################################
# Define app
########################################################################
def serve_layout():
session_id = str(uuid.uuid4())
return dbc.Container(
[
dcc.Store(data=session_id, id='session-id'),
dbc.Row(
dbc.Col(
html.H2(
"Agrihub Active Vessels",
className="text-center bg-primary text-white p-2",
),
)
),
dbc.Row(
[
dbc.Col([map_card,
next_port_card
],
width=12,
lg=6,
className="pt-4",
),
dbc.Col(commodity_card, width=12, lg=4, className="mt-4"),
dbc.Col([commdodity_select_card, vessel_select_card,
], width=12, lg=2, className="mt-4 border"),
],
className="ms-1",
),
dbc.Row(dbc.Col(footer)),
],
fluid=True,
)
dash_app.layout = serve_layout
########################################################################
# Define callbacks for interactivity
########################################################################
# Get data
def clean_data(session_id, commodity='ALL', vessel='ALL'):
df_4 = get_dataframe(session_id)
if commodity != 'ALL':
df_4 = df_4[df_4['commodity'] == commodity]
if vessel != 'ALL':
df_4 = df_4[df_4['vessel_name'] == vessel]
return df_4
# Callback to manage commodity dropdown
@dash_app.callback(
Output('commodity-dropdown', 'options'),
Input('session-id', 'data'),
Input('vessel-dropdown', 'value'),
)
def update_com_dropdown(session_id, vessel):
""" Update commodity dropdown based on vessel
Parameters
----------
vessel : strings
Filter data by vessels.
If vessel='ALL', use all rows in data set.
Returns
----------
commlist : list
A list of commodities on the selected vessels.
"""
table_df=clean_data(session_id, vessel=vessel)
commlist = list(table_df['commodity'].unique())
commlist.sort()
commlist = ['ALL'] + commlist
return commlist
# Callback to manage vessel dropdown
@dash_app.callback(
Output('vessel-dropdown', 'options'),
Input('session-id', 'data'),
Input('commodity-dropdown', 'value'),
)
def update_ves_dropdown(session_id, commodity):
""" Update vessel dropdown based on commodity
Parameters
----------
commodity : string
Filter data by commodity.
If commodity='ALL', use all rows in data set.
Returns
----------
vessellist : list
A list of vessels on the selected commodities.
"""
#datasets = json.loads(jsonified_cleaned_data)
#table_df = pd.read_json(datasets['df_4'], orient='split')
table_df=clean_data(session_id, commodity=commodity)
vessellist = list(table_df['vessel_name'].unique())
vessellist.sort()
vessellist = ['ALL'] + vessellist
return vessellist
# Update vessel-commodity bar graph
@dash_app.callback(
Output('commodity-table', 'children'),
Input('session-id', 'data'),
Input('commodity-dropdown', 'value'),
Input('vessel-dropdown', 'value'),
)
def update_com_table(session_id, commodity, vessel):
""" Generates bar graph indicating commodity volumes by vessel
Parameters
----------
commodity : string
Filter data by commodity.
If commodity='ALL', use all rows in data set.
vessel : string
Filter data by vessel.
If vessel='ALL', use all rows in data set.
Returns
----------
graph : dash core graph component
An HTML package of a barchart
"""
#datasets = json.loads(jsonified_cleaned_data)
#table_df = pd.read_json(datasets['df_4'], orient='split')
table_df=clean_data(session_id, commodity, vessel)
table_df = table_df.sort_values(by='vessel_name', ascending=False)
vessels = table_df.vessel_name.unique()
commodities = table_df.commodity.unique()
fig = go.Figure()
for com in commodities:
df = table_df[table_df['commodity'] == com]
vessels = list(df.vessel_name)
values = list(df.stdunits)
fig.add_trace(go.Bar(
y=vessels,
x=values,
text=values,
textposition='inside',
name=com,
orientation='h',
marker=dict(
color=gd.get_colour(com),
line=dict(color=gd.get_colour(com), width=1)
)
))
fig.update_layout(barmode='stack',
margin={"r": 0, "t": 0, "l": 0, "b": 0},
uniformtext_minsize=8, uniformtext_mode='hide',
legend=dict(
orientation="h",
yanchor="bottom",
y=1.02,
xanchor="right",
x=1
))
graph = dcc.Graph(figure=fig, style={'height': '90vh'}, config={
'displayModeBar': False})
return graph
# Update vessel next port location and ETA
@dash_app.callback(
Output('vessel-table', 'children'),
Input('session-id', 'data'),
Input('commodity-dropdown', 'value'),
Input('vessel-dropdown', 'value'),
)
def update_vessel_table(session_id, commodity, vessel):
""" Generates table indicating Next Port by vessel
Parameters
----------
commodity : string
Filter data by commodity.
If commodity='ALL', use all rows in data set.
vessel : string
Filter data by vessel.
If vessel='ALL', use all rows in data set.
Returns
----------
table : dash core table component
An HTML package of a table
"""
#datasets = json.loads(jsonified_cleaned_data)
#table_df = pd.read_json(datasets['df_4'], orient='split')
table_df=clean_data(session_id, commodity, vessel)
table_df = features.vessel_table(table_df)
table = dbc.Table.from_dataframe(
table_df, striped=True, bordered=True, hover=True)
return table
# Update map visual
@dash_app.callback(
Output('map-vis', 'children'),
Input('session-id', 'data'),
Input('commodity-dropdown', 'value'),
Input('vessel-dropdown', 'value'),
)
def update_map(session_id, commodity, vessel):
""" Generates MAP visual to locate all active vessels
Parameters
----------
commodity : string
Filter data by commodity.
If commodity='ALL', use all rows in data set.
vessel : string
Filter data by vessel.
If vessel='ALL', use all rows in data set.
Returns
----------
map : dash core table component
An HTML package of a map visual
"""
#datasets = json.loads(jsonified_cleaned_data)
#table_df = pd.read_json(datasets['df_4'], orient='split')
table_df=clean_data(session_id, commodity, vessel)
map = dcc.Graph(figure=features.map_viz(table_df), config={
'displayModeBar': False}, className="mb-2")
return map
if __name__ == '__main__':
dash_app.run_server(debug=True)