from datetime import datetime, date, time, timedelta import dash from dash import html from dash import html, dcc, callback, dash_table, clientside_callback import dash_bootstrap_components as dbc from dash.dependencies import Input, Output, State from dash import dash_table from dash.dash_table import DataTable, FormatTemplate from dash.exceptions import PreventUpdate from dash.dash_table.Format import Format, Scheme, Trim import plotly.express as px import traceback import pandas as pd import json import urllib.parse import FlaskApp.app.common as common import FlaskApp.app.data_store as data_store dash.register_page(__name__) layout = html.Div([ dbc.Container( children= [ dbc.Row([ dbc.Col( dbc.Card([ dbc.CardBody([ html.H1("Dashboard"), html.P(''' This is a dashboard for A.Emery '''), ]), ],className="border-0 bg-transparent"), width={"size":3} ), dbc.Col( dbc.Card([ dbc.CardBody([ html.Div([ dbc.Button("LOGOUT",href='/logout',color='light',size='lg',external_link=True,) ]), ]), ],className="border-0 bg-transparent"), width={"size":1,'offset':8} ) ]), dbc.Row([ dbc.Col([ html.Div([ html.Div(id='dd-output-container-graph',children='Data Update Complete') ],style={'backgroundColor':'red','color':'white'}) ]), ], align='center'), dbc.Row([ dbc.Col( html.Div([ dcc.Graph(id='graph-px-alt') ]) ) ]), dbc.Row([ dbc.Col( dcc.RadioItems( ['Absolute','Normalised'], 'Absolute', id ='graph-type-alt', inline=True, inputStyle={"margin-right": "10px"} ) ,width={'size':1}) ],justify='center') ],fluid=True), #dcc.Store(id = 'clientside-figure-store-px'), dcc.Location(id='url'), dcc.Store(id='df-store'), dcc.Store(id='name-text') ]) @callback( Output('df-store', 'data'), Output('name-text','data'), Input('url', 'search'), prevent_initial_call = True ) def get_query(url): try: common.logger.debug('get query call back reached' + str(url)) if url[1:].startswith('date'): #dcc.Location 'search' return query string including '?' - so skip over that parsed_url = urllib.parse.urlparse(url) try: date = urllib.parse.parse_qs(parsed_url.query)['date'][0] data = urllib.parse.parse_qs(parsed_url.query)['data'][0] except Exception as ex: #(ValueError, KeyError): common.logger.info('graph query with invalid parameters - url: ' + str(url) + '\n' + str(ex)) return None,None #data = url[1:].replace('data=','') #common.logger.info('URL call back reached' + str(data)) data = json.loads(urllib.parse.unquote(data)) #need to decode url string before sending through json decoder common.logger.debug(str(data)) if data: data_df = pd.DataFrame.from_records(data) data_cols = data_df.columns.tolist() if 'color' in data_cols: if 'size' in data_cols: keys = ['color','size'] name_text = 'Colour - Size' else: keys = ['color'] name_text = 'Colour' elif 'size' in data_cols: keys = ['size'] name_text = 'Size' else: keys = [] name_text = '' if 'p_name' in data_cols: keys.insert(0,'p_name') if name_text : name_text = 'Product - ' + name_text else: name_text = 'Product' if 'sub_category' in data_cols: keys.insert(0,'sub_category') if name_text: name_text = 'Sub-Category - ' + name_text else: name_text = 'Sub-Catgegory' common.logger.debug(str(type(date)) + '\n' + str(date)) stock_df = data_store.get_data_from_globals()[0].copy() stock_df = stock_df[stock_df['date'] >= datetime.strptime(date,'%Y-%m-%d').date()] common.logger.debug(str(stock_df)) #stock_df['date'] = stock_df['date'].dt.date if keys: # if multiple columns then use index matching approach idx_stock = stock_df.set_index(keys).index idx_data = data_df.set_index(keys).index dff = stock_df[idx_stock.isin(idx_data)] else: #if just p_name then filter on p_name dff = stock_df[stock_df['p_name'].isin(data_df['p_name'].unique().tolist())] keys = ['p_name'] df_grouped = dff[['date'] + keys + ['available_to_sell']].groupby(keys + ['date']).agg({'available_to_sell':'sum'}).reset_index() df_grouped['Name'] = df_grouped[keys].apply(lambda x: ' - '.join(x.astype(str)),axis=1) df_graph = df_grouped.pivot(index='date',columns='Name',values='available_to_sell') for col in df_graph.columns.tolist(): col_max = df_graph[col].max() col_min = df_graph[col].min() abs_max = max(col_max,-col_min) df_graph[col + '_norm'] = df_graph[col] / col_max * 100 plot_cols = [x for x in df_graph.columns.tolist() if '_norm' not in x] #get normalised columns before bringing back 'date' df_graph = df_graph.reset_index() #bring back 'date' into columns #common.logger.info(str(df_graph.head()) + '\n' + str(plot_cols)) '''fig = px.line(df_graph,x='date',y=plot_cols,title='Available To Sell History',\ labels={'variable':name_text,\ 'date':'Date',\ 'value':'Stock Available to Sell'}, #mode = 'markers+lines' ) fig.update_layout( height = 600 ) ''' return df_graph.to_json(date_format='iso', orient='split'), name_text return None,None except Exception as ex: tb = traceback.format_exc() common.logger.warning('Error Process Dashboard Layout' + '\nException Info: ' + str(ex) + '\nTraceback Info: ' + str(tb)) return None,None @callback( Output('graph-px-alt', 'figure'), [Input('df-store','data'), Input('graph-type-alt', 'value'), Input('name-text','data')], running=[(Output("dd-output-container-graph","children"),'Data Being Updated.....Please Wait', 'Data Update Complete'), (Output("dd-output-container-graph","style"),{'backgroundColor':'red','color':'white'},{'backgroundColor':'white','color':'black'})], prevent_initial_call = True ) def update_figure(df_graph,graph_type,name_text): try: common.logger.debug('update figure call back reached' + str(graph_type) + str(name_text) + str(df_graph)) if df_graph: df_graph = pd.read_json(df_graph, orient='split') if graph_type == 'Absolute': plot_cols = [x for x in df_graph.columns.tolist() if '_norm' not in x] dff = df_graph[plot_cols] else: plot_cols = [x for x in df_graph.columns.tolist() if '_norm' in x] dff = df_graph[plot_cols] fig = px.line(df_graph,x='date',y=plot_cols,title='Available To Sell History - ' + graph_type,hover_data={'date':"|%Y-%m-%d"},markers=True,\ labels={'variable':name_text,\ 'date':'Date',\ 'value':'Stock Available to Sell'}\ ) fig.update_layout( height = 600, ) fig.update_yaxes(rangemode='tozero') return fig return {} except Exception as ex: tb = traceback.format_exc() common.logger.warning('Error Process Dashboard Layout' + '\nException Info: ' + str(ex) + '\nTraceback Info: ' + str(tb)) return {}