# Run this app with `python app.py` and # visit http://127.0.0.1:8050/ in your web browser. import dash import dash_core_components as dcc import dash_html_components as html import plotly.express as px import pandas as pd import sqlite3 external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css'] app = dash.Dash(__name__, external_stylesheets=external_stylesheets) # load data df = pd.read_csv('http://192.168.95.6/html-reports/2021-07-20-16-25-05_lf_check/dataplane-2021-07-20-04-28-42/kpi.csv', sep='\t') append_df = pd.read_csv('http://192.168.95.6/html-reports/2021-07-24-03-00-01_lf_check/dataplane-2021-07-24-03-06-02/kpi.csv', sep='\t') df = df.append(append_df, ignore_index=True) # information on sqlite database # https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_sql.html # write to data base local for now conn = sqlite3.connect("qa_db") # can append df.to_sql("dp_table",conn,if_exists='append') conn.close() conn = sqlite3.connect("qa_db") #https://datacarpentry.org/python-ecology-lesson/09-working-with-sql/index.html df2 = pd.read_sql_query("SELECT * from dp_table" ,conn) print(df.head()) conn.close() #print(df) fig = (px.scatter(df2, x="Date", y="numeric-score", color="short-description", hover_name="short-description", size_max=60)).update_traces(mode='lines+markers') ''' fig = px.scatter(df, x="Date", y="numeric-score", color="short-description", hover_name="short-description", size_max=60) ''' ''' fig = px.scatter(df, x="short-description", y="numeric-score", color="short-description", hover_name="short-description", size_max=60) ''' fig.update_layout( title="Throughput vs Packet size", xaxis_title="Packet Size", yaxis_title="Mbps", xaxis = {'type' : 'date'} ) app.layout = html.Div([ dcc.Graph( id='packet-size vs rate', figure=fig ), dcc.Graph( id='packet-size vs rate2', figure=fig ) ]) if __name__ == '__main__': app.run_server(debug=True)