kpi_csv_sq.py: QA prototyping in sandbox.

Signed-off-by: Chuck SmileyRekiere <chuck.smileyrekiere@candelatech.com>

py-scripts/sandbox/kpi_csv_sq.py

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+# 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
+from  pathlib import Path
+
+
+external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
+
+app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
+
+# get a list of the kpi.csv files not the path needs to be bassed in
+path = Path('./2021-07-31-03-00-01_lf_check')
+
+kpi_list = list(path.glob('**/kpi.csv'))
+print(kpi_list)
+
+df = pd.DataFrame()
+
+for kpi in kpi_list:
+    # load data
+    append_df = pd.read_csv(kpi, sep='\t')
+    df = df.append(append_df, ignore_index=True)
+
+print("df {data}".format(data=df))
+
+# information on sqlite database
+# https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_sql.html
+
+# write to database
+conn = sqlite3.connect("qa_db") 
+#df.to_sql("dp_table",conn,if_exists='append')
+df.to_sql("dp_table",conn,if_exists='replace')
+conn.close()
+
+
+#https://datacarpentry.org/python-ecology-lesson/09-working-with-sql/index.html
+conn = sqlite3.connect("qa_db")
+df2 = pd.read_sql_query("SELECT * from dp_table" ,conn)
+print(df2.head())
+conn.close()
+print(df2)
+
+
+conn = sqlite3.connect("qa_db")
+df3 = pd.read_sql_query("SELECT * from  dp_table" ,conn)
+#print(df3.head())
+conn.close()
+
+# works df4 = df3.loc[(df3['Graph-Group'] == 'CX-Time') & (df3['test-tag'] == 'ATH10K(9984)')]
+# works df4 = df3.loc[(df3['Graph-Group'] == 'CX-Time') ]
+# works print(str(df3['test-tag']))
+
+# works df4 = df3.loc[(df3['Graph-Group'] == 'CX-Time') & ('ATH10K' in str(df3['test-tag']) )]
+
+print("df4: {}".format(df4))
+
+#print(df3['Graph-Group'],df3['Date'])
+
+exit(1)
+                 
+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)
+