Example of VSCode Python debugger bahving differently for app.run_server(debug=False) and app.run_server(debug=True)
In the full code snippet below, app.run_server(debug=True) will make it so that the debugger will not stop if a breakpoint is set at df = dfi in this callback:
@app.callback(Output('fig1', 'figure'),
Output('fig2', 'figure'),
Input('slider_rank', 'value'))
def slide_dfi(rankslider):
df = dfi # set breakpoint here and try it out
# df =dfi.iloc[rankslider[0]*-1, rankslider[0]*-1]
print(rankslider)
return go.Figure(), go.Figure()
If app.run_server(debug=False), then the debugger will stop there!
Other settings:
app.run_server(debug=False, threaded=True, port=8099)
json config:
{
// Use IntelliSense to learn about possible attributes.
// Hover to view descriptions of existing attributes.
// For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
"version": "0.2.0",
"configurations": [
{
"name": "Python: Current File",
"type": "python",
"request": "launch",
"program": "${file}",
"console": "integratedTerminal",
"justMyCode": true
}
]
}
# %%
# imports
import warnings
import dash
import dash_bootstrap_components as dbc
from dash import Dash, html, dcc, ctx
from dash import Dash, html, dcc, Input, Output, dash_table
import plotly.express as px
from plotly.subplots import make_subplots
import glob
import numpy as np
from sklearn.linear_model import LinearRegression
from sklearn.cluster import KMeans
from sklearn import datasets
from dash.dependencies import Input, Output
import plotly.graph_objs as go
import pandas as pd
from jupyter_dash import JupyterDash
import statsmodels.api as sm
import os
import plotly.figure_factory as ff
import polars as pl
import json
import sys
sys.path.insert(1, 'c:/repos/pyfx/')
from pdfx import RegressionList_StepWise # nopep8
from pdfx import txt2image # nopep8
from pdfx import powerpoint_com02 # nopep8
from pdfx import ply_bar_single # nopep8
from pdfx import ply_tSerier2 # nopep8
from pdfx import ply_boxScatter01 # nopep8
from pdfx import ply_box # nopep8
from pdfx import ply_tSerier # nopep8
from pdfx import table_offset_V2 # nopep8
from pdfx import LinReg_tTest # nopep8
from pdfx import LinReg_params2 # nopep8
from pdfx import LinReg_models # nopep8
from pdfx import LinReg01_MultipleResults # nopep8
from pdfx import Regresjonslister_stegvis # nopep8
from pdfx import RollRegression_resultsOnly # nopep8
from pdfx import plot_sns_RegressionV2 # nopep8
from pdfx import plot_sns_Regression1 # nopep8
from pdfx import RegressionList_1by1 # nopep8
from pdfx import pptKommentar # nopep8
from pdfx import pptPrint_sns # nopep8
from pdfx import plt_corr # nopep8
from pdfx import pd_timediff # nopep8
from datetime import timedelta # nopep8
# system setup
os.listdir(os.getcwd())
# os.getcwd()
os.chdir(r'C:\repos\fun\cohen\data')
warnings.simplefilter(action='ignore', category=FutureWarning)
sys.path.insert(1, 'c:/repos/pyfx/')
# local imports
# data
df_alb = pd.read_csv(r"C:\repos\fun\cohen\data\CohenAlbums.txt", sep='|')
dfi = pd.read_csv('C:/repos/fun/cohen/data/CohenList.txt', sep='|')
df = dfi.dropna()
# df
albums = list(df_alb['Album'])
albums1 = list(df['Album 1'].dropna())
albums2 = list(df['Album 2'].dropna())
# albums1
album_not_1 = [a for a in albums if a not in albums1]
album_not_1
album_not_2 = [a for a in albums if a not in albums2]
album_not_2
#
df_albumrank1 = df.groupby('Album 1')['Title 1'].count(
).to_frame().reset_index().sort_values('Title 1', ascending=False)
#
df_albumrank2 = df.groupby('Album 2')['Title 2'].count(
).to_frame().reset_index().sort_values('Title 2', ascending=False)
#
# print(df_albumrank1)
# print(df_albumrank2)
#
df_titlerank1 = pd.merge(df[['Position', 'Title 1']], df[[
'Position', 'Title 2']], how='left', left_on=['Title 1'], right_on=['Title 2'])
df_titlerank1 = df_titlerank1[['Position_x', 'Title 1', 'Position_y']]
df_titlerank1.columns = ['AP', 'Title', 'Haakon']
df_titlerank1 = df_titlerank1.dropna()
# %%
fig_rank = go.Figure()
for index, row in df_titlerank1.iterrows():
# print(row)
fig_rank.add_trace(go.Scatter(
x=[1, 2], y=[row['AP']*-1, row['Haakon']*-1], line_shape='spline'))
fig_rank.add_annotation(dict(font=dict( # color="green",
size=14),
# x=x_loc,
x=1,
y=row['AP']*-1,
showarrow=False,
# text="<i>"+k+"</i>",
text=row['Title'],
# textposition = "right",
align="right",
textangle=0,
standoff=100,
xshift=-10,
xanchor="right",
xref="x",
yref="y"
))
fig_rank.add_annotation(dict(font=dict( # color="green",
size=14),
# x=x_loc,
x=2,
y=row['Haakon']*-1,
showarrow=False,
# text="<i>"+k+"</i>",
text=row['Title'],
# textposition = "right",
align="right",
textangle=0,
standoff=100,
xshift=10,
xanchor="left",
xref="x",
yref="y"
))
# fig.show()
# %%
# fig=go.Figure()
# fig.add_trace(go.Scatter(x=df['Year 1'], y = df['Position'], mode = 'markers', trendline = 'ols'))
# fig.add_trace(go.Scatter(x=df['Year 2'], y = df['Position'], mode = 'markers'))
# fig.show()
# pd.wide_to_long()
df_long_year = pd.melt(df, id_vars='Position', value_vars=['Year 1', 'Year 2', ],
var_name='Man', value_name='Year'
)
df_long_year['Man'] = df_long_year['Man'].map(
{'Year 1': 'AP', 'Year 2': 'Haakon'})
df_long_title = pd.melt(df, id_vars='Position', value_vars=['Title 1', 'Title 2', ],
var_name='Man', value_name='Title'
)
df_long_title['Man'] = df_long_title['Man'].map(
{'Title 1': 'AP', 'Title 2': 'Haakon'})
df_long_title
#
df_long_album = pd.melt(df, id_vars='Position', value_vars=['Album 1', 'Album 2', ],
var_name='Man', value_name='Album'
)
df_long_album['Man'] = df_long_album['Man'].map(
{'Album 1': 'AP', 'Album 2': 'Haakon'})
df_long_album
df_long1 = pd.merge(df_long_year, df_long_title, how='left', left_on=[
"Position", "Man"], right_on=["Position", "Man"])
df_long1
df_long = pd.merge(df_long1, df_long_album, how='left', left_on=[
"Position", "Man"], right_on=["Position", "Man"])
df_long['Position'] = df_long['Position']*-1
fig = px.scatter(df_long, x='Year', y='Position', color='Man', trendline='ols',
hover_data=['Title', 'Album']
)
# fig.show()
# marks = [{i: {'label': value, 'style': {'font-size': '10px'}}} for i, value in enumerate(list(df['Title 2'][::-1]))]
# markers = list(df['Title 2'][::-1])
# marks = [{i: {'label': markers[1], 'style': {'font-size': '10px'}}}
# for i in range(-len(df), 0)]
# %%
# slider settings
sliderStart = - len(df)
sliderStops = 0
sliderSteps = 1
app = Dash(external_stylesheets=[dbc.themes.SLATE])
app.layout = dbc.Container(
[html.H1("Cohen connoisseurs",
style={"text-align": "center"}),
dbc.Row([dbc.Col([dbc.Row([dbc.Col([html.H4("List AP",
style={"text-align": "center"}), dash_table.DataTable(data=df[['Title 1', 'Album 1']].to_dict('records'),
columns=[{"name": i, "id": i} for i in df[[
'Title 1', 'Album 1']].columns],
style_cell={
'fontSize': 10, 'font-family': 'sans-serif'}
)], className="mt-3")]), dbc.Row([dbc.Col([html.H4("Cherished albums",
style={"text-align": "center"}), dash_table.DataTable(data=df_albumrank1[['Album 1', 'Title 1']].to_dict('records'),
columns=[{"name": i, "id": i} for i in df_albumrank1[[
'Album 1', 'Title 1']].columns],
style_cell={
'fontSize': 10, 'font-family': 'sans-serif'},
# style={'margin-top': '5px'}
)], className="mt-3")])], width=3, className="bg-primary"),
dbc.Col([dcc.Graph(id="fig1", figure=fig),
dcc.Graph(id="fig2", figure=fig_rank),
dcc.RangeSlider(sliderStart, sliderStops, sliderSteps,
id='slider_rank',
# min=5,
# max=len(df),
# step=1,
# pushable=True,
# value=[0, len(dfi)],
value=[sliderStart, sliderStops],
updatemode='drag',
marks=None,
allowCross=False,
# style={'width':'50%'}
tooltip={'always_visible': True,
'placement': 'bottom'},
)],),
dbc.Col([dash_table.DataTable(data=df[['Title 2', 'Album 2']].to_dict('records'),
columns=[{"name": i, "id": i} for i in df[[
'Title 2', 'Album 2']].columns],
style_cell={
'fontSize': 10, 'font-family': 'sans-serif'}
),
dash_table.DataTable(data=df_albumrank2[['Album 2', 'Title 2']].to_dict('records'),
columns=[{"name": i, "id": i} for i in df_albumrank2[[
'Album 2', 'Title 2']].columns],
style_cell={
'fontSize': 10, 'font-family': 'sans-serif'}
)], width=3)], className="mt-2"),
dbc.Row([]),
dbc.Row([])
])
# %%
print('fu')
@app.callback(Output('fig1', 'figure'),
Output('fig2', 'figure'),
Input('slider_rank', 'value'))
def slide_dfi(rankslider):
df = dfi
# df =dfi.iloc[rankslider[0]*-1, rankslider[0]*-1]
print(rankslider)
return go.Figure(), go.Figure()
if __name__ == "__main__":
app.run_server(debug=False, threaded=True, port=8099)