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How can I pass multiple user input values from PySimpleGUI to a function, then output result to PySimpleGUI?

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I am building a financial trading profit/loss calculator. I have built the script to function in the command line interface (main_cli.py).
Now, I am trying to convert to a desktop GUI via PySimpleGUI, but am having difficulty with passing multiple user input values from PySimpleGUI (main_gui.py) to the calculator function (functions.py), to then output the result in the same PySimpleGUI window.
When I run the main_gui.py script, it still asks for user_input in the CLI.

Just pass values to your function, then convert all fields into your data for the function to calculate the result, and return it back to event loop to update the GUI.
Note: No any entry validation in the code.
import PySimpleGUI as sg
def calculate(values):
ticker = ticker_list[[values[("Ticker", i)] for i in range(len(tickers))].index(1)]
tick_size, contract_amount = tickers[ticker]
position = "Long" if values[("Position", 0)] else "Short"
purchase_price = float(values['Entry'])
selling_price = float(values['Exit'])
contract_size = float(values['Contract'])
tick_value = (((purchase_price - selling_price)*contract_size)/tick_size)
dollar_value = (tick_value*contract_amount)
if position == "Long":
tick_value = abs(tick_value)
dollar_value = abs(dollar_value)
return tick_value, dollar_value
tickers = {
'ES' : (0.25, 12.50),
'NQ' : (0.25, 5.00),
'RTY': (0.10, 5.00),
'YM' : (1.00, 5.00),
'GC' : (0.10, 10.00),
'CL' : (0.01, 10.00),
}
ticker_list = list(tickers.keys())
positions = ['Long', 'Short']
keys = {
'Entry':'Entry price',
'Exit':'Exit price',
'Contract':'Contract size',
}
sg.theme('Dark')
sg.set_options(font=('Helvetica', 10))
layout = [
[sg.Text("Ticker:", size=10)] + [sg.Radio(tick, "Radio 1", key=("Ticker", i)) for i, tick in enumerate(tickers)],
[sg.Text("Position:", size=10)] + [sg.Radio(pos, "Radio 2", key=("Position", i)) for i, pos in enumerate(positions)]] + [
[sg.Text(text, size=10), sg.InputText(size=10, expand_x=True, key=key)] for key, text in keys.items()] + [
[sg.Text("Result"), sg.Text(text_color="white", key="Output")],
[sg.Push(), sg.Button("Reset"), sg.Button("Calculate", button_color=('white', '#007339'))],
]
window = sg.Window('Futures Profit/Loss Calculator', layout=layout)
while True:
event, values = window.read()
print(event, values)
if event == sg.WIN_CLOSED:
break
elif event == "Calculate":
tick_value, dollar_value = calculate(values)
result = f"ticks: {tick_value} | profit/loss: ${dollar_value}"
window['Output'].update(result)
elif event == "Reset":
for key in keys:
window[key].update('')
window.close()
If this function take long time to finish the caluclation, you can call method window.perform_long_operation to run your function, Lambda expression can help to pass the arguments here, then update your GUI when the event '-FUNCTION COMPLETED-' generated, like
elif event == "Calculate":
window.perform_long_operation(lambda x=values:calculate(x), '-FUNCTION COMPLETED-')
elif event == '-FUNCTION COMPLETED-':
tick_value, dollar_value = values[event]
result = f"ticks: {tick_value} | profit/loss: ${dollar_value}"
window['Output'].update(result)

Python code to execute the expression when either A or B or both files is selected

I'm new to Python and I'm trying to use pandas and pysimpleGui to create a project. However, my coding didn't work, any advice would be greatly appreciated.
And the project logic is:
User will need to select either the Customer ID list or Special Price List and then hit the 'Convert' button it will convert the selected file into the correct format.
-These are the requirements:
For Customer ID list:
Must have only 1 column
If the header isn't CUS_ID then show the replace button:
If replace button is clicked then the first row will be replaced, if the button isn't clicked then the header will be created.
If the header is CUS_ID then notify the user under the status bar.
For Special Price List:
Must have 3 columns and the header is: 'PROD_CD','UT_PRICE','EXP_DATE'
the last column is date format mm/dd/yyyy
If the header isn't correct then show the replace button:
If replace button is clicked then the first row will be replaced, if the button isn't clicked then the header will be created.
If the header is correct then notify the user under the status bar.
The transfer button will run either the Customer ID list or the Special Price list or both are selected.
And below are my coding:
import pandas as pd
import PySimpleGUI as sg
def main():
sg.theme('SystemDefaultForReal')
layout = [
[sg.FileBrowse('CUSID',size = (15,2),file_types =(('Excel File', '*.xlsx'),), key='cusid', enable_events=True),
sg.FileBrowse('SPECIAL PRICE LIST',size = (18,2),file_types =(('Excel File', '*.xlsx'),), k='SPlist', enable_events=True)],
[sg.Button('Convert', key='submit'), sg.Button("Cancel", k='cancel')],
[sg.StatusBar('', size=(50,1), key='status', justification='center'), sg.Button('Replace Header', key='-replace-', visible=False), sg.Button('Replace Headers', key='-replace2-', visible=False)]
]
#create the window
window = sg.Window("Special Price Converter", layout, element_justification='center', finalize=True, icon=r'C:\Python\apps\specialpriceconvert\icon.ico')
cusidHeader = ['CUS_ID']
SPlistHeader=['PROD_CD','UT_PRICE','EXP_DATE']
butt_down = False
butt_down2 = False
cusidReplace = False
SPlistReplace = False
#file validation function:
def validation(filename):
file= values[filename]
validation.df = pd.read_excel(file, header=None) #header = None will show 0 at header
col_count = len(validation.df.columns)
if filename == 'cusid':
header = validation.df.iloc[0,0]
if col_count == 1:
#RETURN THE FIRST ROW VALUE
if header == cusidHeader[0]: #iloc[row_index, column_index]
window['status'].update('CUS_ID header already exist')
window['-replace-'].update(visible=False)
return False
else:
window['status'].update('Header: ' + header , visible=True)
window['-replace-'].update(visible=True)
return True
else:
window['status'].update('Error: selected file has more than 1 column!', visible=True)
window['-replace-'].update(visible=False)
return False
elif filename == 'SPlist':
header = validation.df.iloc[0].to_list() #append first row to a list.
if col_count == 3:
if header == SPlistHeader:
window['status'].update('Special Price header already exist')
window['-replace2-'].update(visible=False)
return False
else:
window['status'].update('Header: ' + str(header) , visible=True)
window['-replace2-'].update(visible=True)
return True
else:
window['status'].update('Error: selected file must have 3 columns!', visible=True)
window['-replace2-'].update(visible=False)
return False
while True: # Event Loop
event, values = window.read()
#Close window:
if event in (sg.WIN_CLOSED, 'cancel'):
break
elif 'cusid' in event: #if CUSID is selected
#Validation CUSID:
validation('cusid')
window['-replace2-'].update(visible=False)
elif 'SPlist' in event:
#Validation SPlist:
validation('SPlist')
window['-replace-'].update(visible=False)
#if clicked replace and cusid file is valid:
elif event == '-replace-':
butt_down = not butt_down
window['-replace-'].update( button_color='snow4' if butt_down else 'snow')
if butt_down:
cusidReplace = True
window['status'].update('cusidReplace is: '+ str(cusidReplace), visible=True)
else:
cusidReplace = False
window['status'].update('cusidReplace is: '+ str(cusidReplace), visible=True)
elif event == '-replace2-':
butt_down2 = not butt_down2
window['-replace2-'].update( button_color='snow4' if butt_down2 else 'snow')
if butt_down2:
SPlistReplace = True
window['status'].update('SPlistReplace is: '+ str(SPlistReplace), visible=True)
else:
SPlistReplace = False
window['status'].update('SPlistReplace is: '+ str(SPlistReplace), visible=True)
elif 'submit' in event:
#If only CUSID file is selected and CUS replace button is select:
if cusidReplace and validation('SPlist') is False:
print('Cusid Replace button is off and SPlist does not exist')
# excel_export('cusid')
#If both files are selected:
elif cusidReplace is False and validation('SPlist') is True:
print('Cusid Replace button is off and SPlist exist')
elif SPlistReplace and validation('cusid') is False:
print('SPlist Replace button is off and Cusid does not exist')
elif SPlistReplace is False and validation('cusid') is True:
print('SPlist Replace button is off and Cusid exist')
window.close()
if __name__ == '__main__':
main()

How to appy threading to make it run faster?

I have this code to load data to file. I want to make it run concurrently using threads to make it faster. Some people recommended to use asyncio but I could'nt really understand it. This code is for cleaning a csv file. For eg it cleans reads date in arabic format and changes it to the english calender. Can anyone provide a brief overview of how this can be done.
# -*- coding: utf-8 -*-
"""
Created on Sun Apr 12 00:03:38 2020
#author: siradmin
****** DATE ISSUES CODE ******
The purpose of this code is to correct date in different date columns
"""
import os
os.chdir("D://Medgulf Motor/2022/Code for date cleaning")
os.getcwd()
import pandas as pd
import datetime as dt
#df = pd.read_csv("D://Medgulf Motor/2022/Data/Pricing Data 11.05.2021/Tricast/TricastPolicyData.txt",
# engine='python', sep=';', chunksize=100000)
df = pd.read_csv("D://Medgulf Motor/2022/Data/Pricing Data 11.05.2021/Tricast/TricastPolicyData.csv",
engine='python', chunksize=100000 )
columns = ['Issue Date','Inception Date','Expiry Date', 'Policy Status Date',
'Vehicle Issue Date', 'Vehicle Inception Date','Vehicle Expiry Date',
'Status Date', 'Insured Date of Birth','Main Driver DOB']
# 'Istemarah Exp.', 'Additional Driver DOB']
fmts2 = ['%d/%m/%Y', '%d/%m/%y', '%d-%m-%Y', '%d-%m-%y', '%m/%d/%Y', '%Y/%m/%d',
'%Y-%m-%d', '%d|%m|%Y']
new_date = []
j = []
isd,ind,exd,psd,visd,vind,vexd,sd,ise,idb,mdd,add=(pd.DataFrame,)*12
header_flag = True
## Actual Code ##
print(dt.datetime.now())
for cx, chunk in enumerate(df):
for col in columns:
new_date = []
for idx, x in enumerate(chunk[col]):
try:
x = int(x)
dd = dt.datetime(1900,1,1)
da = dt.timedelta(days=int(x)-2)
nd = dd + da
x = nd.date()
except:
pass
for fmt in fmts2:
try:
x = str(x)
# x = str(x).replace("//0/", "/0")
# x = str(x).replace("//1/", "/1")
# x = str(x).replace("//2/", "/2")
x = str(x).replace(" 00:00:00", "")
x = str(x).replace("0/0/", "1/1/")
x = str(x).replace("/0/", "/01/")
x = str(x).replace("/2/", "/02/")
date_object = dt.datetime.strptime(x.strip(), fmt).date()
new_date.append((date_object))
break
except:
pass
if len(new_date) != idx:
pass
elif "29/02" in x or "29-02" in x:
new_date.append((x))
else:
# x = "None"
new_date.append(("")) #new_date.append((x))
match col:
case "Issue Date":
isd = isd.append(chunk.iloc[[idx]])
case "Inception Date":
ind = ind.append(chunk.iloc[[idx]])
case "Expiry Date":
exd = exd.append(chunk.iloc[[idx]])
case "Policy Status Date":
psd = psd.append(chunk.iloc[[idx]])
case "Vehicle Issue Date":
visd = visd.append(chunk.iloc[[idx]])
case "Vehicle Inception Date":
vind = vind.append(chunk.iloc[[idx]])
case "Vehicle Expiry Date":
vexd = vexd.append(chunk.iloc[[idx]])
case "Istemarah Exp.":
ise = ise.append(chunk.iloc[[idx]])
case "Main Driver DOB":
mdd = mdd.append(chunk.iloc[[idx]])
case "Additional Driver DOB":
add = add.append(chunk.iloc[[idx]])
# if col == "Issue Date":
# isd = isd.append(chunk.iloc[[idx]])
# if col == "Inception Date":
# ind = ind.append(chunk.iloc[[idx]])
# if col == "Expiry Date":
# exd = exd.append(chunk.iloc[[idx]])
# if col == "Policy Status Date":
# psd = psd.append(chunk.iloc[[idx]])
# if col == "Vehicle Issue Date":
# visd = visd.append(chunk.iloc[[idx]])
# if col == "Vehicle Inception Date":
# vind = vind.append(chunk.iloc[[idx]])
# if col == "Vehicle Expiry Date":
# vexd = vexd.append(chunk.iloc[[idx]])
# if col == "Istemarah Exp.":
# ise = ise.append(chunk.iloc[[idx]])
# # if col == "Insured Date of Birth":
# # idb = idb.append(chunk.iloc[[idx]])
# if col == "Main Driver DOB":
# mdd = mdd.append(chunk.iloc[[idx]])
# if col == "Additional Driver DOB":
# add = add.append(chunk.iloc[[idx]])
chunk[col] = j = ['{}'.format(t) for idx, t in enumerate(new_date)]
# chunk[col] = pd.to_datetime(chunk[col])
print ("Completed", col)
print ('we have completed ', cx, 'chunk\n')
chunk.to_csv('Tricast Policy Data.csv', mode='a', index =False, header = header_flag)
header_flag = False
print(dt.datetime.now())
if len(isd) != 0:
isd.to_csv("Issuedate.csv")
if len(ind) != 0:
ind.to_csv("Inceptiondatecsv")
if len(exd) != 0:
exd.to_csv("Expirydate.csv")
if len(psd) != 0:
psd.to_csv("policystatedate.csv")
if len(visd) != 0:
visd.to_csv("vehicleissuedate.csv")
if len(vind) != 0:
vind.to_csv("vehicleinceptiondate.csv")
if len(vexd) != 0:
vexd.to_csv("vehicleexpirydate.csv")
if len(sd) != 0:
sd.to_csv("statusdate.csv")
if len(ise) != 0:
ise.to_csv("istemarhexpiry.csv")
if len(idb) != 0:
idb.to_csv("insureddateofbirth.csv")
if len(mdd) != 0:
mdd.to_csv("maindriverdob.csv")
if len(add) != 0:
add.to_csv("adddriverdob.csv")
###############################################################################
Edit: this is the whole code.
My supervisor told me concurrency can be applied to the last part where the data is being loaded to the csv files.

Same Python code, same Data, outcomes different if Data imported or not?

So I have a Python code that first aggregates and standardizes Data into a file I called "tripFile". Then the code tries to identify the differences between this most recent tripFile and a previous one.
From the first part of the code, if I export the tripFile, and import it again for the second part of the code, it takes around 5 minutes to run and says it is looping over a bit more than 4,000 objects.
newTripFile = pd.read_csv(PATH + today + ' Trip File v6.csv')
However, if I do not export & re-import the Data (just keeping it from the first part of the code), it takes a bit less than 24 hours (!!) and says it is looping over a bit more than 951,691 objects.
newTripFile = tripFile
My Data is a dataframe, and checked the shape of it, it is identical to the file I export.
Any idea what can be causing that ???
Here is the second part of my code:
oldTripFile = pd.read_excel(PATH + OLDTRIPFILE)
oldTripFile.drop(['id'], axis = 1, inplace = True)
oldTripFile['status'] = 'old'
# New version of trip file
newTripFile = pd.read_csv(PATH + today + ' Trip File v6.csv')
newTripFile.drop(['id'], axis = 1, inplace = True)
newTripFile['status'] = 'new'
db_trips = pd.concat([oldTripFile, newTripFile]) #concatenation of the two dataframes
db_trips = db_trips.reset_index(drop = True)
db_trips.drop_duplicates(keep = False, subset = [column for column in db_trips.columns[:-1] ], inplace = True)
db_trips = db_trips.reset_index(drop = True)
db_trips.head()
update_details = []
# Get the duplicates : only consider ['fromCode', 'toCode', 'mode'] for identifying duplicates
# Create a dataframe that contains only the trips that was deleted and was recently added
db_trips_delete_new = db_trips.drop_duplicates(keep = False, subset = ['fromCode', 'toCode', 'mode'])
db_trips_delete_new = db_trips_delete_new.reset_index(drop = True)
# New trips
new_trips = db_trips_delete_new[db_trips_delete_new['status'] == 'new'].values.tolist()
for trip in new_trips:
trip.append('new trip added')
update_details = update_details + new_trips
# Deleted trips
old_trips = db_trips_delete_new[db_trips_delete_new['status'] == 'old'].values.tolist()
for trip in old_trips:
trip.append('trip deleted')
update_details = update_details + old_trips
db_trips_delete_new.head()
# Updated trips
# Ocean: no need to check the transit time column
sea_trips = db_trips.loc[db_trips['mode'].isin(['sea', 'cfs'])]
sea_trips = sea_trips.reset_index(drop = True)
list_trips_sea_update = sea_trips[sea_trips.duplicated(subset = ['fromCode', 'toCode', 'mode'], keep = False)].values.tolist()
if len(list_trips_sea_update) != 0:
for i in tqdm(range(0, len(list_trips_sea_update) - 1)):
for j in range(i + 1, len(list_trips_sea_update)):
if list_trips_sea_update[i][2] == list_trips_sea_update[j][2] and list_trips_sea_update[i][9] == list_trips_sea_update[j][9] and list_trips_sea_update[i][14] == list_trips_sea_update[j][14]:
update_comment = ''
# Check display from / to
if list_trips_sea_update[i][5] != list_trips_sea_update[j][5]:
update_comment = update_comment + 'fromDisplayLocation was updated.'
if list_trips_sea_update[i][12] != list_trips_sea_update[j][12]:
update_comment = update_comment + 'toDisplayLocation was updated.'
# Get the updated trip (the row with status new)
if list_trips_sea_update[i][17] == 'new' and list_trips_sea_update[j][17] != 'new' :
list_trips_sea_update[i].append(update_comment)
update_details = update_details + [list_trips_sea_update[i]]
else:
if list_trips_sea_update[j][17] == 'new' and list_trips_sea_update[i][17] != 'new':
list_trips_sea_update[j].append(update_comment)
update_details = update_details + [list_trips_sea_update[j]]
else:
print('excel files are not organized')
# Ground: transit time column need to be checked
ground_trips = db_trips[~db_trips['mode'].isin(['sea', 'cfs'])]
ground_trips = ground_trips.reset_index(drop = True)
list_trips_ground_update = ground_trips[ground_trips.duplicated(subset = ['fromCode', 'toCode', 'mode'], keep = False)].values.tolist()
if len(list_trips_ground_update) != 0:
for i in tqdm(range(0, len(list_trips_ground_update) - 1)):
for j in range(i + 1, len(list_trips_ground_update)):
if list_trips_ground_update[i][2] == list_trips_ground_update[j][2] and list_trips_ground_update[i][9] == list_trips_ground_update[j][9] and list_trips_ground_update[i][14] == list_trips_ground_update[j][14]:
update_comment = ''
# Check display from / to
if list_trips_ground_update[i][5] != list_trips_ground_update[j][5]:
update_comment = update_comment + 'fromDisplayLocation was updated.'
if list_trips_ground_update[i][12] != list_trips_ground_update[j][12]:
update_comment = update_comment + 'toDisplayLocation was updated.'
# Check transit time
if list_trips_ground_update[i][15] != list_trips_ground_update[j][15]:
update_comment = update_comment + 'transit time was updated.'
# Get the updated trip (the row with status new)
if list_trips_ground_update[i][17] == 'new' and list_trips_ground_update[j][17] != 'new' :
list_trips_ground_update[i].append(update_comment)
update_details=update_details + [list_trips_ground_update[i]]
else:
if list_trips_ground_update[j][17] == 'new' and list_trips_ground_update[i][17] != 'new':
list_trips_ground_update[j].append(update_comment)
update_details = update_details + [list_trips_ground_update[j]]
else:
print('excel files are not organized')
And here an example of what my trip file looks like:
Any help is appreciated :)

If ever it can be useful to someone else, issue was coming from the type. When keeping my tripFile in memory, one of my column was "10.0" for example, whereas when imported this column was "10".
As I'm comparing with another imported tripFile, if both files are imported the column in both files are of same type, but if one of the files is kept in memory the column is of different type in both files and considered as updated. As such takes much longer when kept in memory as every row is considered updated.

How do I update a value in a dataframe in a loop?

I am trying to update a rating row by row. I have one dataframe of players, that all start with the same rating. For each match, I want the rating to change. Another dataframe contains results of each match.
import pandas as pd
gamesdata = [['paul','tom'],['paul','lisa'],['tom','paul'],['lisa','tom'],['paul','lisa'],['lisa','tom'],['paul','tom']]
games = pd.DataFrame(gamesdata, columns = ['Winner', 'Looser'])
playersdata= ['lisa','paul','tom']
players = pd.DataFrame(playersdata, columns = ['Name'])
mean_elo = 1000
elo_width = 400
k_factor = 64
players['elo'] = mean_elo
def update_elo(winner_elo, loser_elo):
expected_win = expected_result(winner_elo, loser_elo)
change_in_elo = k_factor * (1-expected_win)
winner_elo += change_in_elo
loser_elo -= change_in_elo
return winner_elo, loser_elo
def expected_result(elo_a, elo_b):
expect_a = 1.0/(1+10**((elo_b - elo_a)/elo_width))
return expect_a
for index, row in games.iterrows():
winnername = row['Winner']
losername = row['Looser']
web = players['elo'].loc[players['Name'] == winnername].values[0]
wIndex = players.loc[players['Name'] == winnername]
#I want to return just the index, so I can update the value
print(wIndex)
leb = players['elo'].loc[players['Name'] == losername].values[0]
print('Winner Elo before: ' + str(web))
winner_elo, looser_elo = update_elo(web, leb)
print('Winner Elo after: ' + str(winner_elo))
#here I want to update value
#players.at[wIndex,'elo']=winner_elo
I am trying to update the value in the players table using
players.at[wIndex,'elo']=winner_elo
but i struggle to get the index with this code:
wIndex = players.loc[players['Name'] == winnername]

Found a sollution:
wIndex = players.loc[players['Name'] == winnername].index.values
Can't believe i missed that