This Project is public to be shown in my portfolio.
Feel free to be inspired by the script.
If you try to execute the script it will not work, since the script was written for a company and I had to censor/replace confidential components like SQL queries and Server information.
Home side is nothing but an empty screen
"Listen" is a process that generates a list for each employee of the selected Team, who has tasks until the selected date. It saves the file in the employees own folder.
If selected, an E-Mail is generated with calculated dates for all employees with task lists.
"Listen f/ MA" generates task lists for all selected employees.
First there needs a date and a team to be selected. With this information will be a employee list provided from which can be selected.
If selected, it also generates an E-Mail and saves the file in the employees own folder.
"Listen f/ Stakeholder" generates task lists for specific Stakeholder(customer), not my employee.
First needs a date to be selected. With this information will be a stakeholder list provided from which can be selected.
The file will be saved in the default folder for stakeholders.
This windows shows the historical documentation of previously created lists.
In this window the default E-Mail can be managed with HTML.
There are three containers which can be used for specific calculated dates.
In "Einstellung" can the default settings be changed.
First there can be added E-Mail adresses which will be in CC when creating a mail.
Several addresses can be added, when seperated with ;
The number indicates the default calculation for how many weeks are the tasks listed.
The Three folder selections manage the place where the employee folders are,
where a list is saved if no employee folder exists and where to save the stakeholder lists.
The idea of the licence is that anyone can use this code and further develop for privat use. Limitations apply to Liability, Warranty, etc. see Licence for detailed information
This was scripted in Python 3.12.2
PySide6
datetime
openpyxl
pyodbc
json
locale
pandas
os
csv