mattoofahad
adding mutiple tab for each module
d769745
raw
history blame
7.17 kB
import pandas as pd
import streamlit as st
from functions import Functions, StreamlitFunctions
from logs import logger
def calculate_salary_parameters():
logger.info("Calculating based on Salary parameters")
st.session_state.type_to_calculate = "salary_parameters"
def calculate_initial_salary_parameter():
logger.info("Calculating based on Desired Salary")
st.session_state.type_to_calculate = "desired_salary"
def calculate_tax_on_current_salary():
logger.info("Calculating Tax on Current Salary")
st.session_state.type_to_calculate = "tax_on_current_salary"
def calculate_tax_on_yearly_salary():
logger.info("Calculating Tax on Yearly Salary")
st.session_state.type_to_calculate = "tax_on_yearly_salary"
StreamlitFunctions.initialize_session_values()
StreamlitFunctions.print_tax_brackets()
StreamlitFunctions.reset_tax_brackets()
tab1, tab2, tab3, tab4 = st.tabs(
[
"Tax on Monthly Salary",
"Tax on Yearly Salary",
"Final Desired Net Salary",
"Desired Salary Calculation",
]
)
with tab1:
StreamlitFunctions.print_tax_on_current_salary()
StreamlitFunctions.reset_tax_on_current_salary()
st.button(
"Calculate Tax on Current Salary",
use_container_width=True,
on_click=calculate_tax_on_current_salary,
)
with tab2:
StreamlitFunctions.print_tax_on_yearly_salary()
StreamlitFunctions.reset_tax_on_yearly_salary()
st.button(
"Calculate Tax on Yearly Salary",
use_container_width=True,
on_click=calculate_tax_on_yearly_salary,
)
with tab3:
StreamlitFunctions.initial_salary_parameter()
StreamlitFunctions.reset_initial_salary_parameter()
st.button(
"Calculate Based on Desired Net Salary",
use_container_width=True,
on_click=calculate_initial_salary_parameter,
)
with tab4:
StreamlitFunctions.print_salary_parameters()
StreamlitFunctions.reset_salary_parameters()
st.button(
"Calculate Based on Salary Parameters",
use_container_width=True,
on_click=calculate_salary_parameters,
)
if st.session_state.type_to_calculate is not None:
if st.session_state.type_to_calculate == "tax_on_current_salary":
initial_desired_net = Functions.calculated_current_salary_after_tax(
st.session_state.tax_on_current_salary, st.session_state.tax_brackets
)
elif st.session_state.type_to_calculate == "tax_on_yearly_salary":
initial_desired_net = Functions.calculated_yearly_salary_after_tax(
st.session_state.tax_on_yearly_salary, st.session_state.tax_brackets
)
elif st.session_state.type_to_calculate == "desired_salary":
initial_desired_net = st.session_state.user_initial_desired_net
elif st.session_state.type_to_calculate == "salary_parameters":
initial_desired_net = Functions.calculated_initial_desired_net(
st.session_state.current_salary,
st.session_state.desired_increment_percentage,
st.session_state.daily_cost_of_travel,
st.session_state.physical_days_per_week,
)
result = Functions.calculate_additional_amount(
initial_desired_net, st.session_state.tax_brackets
)
# Display how initial_desired_net was determined
st.markdown("---")
if st.session_state.type_to_calculate == "tax_on_current_salary":
st.success(
"βœ… Calculation was done based on the selected value of 'Tax on Current Salary'"
)
summary_df = pd.DataFrame(
{
"Parameter": [
"Current Salary",
"Tax",
"Gross Salary",
],
"Value": [
f"PKR {result['final_net_salary']:,.2f}",
f"PKR {result['tax']:,.2f}",
f"PKR {result['gross_salary_needed']:,.2f}",
],
}
)
elif st.session_state.type_to_calculate == "tax_on_yearly_salary":
st.success(
"βœ… Calculation was done based on the selected value of 'Tax on Yearly Salary'"
)
result = {key: value * 12 for key, value in result.items()}
summary_df = pd.DataFrame(
{
"Parameter": [
"Yearly Salary",
"Yearly Tax",
"Gross Yearly Salary",
],
"Value": [
f"PKR {result['final_net_salary']:,.2f}",
f"PKR {result['tax']:,.2f}",
f"PKR {result['gross_salary_needed']:,.2f}",
],
}
)
elif st.session_state.type_to_calculate == "desired_salary":
st.success(
"βœ… Calculation was done based on the selected value of 'Final Desired Net Salary'"
)
summary_df = pd.DataFrame(
{
"Parameter": [
"Final Net Salary",
"Tax",
"Gross Salary",
],
"Value": [
f"PKR {result['final_net_salary']:,.2f}",
f"PKR {result['tax']:,.2f}",
f"PKR {result['gross_salary_needed']:,.2f}",
],
}
)
elif st.session_state.type_to_calculate == "salary_parameters":
st.success(
"βœ… Calculation was done based on the selected values of 'Salary Parameters'"
)
summary_df = pd.DataFrame(
{
"Parameter": [
"Current Salary",
"Desired Increment",
"Daily Travel Cost",
"On-Site Days/Week",
"Gross Salary",
"Tax",
"Final Net Salary",
],
"Value": [
f"PKR {st.session_state.current_salary:,.2f}",
f"{st.session_state.desired_increment_percentage:.2%}",
f"PKR {st.session_state.daily_cost_of_travel:,.2f}",
f"{st.session_state.physical_days_per_week}",
f"PKR {result['gross_salary_needed']:,.2f}",
f"PKR {result['tax']:,.2f}",
f"PKR {result['final_net_salary']:,.2f}",
],
}
)
st.header("Salary Calculation Results")
col1, col2 = st.columns(2)
with col1:
# custom_metric("Initial Desired Net Salary", result['initial_desired_net'])
StreamlitFunctions.custom_metric("Final Net Salary", result["final_net_salary"])
StreamlitFunctions.custom_metric("Tax", result["tax"])
with col2:
# custom_metric("Additional Amount Needed", result['additional_amount'])
StreamlitFunctions.custom_metric(
"Gross Salary Needed", result["gross_salary_needed"]
)
# Display a summary of the calculation
st.subheader("Calculation Summary")
st.data_editor(summary_df, use_container_width=True, hide_index=True)
st.session_state.type_to_calculate = None