I made a login page with navigation panel in sidebar. Below is the code:
import streamlit as st
from streamlit_option_menu import option_menu
import login, signup, forgot_us, forgot_pass
# Set page configuration
st.set_page_config(page_title="Stock Trend App", page_icon="💹")
class MultiApp:
def __init__(self):
self.apps = []
def add_app(self, title, func):
self.apps.append({
"title": title,
"function": func
})
def run():
# Navigation sidebar
with st.sidebar:
app = option_menu(
menu_title='Navigation',
options=['Sign-In','Sign-Up','Forgot Username','Forgot Password'],
icons=['person-circle','person-add','trophy-fill','chat-fill','info-circle-fill'],
menu_icon='list',
default_index=1,
styles={
"container": {"padding": "5!important","background-color":'black'},
"icon": {"color": "white", "font-size": "23px"},
"nav-link": {"color":"white","font-size": "20px", "text-align": "left", "margin":"0px", "--hover-color": "blue"},
"nav-link-selected": {"background-color": "#02ab21"},}
)
if app == "Sign-In":
login.app()
if app == "Sign-Up":
signup.app()
if app == "Forgot Username":
forgot_us.app()
if app == "Forgot Password":
forgot_pass.app()
run()
Below is the login.py script:
login.py
import streamlit as st
import streamlit_authenticator as stauth
import yaml
from yaml.loader import SafeLoader
import app
def app():
with open('config.yaml') as file:
config = yaml.load(file, Loader=SafeLoader)
# Initialize Streamlit authenticator
authenticator = stauth.Authenticate(
config['credentials'],
config['cookie']['name'],
config['cookie']['key'],
config['cookie']['expiry_days'],
config['pre-authorized']
)
# Attempt to authenticate the user
#name, authentication_status, username = authenticator.login('Login', 'main')
authenticator.login()
if st.session_state["authentication_status"]:
authenticator.logout()
st.write(f'Welcome *{st.session_state["name"]}*')
# Execute the app.py
import app
app.main()
elif st.session_state["authentication_status"] is False:
st.error('Username/password is incorrect')
elif st.session_state["authentication_status"] is None:
st.warning('Please enter your username and password')
Below is the app.py script
app.py
def main():
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from keras.models import load_model
import streamlit as st
import datetime
import yfinance as yf
import pickle
import plotly.express as px
import plotly.graph_objs as go
from neuralprophet import NeuralProphet
# Display a message with the bot icon
st.title("Welcome to Stock Trend App 💹")
st.write("This is a simple Streamlit app to forecast the stock close price.")
tickerSymbol = st.sidebar.text_input('Enter Stock Ticker')
# Display a date input widget
start_date = st.sidebar.date_input("Select Start Date", min_value=datetime.date(2000, 1, 1), max_value=datetime.date.today(), value=datetime.date(2012, 1, 1))
end_date = st.sidebar.date_input("Select End Date", min_value=datetime.date(2000, 1, 1), max_value=datetime.date.today(), value=datetime.date.today())
# Get number of days to forecast
future_days = st.sidebar.number_input("Enter Days to Forecast", min_value=1, value=100, step=1)
button = st.sidebar.button("Submit")
if button:
if not tickerSymbol:
st.write("Please enter a valid Stock Ticker")
elif start_date > end_date:
st.write("Please enter valid dates. Start Date cannot exceed the End Date.")
else:
# Get data on this ticker
tickerData = yf.Ticker(tickerSymbol)
# Get the historical prices for this ticker
df = tickerData.history(period='1d', start=start_date, end=end_date)
df = df.reset_index()
# Get company information
company_name = tickerData.info['longName']
st.sidebar.write(f"Company Name: {company_name}")
# describing data
st.subheader(f'Data from {start_date} to {end_date}')
st.write(df.describe())
## Visualization
st.subheader(f'{tickerSymbol.upper()} Close Price vs Time')
st.line_chart(df, x="Date", y="Close", color="#0514C0")
stock = df[['Date', 'Close']]
# the NeuralProphet model expects the input DataFrame to have two columns: 'ds' (datetime) and 'y' (target variable).
stock.columns = ['ds', 'y']
# Train the model
NP_model = NeuralProphet()
NP_model.fit(stock)
# Evaluate the model
future = NP_model.make_future_dataframe(stock, periods=future_days)
prediction = NP_model.predict(stock)
forecast = NP_model.predict(future)
# Plot the future forecast
st.subheader(f'{future_days} Days Forecasting')
fig3 = px.line(forecast, x="ds", y="yhat1", color_discrete_sequence=['red'])
fig3.update_layout(xaxis_title='Day', yaxis_title='Close Price')
# Plot!
st.plotly_chart(fig3, use_container_width=True)
st.subheader("Components of Forecast")
fig_components = NP_model.plot_components(forecast)
st.plotly_chart(fig_components)
# Calculate the trend component of the forecast
trend = forecast['trend'].values
# Calculate the change in trend
trend_change = np.diff(trend)
# Check if the trend is positive, negative, or flat
if all(change > 0 for change in trend_change):
trend_status = "Sold"
elif all(change < 0 for change in trend_change):
trend_status = "Buy"
else:
trend_status = "Hold"
# Display a bot icon and the trend status to the right side of the icon
st.write(f"<div style='display: flex; align-items: center;'>"
f"<p style='font-size: 48px;'>🤖</p>"
f"<div style='margin-left: 20px; font-size: 24px; font-weight: bold;'>{trend_status}</div>"
f"</div>", unsafe_allow_html=True)
I want that when the login is successful, the Navigation sidebar should be disable. After successfully signed in, the web page should look like this:
But in my case, it look like this:
