I was able to access my csv input main page to check for fraud using machine learning. Then I tried to implement a login authentication which is working. After I attempt to login, the screen stays on the login and doesn’t go to the main page. I am trying to fix it but am having no luck. Please help!
import streamlit as st
import streamlit_authenticator as stauth
import pandas as pd
import numpy as np
import random
import matplotlib.pyplot as plt
import seaborn as sns
from faker import Faker
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score, classification_report
fake = Faker()
num_transactions = 100
data =
for _ in range(num_transactions):
transaction = {
“transaction_id”: fake.uuid4(),
“user_id”: fake.random_int(min=1000, max=2500),
“amount”: round(random.uniform(10, 5000), 2),
“transaction_type”: random.choice([“Online Transaction”, “ATM Transaction”, “Bank Transaction”, “Bill Payment”]),
“timestamp”: fake.date_time(),
“location”: fake.city(),
“account_balance”: round(random.uniform(100, 20000), 2),
“fraudulent”: random.choice([0, 1])
}
data.append(transaction)
df = pd.DataFrame(data)
df[“timestamp”] = pd.to_datetime(df[“timestamp”])
df[“year”] = df[“timestamp”].dt.year
df[“month”] = df[“timestamp”].dt.month
df[“day”] = df[“timestamp”].dt.day
df[“hour”] = df[“timestamp”].dt.hour
df[“minute”] = df[“timestamp”].dt.minute
df[“second”] = df[“timestamp”].dt.second
df[“day_of_week”] = df[“timestamp”].dt.weekday
df[“is_weekend”] = df[“day_of_week”].apply(lambda x: 1 if x >= 5 else 0)
df.drop(columns=[“timestamp”], inplace=True)
df.to_csv(“fake_transactions.csv”, index=False)
hasher = stauth.Hasher()
hashed_passwords = [hasher.hash(“password123”), hasher.hash(“userpass”)]
config = {
‘credentials’: {
‘usernames’: {
‘admin’: {
‘email’: ‘admin@example.com’,
‘name’: ‘Admin’,
‘password’: hashed_passwords[0]
},
‘user’: {
‘email’: ‘user@example.com’,
‘name’: ‘User’,
‘password’: hashed_passwords[1]
}
}
},
‘cookie’: {
‘expiry_days’: 30,
‘key’: ‘random_secret_key’,
‘name’: ‘auth_cookie’
}
}
authenticator = stauth.Authenticate(
credentials=config[‘credentials’],
cookie_name=config[‘cookie’][‘name’],
key=config[‘cookie’][‘key’],
cookie_expiry_days=config[‘cookie’][‘expiry_days’]
)
def rerun(data=None):
“”“Forces Streamlit to refresh after login.”“”
st.rerun()
def login():
“”“Login Screen”“”
st.title(“Login to Your Account”)
st.write(“Please enter your username and password.”)
authentication_status = authenticator.login(callback=rerun)
if authentication_status:
st.session_state["page"] = "main"
st.session_state["username"] = authenticator.username
st.experimental_rerun()
elif authentication_status is False:
st.error("Incorrect username or password!")
elif authentication_status is None:
st.warning("Please enter your credentials.")
def main():
“”“Main Screen after Login”“”
st.sidebar.title(“Menu”)
st.sidebar.write(f"Welcome, {st.session_state[‘username’]}!")
authenticator.logout(“Logout”, “sidebar”)
st.title("Upload Your CSV File for Analysis")
uploaded_file = st.file_uploader("Choose a CSV file", type=["csv"])
if uploaded_file:
df = pd.read_csv(uploaded_file)
st.write("### Preview of Uploaded Data:")
st.write(df.head())
if "fraudulent" in df.columns:
st.write("### Processing Fraud Detection...")
if "timestamp" in df.columns:
df["timestamp"] = pd.to_datetime(df["timestamp"])
df["year"] = df["timestamp"].dt.year
df["month"] = df["timestamp"].dt.month
df["day"] = df["timestamp"].dt.day
df["hour"] = df["timestamp"].dt.hour
df["minute"] = df["timestamp"].dt.minute
df["second"] = df["timestamp"].dt.second
df["day_of_week"] = df["timestamp"].dt.weekday
df["is_weekend"] = df["day_of_week"].apply(lambda x: 1 if x >= 5 else 0)
df.drop(columns=["timestamp"], inplace=True)
feature_columns = ["amount", "account_balance", "year", "month", "day", "hour", "minute", "second", "day_of_week", "is_weekend"]
if "transaction_type" in df.columns:
feature_columns.append("transaction_type")
if all(col in df.columns for col in feature_columns):
X = df[feature_columns].copy()
if "transaction_type" in X.columns:
X = pd.get_dummies(X, columns=["transaction_type"], drop_first=True)
y = df["fraudulent"]
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)
model = RandomForestClassifier(n_estimators=100, random_state=42)
model.fit(X_train, y_train)
y_pred = model.predict(X_test)
accuracy = accuracy_score(y_test, y_pred)
classification_rep = classification_report(y_test, y_pred)
st.write(f"### Model Training Completed! Accuracy: **{accuracy:.2f}**")
st.text("### Classification Report:")
st.text(classification_rep)
else:
missing_columns = [col for col in feature_columns if col not in df.columns]
st.error(f"⚠Missing columns: {missing_columns}. Please upload a valid dataset.")
else:
st.warning("Please upload a CSV file to proceed.")
if “page” not in st.session_state:
st.session_state[“page”] = “login”
if st.session_state[“page”] == “login”:
login()
elif st.session_state[“page”] == “main”:
main()
Attached are before and after logging in.
