personal-library-manager/p-l-m.py at main · kAmmarah/personal-library-manager · GitHub

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import streamlit as st
import pandas as pd
import base64

# App config
st.set_page_config(page_title="📚 Personal Library Manager", page_icon="📖", layout="wide")

# Background image function
def add_bg_image():
    with open("image.png", "rb") as image_file:
        encoded_string = base64.b64encode(image_file.read()).decode()
    st.markdown(
        f"""
        <style>
        .stApp {{
            background-image: url("data:image/png;base64,{encoded_string}");
            background-size: cover;
            background-position: center;
        }}
        </style>
        """,
        unsafe_allow_html=True
    )

add_bg_image()

# Title and header
st.title("📚 Personal Library Manager")
st.markdown("### This app created by Ammara 🎨✨")

# Initialize or load data
if "library_data" not in st.session_state:
    try:
        st.session_state.library_data = pd.read_csv("sample_books.csv")
    except:
        st.session_state.library_data = pd.DataFrame(columns=["📖 Title", "✍️ Author", "⭐ Rating", "📅 Year", "📚 Genre"])

# --- 🚀 Navigation Bar ---
menu = st.sidebar.radio("🔍 Go to", ["📖 View Library", "➕ Add Book", "🔎 Search Books", "📊 Library Statistics"])

# --- 📖 View Library ---
if menu == "📖 View Library":
    st.subheader("📚 My Library Collection")
    st.dataframe(st.session_state.library_data, use_container_width=True)

# --- ➕ Add Book ---
elif menu == "➕ Add Book":
    st.subheader("📘 Add a New Book to Your Library")
    title = st.text_input("📖 Book Title")
    author = st.text_input("✍️ Author Name")
    rating = st.slider("⭐ Rating", 1, 5, 3)
    year = st.number_input("📅 Publication Year", min_value=0, max_value=2025, step=1)
    genre = st.selectbox("📚 Genre", ["Fiction", "Non-Fiction", "Self-Help", "Science", "History", "Fantasy", "Business", "Philosophy", "Classic", "Programming"])

    if st.button("📚 Add Book"):
        new_book = pd.DataFrame([[title, author, rating, year, genre]],
                                columns=["📖 Title", "✍️ Author", "⭐ Rating", "📅 Year", "📚 Genre"])
        st.session_state.library_data = pd.concat([st.session_state.library_data, new_book], ignore_index=True)
        st.success("✅ Book added successfully!")

# --- 🔍 Search Books ---
elif menu == "🔎 Search Books":
    st.subheader("🔍 Search Books in Library")
    search_term = st.text_input("🔎 Enter book title or author")
    if search_term:
        results = st.session_state.library_data[
            st.session_state.library_data["📖 Title"].str.contains(search_term, case=False, na=False) |
            st.session_state.library_data["✍️ Author"].str.contains(search_term, case=False, na=False)
        ]
        st.dataframe(results, use_container_width=True)

# --- 📊 Library Statistics ---
elif menu == "📊 Library Statistics":
    st.subheader("📈 Library Statistics")

    if not st.session_state.library_data.empty:
        genre_count = st.session_state.library_data["📚 Genre"].value_counts()
        st.bar_chart(genre_count)

        avg_rating = st.session_state.library_data["⭐ Rating"].mean()
        st.markdown(f"**📊 Average Rating:** {avg_rating:.2f} ⭐")

        most_recent = st.session_state.library_data.sort_values(by="📅 Year", ascending=False).head(5)
        st.markdown("### 🕑 Most Recent Books")
        st.table(most_recent)
    else:
        st.warning("📭 No data available to show statistics.")

# --- Footer ---
st.markdown("---")
st.markdown("🎨 **Designed by Ammara** 💖")