import streamlit as st
import anndata as ad
import pandas as pd
from pathlib import Path
import io

# Page config
st.set_page_config(page_title="AnnData Explorer", layout="wide")

st.title("AnnData Explorer – X, obs, var")

# Sidebar: file upload
uploaded = st.sidebar.file_uploader("Upload .h5ad", type=["h5ad"])

@st.cache_data
def load_adata(path_or_bytes):
    if isinstance(path_or_bytes, (str, Path)):
        return ad.read_h5ad(path_or_bytes)
    # UploadedFile
    return ad.read_h5ad(io.BytesIO(path_or_bytes.read()))

if uploaded is None:
    st.info("Please upload an .h5ad file from the sidebar.")
    st.stop()

adata = load_adata(uploaded)

# Sidebar: dimension info
st.sidebar.write("### Dataset info")
st.sidebar.write(f"Cells: {adata.n_obs}")
st.sidebar.write(f"Features: {adata.n_vars}")

# Main area: three tables
tab1, tab2, tab3 = st.tabs(["X", "obs", "var"])

with tab1:
    st.subheader("AnnData.X")
    st.dataframe(
        pd.DataFrame(
            adata.X.todense() if hasattr(adata.X, "todense") else adata.X,
            index=adata.obs_names,
            columns=adata.var_names,
        ),
        use_container_width=True,
    )

with tab2:
    st.subheader("AnnData.obs")
    st.dataframe(adata.obs, use_container_width=True)

with tab3:
    st.subheader("AnnData.var")
    st.dataframe(adata.var, use_container_width=True)