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bilan_comptable
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import streamlit as st
import pandas as pd

st.title("📘 Grand Livre Comptable Test")

df = pd.read_csv("src/tcrg-rgat.csv")

# Renommer les colonnes utiles
df = df.rename(columns={
    "General-Ledger-Account-Code-Code-du-compte-du-grand-livre-général": "Compte_GL",
    "Subleger-Account-Identifier-Compte_du_GL_auxiliaire": "Compte_auxiliaire",
    "Journal-Voucher-Item-Amount-Montant-de-l'item-de-la-pièce-de-journal": "Montant",
    "Credit/Debit-Code-Code-Crédit/Débit": "Type",
    "Accounting-Effective-Date-Date-d'entrée-en-vigueur-comptable": "Date",
    "Journal-Voucher-Item-Identifier-Identificateur-de-l'item-de-la-pièce-de-journal": "N°_pièce"
})

df = df[df["Compte_GL"].notna()]
df["Débit"] = df.apply(lambda row: row["Montant"] if row["Type"] == "D" else 0, axis=1)
df["Crédit"] = df.apply(lambda row: row["Montant"] if row["Type"] == "C" else 0, axis=1)
df["Date"] = pd.to_datetime(df["Date"])
df = df.sort_values("Date")

st.subheader("🧾 Écritures comptables")
st.dataframe(df[["Date", "Compte_GL", "Débit", "Crédit", "Montant", "Type", "N°_pièce"]])

st.subheader("📊 Résumé du Grand Livre")
resume = df.groupby("Compte_GL").agg({
    "Débit": "sum",
    "Crédit": "sum",
    "Montant": "count"
}).rename(columns={"Montant": "Nombre_lignes"}).reset_index()
st.dataframe(resume)

# Export bouton
@st.cache_data
def convert_to_excel(df1, df2):
    from io import BytesIO
    output = BytesIO()
    with pd.ExcelWriter(output, engine='xlsxwriter') as writer:
        df1.to_excel(writer, index=False, sheet_name='Ecritures')
        df2.to_excel(writer, index=False, sheet_name='Résumé_GL')
    return output.getvalue()

excel_bytes = convert_to_excel(df, resume)
st.download_button(
    label="📥 Télécharger le fichier Excel",
    data=excel_bytes,
    file_name="grand_livre.xlsx",
    mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
)


# import altair as alt
# import numpy as np
# import pandas as pd
# import streamlit as st

# """
# # Welcome to Streamlit!

# Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
# If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
# forums](https://discuss.streamlit.io).

# In the meantime, below is an example of what you can do with just a few lines of code:
# """

# num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
# num_turns = st.slider("Number of turns in spiral", 1, 300, 31)

# indices = np.linspace(0, 1, num_points)
# theta = 2 * np.pi * num_turns * indices
# radius = indices

# x = radius * np.cos(theta)
# y = radius * np.sin(theta)

# df = pd.DataFrame({
#     "x": x,
#     "y": y,
#     "idx": indices,
#     "rand": np.random.randn(num_points),
# })

# st.altair_chart(alt.Chart(df, height=700, width=700)
#     .mark_point(filled=True)
#     .encode(
#         x=alt.X("x", axis=None),
#         y=alt.Y("y", axis=None),
#         color=alt.Color("idx", legend=None, scale=alt.Scale()),
#         size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
#     ))