from pycen import con_gn
import numpy as np
import pandas as pd
import os

def get_status(lst):
    sql = """
        SELECT 
            t.cd_nom,
            t.cd_ref,
            t.regne,
            t.phylum,
            t.classe,
            t.ordre,
            t.famille,
            t.group1_inpn,
            t.group2_inpn,
            t.nom_vern,
            t.nom_complet,
            t.nom_valide,
            t.lb_nom,
            --s.*
            s.rq_statut,
            s.code_statut,
            s.cd_type_statut,
            s.label_statut,
            s.full_citation,
            s.doc_url
        FROM taxonomie.taxref t
        JOIN taxonomie.v_bdc_status s USING (cd_nom)
        WHERE t.cd_nom IN {cd_nom}
    ;""".format(cd_nom = tuple(lst))
    return pd.read_sql_query(sql,con_gn)

dict_dep = {
    '38':'Isère',
    '42':'Loire',
    '07':'Ardèche',
    '26':'Drôme',
}
    

if __name__ == "__main__":

    PATH = '/media/colas/SRV/FICHIERS/SITES/SITES GERES/ROLA_ROLANDE-MAUPAS/ROLA_PPI/ROLA_2025-2034_PG/donneesnaturalistes'
    file = 'liste sp_ROLA.xlsx'
    sheet = 'liste sp'

    # Liste des CD_NOM en entrée
    cd_col = 'cd_ref'
    taxlist = pd.read_excel(os.path.join(PATH,file),sheet,usecols=[cd_col],header=0)
    tab_sp = pd.read_excel(os.path.join(PATH,file),sheet,index_col=cd_col)
    df = get_status(taxlist[cd_col].astype(str))

    for c in ['cd_ref','cd_nom','lb_nom']:
        if c in tab_sp.columns:
        # if 'cd_nom' not in df.columns and c == 'cd_ref': continue
            tab_sp.drop(c,axis=1,inplace=True)

    # df.to_csv('/media/colas/SRV/FICHIERS/TRANSFERTS-EQUIPE/LC/BOCA_CD_NOM_STATUS.csv')

    pivot = pd.pivot_table(
        df,
        values='code_statut',
        index=['cd_nom', 'cd_ref','lb_nom'#,'niveau_admin','lb_adm_tr'
        ],
        columns=['cd_type_statut'],
        aggfunc=list,fill_value=None)

    for c in pivot.columns:
        pivot[c] = [x[0] if x is not np.NaN and len(x)==1 else x for x in pivot[c]]
    if 'DH' in pivot.columns:
        pivot['DH'] = [','.join(x) if (x is not np.NaN) and (len(x)==2) else x for x in pivot['DH']]
        pivot.DH.replace({'CDH':''},regex=True,inplace=True)

    pivot = tab_sp.merge(pivot,on=[cd_col],how='left')


    pivlib = pd.pivot_table(
        df,
        values='label_statut',
        index=['cd_nom', 'cd_ref','lb_nom'#,'niveau_admin','lb_adm_tr'
        ],
        columns=['cd_type_statut'],
        aggfunc=list,fill_value=None)
    for c in pivlib.columns:
        pivlib[c] = [x[0] if x is not np.NaN and len(x)==1 else x for x in pivlib[c]]
    if 'DH' in pivot.columns:
        pivlib['DH'] = [','.join(x) if (x is not np.NaN) and (len(x)==2) else x for x in pivlib['DH']]
        pivlib.DH.replace({'CDH':''},regex=True,inplace=True)

    pivlib = tab_sp.merge(pivlib,on=[cd_col],how='left')

    print('INIT writer')
    NAME_OUT = os.path.join(PATH,sheet+'_status.xlsx')
    with pd.ExcelWriter(NAME_OUT) as writer:
        df.to_excel(
            writer,sheet_name='v_bdc_status',index=False
            )
        # writer.save()
        print('v_bdc_status OK !')
        pivot.to_excel(
            writer,sheet_name='pivot_table'
            )
        # writer.save()
        print('pivot_table OK !')
        pivlib.to_excel(
            writer,sheet_name='pivot_libel'
            )
        # writer.save()
        print('pivot_libel OK !')