73 lines
2.4 KiB
Python
73 lines
2.4 KiB
Python
#!/usr/bin/env python3
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# -*- coding: UTF-8 -*-
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import pandas as pd
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import pyzh
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zh = pyzh.zh()
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con = pyzh.con
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sch = 'zones_humides'
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lst_site_old = ['38RD0146','38RD0147']
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lst_site_new = ['38RD0164','38RD0165']
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df = zh.get_habitat(id_site=lst_site_old)
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geomsite = zh.get_sitesGeom(id_site=lst_site_new)
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aut = pyzh.pers.get_auteur()
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tab = 'r_site_habitat'
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rtab_aut = 'r_rsitehab_auteur'
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id_rsiteaut = 'id_sitehab'
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date_champ = 'date_habit'
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nom_champ = 'code_cb'
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id_champ = 'id_cb'
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# delim = zh._get_param(param_table='param_fct_eco_socio_patri',type_table='type_param_fct')
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df.drop(
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columns=['id','valid', 'date_geom', 'auteur_geom', 'desc_param','type','lb_hab_fr'],
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inplace=True,
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errors='ignore')
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for i, s in enumerate(lst_site_new):
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df.loc[df.id_site==lst_site_old[i], 'id_site'] = s
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df.loc[df.id_site==s, ['id_geom_site']] = geomsite.loc[geomsite.id_site==s,'id'].values[0].astype(str)
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df['id_geom_site'] = df.id_geom_site.astype(int)
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df[id_champ] = df[nom_champ]
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# df[id_champ] = df[id_champ].replace(delim.nom.tolist(),delim.id.tolist())
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df['date'] = df[date_champ]
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df.drop(columns=['id_site',nom_champ,date_champ], inplace=True)
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lst_idgeom = df.id_geom_site.unique().astype(str)
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# check si data in bdd
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sql = 'select exists(select * from {sch}.{tab} where id_geom_site in ({lst_id}));'.format(
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sch=sch, tab=tab, lst_id=','.join(lst_idgeom)
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)
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res = pd.read_sql(sql,con)
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if res.exists[0]:
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# delete if exist
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sql = 'delete from {sch}.{tab} where id_geom_site in ({lst_id});'.format(
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sch=sch, tab=tab, lst_id=','.join(lst_idgeom)
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)
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pd.read_sql(sql,con)
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# insert new line in bdd
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col = df.columns[~df.columns.str.contains('auteur')]
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colaut = df.columns[df.columns.str.contains('auteur')]
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df[col].to_sql(
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tab, con, schema=sch,
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if_exists='append',index=False,method='multi'
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)
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# Récupération des nouveaux ids insérés
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sql = 'select * from {sch}.{tab} where id_geom_site in ({lst_id});'.format(
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sch=sch, tab=tab, lst_id=','.join(lst_idgeom)
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)
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res = pd.read_sql(sql,con)
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df = df.merge(res, how='left', on=[*col])
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ins_aut = df[['id',*colaut]].copy()
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aut['nom_prenom'] = aut.nom + ' ' + aut.prenom
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aut.loc[aut.nom_prenom.isna(), 'nom_prenom'] = aut.loc[aut.nom_prenom.isna(), 'nom']
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ins_aut[colaut] = ins_aut[colaut].replace(aut.nom_prenom.tolist(), aut.id.tolist())
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ins_aut.columns = [id_rsiteaut, 'id_auteur']
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ins_aut.to_sql(
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rtab_aut, con, schema=sch,
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if_exists='append',index=False,method='multi') |