#!/usr/bin/env python3
# -*- coding: UTF-8 -*-

from sqlalchemy import create_engine
from sqlalchemy.engine import URL
from datetime import datetime as dt
import pandas as pd
import pycen



# Parametres bdd
user = 'cgeier'
pwd  = 'adm1n*bdCen'
adr    = '91.134.194.221'
port   = '5432'
base   = 'sicen2'
url = URL.create('postgresql+psycopg2', 
  username=user,
  password=pwd,
  host=adr,
  database=base,
)
con = create_engine(url)

sch = 'saisie'
tab = 'saisie_observation'
ids = 'id_obs'
col_updt = 'phenologie'

sql = """
SELECT 
    {ids},
    {col}
FROM {sch}.{tab}
WHERE {col} = 'Inderterminé'
""".format(sch=sch,tab=tab,ids=ids,col=col_updt)
df = pd.read_sql_query(sql,con)
df[col_updt] = 'Indéterminé'
pycen.update_to_sql(df,con,tab,sch,ids,geom_col=None)


tab_suivi = 'suivi_saisie_observation'
ids_suivi = ['operation','date_operation','id_obs']
col_updtSuivi = 'utilisateur'
date = dt.today().date().isoformat()
sql = """
SELECT 
    {ids},
    {col}
FROM {sch}.{tab}
WHERE {col} = 'inconnu'
    AND date_operation > '{date}'
""".format(sch=sch,tab=tab_suivi,ids=','.join(ids_suivi),col=col_updtSuivi, date=date)
df = pd.read_sql_query(sql,con)
df[col_updtSuivi] = 'colas.geier@cen-isere.org'
pycen.update_to_sql(
    df,
    con,
    table_name=tab_suivi,
    schema_name=sch,
    key_name = ids_suivi,
    geom_col=None)