Clean dépot
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#!/usr/bin/env python3
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# -*- coding: UTF-8 -*-
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def test_data(con,tab,col,status):
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sql = '''
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SELECT count({col}) FROM {sch}.{tab} WHERE {col} = '{status}'
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;'''.format(sch='taxonomie',tab=tab,col=col,status=status)
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with con.begin() as cnx:
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return cnx.execute(sql).one()[0]
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def test_cor_values(con,vals):
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sql = '''
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SELECT count(id_value_text) FROM {sch}.{tab} WHERE (id_value,id_text) = {vals}
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;'''.format(sch='taxonomie',tab='bdc_statut_cor_text_values',vals=vals)
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with con.begin() as cnx:
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return cnx.execute(sql).one()[0]
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def test_status_type(con,col,status):
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sql = '''
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SELECT count({col}) FROM {sch}.{tab} WHERE {col} = '{status}'
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;'''.format(sch='taxonomie',tab='bdc_statut_type',col=col,status=status)
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with con.begin() as cnx:
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return cnx.execute(sql).one()[0]
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def insert_status_alerte(con):
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"""
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Insert type de statut pour les alertes
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Si la valeur AL n'existe pas dans la table bdc_statut_type, on l'insert
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"""
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if test_data(con,'bdc_statut_type','cd_type_statut','AL') > 0:
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# if test_status_type(con,'cd_type_statut','AL') > 0:
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print('ALERTE STATUS ALREADY EXISTS')
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else:
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sql = '''
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INSERT INTO {sch}.{tab} (cd_type_statut,lb_type_statut,regroupement_type,thematique,type_value) VALUES
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('AL','Liste d''alerte départementale','Alerte','STATUTS','VALUE')
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;'''.format(sch='taxonomie',tab='bdc_statut_type')
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with con_gn.begin() as cnx:
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cnx.execute(sql)
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def insert_status_values(con):
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"""
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Inserts predefined status values into the 'bdc_statut_values' table if they do not already exist.
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This function iterates over a list of status values, checking whether each value already exists in the
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specified database table. If a value does not exist, it inserts the value into the table. Status values
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include a code and a label, which describe the extinction risk or conservation status of a taxonomic
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group at the departmental level.
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Args:
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con: A SQLAlchemy connection object to the database.
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Note:
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This function assumes the existence of a schema named 'taxonomie' and a table named
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'bdc_statut_values' in the database connected via 'con'. It also assumes the availability of a
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'con_gn' connection for executing the SQL commands.
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"""
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vals = [
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['RE','Disparue au niveau départemental'],
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['AS-1','Quasi menacée (localisées sans signe de déclin)'],
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['AS-2','Quasi menacée (répandues mais en déclin)'],
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['AS-3','Quasi menacée (répandues, déclin à confirmer)']
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]
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for val in vals:
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if test_data(con,'bdc_statut_values','label_statut',val[1]) > 0:
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print('ALERTE VALUE STATUS ALREADY EXISTS : ',val[1])
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else:
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sql = '''
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INSERT INTO {sch}.{tab} (code_statut,label_statut) VALUES
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('{val0}','{val1}')
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'''.format(sch='taxonomie',tab='bdc_statut_values',val0=val[0],val1=val[1])
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with con_gn.begin() as cnx:
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cnx.execute(sql)
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def get_text_id(con,cd_doc):
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sql = '''
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SELECT id_text FROM {sch}.{tab} WHERE cd_doc = '{cd_doc}'
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;'''.format(sch='taxonomie',tab='bdc_statut_text',cd_doc=cd_doc)
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with con.begin() as cnx:
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return cnx.execute(sql).one()[0]
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def get_area_id(con,area):
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sql = '''
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SELECT id_area FROM {sch}.{tab} WHERE area_name = '{area}'
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;'''.format(sch='ref_geo',tab='l_areas',area=area)
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with con.begin() as cnx:
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return cnx.execute(sql).one()[0]
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def get_values_id(con,col,terme):
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if isinstance(terme,int|str):
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terme = [terme]
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else:
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terme = list(terme)
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sql = '''
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SELECT id_value FROM {sch}.{tab} WHERE {col} IN {terme} AND label_statut <> 'Disparue au niveau régional'
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;'''.format(sch='taxonomie',tab='bdc_statut_values',col=col,terme=tuple(terme)).replace(',)',')')
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with con.begin() as cnx:
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return cnx.execute(sql).all()
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def insert_status_cor_text_area(con,id_doc):
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id_text = get_text_id(con,id_doc)
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id_area = get_area_id(con,'Isère')
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check_sql = '''
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SELECT count(id_text) FROM {sch}.{tab} WHERE (id_text,id_area) = ({id_text},{id_area})
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;'''.format(sch='taxonomie',tab='bdc_statut_cor_text_area',id_text=id_text,id_area=id_area)
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with con.begin() as cnx:
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if cnx.execute(check_sql).one()[0] == 0:
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sql = ('''
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INSERT INTO {sch}.{tab} (id_text,id_area) VALUES ({id_text},{id_area})
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;'''.format(sch='taxonomie',tab='bdc_statut_cor_text_area',id_text=id_text,id_area=id_area))
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cnx.execute(sql)
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def insert_status_cor_text_values(con,id_doc,values):
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insert_status_values(con)
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id_text = get_text_id(con,id_doc)
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id_vals = [x[0] for x in get_values_id(con,'code_statut',values)]
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zip_vals = tuple(zip(id_vals,[id_text]*len(id_vals)))
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cor_vals = [x for x in zip_vals if test_cor_values(con,x)==0]
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sql = ('''
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INSERT INTO {sch}.{tab} (id_value,id_text) VALUES {values}
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;'''
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.format(sch='taxonomie',tab='bdc_statut_cor_text_values',values=cor_vals)
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.replace(r'[','')
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.replace(r']',''))
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with con_gn.begin() as cnx:
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cnx.execute(sql)
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def get_id_status_cor_text_values(con,id_doc,values):
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id_text = get_text_id(con,id_doc)
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id_vals = [x[0] for x in get_values_id(con,'code_statut',values)]
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zip_vals = tuple(zip(id_vals,[id_text]*len(id_vals)))
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cor_vals = tuple(x for x in zip_vals if test_cor_values(con,x)>0)
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sql = ('''
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SELECT id_value_text FROM {sch}.{tab} WHERE (id_value,id_text) IN {cor_vals}
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;'''
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.format(sch='taxonomie',tab='bdc_statut_cor_text_values',cor_vals=cor_vals)
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.replace('),)','))'))
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with con.begin() as cnx:
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return cnx.execute(sql).all()
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def test_status_text(con,col,cd_doc):
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sql = '''
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SELECT count({col}) FROM {sch}.{tab} WHERE {col} = '{cd_doc}'
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;'''.format(sch='taxonomie',tab='bdc_statut_text',col=col,cd_doc=cd_doc)
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with con.begin() as cnx:
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return cnx.execute(sql).one()[0]
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def insert_statut_text(con,cd_doc,doc):
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if test_data(con,'bdc_statut_text','cd_doc',cd_doc['id_doc']) > 0:
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# if test_status_text(con,'cd_doc',cd_doc) > 0:
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print('ALERTE TEXT STATUS ALREADY EXISTS : ',doc)
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else:
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sql = '''
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INSERT INTO {sch}.{tab} (cd_type_statut,cd_doc,cd_sig,niveau_admin,lb_adm_tr,doc_url,enable) VALUES
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('AL',{cd_doc},'INSEED38','Département','Isère','{doc}',TRUE)
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;'''.format(sch='taxonomie',tab='bdc_statut_text',cd_doc=cd_doc['id_doc'],doc=doc)
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with con_gn.begin() as cnx:
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cnx.execute(sql)
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insert_status_cor_text_area(con,cd_doc['id_doc'])
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insert_status_cor_text_values(con,cd_doc['id_doc'],cd_doc['id_values'])
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def get_cd_ref(con,cd_nom):
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sql = '''
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SELECT cd_ref FROM {sch}.{tab} WHERE cd_nom = '{cd_nom}'
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;'''.format(sch='taxonomie',tab='taxref',cd_nom=cd_nom)
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with con.begin() as cnx:
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return cnx.execute(sql).one()[0]
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def get_max_idstatuttaxo(con):
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sql = '''
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SELECT max(id) FROM {sch}.{tab}
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;'''.format(sch='taxonomie',tab='bdc_statut_taxons')
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with con.begin() as cnx:
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return cnx.execute(sql).one()[0]
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def insert_status_taxo(con,cd_nom,cd_doc,status):
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id_statut_cor = get_id_status_cor_text_values(con,cd_doc,status)[0][0]
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cd_ref = get_cd_ref(con,cd_nom)
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id_statut_taxo = get_max_idstatuttaxo(con) + 1
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sql_check = '''
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SELECT count(id) FROM {sch}.{tab}
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WHERE id_value_text = '{id_statut_cor}' AND cd_nom = '{cd_nom}' AND cd_ref = '{cd_ref}'
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;'''.format(sch='taxonomie',tab='bdc_statut_taxons',cd_ref=cd_ref,cd_nom=cd_nom,id_statut_cor=id_statut_cor)
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with con.begin() as cnx:
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check = cnx.execute(sql_check).one()[0]
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if check == 0:
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sql = '''
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INSERT INTO {sch}.{tab} (id,id_value_text,cd_nom,cd_ref) VALUES
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('{id_statut_taxo}','{id_statut_cor}','{cd_nom}','{cd_ref}')
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;'''.format(sch='taxonomie',tab='bdc_statut_taxons',id_statut_taxo=id_statut_taxo,cd_ref=cd_ref,cd_nom=cd_nom,id_statut_cor=id_statut_cor)
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with con_gn.begin() as cnx:
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cnx.execute(sql)
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def get_status_type(con,col,status):
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sql = '''
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SELECT * FROM {sch}.{tab} WHERE {col} = '{status}'
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;'''.format(sch='taxonomie',tab='bdc_statut_type',col=col,status=status)
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return pd.read_sql(sql,con)
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def get_taxonomie(con,cd_nom):
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if isinstance(cd_nom,int):
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cd_nom = [cd_nom]
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else:
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cd_nom = list(cd_nom)
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sql = '''
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SELECT cd_nom,cd_ref,cd_sup,lb_nom,lb_auteur,nom_complet_html,nom_valide,regne,phylum,classe,ordre,famille,group1_inpn,group2_inpn FROM {sch}.{tab} WHERE cd_nom IN {cd_nom}
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;'''.format(sch='taxonomie',tab='taxref',cd_nom=tuple(cd_nom)).replace(",)",")")
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return pd.read_sql(sql,con)
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if __name__ == "__main__":
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import pandas as pd
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# Définition de la connection à la bdd GéoNature
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from pycen import con_gn
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# Le premier feuillet du fichier Excel lu.
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# Composition minimale: [CD_NOM,Statut, Source, Source_url]
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# ATTENTION:
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# - le CD_NOM doit correspondre au CD_NOM de la table taxref
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# - Les taxons dont la Source_url est None ou NA seront ignorés
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file = '/home/colas/Documents/9_PROJETS/6_GEONATURE/listes_alertes_isère.xlsx'
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# Echelle administratif des listes à implémenter
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niveau_admin = 'Département'
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# Nom du niveau adminsitratif
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lb_adm_tr = 'Isère'
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# Code SIG du niveau adminnistratif
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cd_sig = 'INSEED38'
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insert_status_alerte(con_gn)
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# Dictionnaire des listes d’alerte à intégrer,
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# identifiant et codes status respectivement concernés
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cd_doc = {
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'Statut_de_conservation_des_poissons_et_écrevisses_en_Isère_2015':{'id_doc':999990,'id_values':['RE','CR','EN','VU','NT','LC','DD','NA',]},
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'Liste_d’alerte_sur_les_orthoptères_menacés_en_Isère_2014':{'id_doc':999991,'id_values':['RE','CR','EN','VU','AS-1','AS-2','AS-3','LC','DD','NA']},
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'Statuts_de_conservation_de_la_faune_sauvage_en_isere_2016':{'id_doc':999992,'id_values':['RE','CR','EN','VU','NT','LC','DD','NA','NE',]},
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'Liste_rouge_des_Odonates_de_l’Isère_2013':{'id_doc':999993,'id_values':['RE','CR','EN','VU','NT','LC','DD','NA',]},
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'Liste_rouge_des_lépidoprere_rhopaloceres_et_zygenes_de_l’Isère_2015':{'id_doc':999994,'id_values':['RE','CR','EN','VU','NT','LC','DD','NA','NE','EX']},
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}
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df = (pd.read_excel(file,keep_default_na=False)
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.rename(columns={
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'Statut':'code_statut',
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'CD_NOM':'cd_nom',
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'Source':'source',
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'Source_url':'doc_url',
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}))
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df = df.loc[df.doc_url!='']
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for d in df.source.unique():
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doc_url = df.loc[df.source==d,'doc_url'].unique()[0]
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insert_statut_text(con_gn,cd_doc[d],doc_url)
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# INSERTION dans la table bdc_statut_taxons
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# Boucle sur chaque taxon. Peu prendre quelques minutes.
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[
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insert_status_taxo(
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con = con_gn,
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cd_nom = row.cd_nom,
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cd_doc = cd_doc[row.source]['id_doc'],
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status = row.code_statut)
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for row in df.itertuples()
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]
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st = get_status_type(con_gn,'cd_type_statut','AL')
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for c in st:
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df[c] = st[c][0]
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tax = get_taxonomie(con_gn,df['cd_nom'])
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del tax['nom_valide']
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del df['source']
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del df['nom_français']
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del df['nom_latin']
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df = df.merge(tax,how='inner',on='cd_nom')
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df['cd_sig'] = cd_sig
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df['lb_adm_tr'] = lb_adm_tr
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df['niveau_admin'] = niveau_admin
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df.to_sql('bdc_statut',con_gn,schema='taxonomie',if_exists='append',index=False)
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@ -1,289 +0,0 @@
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#!/usr/bin/env python3
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# -*- coding: UTF-8 -*-
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import requests
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import numpy as np
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import pandas as pd
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import os
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def get_status(lst,con):
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sql = """
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SELECT
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t.cd_nom,
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t.cd_ref,
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t.regne,
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t.phylum,
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t.classe,
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t.ordre,
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t.famille,
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t.group1_inpn,
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t.group2_inpn,
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t.group3_inpn,
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t.nom_vern,
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t.nom_complet,
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t.nom_valide,
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t.lb_nom,
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--s.*
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s.rq_statut,
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s.code_statut,
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s.cd_type_statut,
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s.label_statut,
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s.niveau_admin,
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s.full_citation,
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s.doc_url
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FROM taxonomie.taxref t
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JOIN taxonomie.v_bdc_status s USING (cd_nom)
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WHERE t.cd_nom IN {cd_nom}
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;""".format(cd_nom = tuple(lst))
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return pd.read_sql_query(sql,con)
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def get_api_status(api,cd_nom:int):
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res = requests.api.get('%s/%i'%(api,cd_nom))
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if res.status_code == 200:
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return res.json()
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else :
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raise('Error : %i\tcd_nom : %i'%(res.status_code,cd_nom))
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def get_taxon_status(lst,api):
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from datetime import datetime as dt
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init = dt.now()
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st = [get_api_status(api,x) for x in lst] # TOO LONG
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print(dt.now()-init)
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phylo = {
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'cd_ref':[x['cd_ref'] for x in st],
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'nom_valide':[x['nom_valide'] if 'nom_valide' in x.keys() else None for x in st],
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'nom_vernac':[x['nom_vern'] if 'nom_vern' in x.keys() else None for x in st],
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'regne':[x['regne'] if 'regne' in x.keys() else None for x in st],
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'group1_inp':[x['group1_inpn'] if 'group1_inpn' in x.keys() else None for x in st],
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'group2_inp':[x['group2_inp'] if 'group2_inp' in x.keys() else None for x in st],
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'group3_inpn':[x['group3_inpn'] for x in st],
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'classe':[x['classe'] if 'classe' in x.keys() else None for x in st],
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'ordre':[x['ordre'] if 'ordre' in x.keys() else None for x in st],
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'famille':[x['famille'] if 'famille' in x.keys() else None for x in st]}
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cd_status = {
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'AL':[
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[val['values'][v]['code_statut']
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for val in x['status']['AL']['text'].values() for v in val['values'] ]
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if 'AL' in x['status'].keys() else None
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for x in st
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],
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'BERN':[
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[val['values'][v]['code_statut']
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for val in x['status']['BERN']['text'].values() for v in val['values'] ]
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if 'BERN' in x['status'].keys() else None
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for x in st
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],
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'BONN':[
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[val['values'][v]['code_statut']
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for val in x['status']['BONN']['text'].values() for v in val['values'] ]
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if 'BONN' in x['status'].keys() else None
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for x in st
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],
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'DH':[
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[val['values'][v]['code_statut']
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for val in x['status']['DH']['text'].values() for v in val['values'] ]
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if 'DH' in x['status'].keys() else None
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for x in st
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],
|
||||
'DO':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['DO']['text'].values() for v in val['values'] ]
|
||||
if 'DO' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'LRE':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['LRE']['text'].values() for v in val['values'] ]
|
||||
if 'LRE' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'LRM':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['LRM']['text'].values() for v in val['values'] ]
|
||||
if 'LRM' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'LRN':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['LRN']['text'].values() for v in val['values'] ]
|
||||
if 'LRN' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'LRR':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['LRR']['text'].values() for v in val['values'] ]
|
||||
if 'LRR' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'PAPNAT':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['PAPNAT']['text'].values() for v in val['values'] ]
|
||||
if 'PAPNAT' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'PD':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['PD']['text'].values() for v in val['values'] ]
|
||||
if 'PD' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'PNA':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['PNA']['text'].values() for v in val['values'] ]
|
||||
if 'PNA' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'PR':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['PR']['text'].values() for v in val['values'] ]
|
||||
if 'PR' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'REGL':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['REGL']['text'].values() for v in val['values'] ]
|
||||
if 'REGL' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'REGLII':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['REGLII']['text'].values() for v in val['values'] ]
|
||||
if 'REGLII' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'REGLLUTTE':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['REGLLUTTE']['text'].values() for v in val['values'] ]
|
||||
if 'REGLLUTTE' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'REGLSO':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['REGLSO']['text'].values() for v in val['values'] ]
|
||||
if 'REGLSO' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'SCAP NAT':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['SCAP NAT']['text'].values() for v in val['values'] ]
|
||||
if 'SCAP NAT' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'SCAP REG':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['SCAP REG']['text'].values() for v in val['values'] ]
|
||||
if 'SCAP REG' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'SENSNAT':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['SENSNAT']['text'].values() for v in val['values'] ]
|
||||
if 'SENSNAT' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'ZDET':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['ZDET']['text'].values() for v in val['values'] ]
|
||||
if 'ZDET' in x['status'].keys() else None
|
||||
for x in st
|
||||
],
|
||||
'exPNA':[
|
||||
[val['values'][v]['code_statut']
|
||||
for val in x['status']['exPNA']['text'].values() for v in val['values'] ]
|
||||
if 'exPNA' in x['status'].keys() else None
|
||||
for x in st
|
||||
]
|
||||
}
|
||||
return pd.DataFrame({**phylo,**cd_status})
|
||||
|
||||
dict_dep = {
|
||||
'38':'Isère',
|
||||
'42':'Loire',
|
||||
'07':'Ardèche',
|
||||
'26':'Drôme',
|
||||
}
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Définition de la connection à la bdd GéoNature
|
||||
from pycen import con_gn
|
||||
# NOT USE FOR NOW - API Taxref
|
||||
api_taxref = 'https://geonature.cen-isere.fr/taxhub/api/taxref'
|
||||
|
||||
# Paramètres de chargement du fichier des taxons
|
||||
PATH = '/home/colas/Documents/tmp/CHARVAS'
|
||||
file = 'liste_sp_CHAR.xlsx'
|
||||
sheet = 'liste_sp'
|
||||
|
||||
# Liste des CD_NOM en entrée
|
||||
cd_col = 'cd_ref' # Nom de la colonne à utiliser dans le feuillet ``sheet``
|
||||
|
||||
# Lecture des données
|
||||
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)
|
||||
lst = taxlist[cd_col]
|
||||
|
||||
# Récupération des statuts
|
||||
df = get_status(taxlist[cd_col].astype(str),con_gn)
|
||||
|
||||
# Distinction LRR [old vs new] région
|
||||
is_lrr = df.cd_type_statut == 'LRR'
|
||||
df.loc[is_lrr & (df.niveau_admin == 'Région'),'cd_type_statut'] = 'LRR_AURA'
|
||||
df.loc[is_lrr & (df.niveau_admin == 'Ancienne région'),'cd_type_statut'] = 'LRR_RA'
|
||||
del df['niveau_admin']
|
||||
|
||||
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)
|
||||
|
||||
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 !')
|
||||
Loading…
x
Reference in New Issue
Block a user