81 lines
2.2 KiB
Python
81 lines
2.2 KiB
Python
#!/usr/bin/env python3
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# -*- coding: UTF-8 -*-.
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import geopandas as gpd
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import pandas as pd
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from geoalchemy2 import Geometry
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from sqlalchemy.engine import URL
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from sqlalchemy import create_engine
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import sys
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# Liste des sites
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lst_site = ['GOUT']
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# Suppression des champs souhaités
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delete = True
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lst_cols_del = ['geometrie','date_debut_obs']
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# Format d'extraction ['xls', 'xlsx', 'csv']
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FORMAT = 'xlsx'
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# Localistation du fichier de sortie
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OUTPUT = '~/Documents/tmp/Jean_Luc/'
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# Nom du fichier de sortie
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NAME_OUT = 'observation_site_GOUT'
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from pycen import con_sicen as engine_hom
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# Parametres bdd HOMER (out)
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schema_hom = 'saisie'
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table_hom = 'saisie_observation'
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# engine_hom = create_engine('postgresql+psycopg2://{0}:{1}@{2}:{3}/{4}'.format(user_hom,pwd_hom,adr_hom,port_hom,base_hom), echo=False)
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# Parametres bdd BART (in)
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# BART ETEINT : OBSOLETE
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adr_bart = '192.168.0.3'
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port_bart = '5432'
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base_bart = 'bd_cen38'
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schema_bart = 'sites'
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table_bart = "c_sites_zonages"
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url_bart = URL.create('postgresql+psycopg2',
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username=user_bart,
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password=pwd_bart,
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host=adr_bart,
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database=base_bart,
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)
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con_bart = create_engine(url_bart)
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# con_bart = create_engine('postgresql+psycopg2://{0}:{1}@{2}:{3}/{4}'.format(user_bart,pwd_bart,adr_bart,port_bart,base_bart), echo=False)
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epsg = '2154'
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crs = 'EPSG:%s'%epsg
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sql = "SELECT geom FROM {sch}.{tab} WHERE code_site in ('{lst_site}') AND type_zonage = 'ZO'".format(sch=schema_bart, tab=table_bart, lst_site="','".join(lst_site))
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gdf_site = gpd.read_postgis(
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sql = sql,
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con = con_bart,
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)
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if gdf_site.shape[0] > 1 :
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union = gdf_site.geom.cascaded_union
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Sunion = gpd.GeoSeries(union)
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gdf_union = gpd.GeoDataFrame(Sunion, geometry='geom', columns=['geom'], crs=crs)
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gdf_site = gdf_union
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sql = '''SELECT * FROM {sch}.{tab} WHERE ST_Intersects (geometrie, 'SRID={epsg};{poly}')'''.format(sch=schema_hom, tab=table_hom, epsg=epsg, poly=gdf_site.geom[0])
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gdf_saisie = gpd.read_postgis(
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sql = sql,
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con = engine_hom,
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geom_col = 'geometrie'
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)
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df = pd.DataFrame(gdf_saisie)
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if delete:
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df.drop(columns= lst_cols_del, inplace=True)
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if FORMAT in ['xls', 'xlsx']:
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df.to_excel(OUTPUT + NAME_OUT + '.' + FORMAT)
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if FORMAT == 'csv':
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df.to_file(OUTPUT + NAME_OUT + '.' + FORMAT)
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sys.exit('END') |