# -*- coding: utf-8 -*-
'''
Created on May 25, 2011

- after `import_rdf` call commands `import_hdabo_db -c` then `rebuild_index`

@author: ymh
'''

import base64
import collections
import logging
import math
from optparse import make_option
import os
import shutil
import sys
import tempfile

import RDF
from django.core.management.base import BaseCommand, CommandError
from django.core.management.color import no_style
from django.db import connections, DEFAULT_DB_ALIAS
from django.db import models
from django.db import transaction
import isodate
import pytz

from hdabo.models import (Datasheet, DocumentFormat, Domain, Organisation,
    Tag, TaggedSheet, TimePeriod, Location, TagCategory)


logger = logging.getLogger(__name__)

RDF_EXT_MAP = {
    '.xml': 'rdfxm',
    '.rdf': 'rdfxm',
    '.ttl': 'turtle',
    '.nt': 'ntriples'
}

class ProcessedObjects(models.Model):
    obj_name = models.CharField(max_length=1024, db_index=True, null=False, blank=False)
    obj_id = models.IntegerField(db_index=True, null=False, blank=False)

    def __unicode__(self):
        return "ProcessedObject -> id : %d, obj_name: %s, obj_id: %d" % (self.id or "None", self.obj_name, self.obj_id)
    class Meta:
        app_label = 'import_rdf'


class KeyDefaultdict(collections.defaultdict):
    def __missing__(self, key):
        if self.default_factory:
            dict.__setitem__(self, key, self.default_factory(key))
            return self[key]
        else:
            collections.defaultdict.__missing__(self, key)


class GraphCacheMap(collections.defaultdict):
    def __init__(self, key=[]):
        self.key = key
        super(GraphCacheMap, self).__init__(GraphCacheMap)
        self.key_index = 0

    def get_index(self):
        self.key_index += 1
        return "%016x" % self.key_index

class GraphCache(object):

    def __init__(self, temp_folder=tempfile.tempdir, fmt='turtle'):
        self.base_temp_folder = temp_folder
        self.temp_folder = None
        self.format = fmt
        self.filename_map = GraphCacheMap()

    def clear_filename_cache(self, keys=None):
        """Clear from filename cache (memory)

        :param tuple keys: the key to clear. ``None`` will clear all.
        """
        if not keys:
            self.filename_map.clear()
            return
        if not isinstance(keys, (list,tuple)):
            keys = (keys,)
        current_cache_dict = self.filename_map
        for k in keys[:-1]:
            current_cache_dict = current_cache_dict.get(k)
            if not isinstance(current_cache_dict,dict):
                raise KeyError("%r not found " % keys)
        current_cache_dict.pop(keys[-1])


    def clear(self, keys=None):
        """Clear from disk cache

        :param tuple keys: the key to clear. ``None`` will clear all.
        """
        if not keys:
            path = self.temp_folder
            self.temp_folder = None
            self.filename_map.clear()
        else:
            path = self.__build_path(keys)

        if not os.path.exists(path):
            raise KeyError("%r not found" % keys)
        if os.path.isfile(path):
            os.remove(path)
        else:
            shutil.rmtree(path)
        self.clear_filename_cache(keys)

    def get_from_filename_cache(self, keys):
        """get from filename cache.
        :raises: KeyError if not found
        """
        if not keys:
            raise KeyError("Keys is None or empty")
        if not isinstance(keys, (tuple,list)):
            keys = (keys,)
        #print("FILENAME MAP : " + repr(self.filename_map))
        try:
            res = reduce(lambda d,k: d[k], keys, self.filename_map)
            if(isinstance(res,GraphCacheMap)):
                return res.key
            else:
                return res
        except:
            KeyError("%r not found" % keys)


    def __build_path(self, keys):
        if not keys:
            raise KeyError("Keys is None or empty")
        if not isinstance(keys, (tuple,list)):
            keys = (keys,)
        file_parts = self.get_from_filename_cache(keys)
        if file_parts:
            return os.path.join(self.temp_folder,os.path.join(*file_parts))
        else:
            return self.temp_folder

    def get_len(self, keys):
        if not isinstance(keys, (tuple,list)):
            keys = [keys,]
        elif isinstance(keys, tuple):
            keys = list(keys)
        res = reduce(lambda d,k: d[k], keys, self.filename_map)
        return len(res)

    #TODO: treat errors
    def get_iter(self,keys):
        if not isinstance(keys, (tuple,list)):
            keys = [keys,]
        elif isinstance(keys, tuple):
            keys = list(keys)
        res = reduce(lambda d,k: d[k], keys, self.filename_map)

        for graphfile_key in res.keys():
            g = RDF.Model()
            parser=RDF.Parser(name=self.format)
            parser.parse_into_model(g, "file://"+self.__build_path(keys + [graphfile_key,]))
            yield g

    def get(self, keys, default=None):
        """get graph from disk cache
        :raises: KeyError if file not found"""
        path = self.__build_path(keys)

        if not os.path.exists(path):
            return default

        if not os.path.isfile(path):
            raise KeyError("%r found but not a file" % keys)

        #g = rdflib.Graph()
        g = RDF.Model()
        try:
        #    g.parse(path, format=self.format)
            parser=RDF.Parser(name=self.format)
            parser.parse_into_model(g, "file://"+path)
        except Exception as e:
            raise KeyError("Bad key %r. Error when reading file %r" % (keys, e))
        return g


    def get_content(self, keys, default=[]):
        """get dir content from disk cache
        :returns: list of (keys, name, is_dir) with is_dir = True when item is a sub folder. Default when nothing is found.
        :raises: KeyError if dir exists but is not folder"""

        vir_folder = self.get_from_filename_cache(keys)
        if not isinstance(vir_folder, dict):
            raise KeyError("Bad key %r. path is not a folder" % keys)

        return [(tuple(keys)+(k,),k,isinstance(v, dict)) for k,v in vir_folder.items()]


    def put_in_filename_cache(self, keys, val):
        if not keys:
            raise KeyError("Keys is None or empty")
        if not isinstance(keys, (tuple,list)):
            keys = (keys,)

        reduce(lambda d,k: d.setdefault(k,{}), keys[:-1], self.obj_cache)[keys[-1]] = val


    def put(self, keys, g):
        if g is None:
            raise Exception("Null graph")
        if not self.temp_folder or not os.path.exists(self.temp_folder):
            self.temp_folder = tempfile.mkdtemp(dir=self.base_temp_folder)
        if not os.path.isdir(self.temp_folder):
            raise Exception("Temp folder for disk cache is not a dir")

        path_parts = []
        current_map = self.filename_map
        for k in keys[:-1]:
            if k in current_map:
                current_map = current_map[k]
            else:
                new_key = current_map.key + [current_map.get_index(),]
                current_map = current_map.setdefault(k, GraphCacheMap(new_key))

            path_parts.append(current_map.key[-1])
        current_index = current_map.get_index()
        path_parts.append(current_index)
        current_map[keys[-1]] = path_parts;

        if len(keys)>1:
            path_dir = self.__build_path(keys[:-1])
            if not os.path.isdir(path_dir):
                os.makedirs(path_dir)
        path = self.__build_path(keys)
        ser = RDF.Serializer(name=self.format)
        ser.serialize_model_to_file(path, g)

HDA_ONTOLOGY_BASE_URL = 'http://data.culture.fr/ontologies/hda/0.1#'

TYPES_LIST = [
    'Categorie',
    'Tag',
    'Site',
    'Ville',
    'Institution',
    'Theme',
    'Domaine',
    'SousDomaine',
    'Periode',
    'Notice'
]

TARGET_TYPE_LIST = [
    TaggedSheet,
    Datasheet,
    Domain,
    TimePeriod,
    Tag,
    TagCategory,
    Organisation,
    Location,
    DocumentFormat
]

RDF_NS = RDF.NS('http://www.w3.org/1999/02/22-rdf-syntax-ns#')
RDFS_NS = RDF.NS('http://www.w3.org/2000/01/rdf-schema#')
HDA_NS = RDF.NS(HDA_ONTOLOGY_BASE_URL)
DC_NS = RDF.NS("http://purl.org/dc/terms/")
INSEE_NS = RDF.NS("http://rdf.insee.fr/def/geo#")
XMLSCHEMA_NS = RDF.NS("http://www.w3.org/2001/XMLSchema#")
FOAF_NS = RDF.NS("http://xmlns.com/foaf/0.1/")
DBPEDIA_NS = RDF.NS("http://dbpedia.org/ontology/")

def show_progress(current_line, total_line, width, message=""):

    percent = (float(current_line) / float(total_line)) * 100.0

    marks = math.floor(width * (percent / 100.0))
    spaces = math.floor(width - marks)

    loader = '[' + ('=' * int(marks)) + (' ' * int(spaces)) + ']'

    message_fill = " " * max(0,width - len(message))

    sys.stdout.write("%s %d%% %d/%d %s%s\r" % (loader, percent, current_line, total_line, message, message_fill)) #takes the header into account
    if percent >= 100:
        sys.stdout.write("\n")
    sys.stdout.flush()


class RdfImporter(object):

    importer_stats = KeyDefaultdict(lambda k: {'object_name': k, 'created': 0, 'updated': 0, 'untouched': 0, 'deleted': 0})

    def __init__(self, g, obj_type):
        self.graph = g
        self.obj_type = obj_type
        self.obj_uri_node = self.graph.get_source(RDF_NS.type, HDA_NS[self.obj_type])
        if self.obj_uri_node is None:
            raise Exception("For importer %s type node is not foud" % self.obj_type)
        self.attr_rdf_map = {'id': DC_NS.identifier}
        self.attr_cache = {}

    def import_graph(self):
        for obj_instance, created, dirty in self.do_import_graph():
            obj_name = type(obj_instance).__name__
            ProcessedObjects.objects.create(obj_name = obj_name, obj_id = obj_instance.pk)
            obj_stat = self.importer_stats[obj_name]
            if created:
                obj_stat['created'] += 1
            elif dirty:
                obj_stat['updated'] += 1
            else:
                obj_stat['untouched'] += 1

    def do_import_graph(self):
        pass
    
    def _process_attr_node(self, attr_node):
        if attr_node is None:
            return None

        if attr_node.is_resource():
            return str(attr_node.uri)
        
        if attr_node.is_blank():
            new_g = RDF.Model()
            qs = RDF.Statement(subject=attr_node, predicate=None, object=None)
            new_g.add_statements(self.graph.find_statements(qs))
            return new_g

        #attr_node is litteral
        lit_val = attr_node.literal_value
        res_type = lit_val['datatype']
        res_raw = lit_val['string']
        res = res_raw
        if res_type == XMLSCHEMA_NS.dateTime.uri:
            res = isodate.parse_datetime(res_raw)
        elif res_type == XMLSCHEMA_NS.integer.uri:
            res = int(res_raw)
        return res


    def __getattr__(self, name):
        if name in ('attr_cache'):
            raise AttributeError, name
        if name in self.attr_cache:
            return self.attr_cache[name]
        if name not in self.attr_rdf_map:
            raise AttributeError("%s not in attributes", name)
        
        res = None
        if isinstance(self.attr_rdf_map[name], (list, tuple, set)):
            res = reduce(
                lambda r, pred: r + [self._process_attr_node(attr_node) for attr_node in self.graph.get_targets(self.obj_uri_node, pred)],
                self.attr_rdf_map[name],
                []
            )
        else:
            attr_node = self.graph.get_target(self.obj_uri_node, self.attr_rdf_map[name])
            res = self._process_attr_node(attr_node)

        self.attr_cache[name] = res
        return res

def RdfImporterFactory(type_name):
    newImporter = type(type_name+"RdfImporter", (RdfImporter,), {"__init__": lambda self,g: RdfImporter.__init__(self, g, type_name)})
    return newImporter

class VilleImporter(RdfImporter):

    def __init__(self, g):
        super(VilleImporter, self).__init__(g, 'Ville')
        self.attr_rdf_map.update({
            'codeINSEE': INSEE_NS.codeINSEE,
            'nom': INSEE_NS.nom
        })

    def do_import_graph(self):
        loc, created = Location.objects.get_or_create(insee=self.codeINSEE)
        dirty = False
        if loc.name != self.nom:
            loc.name = self.nom
            dirty = True
        if dirty:
            loc.save()
        return [(loc, created, dirty), ]


class CategorieImporter(RdfImporter):

    def __init__(self, g):
        super(CategorieImporter, self).__init__(g, 'Categorie')
        self.attr_rdf_map.update({
            'label': RDFS_NS.label
        })

    def do_import_graph(self):
        cat, created = TagCategory.objects.get_or_create(label=self.label)
        dirty = True
        val = self.id
        if cat.natural_key != val:
            cat.natural_key = val
            dirty = True
        
        if dirty :
            cat.save()
            
        return [(cat, created, dirty), ]


class TagImporter(RdfImporter):

    def __init__(self, g):
        super(TagImporter, self).__init__(g, 'Tag')
        self.attr_rdf_map.update({
            "label": RDFS_NS.label,
            "alternative_label": HDA_NS.alternativeLabel,
            "normalized_label": HDA_NS.normalizedLabel,
            "original_label": HDA_NS.originalLabel,
            "alias": HDA_NS.alias,
            "category": HDA_NS.category,
            "wikipedia_url": HDA_NS.wikipediaURL,
            "wikipedia_pageid": HDA_NS.wikipediaPageId,
            "alternative_wikipedia_url": HDA_NS.alternativeWikipediaURL,
            "alternative_wikipedia_pageid": HDA_NS.alternativeWikipediaPageId,
            "url_status": HDA_NS.urlStatus,
            "dbpedia_uri": HDA_NS.dbpediaURI,
            "popularity": HDA_NS.popularity,
            "created_at": DC_NS.created
        })

    def do_import_graph(self):
        
        if self.id == "___":
            return []
        
        tag, created = Tag.objects.get_or_create(label=self.label, original_label=self.original_label, url_status=self.url_status, defaults={'natural_key': self.id})
        
        dirty = False
        tag.force_natural_key = True
        tag.natural_key = self.id
        for field in [f for f in self.attr_rdf_map.keys() if f not in ['label', 'original_label', 'url_status']]:
            if field == 'id':
                val = self.id
                if tag.natural_key != val:
                    dirty = True
                    tag.natural_key = val
            elif field == 'created_at':
                val = self.created_at
                if tag.created_at.replace(tzinfo=pytz.UTC) != val:
                    dirty = True
                    tag.created_at = val
            elif field in ['alternative_wikipedia_pageid', 'wikipedia_pageid']:
                val = getattr(self, field)
                if val == '':
                    val = None
                if getattr(tag, field) != val:
                    dirty = True
                    setattr(tag, field, val)
            elif field != 'category':
                val = getattr(self, field)
                if getattr(tag, field) != val:
                    dirty = True
                    setattr(tag, field, val)
            elif self.category:
                catid = self.category.split("/")[-1]
                newCat = TagCategory.objects.filter(natural_key=catid).first()
                if tag.category != newCat:
                    tag.category = newCat
                    dirty = True
        if dirty:
            tag.save()

        return [(tag, created, dirty), ]


class DomaineImporter(RdfImporter):
    def __init__(self, g, obj_type='Domaine'):
        super(DomaineImporter, self).__init__(g, obj_type)
        self.attr_rdf_map.update({
            'label': RDFS_NS.label,
            'value': RDF_NS.value
        })

    def do_import_graph(self):
        
        domain, created = Domain.objects.get_or_create(natural_key=self.id, defaults={'label': self.value, 'school_period': Domain.DOMAIN_PERIOD_DICT[u'Global']})

        dirty = False
        if domain.label != self.value:
            domain.label=self.value
            dirty = True
        if domain.school_period != Domain.DOMAIN_PERIOD_DICT[u'Global']:
            domain.school_period = Domain.DOMAIN_PERIOD_DICT[u'Global']
            dirty = True
        
        if dirty:
            domain.save()

        return [(domain, created, dirty),]


class SousDomaineImporter(DomaineImporter):
    def __init__(self, g):
        super(SousDomaineImporter, self).__init__(g, 'SousDomaine')


class ThemeImporter(DomaineImporter):
    LEVEL_MAP = {
        1: Domain.DOMAIN_PERIOD_DICT[u'Primaire'],
        2: Domain.DOMAIN_PERIOD_DICT[u'Collège'],
        3: Domain.DOMAIN_PERIOD_DICT[u'Lycée']
    }

    def __init__(self, g):
        super(ThemeImporter, self).__init__(g, 'Theme')
        self.attr_rdf_map.update({
            'level': HDA_NS.niveau
        })


    def do_import_graph(self):
        domain, created = Domain.objects.get_or_create(natural_key=self.id, defaults={'label': self.value, 'school_period': ThemeImporter.LEVEL_MAP[self.level]})

        dirty = False
        if domain.label != self.value:
            domain.label=self.value
            dirty = True
        if domain.school_period != ThemeImporter.LEVEL_MAP[self.level]:
            domain.school_period = ThemeImporter.LEVEL_MAP[self.level]
            dirty = True
        
        if dirty:
            domain.save()


        return [(domain, created, dirty),]


class PeriodeImporter(RdfImporter):
    LEVEL_MAP = {
        1: Domain.DOMAIN_PERIOD_DICT[u'Primaire'],
        2: Domain.DOMAIN_PERIOD_DICT[u'Collège'],
        3: Domain.DOMAIN_PERIOD_DICT[u'Lycée']
    }

    def __init__(self, g):
        super(PeriodeImporter, self).__init__(g, 'Periode')
        self.attr_rdf_map.update({
            'value': RDF_NS.value,
            'level': HDA_NS.niveau
        })


    def do_import_graph(self):

        period, created = TimePeriod.objects.get_or_create(natural_key=self.id, defaults={'label': self.value, 'school_period': ThemeImporter.LEVEL_MAP[self.level]})

        dirty = False
        if period.label != self.value:
            period.label=self.value
            dirty = True
        if period.school_period != ThemeImporter.LEVEL_MAP[self.level]:
            period.school_period = ThemeImporter.LEVEL_MAP[self.level]
            dirty = True
        
        if dirty:
            period.save()


        return [(period, created, dirty),]


class SiteImporter(RdfImporter):
    
    def __init__(self, g):
        super(SiteImporter, self).__init__(g, 'Site')
        self.attr_rdf_map.update({
            'name': RDFS_NS.label,
            'website': FOAF_NS.homepage,
        })
    
    def do_import_graph(self):
        
        org, created = Organisation.objects.get_or_create(hda_id = self.id)
        
        dirty = False
        if self.name != org.name:
            org.name = self.name
            dirty = True
        if self.website != org.website:
            org.website = self.website
            dirty = True

        if dirty:
            org.save()

        return [(org, created, dirty),]


class InstitutionImporter(RdfImporter):
    
    def __init__(self, g):
        super(InstitutionImporter, self).__init__(g, 'Institution')
        self.attr_rdf_map.update({
            'name': RDFS_NS.label,
            'website': FOAF_NS.homepage,
            'location': HDA_NS.ville
        })
    
    def do_import_graph(self):
        
        org, created = Organisation.objects.get_or_create(hda_id = self.id)
        
        dirty = False
        if self.name != org.name:
            org.name = self.name
            dirty = True
        if self.website != org.website:
            org.website = self.website
            dirty = True
        ville = self.location
        if ville:
            ville_id = ville.split("/")[-1]
            location = Location.objects.filter(insee=ville_id).first()
            if location and location.name != org.location:
                org.location = location.name
                dirty = True

        if dirty:
            org.save()

        return [(org, created, dirty),]

class DocumentTagImporter(RdfImporter):
    def __init__(self, g, datasheet):
        super(DocumentTagImporter, self).__init__(g, 'DocumentTag')
        self.datasheet = datasheet
        self.attr_rdf_map.update({
            'created_at': DC_NS.created,
            'order': HDA_NS.order,
            'original_order': HDA_NS.originalOrder,
            'index_note': HDA_NS.indexNote,
            'wikipedia_revision_id': DBPEDIA_NS.wikiPageRevisionID,
            'tag': HDA_NS.tag
        })
    
    def do_import_graph(self):
        tag = Tag.objects.filter(natural_key=self.tag.split("/")[-1]).first()
        if tag is None:
            logger.warn("Tag %r not found for datasheet %r", self.tag.split("/")[-1], self.datasheet.hda_id)
        ts = TaggedSheet.objects.filter(tag=tag, datasheet=self.datasheet).first()
        created = False
        if ts is None:
            ts = TaggedSheet.objects.create(tag=tag, datasheet=self.datasheet)
            created = True
        
        dirty = False
        
        val = self.created_at
        if ts.created_at.replace(tzinfo=pytz.UTC) != val:
            dirty = True
            ts.created_at = val

        for field in ['order', 'original_order', 'index_note', 'wikipedia_revision_id']:
            val = getattr(self, field)
            if val == '':
                val = None
            if getattr(ts, field) != val:
                setattr(ts, field, val)
                dirty = True

        if dirty:
            ts.save()
        
        return [(ts,created,dirty),]


class NoticeImporter(RdfImporter):

    def __init__(self, g):
        super(NoticeImporter, self).__init__(g, 'Notice')
        #print("NOTICE IMPORTER")
        #ser = RDF.Serializer(name='turtle')
        #print(ser.serialize_model_to_string(g))
        
        self.attr_rdf_map.update({
            'title': DC_NS.title,
            'description': DC_NS.description,
            'url': HDA_NS.url,
            'organisation': HDA_NS.institution,
            'original_creation_date': DC_NS.created,
            'original_modification_date': DC_NS.issued,
            'town': HDA_NS.ville,
            'format': DC_NS.format,
            'domains': [HDA_NS.domaine, HDA_NS.sousDomainePrimaire],
            'primary_periods': [HDA_NS.periodePrimaire,],
            'college_periods': [HDA_NS.periodeCollege,],
            'highschool_periods': [HDA_NS.periodeLycee,],
            'primary_themes': [HDA_NS.themePrimaire,],
            'college_themes': [HDA_NS.themeCollege,],
            'highschool_themes': [HDA_NS.themeLycee,],
            'tags': [HDA_NS.documentTag,]
        })

    @transaction.atomic
    def do_import_graph(self):
        
        
        ds, created = Datasheet.objects.get_or_create(hda_id=self.id, defaults={'original_creation_date': self.original_creation_date, 'original_modification_date': self.original_modification_date})
        dirty=False
        
        res = []

        for field in ['title', 'description', 'url']:
            val = getattr(self, field)
            if getattr(ds, field) != val:
                setattr(ds, field, val)
                dirty = True
        for field in [ 'original_creation_date', 'original_modification_date']:
            val = getattr(self, field).date()
            if getattr(ds, field) != val:
                setattr(ds, field, val)
                dirty = True
        
        org_url = self.organisation
        org = None
        if org_url:
            org_id = org_url.split("/")[-1]
            org = Organisation.objects.filter(hda_id=org_id).first()
        
        if org != ds.organisation:
            ds.organisation = org
            dirty = True

        town_url = self.town
        town = None
        if town_url:
            town_id = town_url.split("/")[-1]
            town = Location.objects.filter(insee=town_id).first()
        if town != ds.town:
            ds.town = town
            dirty = True
        
        fmt = self.format
        format_obj = None
        if fmt:
            format_obj, f_created = DocumentFormat.objects.get_or_create(label=fmt)
            res.append((format_obj, f_created, False))

        if format_obj != ds.format:
            ds.format = format_obj
            dirty = True
            
        if not ds.validated:
            ds.validated = True
            dirty = True
        
        for (field, ObjKlass) in [('domains',Domain), ('primary_periods', TimePeriod), ('college_periods', TimePeriod), ('highschool_periods', TimePeriod), ('primary_themes', Domain), ('college_themes', Domain), ('highschool_themes', Domain)]:
            tgt_obj_ids = [obj_url.split("/")[-1] for obj_url in getattr(self, field)]
            tgt_obj_ids.sort()
            
            ds_objs_ids = [d.natural_key for d in getattr(ds, field).all()]
            ds_objs_ids.sort()
            if ds_objs_ids !=  tgt_obj_ids:
                #get trought class
                ThroughKlass = getattr(Datasheet, field).through
                ThroughKlass.objects.filter(datasheet=ds).delete()
                for i,tgt_obj in enumerate(ObjKlass.objects.filter(natural_key__in = tgt_obj_ids)):
                    link_args = {'datasheet': ds, ObjKlass.__name__.lower(): tgt_obj, 'sort_value': i}
                    ThroughKlass.objects.create(**link_args)
                dirty = True
        
        if dirty:
            ds.save()
        
        res.append((ds, created, dirty))
        
        #create TaggedSheet
        for tagged_sheet_graph in self.tags:
            importer = DocumentTagImporter(tagged_sheet_graph, ds)
            importer.import_graph()
        
        return res


RDF_IMPORTERS = KeyDefaultdict(RdfImporterFactory, {
    'Ville': VilleImporter,
    'Categorie': CategorieImporter,
    'Tag': TagImporter,
    'Domaine': DomaineImporter,
    'SousDomaine': SousDomaineImporter,
    'Theme': ThemeImporter,
    'Periode': PeriodeImporter,
    'Site': SiteImporter,
    'Institution': InstitutionImporter,
    'Notice': NoticeImporter
})

class Command(BaseCommand):
    '''
    Command to import csvfile
    '''
    args = '<path_to_csv_file path_to_csv_file ...>'
    options = '[--type TYPE]'
    help = """Import of a csv file for hdabo
Options:
    --ignore-existing : ignore existing datasheets
    --lines : max number of lines to load (for each file). 0 means all.
"""

    option_list = BaseCommand.option_list + (
        make_option('-t', '--type',
            action='append',
            type='string',
            dest='types',
            default=[],
            help='types to process.'),
        )



    def get_entity_cache_keys(self, s):
        return [base64.urlsafe_b64encode(p) for p in s.rstrip("/").rsplit("/",1)]

    def handle(self, *args, **options):

        if len(args) == 0:
            raise CommandError("Gives at last one rdf file to import")

        self.types_list = options.get('types', TYPES_LIST) or TYPES_LIST

        if any([t not in TYPES_LIST for t in self.types_list]):
            raise CommandError("Types is %r : all types mus be in %r" % (self.types_list, TYPES_LIST))

        models.register_models('import_rdf', ProcessedObjects)
        connection = connections[DEFAULT_DB_ALIAS]
        sql_temp, _ = connection.creation.sql_create_model(ProcessedObjects, no_style(), [])
        cursor = connection.cursor()
        for stmt in sql_temp:
            cursor.execute(stmt.replace("CREATE TABLE", "CREATE TEMPORARY TABLE"))

        transaction.set_dirty()
        transaction.commit()
        #lines = options.get('lines', 0)
        #self.ignore_existing = options.get('ignore_existing', False)

        #open rdf file
        src_uri = RDF.Uri("file://" + args[0])
        _, fileExtension = os.path.splitext(args[0])

        parser = RDF.Parser(name=RDF_EXT_MAP.get(fileExtension, 'rdfxml'))

        current_graph = RDF.Model()
        current_entity = None
        current_id = None
        current_type = None
        blank_node_statements = {}

        graph_disk_cache = GraphCache()

        for statement in parser.parse_as_stream(uri=src_uri):
            if statement.predicate.uri == RDF.Uri("http://www.w3.org/1999/02/22-rdf-syntax-ns#type") and statement.subject.type != RDF.node_type('NODE_TYPE_BLANK'):
                current_type = unicode(statement.object.uri)
            if statement.predicate.uri == RDF.Uri("http://purl.org/dc/terms/identifier") and statement.subject.type != RDF.node_type('NODE_TYPE_BLANK'):
                current_id = statement.object.literal[0]

            if statement.subject.type == RDF.node_type('NODE_TYPE_RESOURCE'):
                if current_entity is not None and current_entity != statement.subject:
                    cache_keys = [current_type, current_id]
                    graph_disk_cache.put(cache_keys, current_graph)
                    current_graph = RDF.Model()
                    current_id = None
                    current_type = None
                current_graph.append(RDF.Statement(statement=statement))
                current_entity = statement.subject
            elif statement.subject.type == RDF.node_type('NODE_TYPE_BLANK'):
                if not current_graph.find_statements(RDF.Statement(None, None, statement.subject)).end():
                    current_graph.append(RDF.Statement(statement=statement))
                else:
                    blank_node_statements.setdefault(statement.subject,[]).append(statement)
            else:
                current_graph.append(RDF.Statement(statement=statement))

            if statement.object.type == RDF.node_type('NODE_TYPE_BLANK') and statement.object in blank_node_statements:
                for stmt in blank_node_statements.pop(statement.object):
                    current_graph.append(RDF.Statement(statement=stmt))

        if current_entity is not None and current_type is not None and current_id is not None:
            cache_keys = [current_type, current_id]
            graph_disk_cache.put(cache_keys, current_graph)


        if blank_node_statements:
            raise CommandError("Orphan rdf statements for blank nodes %r", blank_node_statements)


        for i, obj_type in enumerate(self.types_list):
            print("stage %d/%d : processing %s :" % (i+1, len(self.types_list), obj_type))
            obj_type_url = HDA_ONTOLOGY_BASE_URL+obj_type
            obj_len = graph_disk_cache.get_len(obj_type_url)
            for i,g in enumerate(graph_disk_cache.get_iter(obj_type_url)):
                importer_class = RDF_IMPORTERS[obj_type]
                importer = importer_class(g)
                obj_id = importer.id
                show_progress(i+1, obj_len, 80, "ID: %s" % obj_id[:76])
                importer.import_graph()
            print("")


        for target_type in TARGET_TYPE_LIST:
            delete_qs = target_type.objects.exclude(id__in = ProcessedObjects.objects.filter(obj_name=target_type.__name__).values_list('obj_id', flat=True))
            RdfImporter.importer_stats[target_type.__name__]['deleted'] = delete_qs.count()
            print("Deleting %s : %d " % (target_type.__name__, RdfImporter.importer_stats[target_type.__name__]['deleted']))
            delete_qs.delete()

        print("Import stats :")
        for obj_stat in RdfImporter.importer_stats.values():
            print("    Obj: {object_name} -> created: {created:d}, updated: {updated:d}, deleted: {deleted:d}, untouched: {untouched:d}".format(**obj_stat))
        print("")

        #print(graph_disk_cache.temp_folder)
        shutil.rmtree(graph_disk_cache.temp_folder)

#]
