def load_es_template(apps, schema_editor):
es = Elasticsearch(hosts=[settings.ES_URL], verify_certs=False)
es.put_template(id="climate_data_template", body=json.dumps({
"template": "climate_data",
"mappings": {
"*": {
"properties": {
"measurement": {
"type": "double"
},
"tmax": {
"type": "double"
},
"tmin": {
"type": "double"
},
"tmean": {
"type": "double"
},
"tdev": {
"type": "double"
},
"rainfall": {
"type": "double"
},
"sunshine": {
"type": "double"
},
"region": {
"type": "keyword"
}
}
}
}
}))
class BaseElasticsearchBackend(Base):
"""Base connection wrapper based on the ElasticSearch official library.
It uses two entry points to configure the underlying connection:
* ``transport_class``: the transport class from ``elasticsearch``. By
default ``elasticsearch.transport.Transport``.
* ``connection_class``: the connection class used by the transport class.
It's undefined by default, as it is on the subclasses to provide one.
If any of these elements is not defined, an ``ImproperlyConfigured`` error
will be raised when the backend will try to configure the client.
"""
#: ElasticSearch transport class used by the client class to perform
#: requests.
transport_class = Transport
#: ElasticSearch connection class used by the transport class to perform
#: requests.
connection_class = None
def configure_client(self):
"""Instantiate and configure the ElasticSearch client.
It simply takes the given HOSTS list and uses PARAMS as the keyword
arguments of the ElasticSearch class.
The client's transport_class is given by the class attribute
``transport_class``, and the connection class used by the transport
class is given by the class attribute ``connection_class``.
An ``ImproperlyConfigured`` exception is raised if any of these
elements is undefined.
"""
hosts = self.server['HOSTS']
params = self.server['PARAMS']
if not self.transport_class:
raise ImproperlyConfigured(
'Djangoes backend %r is not properly configured: '
'no transport class provided' % self.__class__)
if not self.connection_class:
raise ImproperlyConfigured(
'Djangoes backend %r is not properly configured: '
'no connection class provided' % self.__class__)
#pylint: disable=star-args
self.client = Elasticsearch(hosts,
transport_class=self.transport_class,
connection_class=self.connection_class,
**params)
# Server methods
# ==============
# The underlying client does not require index names to perform server
# related queries, such as "ping" or "info". The connection wrapper act
# for them as a proxy.
def ping(self, **kwargs):
return self.client.ping(**kwargs)
def info(self, **kwargs):
return self.client.info(**kwargs)
def put_script(self, lang, script_id, body, **kwargs):
return self.client.put_script(lang, script_id, body, **kwargs)
def get_script(self, lang, script_id, **kwargs):
return self.client.get_script(lang, script_id, **kwargs)
def delete_script(self, lang, script_id, **kwargs):
return self.client.delete_script(lang, script_id, **kwargs)
def put_template(self, template_id, body, **kwargs):
return self.client.put_template(template_id, body, **kwargs)
def get_template(self, template_id, body=None, **kwargs):
return self.client.get_template(template_id, body, **kwargs)
def delete_template(self, template_id=None, **kwargs):
return self.client.delete_template(template_id, **kwargs)
# Bulk methods
# ============
# The underlying client does not require index names, but it can be used.
# As it makes sense to not give an index, developers are free to use these
# as they want, as long as they are careful.
def mget(self, body, index=None, doc_type=None, **kwargs):
return self.client.mget(body, index, doc_type, **kwargs)
def bulk(self, body, index=None, doc_type=None, **kwargs):
return self.client.bulk(body, index, doc_type, **kwargs)
def msearch(self, body, index=None, doc_type=None, **kwargs):
return self.client.msearch(body, index, doc_type, **kwargs)
def mpercolate(self, body, index=None, doc_type=None, **kwargs):
return self.client.mpercolate(body, index, doc_type, **kwargs)
# Scroll methods
# ==============
# The underlying client does not require an index to perform scroll.
def scroll(self, scroll_id, **kwargs):
return self.client.scroll(scroll_id, **kwargs)
def clear_scroll(self, scroll_id, body=None, **kwargs):
return self.client.clear_scroll(scroll_id, body, **kwargs)
# Query methods
# =============
# The underlying client requires index names (or alias names) to perform
# queries. The connection wrapper overrides these client methods to
# automatically uses the configured names (indices and/or aliases).
def create(self, doc_type, body, doc_id=None, **kwargs):
return self.client.create(
self.indices, doc_type, body, doc_id, **kwargs)
def index(self, doc_type, body, doc_id=None, **kwargs):
return self.client.index(
self.indices, doc_type, body, doc_id, **kwargs)
def exists(self, doc_id, doc_type='_all', **kwargs):
return self.client.exists(self.indices, doc_id, doc_type, **kwargs)
def get(self, doc_id, doc_type='_all', **kwargs):
return self.client.get(self.indices, doc_id, doc_type, **kwargs)
def get_source(self, doc_id, doc_type='_all', **kwargs):
return self.client.get_source(self.indices, doc_id, doc_type, **kwargs)
def update(self, doc_type, doc_id, body=None, **kwargs):
return self.client.update(
self.indices, doc_type, doc_id, body, **kwargs)
def search(self, doc_type=None, body=None, **kwargs):
return self.client.search(self.indices, doc_type, body, **kwargs)
def search_shards(self, doc_type=None, **kwargs):
return self.client.search_shards(self.indices, doc_type, **kwargs)
def search_template(self, doc_type=None, body=None, **kwargs):
return self.client.search_template(
self.indices, doc_type, body, **kwargs)
def explain(self, doc_type, doc_id, body=None, **kwargs):
return self.client.explain(
self.indices, doc_type, doc_id, body, **kwargs)
def delete(self, doc_type, doc_id, **kwargs):
return self.client.delete(self.indices, doc_type, doc_id, **kwargs)
def count(self, doc_type=None, body=None, **kwargs):
return self.client.count(self.indices, doc_type, body, **kwargs)
def delete_by_query(self, doc_type=None, body=None, **kwargs):
return self.client.delete_by_query(
self.indices, doc_type, body, **kwargs)
def suggest(self, body, **kwargs):
return self.client.suggest(body, self.indices, **kwargs)
def percolate(self, doc_type, doc_id=None, body=None, **kwargs):
return self.client.percolate(
self.indices, doc_type, doc_id, body, **kwargs)
def count_percolate(self, doc_type, doc_id=None, body=None, **kwargs):
return self.client.count_percolate(
self.indices, doc_type, doc_id, body, **kwargs)
def mlt(self, doc_type, doc_id, body=None, **kwargs):
return self.client.mlt(self.indices, doc_type, doc_id, body, **kwargs)
def termvector(self, doc_type, doc_id, body=None, **kwargs):
return self.client.termvector(
self.indices, doc_type, doc_id, body, **kwargs)
def mtermvectors(self, doc_type=None, body=None, **kwargs):
return self.client.mtermvectors(self.indices, doc_type, body, **kwargs)
def benchmark(self, doc_type=None, body=None, **kwargs):
return self.client.benchmark(self.indices, doc_type, body, **kwargs)
def abort_benchmark(self, name=None, **kwargs):
return self.client.abort_benchmark(name, **kwargs)
def list_benchmarks(self, doc_type=None, **kwargs):
return self.client.list_benchmarks(self.indices, doc_type, **kwargs)
class BaseElasticsearchBackend(Base):
"""Base connection wrapper based on the ElasticSearch official library.
It uses two entry points to configure the underlying connection:
* ``transport_class``: the transport class from ``elasticsearch``. By
default ``elasticsearch.transport.Transport``.
* ``connection_class``: the connection class used by the transport class.
It's undefined by default, as it is on the subclasses to provide one.
If any of these elements is not defined, an ``ImproperlyConfigured`` error
will be raised when the backend will try to configure the client.
"""
#: ElasticSearch transport class used by the client class to perform
#: requests.
transport_class = Transport
#: ElasticSearch connection class used by the transport class to perform
#: requests.
connection_class = None
def configure_client(self):
"""Instantiate and configure the ElasticSearch client.
It simply takes the given HOSTS list and uses PARAMS as the keyword
arguments of the ElasticSearch class.
The client's transport_class is given by the class attribute
``transport_class``, and the connection class used by the transport
class is given by the class attribute ``connection_class``.
An ``ImproperlyConfigured`` exception is raised if any of these
elements is undefined.
"""
hosts = self.server['HOSTS']
params = self.server['PARAMS']
if not self.transport_class:
raise ImproperlyConfigured(
'Djangoes backend %r is not properly configured: '
'no transport class provided' % self.__class__)
if not self.connection_class:
raise ImproperlyConfigured(
'Djangoes backend %r is not properly configured: '
'no connection class provided' % self.__class__)
#pylint: disable=star-args
self.client = Elasticsearch(hosts,
transport_class=self.transport_class,
connection_class=self.connection_class,
**params)
# Server methods
# ==============
# The underlying client does not require index names to perform server
# related queries, such as "ping" or "info". The connection wrapper act
# for them as a proxy.
def ping(self, **kwargs):
return self.client.ping(**kwargs)
def info(self, **kwargs):
return self.client.info(**kwargs)
def put_script(self, lang, script_id, body, **kwargs):
return self.client.put_script(lang, script_id, body, **kwargs)
def get_script(self, lang, script_id, **kwargs):
return self.client.get_script(lang, script_id, **kwargs)
def delete_script(self, lang, script_id, **kwargs):
return self.client.delete_script(lang, script_id, **kwargs)
def put_template(self, template_id, body, **kwargs):
return self.client.put_template(template_id, body, **kwargs)
def get_template(self, template_id, body=None, **kwargs):
return self.client.get_template(template_id, body, **kwargs)
def delete_template(self, template_id=None, **kwargs):
return self.client.delete_template(template_id, **kwargs)
# Bulk methods
# ============
# The underlying client does not require index names, but it can be used.
# As it makes sense to not give an index, developers are free to use these
# as they want, as long as they are careful.
def mget(self, body, index=None, doc_type=None, **kwargs):
return self.client.mget(body, index, doc_type, **kwargs)
def bulk(self, body, index=None, doc_type=None, **kwargs):
return self.client.bulk(body, index, doc_type, **kwargs)
def msearch(self, body, index=None, doc_type=None, **kwargs):
return self.client.msearch(body, index, doc_type, **kwargs)
def mpercolate(self, body, index=None, doc_type=None, **kwargs):
return self.client.mpercolate(body, index, doc_type, **kwargs)
# Scroll methods
# ==============
# The underlying client does not require an index to perform scroll.
def scroll(self, scroll_id, **kwargs):
return self.client.scroll(scroll_id, **kwargs)
def clear_scroll(self, scroll_id, body=None, **kwargs):
return self.client.clear_scroll(scroll_id, body, **kwargs)
# Query methods
# =============
# The underlying client requires index names (or alias names) to perform
# queries. The connection wrapper overrides these client methods to
# automatically uses the configured names (indices and/or aliases).
def create(self, doc_type, body, doc_id=None, **kwargs):
return self.client.create(self.indices, doc_type, body, doc_id,
**kwargs)
def index(self, doc_type, body, doc_id=None, **kwargs):
return self.client.index(self.indices, doc_type, body, doc_id,
**kwargs)
def exists(self, doc_id, doc_type='_all', **kwargs):
return self.client.exists(self.indices, doc_id, doc_type, **kwargs)
def get(self, doc_id, doc_type='_all', **kwargs):
return self.client.get(self.indices, doc_id, doc_type, **kwargs)
def get_source(self, doc_id, doc_type='_all', **kwargs):
return self.client.get_source(self.indices, doc_id, doc_type, **kwargs)
def update(self, doc_type, doc_id, body=None, **kwargs):
return self.client.update(self.indices, doc_type, doc_id, body,
**kwargs)
def search(self, doc_type=None, body=None, **kwargs):
return self.client.search(self.indices, doc_type, body, **kwargs)
def search_shards(self, doc_type=None, **kwargs):
return self.client.search_shards(self.indices, doc_type, **kwargs)
def search_template(self, doc_type=None, body=None, **kwargs):
return self.client.search_template(self.indices, doc_type, body,
**kwargs)
def explain(self, doc_type, doc_id, body=None, **kwargs):
return self.client.explain(self.indices, doc_type, doc_id, body,
**kwargs)
def delete(self, doc_type, doc_id, **kwargs):
return self.client.delete(self.indices, doc_type, doc_id, **kwargs)
def count(self, doc_type=None, body=None, **kwargs):
return self.client.count(self.indices, doc_type, body, **kwargs)
def delete_by_query(self, doc_type=None, body=None, **kwargs):
return self.client.delete_by_query(self.indices, doc_type, body,
**kwargs)
def suggest(self, body, **kwargs):
return self.client.suggest(body, self.indices, **kwargs)
def percolate(self, doc_type, doc_id=None, body=None, **kwargs):
return self.client.percolate(self.indices, doc_type, doc_id, body,
**kwargs)
def count_percolate(self, doc_type, doc_id=None, body=None, **kwargs):
return self.client.count_percolate(self.indices, doc_type, doc_id,
body, **kwargs)
def mlt(self, doc_type, doc_id, body=None, **kwargs):
return self.client.mlt(self.indices, doc_type, doc_id, body, **kwargs)
def termvector(self, doc_type, doc_id, body=None, **kwargs):
return self.client.termvector(self.indices, doc_type, doc_id, body,
**kwargs)
def mtermvectors(self, doc_type=None, body=None, **kwargs):
return self.client.mtermvectors(self.indices, doc_type, body, **kwargs)
def benchmark(self, doc_type=None, body=None, **kwargs):
return self.client.benchmark(self.indices, doc_type, body, **kwargs)
def abort_benchmark(self, name=None, **kwargs):
return self.client.abort_benchmark(name, **kwargs)
def list_benchmarks(self, doc_type=None, **kwargs):
return self.client.list_benchmarks(self.indices, doc_type, **kwargs)