pandagg.node.aggs.abstract module

pandagg.node.aggs.abstract.A(name, type_or_agg=None, **body)

Accept multiple syntaxes, return a AggNode instance.

Parameters:

• type_or_agg –
• body –

Returns:

AggNode

class pandagg.node.aggs.abstract.AggClause(meta=None, **body)

Bases: pandagg.node._node.Node

Wrapper around elasticsearch aggregation concept. https://www.elastic.co/guide/en/elasticsearch/reference/2.3/search-aggregations.html

Each aggregation can be seen both a Node that can be encapsulated in a parent agg.

Define a method to build aggregation request.

BLACKLISTED_MAPPING_TYPES = None

KEY = None

VALUE_ATTRS = None

WHITELISTED_MAPPING_TYPES = None

classmethod extract_bucket_value(response, value_as_dict=False)

extract_buckets(response_value)

get_filter(key)

Return filter query to list documents having this aggregation key.

Parameters:key – string Returns:elasticsearch filter query

line_repr(depth, **kwargs)

Control how node is displayed in tree representation. _ ├── one end │ └── two myEnd └── three

to_dict()

ElasticSearch aggregation queries follow this formatting:

{
    "<aggregation_name>" : {
        "<aggregation_type>" : {
            <aggregation_body>
        }
        [,"meta" : {  [<meta_data_body>] } ]?
    }
}

to_dict() returns the following part (without aggregation name):

{
    "<aggregation_type>" : {
        <aggregation_body>
    }
    [,"meta" : {  [<meta_data_body>] } ]?
}

classmethod valid_on_field_type(field_type)

class pandagg.node.aggs.abstract.BucketAggClause(meta=None, **body)

Bases: pandagg.node.aggs.abstract.AggClause

Bucket aggregation have special abilities: they can encapsulate other aggregations as children. Each time, the extracted value is a ‘doc_count’.

Provide methods: - to build aggregation request (with children aggregations) - to to extract buckets from raw response - to build query to filter documents belonging to that bucket

Note: the aggs attribute’s only purpose is for children initiation with the following syntax: >>> from pandagg.aggs import Terms, Avg >>> agg = Terms( >>> field=’some_path’, >>> aggs={ >>> ‘avg_agg’: Avg(field=’some_other_path’) >>> } >>> )

VALUE_ATTRS = None

extract_buckets(response_value)

get_filter(key)

Provide filter to get documents belonging to document of given key.

class pandagg.node.aggs.abstract.FieldOrScriptMetricAgg(field=None, script=None, meta=None, **body)

Bases: pandagg.node.aggs.abstract.MetricAgg

Metric aggregation based on single field.

VALUE_ATTRS = None

class pandagg.node.aggs.abstract.MetricAgg(meta=None, **body)

Bases: pandagg.node.aggs.abstract.AggClause

Metric aggregation are aggregations providing a single bucket, with value attributes to be extracted.

VALUE_ATTRS = None

extract_buckets(response_value)

get_filter(key)

Return filter query to list documents having this aggregation key.

Parameters:key – string Returns:elasticsearch filter query

class pandagg.node.aggs.abstract.MultipleBucketAgg(keyed=None, key_path='key', meta=None, **body)

Bases: pandagg.node.aggs.abstract.BucketAggClause

IMPLICIT_KEYED = False

VALUE_ATTRS = None

extract_buckets(response_value)

get_filter(key)

Provide filter to get documents belonging to document of given key.

class pandagg.node.aggs.abstract.Pipeline(buckets_path, gap_policy=None, meta=None, **body)

Bases: pandagg.node.aggs.abstract.UniqueBucketAgg

VALUE_ATTRS = None

get_filter(key)

Provide filter to get documents belonging to document of given key.

class pandagg.node.aggs.abstract.Root(meta=None, **body)

Bases: pandagg.node.aggs.abstract.AggClause

Not a real aggregation. Just the initial empty dict (used as lighttree.Tree root).

KEY = '_root'

classmethod extract_bucket_value(response, value_as_dict=False)

extract_buckets(response_value)

line_repr(depth, **kwargs)

Control how node is displayed in tree representation. _ ├── one end │ └── two myEnd └── three

class pandagg.node.aggs.abstract.ScriptPipeline(script, buckets_path, gap_policy=None, meta=None, **body)

Bases: pandagg.node.aggs.abstract.Pipeline

KEY = None

VALUE_ATTRS = 'value'

class pandagg.node.aggs.abstract.UniqueBucketAgg(meta=None, **body)

Bases: pandagg.node.aggs.abstract.BucketAggClause

Aggregations providing a single bucket.

VALUE_ATTRS = None

extract_buckets(response_value)

get_filter(key)

Provide filter to get documents belonging to document of given key.