ElasticQuery

A simple query builder for Elasticsearch. Install with pip install elasticquery.

Synopsis

from elasticquery import ElasticQuery, Filter, Query, Aggregate

q = ElasticQuery()

# Filters & queries
q.must(
    Filter.range('field', 0, 500),
    Filter.terms(my_field=['list', 'of', 'terms']),
    Filter.or_filter(
        Query.string(field='matching string'),
        Query.raw_string('field: another matching string')
    )
)

# Nested filter/query
q.should(
    Query.nested('path', must=[
        Query.term(field='match')
    ])
)

# Aggregates
q.aggregate(Aggregate.sum('aggregate_name', 'field_name'))

# Sub aggregates
q.aggregate(
    Aggregate.terms('aggregate_name', 'field_name') \
    .sub(Aggregate.sum('sub_aggregate_name', 'field_name'))
)

# Print out JSON ready for ES
print q.json(indent=4)

API: ElasticQuery

q = ElasticQuery()

q.json()

Return a json string ready to send to Elasticsearch.

q.fields(fields)

fields: list of fields to return

q.sort(field, order=False)

Sort the result set by a field, order optional.

q.must(*Query/Filter)

Search where the Query/Filter object matches.

q.should(*Query/Filter)

Search where the Query/Filter object might matches.

q.must_not(*Query/Filter)

Search where the Query/Filter object does not match.

q.aggregate(*Aggregate)

Add some Aggregates to our search query.

Filter

Filter.nested(path, must=None, should=None, must_not=None)

Adds a nested query.

musts, shoulds & must_nots: all lists containing Query or Filter objects.

Filter.range(field, gt=None, gte=None, lt=None, lte=None)

Filter.prefix(**kwargs)

Prefix multiple keys.

Filter.term(**kwargs)

Search multiple key=>value terms.

Filter.terms(**kwargs)

Search multiple key=>[values] terms.

Filter.match(**kwargs)

Search multiple key=>[values].

Filter.missing(field)

Filter for missing/null fields.

Filter.raw_string(string, default_operator='AND')

Adds a raw query string to match against.

Filter.string(default_operator='AND', **kwargs)

This builds a query string based on kwargs. Values can be simple (ints/strings) or lists, in which case they are OR'd together.

Filter.or_filter(*args)

Or the arg filters/queries together.

Query

The Query class inherits from Filter, see above for API details.

Query.mlt(field, match, min_term_frequency=1, max_query_terms=False)

Searches objects where field is similar to the match.

Aggregate

Aggregate.sum(name, field)

Get sum of a field.

Aggregate.avg(name, field)

Get the average value across a field.

Aggregate.min(name, field)

Get the lowest value of a field.

Aggregate.max(name, field)

Get the highest value of a field.

Aggregate.stats(name, field)

Get stats on a field.

Aggregate.extended_stats(name, field)

Get extended stats on a field.

Aggregate.missing(name, field)

Count how many documents are missing a given field.

Aggregate.value_count(name, field)

Count how many documents contain a given field.

Aggregate.range(name, field, ranges)

Generate multiple buckets based on the input ranges.

Aggregate.histogram(name, field, interval)

Generate a histogram.

Aggregate.date_histogram(name, field, interval='day')

Generate a date histogram.

Aggregate.terms(name, field)

Count number of terms on a field.

Aggregate.nested(name, path)

Create a nested aggregation (for use with sub aggregates, see Aggregate.sub).

Aggregate.filter(name, musts=None, shoulds=None, must_nots=None)

Creates a filtered aggregate (for use with sub aggregates, see Aggregate.sub).