ESFluent

A user-friendly module for managing and composing elasticsearch queries.

>>> from es_fluent.builder import QueryBuilder
>>> query_builder = QueryBuilder()
>>> query_builder.and_filter('term', 'planet', 'earth')
>>> query_builder.enable_source()
>>> query_builder.to_query()
{'filter': {'and': [{'term': {'planet': 'earth'}}]}, 'fields': [], '_source': True}

Supported Servers

ESFluent only supports the 1.x stream of elasticsearch.

Features

• A Fluent API for generating and composing queries.
• Support for many elasticsearch filter types.
• Pluggable filter definitions, currently we simply model existing elasticsearch filters.

Concepts and Walkthrough

We’ll walk through some examples of getting started with ESFluent. If you’re the type that likes to shoot first and ask questions later, the tests will exercise all of the API concepts.

The QueryBuilder

The QueryBuilder encapsulates the entire query. It features a to_query() method which generates a JSON payload suitable for POST’ing to elasticsearch.

For the most part, you’ll be adding chains of filters. The QueryBuilder offers additional support for:

• Enabling or disabling the _source document. By default this is not returned, but many use cases demand it. See enable_source() and disable_source().
• Limiting returned fields. See add_field().
• Configuring sorting. See sort().

To create a QueryBuilder instance:

from es_fluent.builder import QueryBuilder
query = QueryBuilder()

Filter Basics

Having created a QueryBuilder instance, you’re likely going to want to add filter criteria. There are two ways of doing this: importing the filter class directly and creating an instance of a filter by hand then agumenting your QueryBuilder instance:

from es_fluent.builder import QueryBuilder
from es_fluent.filters import Term

query = QueryBuilder()
query.add_filter(Term('field_name', 'field_value'))

The alternative approach is to use a shorthand notation:

from es_fluent.builder import QueryBuilder

query = QueryBuilder()
# Args and kwargs are forwarded to appropriate constructors.
query.add_filter('range', 'field_name', lte=0.5)

Each Filter class has a registered name - see the name class attribute - that is used as it’s shorthand identifier.

Negation

Taking a page out of various Python ORMs, we support the ~ operator to negate filters. This effectively wraps the filter in a not filter in elasticsearch:

from es_fluent.builder import QueryBuilder
from es_fluent.filters import Term

query = QueryBuilder()
query.add_filter(~Term('field_name', 'field_value'))

This is equivalent to:

from es_fluent.builder import QueryBuilder
from es_fluent.filters import Not, Term
query = QueryBuilder()
query.add_filter(Not(Term('field_name', 'field_value')))

And also equivalent to:

from es_fluent.builder import QueryBuilder
query = QueryBuilder()
query.add_filter('~term', 'field_name', 'field_value')

Boolean Filters

Boolean filters contain a list of sub-filters. The API provides conveniences for creating nested and / or clauses:

from es_fluent.builder import QueryBuilder
query = QueryBuilder()
query.or_filter('term', 'field_name', 'field_value')
query.or_filter('term', 'another_field', 'another_value')

from es_fluent.builder import QueryBuilder
query = QueryBuilder()
query.and_filter('term', 'field_name', 'field_value')
query.and_filter('term', 'another_field', 'another_value')

Note that with elasticsearch, you cannot have both an And and Or clause at the root level:

from es_fluent.builder import QueryBuilder
query = QueryBuilder()
query.or_filter('term', 'or_clause_field', 'or_clause_value')
query.and_filter('term', 'and_clause_field', 'and_clause_value')

But this can be achieved using:

from es_fluent.builder import QueryBuilder
query = QueryBuilder()

and_clauses = And()
and_clauses.or_filter('term', 'or_clause_field', 'or_clause_value')
and_clauses.and_filter('term', 'and_clause_field', 'and_clause_value')

query.add_filter(and_clauses)