The Python Way to Elasticsearch

Simplify Elasticsearch
Amplify Productivity

You Know, For Elasticsearch

Elastro turns Elasticsearch into a high-velocity developer tool that replaces verbose REST calls with focused Python constructs and a unified CLI. Now teams can build, test, and automate faster.

Get Started View Documentation

example.py

1from elastro import ElasticsearchClient, DocumentManager
2from elastro.advanced import QueryBuilder
3 
4# Initialize and connect
5client = ElasticsearchClient()
6client.connect()
7doc_manager = DocumentManager(client)
8 
9# Build queries with QueryBuilder
10query_builder = QueryBuilder()
11bool_query = query_builder.bool()
12bool_query.must(QueryBuilder().match("name", "laptop"))
13bool_query.must(QueryBuilder().range("price", gte=500, lte=2000))
14query = query_builder.build()
15 
16results = doc_manager.search("products", query)
17print(f"Found {results['hits']['total']['value']} products!")

from elastro import ElasticsearchClient, DocumentManager
from elastro.advanced import QueryBuilder

# Initialize and connect
client = ElasticsearchClient()
client.connect()
doc_manager = DocumentManager(client)

# Build queries with QueryBuilder
query_builder = QueryBuilder()
bool_query = query_builder.bool()
bool_query.must(QueryBuilder().match("name", "laptop"))
bool_query.must(QueryBuilder().range("price", gte=500, lte=2000))
query = query_builder.build()

results = doc_manager.search("products", query)
print(f"Found {results['hits']['total']['value']} products!")

Everything You Need

Features that make Elasticsearch feel effortless

From index management to complex aggregations, Elastro provides a complete toolkit for Python developers working with Elasticsearch.

Index Management

Create, update, and delete indices with intuitive methods. No more complex JSON mappings.

Powerful Query Builder

Build complex queries with a fluent, chainable API. Match, filter, range, and more.

CLI & API Combined

Use the command-line for quick operations or integrate seamlessly via Python API.

Advanced Aggregations

Powerful aggregation builder for analytics, metrics, and data visualization.

Datastream Support

Handle time-series data and datastreams with dedicated management tools.

Type-Safe with Pydantic

Built-in validation and type safety using Pydantic models for reliable data handling.

Smart Ingest Engine

Client-side data processing, format conversion (CSV, SQL, NDJSON), and pre-flight schema validation.

AI Enrichment

Build Grok patterns interactively, summarize text, and detect PII with local and remote LLMs.

Reduce Boilerplate

Lightning Fast

Production Ready

Well Documented

Before & After

Write cleaner code, faster

See how Elastro transforms verbose Elasticsearch interactions into elegant, readable Python code.

Before Elastro

Traditional elasticsearch-py

query_before.py

1from elasticsearch import Elasticsearch
2 
3es = Elasticsearch(['http://localhost:9200'])
4 
5# Complex nested dictionary structure
6query = {
7    "query": {
8        "bool": {
9            "must": [
10                {"match": {"name": "laptop"}},
11                {"range": {
12                    "price": {
13                        "gte": 500,
14                        "lte": 2000
15                    }
16                }}
17            ]
18        }
19    },
20    "sort": [{"rating": {"order": "desc"}}],
21    "size": 10
22}
23 
24results = es.search(index="products", body=query)

❌ Verbose • ❌ Error-prone • ❌ Hard to maintain

With Elastro

Clean, fluent API

query_after.py

1from elastro import ElasticsearchClient, DocumentManager
2from elastro.advanced import QueryBuilder
3 
4client = ElasticsearchClient()
5client.connect()
6doc_manager = DocumentManager(client)
7 
8# Clean, builder API
9query_builder = QueryBuilder()
10bool_query = query_builder.bool()
11bool_query.must(QueryBuilder().match("name", "laptop"))
12bool_query.must(QueryBuilder().range("price", gte=500, lte=2000))
13query = query_builder.build()
14 
15results = doc_manager.search(
16    "products",
17    query,
18    {"sort": [{"rating": {"order": "desc"}}], "size": 10}
19)

✓ Readable • ✓ Type-safe • ✓ Maintainable

60%

Less Code

Faster Development

Dict Nesting

Ready in Seconds

Get started in one command

Install Elastro and start simplifying your Elasticsearch operations immediately.

$ pip install elastro-client

Quick Start Example

Full Docs

quickstart.py

1from elastro import ElasticsearchClient, IndexManager, DocumentManager
2from elastro.advanced import QueryBuilder
3 
4# Connect to your Elasticsearch cluster
5client = ElasticsearchClient(
6    hosts=["http://localhost:9200"]
7)
8client.connect()
9 
10# Create managers
11index_manager = IndexManager(client)
12doc_manager = DocumentManager(client)
13 
14# Create an index with mappings
15index_manager.create(
16    "my_index",
17    mappings={
18        "properties": {
19            "title": {"type": "text"},
20            "views": {"type": "integer"}
21        }
22    }
23)
24 
25# Index a document
26doc_manager.index(
27    "my_index",
28    id="1",
29    document={"title": "Hello Elastro!", "views": 100}
30)
31 
32# Search with QueryBuilder
33query_builder = QueryBuilder()
34query_builder.match_all()
35query = query_builder.build()
36results = doc_manager.search("my_index", query)
37print(results["hits"]["hits"])

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Simplify ElasticsearchAmplify Productivity