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Meilisearch Python is the Meilisearch API client for Python developers.

Meilisearch is an open-source search engine. Learn more about Meilisearch.

Table of Contents <!-- omit in TOC -->

• 📖 Documentation
• ⚡ Supercharge your Meilisearch experience
• 🔧 Installation
• 🚀 Getting started
• 🤖 Compatibility with Meilisearch
• 💡 Learn more
• ⚙️ Contributing

📖 Documentation

To learn more about Meilisearch Python, refer to the in-depth Meilisearch Python documentation. To learn more about Meilisearch in general, refer to our documentation or our API reference.

⚡ Supercharge your Meilisearch experience

Say goodbye to server deployment and manual updates with Meilisearch Cloud. Get started with a 14-day free trial! No credit card required.

🔧 Installation

Note: Python 3.8+ is required.

With pip3 in command line:

pip3 install meilisearch

Run Meilisearch <!-- omit in toc -->

There are many easy ways to download and run a Meilisearch instance.

For example, using the curl command in your Terminal:

# Install Meilisearch
curl -L https://install.meilisearch.com | sh

# Launch Meilisearch
./meilisearch --master-key=masterKey

NB: you can also download Meilisearch from Homebrew or APT or even run it using Docker.

🚀 Getting started

Add Documents <!-- omit in toc -->

import meilisearch

client = meilisearch.Client('http://127.0.0.1:7700', 'masterKey')

# An index is where the documents are stored.
index = client.index('movies')

documents = [
      { 'id': 1, 'title': 'Carol', 'genres': ['Romance', 'Drama'] },
      { 'id': 2, 'title': 'Wonder Woman', 'genres': ['Action', 'Adventure'] },
      { 'id': 3, 'title': 'Life of Pi', 'genres': ['Adventure', 'Drama'] },
      { 'id': 4, 'title': 'Mad Max: Fury Road', 'genres': ['Adventure', 'Science Fiction'] },
      { 'id': 5, 'title': 'Moana', 'genres': ['Fantasy', 'Action']},
      { 'id': 6, 'title': 'Philadelphia', 'genres': ['Drama'] },
]

# If the index 'movies' does not exist, Meilisearch creates it when you first add the documents.
index.add_documents(documents) # => { "uid": 0 }

With the task uid, you can check the status (enqueued, canceled, processing, succeeded or failed) of your documents addition using the task.

Basic Search <!-- omit in toc -->

# Meilisearch is typo-tolerant:
index.search('caorl')

Output:

{
  "hits": [
    {
      "id": 1,
      "title": "Carol",
      "genre": ["Romance", "Drama"]
    }
  ],
  "offset": 0,
  "limit": 20,
  "processingTimeMs": 1,
  "query": "caorl"
}

Custom Search <!-- omit in toc -->

All the supported options are described in the search parameters

index.search(
  'phil',
  {
    'attributesToHighlight': ['*'],
  }
)

JSON output:

{
  "hits": [
    {
      "id": 6,
      "title": "Philadelphia",
      "_formatted": {
        "id": 6,
        "title": "<em>Phil</em>adelphia",
        "genre": ["Drama"]
      }
    }
  ],
  "offset": 0,
  "limit": 20,
  "processingTimeMs": 0,
  "query": "phil"
}

Custom Search With Filters <!-- omit in toc -->

If you want to enable filtering, you must add your attributes to the filterableAttributes index setting.

index.update_filterable_attributes([
  'id',
  'genres'
])

Custom Serializer for documents <!-- omit in toc -->

If your documents contain fields that the Python JSON serializer does not know how to handle you can use your own custom serializer.

from datetime import datetime
from json import JSONEncoder
from uuid import uuid4


class CustomEncoder(JSONEncoder):
    def default(self, o):
        if isinstance(o, (UUID, datetime)):
            return str(o)

        # Let the base class default method raise the TypeError
        return super().default(o)


documents = [
    {"id": uuid4(), "title": "test 1", "when": datetime.now()},
    {"id": uuid4(), "title": "Test 2", "when": datetime.now()},
]
index.add_documents(documents, serializer=CustomEncoder)

You only need to perform this operation once.

Note that Meilisearch will rebuild your index whenever you update filterableAttributes. Depending on the size of your dataset, this might take time. You can track the process using the task.

Then, you can perform the search:

index.search(
  'wonder',
  {
    'filter': ['id > 1 AND genres = Action']
  }
)

{
  "hits": [
    {
      "id": 2,
      "title": "Wonder Woman",
      "genres": ["Action", "Adventure"]
    }
  ],
  "offset": 0,
  "limit": 20,
  "estimatedTotalHits": 1,
  "processingTimeMs": 0,
  "query": "wonder"
}

🤖 Compatibility with Meilisearch

This package guarantees compatibility with version v1.2 and above of Meilisearch, but some features may not be present. Please check the issues for more info.

💡 Learn more

The following sections in our main documentation website may interest you:

• Manipulate documents: see the API references or read more about documents.
• Search: see the API references.
• Manage the indexes: see the API references or read more about indexes.
• Configure the index settings: see the API references or follow our guide on settings parameters.

⚙️ Contributing

Any new contribution is more than welcome in this project!

If you want to know more about the development workflow or want to contribute, please visit our contributing guidelines for detailed instructions!

Meilisearch provides and maintains many SDKs and Integration tools like this one. We want to provide everyone with an amazing search experience for any kind of project. If you want to contribute, make suggestions, or just know what's going on right now, visit us in the integration-guides repository.