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Update the code-samples.meilisearch.yml according to the [integration-guides issue](meilisearch/integration-guides#209) for more information and the complete description about what should be done here check that issue.

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Meilisearch Python

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The Meilisearch API client written for Python 🐍

Meilisearch Python is the Meilisearch API client for Python developers.

Meilisearch is an open-source search engine. Discover what Meilisearch is!

Table of Contents

📖 Documentation

See our Documentation or our API References.

🔧 Installation

Note: Python 3.6+ is required.

With pip3 in command line:

pip3 install meilisearch

Run Meilisearch

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 | 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

import meilisearch

client = meilisearch.Client('', '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, processing, succeeded or failed) of your documents addition using the task.

Basic Search

# Meilisearch is typo-tolerant:'caorl')


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

Custom Search

All the supported options are described in the search parameters section of the documentation.
    '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

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


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:
    '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 only guarantees the compatibility with the version v0.28.0 of Meilisearch.

💡 Learn More

The following sections may interest you:

⚙️ Development Workflow and 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.