pydantic-to-elastic

A simple CLI utility for converting Pydantic models to Elasticsearch mappings.

Installation

From source

git clone https://github.com/malinkinsa/pydantic-to-elastic.git && cd pydantic-to-elastic
pip install .

CLI options

Prop	Description	Required	Default value
--input	Path to the file containing Pydantic models.	True
--output	Output type of result. Possible values: "console" or "file".	False	console
--output_path	Path and filename to save the output file (required if --output is set to 'file').	False
--output_format	Output format for JSON data. Use 'json' for compact single-line JSON or 'pretty' for pretty-printed JSON with 4-space indentation.	False	json
--submodel_type	Specifies the submodel type. Possible values: "nested" or "object"	False	nested
--text_fields	List of fields that must be of type 'text'. Can be specified multiple times.	False

Usage

For example, you have a model user_models.py

from pydantic import BaseModel
from typing import List

class Address(BaseModel):
    street: str
    city: str
    zip_code: str

class User(BaseModel):
    name: str
    age: int
    address: Address
    hobbies: List[str]

Execute the command for converting these models into mapping json:

pydantic2es --input ./user_models.py --output_format pretty

And you will obtain the following result:

{
    "mappings": {
        "properties": {
            "name": {
                "type": "keyword"
            },
            "age": {
                "type": "integer"
            },
            "address": {
                "type": "nested",
                "properties": {
                    "street": {
                        "type": "keyword"
                    },
                    "city": {
                        "type": "keyword"
                    },
                    "zip_code": {
                        "type": "keyword"
                    }
                }
            },
            "hobbies": {
                "type": "keyword"
            }
        }
    }
}