pip install pydantic-glue

Converts pydantic schemas to json schema and then to AWS glue schema, so in theory anything that can be converted to JSON Schema could also work.

When using AWS Kinesis Firehose in a configuration that receives JSONs and writes parquet files on S3, one needs to define a AWS Glue table so Firehose knows what schema to use when creating the parquet files.

AWS Glue lets you define a schema using Avro or JSON Schema and then to create a table from that schema, but as of *May 2022` there are limitations on AWS that tables that are created that way can't be used with Kinesis Firehose.

https://stackoverflow.com/questions/68125501/invalid-schema-error-in-aws-glue-created-via-terraform

This is also confirmed by AWS support.

What one could do is create a table set the columns manually, but this means you now have two sources of truth to maintain.

This tool allows you to define a table in pydantic and generate a JSON with column types that can be used with terraform to create a Glue table.

Take the following pydantic class

from pydantic import BaseModel
from typing import List


class Bar(BaseModel):
    name: str
    age: int


class Foo(BaseModel):
    nums: List[int]
    bars: List[Bar]
    other: str

Running pydantic-glue

pydantic-glue -f example.py -c Foo

you get this JSON in the terminal:

{
  "//": "Generated by pydantic-glue at 2022-05-25 12:35:55.333570. DO NOT EDIT",
  "columns": {
    "nums": "array<int>",
    "bars": "array<struct<name:string,age:int>>",
    "other": "string"
  }
}

and can be used in terraform like that

locals {
  columns = jsondecode(file("${path.module}/glue_schema.json")).columns
}

resource "aws_glue_catalog_table" "table" {
  name          = "table_name"
  database_name = "db_name"

  storage_descriptor {
    dynamic "columns" {
      for_each = local.columns

      content {
        name = columns.key
        type = columns.value
      }
    }
  }
}

Alternatively you can run CLI with -o flag to set output file location:

pydantic-glue -f example.py -c Foo -o example.json -l

• pydantic gets converted to JSON Schema
• the JSON Schema types get mapped to Glue types recursively

• Not all types are supported, I just add types as I need them, but adding types is very easy, feel free to open issues or send a PR if you stumbled upon a non-supported use case
• the tool could be easily extended to working with JSON Schema directly
• thus, anything that can be converted to a JSON Schema should also work.