turms 0.10.2

graphql-codegen powered by pydantic

turms

Goal

Turms is a graphql-codegen inspired code generator for python that generates typed and serializable python code from your graphql schema and documents. Just define your query in standard graphql syntax and let turms create fully typed queries/mutation and subscriptions, that you can use in your favourite IDE.

Turms allows you to easily generate both server-side and client-side code for your GraphQL API.

Schema (Server) Generation:

Can generate the following types from your graphql SDL schema:

• Enums
• Inputs
• Objects
• Scalars
• Directives

Sepcific generation supported for:

• Strawberry

Documents (Client) Generation

Can generate the following pydantic models from your graphql documents:

• Enums
• Inputs
• Scalars
• Fragments
• Operations

Features

• Fully typed, fully documented code generation
• Schema and Document based code generation
• Compatible with popular graphql libraries (strawberry, gql, rath, etc.)
• Support for custom scalars, custom directives, ...
• Powerful plugin system (e.g. custom Linting, custom formatting, etc.)
• Operation functions like query, mutation, subscription (e.g. data= get_capsules())
• Compliant with graphl-config
• Code migration support (trying to merge updates into existing code)

Installation

pip install turms

turms is a pure development library and will not introduce any dependency on itself into your code, so we recommend installing turms as a development dependency.

uvx turms init

As of now turms only supports python 3.9 and higher (as we rely on ast unparsing)

Configuration

Turms relies on and complies with graphql-config and searches your current working dir for the graphql-config file.

Document based generation

Based on pydantic models

projects:
  default:
    schema: http://api.spacex.land/graphql/
    documents: graphql/**.graphql
    extensions:
      turms: # path for configuration for turms
        out_dir: examples/api
        plugins: # path for plugin configuration
          - type: turms.plugins.enums.EnumsPlugin
          - type: turms.plugins.inputs.InputsPlugin
          - type: turms.plugins.fragments.FragmentsPlugin
          - type: turms.plugins.operation.OperationsPlugin
          - type: turms.plugins.funcs.FuncsPlugin
        processors:
          - type: turms.processor.black.BlackProcessor
          - type: turms.processor.isort.IsortProcessor
        scalar_definitions:
          uuid: str
          timestamptz: str
          Date: str

Schema based generation

Based on strawberry models

projects:
  default:
    schema: beasts.graphql
    extensions:
      turms:
        skip_forwards: true
        out_dir: api
        stylers:
          - type: turms.stylers.capitalize.CapitalizeStyler
          - type: turms.stylers.snake_case.SnakeCaseStyler
        plugins:
          - type: turms.plugins.strawberry.StrawberryPlugin # generates a strawberry schema
        processors:
          - type: turms.processors.disclaimer.DisclaimerProcessor
          - type: turms.processors.black.BlackProcessor
          - type: turms.processors.isort.IsortProcessor
          - type: turms.processors.merge.MergeProcessor # merges the formated schema with already defined functions
        scalar_definitions:
          uuid: str
          _Any: typing.Any

Usage

Once you have configured turms you can generate your code by running

turms gen

Why Turms

In Etruscan religion, Turms (usually written as 𐌕𐌖𐌓𐌌𐌑 Turmś in the Etruscan alphabet) was the equivalent of Roman Mercury and Greek Hermes, both gods of trade and the messenger god between people and gods.

Transport Layer

Turms does not come with a default transport layer but if you are searching for an Apollo-like GraphQL Client you can check out rath, that works especially well with turms.

Examples

This github repository also contains some examples on how to use turms with popular libraries in the graphql ecosystem.