Awesome
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
- Graphene
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.
poetry add -D turms
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.