Python code generator that takes graphql schema, queries, mutations and subscriptions and generates Python package with fully typed and asynchronous GraphQL client.
It's available as ariadne-codegen
command and reads configuration from the pyproject.toml
file:
$ ariadne-codegen
It can also be run as python -m ariadne_codegen
.
- Generate pydantic models from schema types, inputs and enums.
- Generate pydantic models for GraphQL results.
- Generate client package with each GraphQL operation available as async method.
Ariadne Code Generator can be installed with pip:
$ pip install ariadne-codegen
To support subscriptions, default base client requires websockets
package:
$ pip install ariadne-codegen[subscriptions]
ariadne-codegen
reads configuration from [tool.ariadne-codegen]
section in your pyproject.toml
. You can use other configuration file with --config
option, eg. ariadne-codegen --config custom_file.toml
Minimal configuration for client generation:
[tool.ariadne-codegen]
schema_path = "schema.graphql"
queries_path = "queries.graphql"
Required settings:
queries_path
- path to file/directory with queries (Can be optional ifenable_custom_operations
is used)
One of the following 2 parameters is required, in case of providing both of them schema_path
is prioritized:
schema_path
- path to file/directory with graphql schemaremote_schema_url
- url to graphql server, where introspection query can be perfomed
Optional settings:
remote_schema_headers
- extra headers that are passed along with introspection query, eg.{"Authorization" = "Bearer: token"}
. To include an environment variable in a header value, prefix the variable with$
, eg.{"Authorization" = "$AUTH_TOKEN"}
remote_schema_verify_ssl
(defaults totrue
) - a flag that specifies wheter to verify ssl while introspecting remote schematarget_package_name
(defaults to"graphql_client"
) - name of generated packagetarget_package_path
(defaults to cwd) - path where to generate packageclient_name
(defaults to"Client"
) - name of generated client classclient_file_name
(defaults to"client"
) - name of file with generated client classbase_client_name
(defaults to"AsyncBaseClient"
) - name of base client classbase_client_file_path
(defaults to.../ariadne_codegen/client_generators/dependencies/async_base_client.py
) - path to file wherebase_client_name
is definedenums_module_name
(defaults to"enums"
) - name of file with generated enums modelsinput_types_module_name
(defaults to"input_types"
) - name of file with generated input types modelsfragments_module_name
(defaults to"fragments"
) - name of file with generated fragments modelsinclude_comments
(defaults to"stable"
) - option which sets content of comments included at the top of every generated file. Valid choices are:"none"
(no comments),"timestamp"
(comment with generation timestamp),"stable"
(comment contains a message that this is a generated file)convert_to_snake_case
(defaults totrue
) - a flag that specifies whether to convert fields and arguments names to snake caseinclude_all_inputs
(defaults totrue
) - a flag specifying whether to include all inputs defined in the schema, or only those used in supplied operationsinclude_all_enums
(defaults totrue
) - a flag specifying whether to include all enums defined in the schema, or only those used in supplied operationsasync_client
(defaults totrue
) - default generated client isasync
, change this to optionfalse
to generate synchronous client insteadopentelemetry_client
(defaults tofalse
) - default base clients don't support any performance tracing. Change this option totrue
to use the base client with Open Telemetry support.files_to_include
(defaults to[]
) - list of files which will be copied into generated packageplugins
(defaults to[]
) - list of plugins to use during generationenable_custom_operations
(defaults tofalse
) - enables building custom operations. Generates additional files that contains all the classes and methods for generation.
The custom operation builder allows you to create complex GraphQL queries in a structured and intuitive way.
import asyncio
from graphql_client import Client
from graphql_client.custom_fields import (
ProductFields,
ProductTranslatableContentFields,
ProductTranslationFields,
TranslatableItemConnectionFields,
TranslatableItemEdgeFields,
)
from graphql_client.custom_queries import Query
from graphql_client.enums import LanguageCodeEnum, TranslatableKinds
async def get_products():
# Create a client instance with the specified URL and headers
client = Client(
url="https://saleor.cloud/graphql/",
headers={"authorization": "bearer ..."},
)
# Build the queries
product_query = Query.product(id="...", channel="channel-uk").fields(
ProductFields.id,
ProductFields.name,
)
translation_query = Query.translations(kind=TranslatableKinds.PRODUCT, first=10).fields(
TranslatableItemConnectionFields.edges().alias("aliased_edges").fields(
TranslatableItemEdgeFields.node.on(
"ProductTranslatableContent",
ProductTranslatableContentFields.id,
ProductTranslatableContentFields.product_id,
ProductTranslatableContentFields.name,
)
)
)
# Execute the queries with an operation name
response = await client.query(
product_query,
translation_query,
operation_name="get_products",
)
print(response)
# Run the async function
asyncio.run(get_products())
- Building the Product Query:
- The Query.product(id="...", channel="channel-uk") initiates a query for a product with the specified ID and channel.
- .fields(ProductFields.id, ProductFields.name) specifies the fields to retrieve for the product: id and name.
- Building the Translation Query:
- The Query.translations(kind=TranslatableKinds.PRODUCT, first=10) initiates a query for product translations.
- .fields(...) specifies the fields to retrieve for the translations.
- .alias("aliased_edges") renames the edges field to aliased_edges.
- .on("ProductTranslatableContent", ...) specifies the fields to retrieve if the node is of type ProductTranslatableContent: id, product_id, and name.
- Executing the Queries:
- The client.query(...) method is called with the built queries and an operation name "get_products".
- This method sends the queries to the server and retrieves the response.
Note: queries_path is optional when enable_custom_operations is set to true
[tool.ariadne-codegen]
schema_path = "schema.graphql"
include_comments = "none"
target_package_name = "example_client"
enable_custom_operations = true
Ariadne Codegen implements a plugin system that enables further customization and fine-tuning of generated Python code. It’s documentation is available separately in the PLUGINS.md file.
Ariadne Codegen ships with optional plugins importable from the ariadne_codegen.contrib
package:
-
ariadne_codegen.contrib.shorter_results.ShorterResultsPlugin
- This plugin processes generated client methods for operations where only single top field is requested, so they return this field's value directly instead of operation's result type. For example get_user method generated for queryGetUser() { user(...) { ... }}
will return value of user field directly instead ofGetUserResult
. -
ariadne_codegen.contrib.extract_operations.ExtractOperationsPlugin
- This extracts query strings from generated client's methods into separateoperations.py
module. It also modifies the generated client to import these definitions. Generated module name can be customized by addingoperations_module_name="custom_name"
to the[tool.ariadne-codegen.operations]
section in config. Eg.:[tool.ariadne-codegen] ... plugins = ["ariadne_codegen.contrib.extract_operations.ExtractOperationsPlugin"] [tool.ariadne-codegen.extract_operations] operations_module_name = "custom_operations_module_name"
-
ariadne_codegen.contrib.client_forward_refs.ClientForwardRefsPlugin
- This plugin changes generated client module moving all Pydantic models imports under theTYPE_CHECKING
condition, making them forward references. This greatly improves the import performance of theclient
module. -
ariadne_codegen.contrib.no_reimports.NoReimportsPlugin
- This plugin removes content of generated__init__.py
. This is useful in scenarios where generated plugins contain so many Pydantic models that client's eager initialization of entire package on first import is very slow.
Generated client can be imported from package:
from {target_package_name}.{client_file_name} import {client_name}
Example with default settings:
from graphql_client.client import Client
Client (with default base client), takes passed headers and attaches them to every sent request.
client = Client("https://example.com/graphql", {"Authorization": "Bearer token"})
For more complex scenarios, you can pass your own http client:
client = Client(http_client=CustomComplexHttpClient())
CustomComplexHttpClient
needs to be an instance of httpx.AsyncClient
for async client, or httpx.Client
for sync.
To handle subscriptions, default AsyncBaseClient
uses websockets and implements graphql-transport-ws subprotocol. Arguments ws_origin
and ws_headers
are added as headers to the handshake request and ws_connection_init_payload
is used as payload of ConnectionInit message.
Default base client (AsyncBaseClient
or BaseClient
) checks if any part of variables
dictionary is an instance of Upload
. If at least one instance is found then client sends multipart request according to GraphQL multipart request specification.
Class Upload
is included in generated client and can be imported from it:
from {target_package_name} import Upload
By default we use this class to represent graphql scalar Upload
. For schema with different name for this scalar, you can still use Upload
and default client for file uploads:
[tool.ariadne-codegen.scalars.OTHERSCALAR]
type = "Upload"
When config option opentelemetry_client
is set to true
then default, included base client is replaced with one that implements the opt-in Open Telemetry support. By default this support does nothing but when the opentelemetry-api
package is installed and the tracer
argument is provided then the client will create spans with data about performed requests.
Tracing arguments handled by BaseClientOpenTelemetry
:
tracer
:Optional[Union[str, Tracer]] = None
- tracer object or name which will be passed to theget_tracer
methodroot_context
:Optional[Context] = None
- optional context added to root spanroot_span_name
:str = "GraphQL Operation"
- name of root span
AsyncBaseClientOpenTelemetry
supports all arguments which BaseClientOpenTelemetry
does, but also exposes additional arguments regarding websockets:
ws_root_context
:Optional[Context] = None
- optional context added to root span for websocket connectionws_root_span_name
:str = "GraphQL Subscription"
- name of root span for websocket connection
By default, not built-in scalars are represented as typing.Any
in generated client.
You can provide information about specific scalar by adding section to pyproject.toml
:
[tool.ariadne-codegen.scalars.{graphql scalar name}]
type = "(required) python type name"
serialize = "function used to serialize scalar"
parse = "function used to create scalar instance from serialized form"
For each custom scalar client will use given type
in all occurrences of {graphql scalar name}
. If provided, serialize
and parse
will be used for serialization and deserialization. In result models type
will be annotated with BeforeValidator
, eg. Annotated[type, BeforeValidator(parse)]
. In inputs annotation will use PlainSerializer
, eg. Annotated[type, PlainSerializer(serialize)]
.
If type
/serialize
/parse
contains at least one .
then string will be split by it's last occurrence. First part will be used as module to import from, and second part as type/method name. For example, type = "custom_scalars.a.ScalarA"
will produce from custom_scalars.a import ScalarA
.
In this case scalar is mapped to built-in str
which doesn't require custom serialize
and parse
methods.
[tool.ariadne-codegen.scalars.SCALARA]
type = "str"
In this scenario scalar is represented as datetime
, so it needs to be imported. Pydantic handles serialization and deserialization so custom parse
and serialize
is not necessary.
[tool.ariadne-codegen.scalars.DATETIME]
type = "datetime.datetime"
In this example scalar is represented as class TypeB
. Pydantic can't handle serialization and deserialization so custom parse
and serialize
is necessary. To provide type
, parse
and serialize
implementation we can use files_to_include
to copy type_b.py
file.
[tool.ariadne-codegen]
...
files_to_include = [".../type_b.py"]
[tool.ariadne-codegen.scalars.SCALARB]
type = ".type_b.TypeB"
parse = ".type_b.parse_b"
serialize = ".type_b.serialize_b"
# inputs.py
class TestInput(BaseModel):
value_b: Annotated[TypeB, PlainSerializer(serialize_b)]
# get_b.py
class GetB(BaseModel):
query_b: Annotated[TypeB, BeforeValidator(parse_b)]
# client.py
class Client(AsyncBaseClient):
async def test_mutation(self, value: TypeB) -> TestMutation:
...
variables: Dict[str, object] = {
"value": serialize_b(value),
}
...
mixin
directive allows to extend class generated for query/mutation field with custom logic.
mixin
takes two required arguments:
from
- name of a module to import fromimport
- name of a parent class
Generated class will use import
as extra base class, and import will be added to the file.
from {from} import {import}
...
class OperationNameField(BaseModel, {import}):
...
This directive can be used along with files_to_include
option to extend functionality of generated classes.
Query with mixin
directive:
query listUsers {
users @mixin(from: ".mixins", import: "UsersMixin") {
id
}
}
Part of pyproject.toml
with files_to_include
(mixins.py
contains UsersMixin
implementation)
files_to_include = [".../mixins.py"]
Part of generated list_users.py
file:
...
from .mixins import UsersMixin
...
class ListUsersUsers(BaseModel, UsersMixin):
...
To generate multiple different clients you can store config for each in different file, then provide path to config file by --config
option, eg.
ariadne-codegen --config clientA.toml
ariadne-codegen --config clientB.toml
Generated code requires:
- pydantic
- httpx
- websockets (only for default async base client)
Both httpx
and websockets
dependencies can be avoided by providing another base client class with base_client_file_path
and base_client_name
options.
Example with simple schema and few queries and mutations is available here.
Instead of generating a client, you can generate a file with a copy of a GraphQL schema. To do this call ariadne-codegen
with graphqlschema
argument:
ariadne-codegen graphqlschema
graphqlschema
mode reads configuration from the same place as client
but uses only schema_path
, remote_schema_url
, remote_schema_headers
, remote_schema_verify_ssl
options to retrieve the schema and plugins
option to load plugins.
In addition to the above, graphqlschema
mode also accepts additional settings specific to it:
A string with destination path for generated file. Must be either a Python (.py
), or GraphQL (.graphql
or .gql
) file.
Defaults to schema.py
.
Generated Python file will contain:
- Necessary imports
- Type map declaration
{type_map_variable_name}: TypeMap = {...}
- Schema declaration
{schema_variable_name}: GraphQLSchema = GraphQLSchema(...)
Generated GraphQL file will contain a formatted output of the print_schema
function from the graphql-core
package.
A string with a name for schema variable, must be valid python identifier.
Defaults to "schema"
. Used only if target is a Python file.
A string with a name for type map variable, must be valid python identifier.
Defaults to "type_map"
. Used only if target is a Python file.
We welcome all contributions to Ariadne! If you've found a bug or issue, feel free to use GitHub issues. If you have any questions or feedback, don't hesitate to catch us on GitHub discussions.
For guidance and instructions, please see CONTRIBUTING.md.
Also make sure you follow @AriadneGraphQL on Twitter for latest updates, news and random musings!