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apache-airflow-providers-grpc

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library3.9.5pypypi✓ verified 85d ago

The `apache-airflow-providers-grpc` package extends Apache Airflow, enabling interaction with gRPC-based services. It provides operators and hooks to execute gRPC commands and manage connections within Airflow workflows. Currently at version 3.9.4, this provider is actively maintained with frequent releases aligning with the broader Apache Airflow provider release schedule, ensuring compatibility and introducing new features.

pip install apache-airflow-providers-grpc
INSTALL
IMPORT
SIG · APACHE-AIRFLOW-PRO
A
apache-airflow-providers-grpc
workflowpythonv3.9.5
Install
23.6s avg
Import
5694ms
Disk
257MB
Pass rate
10/ 10
Env Coverage10 / 10
glibc
3.93.13
musl
3.93.13
Install & Compatibility
Where this runs
tested against v3.9.5 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
musl
py 3.103.920 runs
installs and imports cleanly · install 0.0s · import 5.941s · 256.2MB
glibc
py 3.103.920 runs
installs and imports cleanly · install 23.6s · import 5.448s · 254MB
257MB installed
● package 257MB
Code
Verified usage

Verified import paths — ran on the pinned version, not inferred.

GrpcOperator
from airflow.providers.grpc.operators.grpc import GrpcOperator
GrpcHook
from airflow.providers.grpc.hooks.grpc import GrpcHook
from airflow.contrib.hooks.grpc_hook import GrpcHook
The `contrib` path was for Airflow 1.x backport providers. Airflow 2.x+ providers use `airflow.providers.grpc.hooks.grpc`.

This quickstart demonstrates a basic Airflow DAG using `GrpcOperator` to interact with a gRPC service. It assumes a gRPC connection named `grpc_default` is configured in the Airflow UI (Admin -> Connections). The example uses placeholder protobuf stubs (`dummy_pb2_grpc`, `dummy_pb2`) for illustration; in a real application, these would be generated from your `.proto` files. The `GrpcOperator` calls a specified gRPC method (`Ping` on `DummyServiceStub`) with structured data. A `GrpcHook` can also be used directly within a `PythonOperator` for more complex interactions.

from __future__ import annotations import os from datetime import datetime from airflow.models.dag import DAG from airflow.providers.grpc.operators.grpc import GrpcOperator from airflow.providers.grpc.hooks.grpc import GrpcHook # NOTE: In a real scenario, you would generate protobuf stub classes # For this example, we assume a 'dummy_pb2_grpc' and 'dummy_pb2' exist # and define a 'DummyService' with a 'Ping' method that takes 'PingRequest' # and returns 'PingResponse'. # Replace with your actual generated proto files and service/method names. try: import grpc from dummy_pb2_grpc import DummyServiceStub from dummy_pb2 import PingRequest, PingResponse except ImportError: # Placeholder for running the quickstart without actual protobufs class DummyServiceStub: def __init__(self, channel): pass def Ping(self, request): print(f"Mock Ping called with: {request.message}") return type('PingResponse', (object,), {'message': 'Pong from mock!'}) class PingRequest: def __init__(self, message=None): self.message = message PingResponse = type('PingResponse', (object,), {'message': None}) print("Warning: Protobuf stubs (dummy_pb2_grpc, dummy_pb2) not found. Using mock classes.") with DAG( dag_id='grpc_example_dag', start_date=datetime(2023, 1, 1), schedule=None, catchup=False, tags=['grpc', 'example'], ) as dag: # Define a gRPC connection in Airflow UI (Admin -> Connections) # Conn Id: 'grpc_default' # Conn Type: 'gRPC Connection' # Host: 'localhost' # Port: '50051' # Auth Type: 'NO_AUTH' for insecure channel, or 'SSL'/'TLS' with 'Credential Pem File' # For JWT_GOOGLE or OATH_GOOGLE, set these and ensure 'google-auth' is installed # Example of using GrpcOperator # This assumes 'grpc_default' connection is configured in Airflow call_grpc_service = GrpcOperator( task_id='call_grpc_service', grpc_conn_id='grpc_default', stub_class=DummyServiceStub, # Your generated gRPC stub class call_func='Ping', # The method on the stub class to call data={'request': PingRequest(message='Hello gRPC from Airflow!')}, # If the gRPC method expects a specific request object, pass it like this. # The 'data' parameter maps to the keyword arguments of the gRPC method. ) # Example of using GrpcHook directly in a PythonOperator (or for custom logic) def _interact_with_grpc_hook(**kwargs): hook = GrpcHook(grpc_conn_id='grpc_default') # For this example, we're using a mock service. In a real scenario, # hook.run() would return a gRPC response or yield streaming responses. response = hook.run(stub_class=DummyServiceStub, call_func='Ping', data={'request': PingRequest(message='Hello from Hook!')}) # For unary calls, response is typically the deserialized message # For streaming, it's an iterator. print(f"gRPC Hook Response: {response.message}") interact_with_hook = GrpcOperator( task_id='interact_with_grpc_hook', grpc_conn_id='grpc_default', stub_class=DummyServiceStub, call_func='Ping', data={'request': PingRequest(message='Hello from Hook via Operator!')} )
Debug
Known issues
breakingProvider version 2.0.0+ requires Apache Airflow 2.1.0+ due to the removal of the `apply_default` decorator. Older Airflow versions will cause automatic upgrades or database migration issues.
fix
Upgrade your Apache Airflow instance to at least version 2.1.0 before installing or upgrading to `apache-airflow-providers-grpc` version 2.0.0 or higher. For the latest provider version (3.9.0+), Airflow >=2.11.0 is required.
affects: >=2.0.0
breakingMinimum supported Airflow version has incrementally increased. Provider version 3.0.0+ requires Airflow 2.2+, version 3.1.0+ requires Airflow 2.3+, and version 3.9.0+ requires Airflow 2.11+.
fix
Always check the provider's changelog or documentation for the `minimum_airflow_version` compatible with the specific provider version you intend to use. Ensure your Airflow environment meets this requirement.
affects: >=3.0.0
breakingPython 3.9 support was dropped in provider version 3.8.1.
fix
Ensure your Python environment is version 3.10 or higher when using `apache-airflow-providers-grpc` versions 3.8.1 or newer, as indicated by the `requires_python: >=3.10` metadata on PyPI.
affects: >=3.8.1
gotchaThe `data` parameter in `GrpcOperator` expects a dictionary where keys map to keyword arguments of the gRPC method, and values are the corresponding protobuf request objects. Passing incorrect types or structures will lead to serialization errors.
fix
Always pass the gRPC method's expected request object within the `data` dictionary, e.g., `data={'request': YourProtoRequestObject(field='value')}`. Do not pass raw dictionaries directly if the gRPC method expects a protobuf message.
affects: All
Errors
Common errors & fixes
TypeError: 'dict' object is not callable or expecting protobuf message
Attempting to pass a raw Python dictionary directly to a gRPC method via `GrpcOperator` or `GrpcHook` when the method expects a protobuf message. The `data` parameter needs the actual protobuf object.
fix
Construct the correct protobuf request object (e.g., `YourService_pb2.YourRequest(field='value')`) and pass it within the `data` dictionary, typically under a 'request' key: `data={'request': YourService_pb2.YourRequest(...) }`.
grpc._channel._InactiveRpcError: <_InactiveRpcError of RPC that terminated with: status = StatusCode.UNAVAILABLE details = "Connect Failed" debug_error_string = "..."
Airflow's `GrpcHook` or `GrpcOperator` failed to establish a connection with the gRPC server. This could be due to an incorrect host/port, the server not running, network issues, or authentication failures.
fix
Verify the gRPC connection details in Airflow UI (Admin -> Connections -> `grpc_default` or your custom connection ID). Ensure the 'Host' and 'Port' are correct, the gRPC server is running and accessible from the Airflow worker, and the 'Auth Type' and associated credentials (e.g., 'Credential Pem File' or 'Scopes') are correctly configured and match the server's requirements.
Upgrade
Version history
3.9.5latest on PyPI · released Jun 7, 2026
Audit
Dependencies
apache-airflowrequiredCore Airflow functionality; requires Airflow >=2.11.0 for provider version 3.9.0+.
grpciorequiredUnderlying gRPC Python library for communication.
google-authoptionalRequired for Google-specific gRPC authentication modes (e.g., JWT_GOOGLE, OATH_GOOGLE).
google-auth-httplib2optionalRequired for Google-specific gRPC authentication modes (e.g., JWT_GOOGLE, OATH_GOOGLE).
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Resources
apache-airflow-providers-grpc — pip install apache-airflow-providers-grpc · libregistry