Skip to main content

LARA Django Organisms - gRPC API

This directory contains the gRPC interface for the lara-django-organisms application, providing a high-performance API for managing organism taxonomic data in the LARA database.

Overview

The gRPC API provides remote procedure call access to the LARA Django Organisms service with support for multiple programming languages through protocol buffer definitions. It also contains a high-level Python interface for easy integration with Python applications.

Package: lara-django-organisms-grpc
Python Requirement: 3.13.*

Project Structure

api/grpc/
├── go/                          # Go gRPC client code
├── connect-es/                  # Connect-ES client code
├── connectrpc-es/               # ConnectRPC ES implementations
├── grpc-web/                    # gRPC-Web client code
├── gen/                         # Generated code from protobuf definitions
├── dist/                        # Distribution packages
├── pyproject.toml               # Python project configuration
└── python/                      # Python API module root
    └── lara_django_organisms_grpc/
        ├── lara_django_organisms_data_model.py   # Data model definitions
        ├── lara_django_organisms_interfaces.py   # High-level interface
        └── v1/
            └── *_pb2.py         # Generated protocol buffer code

## Installation

### Using uv (Recommended)

Install the `lara-django-organisms-grpc` package with uv for faster dependency resolution:

```bash
cd api/grpc
uv pip install .

Or with development dependencies:

uv pip install -e ".[dev]"

For development, install with editable mode and all dependency groups:

cd api/grpc
uv sync --all-groups

Using pip

Alternatively, install with pip:

pip install lara-django-organisms-grpc

Or from the local directory:

cd api/grpc
pip install .

Dependencies

  • Runtime: grpcio>=1.73.0
  • Development:
    • grpcio-tools>=1.73.0
    • pytest>=8,<9
    • pytest-cov>=6,<7
    • pytest-asyncio

Code Generation

Protocol buffer definitions are located in ../proto/lara_django_organisms_grpc/. To regenerate gRPC code from protobuf definitions, e.g. in case you changed the .proto file, use the Buf CLI:

cd api
buf generate

This will generate code for multiple targets as configured in buf.gen.yaml:

  • Python
  • Go
  • JavaScript/TypeScript (Connect-ES, ConnectRPC, gRPC-Web)

Running Tests

The test suite is located in api/tests/ and includes tests for all major entities:

Using uv

# From the api/grpc directory
uv run pytest api/tests/

# With coverage
uv run pytest api/tests/ --cov

Using pytest directly

# From the api/grpc directory
pytest api/tests/

# With coverage
pytest api/tests/ --cov

Test Files

  • test_lara_django_organisms_Classis_grpc.py - Classis (class) tests
  • test_lara_django_organisms_Cultivar_grpc.py - Cultivar tests
  • test_lara_django_organisms_Domain_grpc.py - Domain tests
  • test_lara_django_organisms_ExtraData_grpc.py - Extra data tests
  • test_lara_django_organisms_Familia_grpc.py - Familia (family) tests
  • And other taxonomic entity tests

Usage Examples

Python Client

import grpc
from lara_django_organisms_grpc import domain_pb2, domain_pb2_grpc

# Create a channel to the gRPC server
channel = grpc.insecure_channel('localhost:50051')

# Create a stub (client)
stub = domain_pb2_grpc.DomainServiceStub(channel)

# Make a request
response = stub.GetDomain(domain_pb2.GetDomainRequest(id=1))
print(response)

# Don't forget to close the channel when done
channel.close()

For more comprehensive examples, see the demo clients in ../../demo_clients/.

Development

Building

The project uses the uv_build backend for building:

# Using uv (recommended)
uv build

# Or using Python build module
python -m build

Working with uv

This project is configured for uv with the following features:

  • Build Backend: uv_build>=0.9.0,<=0.10.0
  • Module Root: python/ (all Python gRPC code should be placed here)
  • Dependency Groups: Development dependencies are organized in groups

Common uv commands:

# Sync dependencies
uv sync

# Sync with development dependencies
uv sync --all-groups

# Add a new dependency
uv add package-name

# Add a development dependency
uv add --dev package-name

# Run a command in the uv environment
uv run python script.py

# Build the package
uv build

Module Root

The Python module root is configured at python/, meaning all Python gRPC code should be placed in that directory.

Documentation

Protocol Buffer Linting

The project uses Buf for linting and breaking change detection. Configuration is in ../buf.yaml:

  • Follows DEFAULT lint rules with specific exceptions
  • Breaking change detection enabled
  • Ignores certain Google type definitions

Contributing

Contributions are welcome! Please see the CONTRIBUTING.md file in the project root for guidelines.

When modifying protobuf definitions:

  1. Edit .proto files in ../proto/lara_django_organisms_grpc/
  2. Run buf generate to regenerate code
  3. Update tests as needed
  4. Run the test suite to ensure compatibility

License

See the LICENSE file in the project root.

Metadata

Release files for lara-django-organisms-grpc 0.2.113

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for lara-django-organisms-grpc 0.2.113
File Size Uploaded Provenance Actions
lara_django_organisms_grpc-0.2.113.tar.gz 44.4 kB Without provenance Details for lara_django_organisms_grpc-0.2.113.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for lara-django-organisms-grpc 0.2.113
File Interpreter ABI Platform Actions
lara_django_organisms_grpc-0.2.113-py3-none-any.whl Python 3 none any Details for lara_django_organisms_grpc-0.2.113-py3-none-any.whl

Total release size: 90.4 kB

Release files / lara_django_organisms_grpc-0.2.113.tar.gz

Download URL lara_django_organisms_grpc-0.2.113.tar.gz
Size 44.4 kB
Tags Source
SHA-256 checksum
How to use checksums
2ac2ba98e9fb6dbfd1f44cc165561de321cde58faecd6aa6aaccf46c52404319
BLAKE2b-256 checksum
How to use checksums
b8e6c023c9ddb57eabdefaac19b003f73c03e05083020fabefb7673910255784
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.2.0 CPython/3.13.12

Release files / lara_django_organisms_grpc-0.2.113-py3-none-any.whl

Download URL lara_django_organisms_grpc-0.2.113-py3-none-any.whl
Size 46.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums
90956699e62141136b9645df7274dd2a5a7a4c222c8fe3bc8496ec192c27a536
BLAKE2b-256 checksum
How to use checksums
e7fb65b9f004f90e57cfc2fa7517353effd05e572eb40248d13e3ed91a769307
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.2.0 CPython/3.13.12

Security for lara-django-organisms-grpc 0.2.113

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page