Skip to main content

Iris Interoperability based on Embedded Python

Project description

IoP (Interoperability On Python)

PyPI - Status PyPI PyPI - Downloads PyPI - License GitHub last commit

Welcome to the Interoperability On Python (IoP) proof of concept! This project demonstrates how the IRIS Interoperability Framework can be utilized with a Python-first approach.

Documentation can be found here. For prompt-driven workflows, see AI-assisted coding with IoP. For task-oriented examples, see the IoP cookbooks. For application repositories, start from the reusable AGENTS.md template.

Example

Here's a tiny Python-authored production:

from dataclasses import dataclass

from iop import BusinessOperation, Message, PollingBusinessService, Production, target


@dataclass
class HelloRequest(Message):
    text: str = "Hello World"


class HelloService(PollingBusinessService):
    Output = target()

    def on_poll(self):
        self.send_request_async(self.Output, HelloRequest())


class HelloOperation(BusinessOperation):
    def on_message(self, request: HelloRequest):
        self.log_info(request.text)
        return request


prod = Production("HelloWorld.Production", testing_enabled=True)
service = prod.service("HelloService", HelloService)
operation = prod.operation("HelloOperation", HelloOperation)
service.connect(HelloService.Output, operation)

PRODUCTIONS = [prod]

Installation

To start using this proof of concept, install it using pip:

pip install iris-pex-embedded-python

Getting Started

If you're new to this project, begin by reading the installation guide. Then, follow the first steps to create your first Python-authored production.

If you are using an AI coding assistant, start with AI-assisted coding with IoP. For concrete workflows, use the IoP cookbooks. For healthcare productions, also see Healthcare AI-assisted coding.

Happy coding!

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

iris_pex_embedded_python-4.0.1b8.tar.gz (210.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

iris_pex_embedded_python-4.0.1b8-py3-none-any.whl (180.0 kB view details)

Uploaded Python 3

File details

Details for the file iris_pex_embedded_python-4.0.1b8.tar.gz.

File metadata

File hashes

Hashes for iris_pex_embedded_python-4.0.1b8.tar.gz
Algorithm Hash digest
SHA256 39a22ecd781182402be91e0cf6791eea6937d3d06752ed6f90b2f870aa463c95
MD5 59b8bc6549b57bb48d6856fbd2d0650a
BLAKE2b-256 45f7c4000b84f3acc85fcd6f8d913a65f6576ba50f5bbd481693aa948052f9c6

See more details on using hashes here.

Provenance

The following attestation bundles were made for iris_pex_embedded_python-4.0.1b8.tar.gz:

Publisher: publish.yml on grongierisc/interoperability-embedded-python

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file iris_pex_embedded_python-4.0.1b8-py3-none-any.whl.

File metadata

File hashes

Hashes for iris_pex_embedded_python-4.0.1b8-py3-none-any.whl
Algorithm Hash digest
SHA256 9b12f300482ebb3b65d4d2f138c9123071bb91b8d2d3a9ad2ae9aef736692c58
MD5 17672d12a8132ddebd7313ee843778d4
BLAKE2b-256 fc5907c62fbceb3a1c426d344d42e07119d1d545416ca241739f2f86244896f9

See more details on using hashes here.

Provenance

The following attestation bundles were made for iris_pex_embedded_python-4.0.1b8-py3-none-any.whl:

Publisher: publish.yml on grongierisc/interoperability-embedded-python

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page