semvec/pypi-packages huggingface dataset:
pypz-rmq-io 0.9.6
Provides an AMQP implementation for RabbitMQ of the ChannelInput/OutputPort in pypz.
License: Apache-2.0
Requires Python: >=3.11
Keywords: pypz, plugin, amqp

# Description

This package contains the RabbitMQ implementation of the Input-/OutputPortPlugin 
interface of *pypz*. It enables the operators to send and receive data records
through queues allowing load sharing.

Check the [documentation](https://lazlowa.github.io/pypz-python/plugins/rmq_io.html) for
more details.

# Install

The python artifact is hosted on https://pypi.org/, so you can install
it via pip:

```shell
pip install pypz-rmq-io
```

If you want to work on it locally, then you should install in editable mode:

```shell
pip install -e ./plugins/rmq_io
```

# Test

You can run tests against an existing RabbitMQ cluster, however, it is
more convenient and safe to use a local test cluster.


1. Run the [official image](https://hub.docker.com/_/rabbitmq) to start a local cluster
```shell
docker run -d --rm --name rabbitmq --hostname test -p 15672:15672 -p 5672:5672 rabbitmq:3-management
```
2. Install the subproject in editable more.
```shell
pip install -e ./plugins/rmq_io
```
3. To run the tests locally, you need to execute the following command:
```shell
python -m unittest discover .\plugins\rmq_io\test\ -p "*.py"
```
4. Delete cluster
```shell
docker stop rabbitmq
```

# Build

Before you build, you will need to install the "build" package:

```shell
pip install build
```

Then from the subproject's root, you will need to execute the following command:

```shell
python -m build
```

It will create the source distribution and the wheel file in the "dist" folder.
pypz-kafka-io 0.9.6
Provides a Kafka implementation of the ChannelInput/OutputPort in pypz.
License: Apache-2.0
Requires Python: >=3.11
Keywords: pypz, plugin, kafka

# Description

This package contains the Kafka implementation of the Input-/OutputPortPlugin 
interface of *pypz*. It enables the operators to send and receive data records
in a real streaming fashion.

Check the [documentation](https://lazlowa.github.io/pypz-python/plugins/kafka_io.html) for
more details.

# Install

The python artifact is hosted on https://pypi.org/, so you can install
it via pip:

```shell
pip install pypz-kafka-io
```

If you want to work on it locally, then you should install in editable mode:

```shell
pip install -e ./plugins/kafka_io
```

# Test

You can run tests against an existing Kafka cluster, however, it is
more convenient and safe to use a local test cluster.


1. Run the [confluent image](https://hub.docker.com/r/confluentinc/confluent-local) to start a local cluster
```shell
docker run --name kafka-test-cluster -d --rm -p 9092:9092 confluentinc/confluent-local
```
2. Install the subproject in editable more.
```shell
pip install -e ./plugins/kafka_io
```
3. To run the tests locally, you need to execute the following command:
```shell
python -m unittest discover .\plugins\kafka_io\test\ -p "*.py"
```
4. Delete cluster
```shell
docker stop kafka-test-cluster
```

## Known issues

Due to the fact that the test execution is sometimes faster than the Kafka
cluster, there might be failed tests. Although there are already several
delays inserted into the test code, it still can happen. Try to rerun the
test and give a notification to the maintainer(s). Thank you.

# Build

Before you build, you will need to install the "build" package:

```shell
pip install build
```

Then from the subproject's root, you will need to execute the following command:

```shell
python -m build
```

It will create the source distribution and the wheel file in the "dist" folder.
pypz-io-sniffer 0.9.6
A small tool that is capable to sniff and visualize the control messages between Operators.
License: Apache-2.0
Requires Python: >=3.11
Keywords: pypz, sniffer

# Description

This package contains the experimental implementation of the IO Sniffer.
The Sniffer allows you to visualize the control plane of the IO ports of
the operators, so you can have a better understanding, what happens during
the execution of your pipeline.

Check the [documentation](https://lazlowa.github.io/pypz-python/sniffer/overview.html) for
more details.

# Install

The python artifact is hosted on https://pypi.org/, so you can install
it via pip:

```shell
pip install pypz-io-sniffer
```

If you want to work on it locally, then you should install in editable mode:

```shell
pip install -e ./sniffer
```

# Test

Before you run the tests, you need to install the subproject in editable mode.
To run the tests locally, you need to execute the following command:

```shell
python -m unittest discover .\sniffer\test\ -p "*.py"
```

# Build

Before you build, you will need to install the "build" package:

```shell
pip install build
```

Then from the subproject's root, you will need to execute the following command:

```shell
python -m build
```

It will create the source distribution and the wheel file in the "dist" folder.
pypz-k8s-deployer 0.9.6
This package provides the Kubernetes implementation of the deployer interface for pypz.
License: Apache-2.0
Requires Python: >=3.11
Keywords: pypz, k8s, kubernetes, deployer

# Description

This package contains the Kubernetes implementation of the deployer interface
of *pypz*. It enables the deployment of the pipelines to a Kubernetes cluster.

Check the [documentation](https://lazlowa.github.io/pypz-python/deployers/kubernetes.html) for
more details.

# Install

The python artifact is hosted on https://pypi.org/, so you can install
it via pip:

```shell
pip install pypz-k8s-deployer
```

If you want to work on it locally, then you should install in editable mode:

```shell
pip install -e ./deployers/k8s
```

# Test

You can run tests against an existing Kubernetes cluster, however, it is
more convenient and safe to use [Kind](https://kind.sigs.k8s.io/) for this
purpose. 

1. Follow the instructions to install Kind. Note that Kind prepares the
required config file **~/.kube/config**. If you work with your own cluster,
make sure, you have this file already in place.
2. Install the subproject in editable more.
```shell
pip install -e ./deployers/k8s
```
3. Start the cluster
```shell
kind create cluster
```
4. Build the test image from the project root
```shell
docker build -t pypz-test-base -f deployers/k8s/test/resources/docker/Dockerfile .
```
5. Load the test image onto the Kind node
```shell
kind load docker-image pypz-test-base
```
6. To run the tests locally, you need to execute the following command:
```shell
python -m unittest discover .\deployers\k8s\test\ -p "*.py"
```
7. Delete cluster
```shell
kind delete cluster
```

# Build

Before you build, you will need to install the "build" package:

```shell
pip install build
```

Then from the subproject's root, you will need to execute the following command:

```shell
python -m build
```

It will create the source distribution and the wheel file in the "dist" folder.
pypz-core 0.9.6
Core components of pypz (pipes), which is a lightweight Pipeline as Code (PaC) framework.
License: Apache-2.0
Requires Python: >=3.11
Keywords: pypz, pypz-core

# Description

This package contains all the necessary core components to realize the
functionalities of *pypz*.

Check the [documentation](https://lazlowa.github.io/pypz-python/index.html) for
more details.

# Install

The python artifact is hosted on https://pypi.org/, so you can install
it via pip:

```shell
pip install pypz-core
```

If you want to work on it locally, then you should install in editable mode:

```shell
pip install -e ./core
```

# Test

Before you run the tests, you need to install the subproject in editable mode.
To run the tests locally, you need to execute the following command:

```shell
python -m unittest discover .\core\test\ -p "*.py"
```

# Build

Before you build, you will need to install the "build" package:

```shell
pip install build
```

Then from the subproject's root, you will need to execute the following command:

```shell
python -m build
```

It will create the source distribution and the wheel file in the "dist" folder.
constructs 10.5.1
A programming model for software-defined state
License: Apache-2.0
Requires Python: ~=3.9

# Constructs

> Software-defined persistent state

[![Release](https://github.com/aws/constructs/actions/workflows/release.yml/badge.svg)](https://github.com/aws/constructs/actions/workflows/release.yml)
[![npm version](https://badge.fury.io/js/constructs.svg)](https://badge.fury.io/js/constructs)
[![PyPI version](https://badge.fury.io/py/constructs.svg)](https://badge.fury.io/py/constructs)
[![NuGet version](https://badge.fury.io/nu/Constructs.svg)](https://badge.fury.io/nu/Constructs)
[![Maven Central](https://maven-badges.sml.io/maven-central/software.constructs/constructs/badge.svg?style=plastic)](https://maven-badges.sml.io/maven-central/software.constructs/constructs)

## What are constructs?

Constructs are classes which define a "piece of system state". Constructs can be composed together to form higher-level building blocks which represent more complex state.

Constructs are often used to represent the *desired state* of cloud applications. For example, in the AWS CDK, which is used to define the desired state for AWS infrastructure using CloudFormation, the lowest-level construct represents a *resource definition* in a CloudFormation template. These resources are composed to represent higher-level logical units of a cloud application, etc.

## Support policy

All [maintained Node.js versions](https://nodejs.org/en/about/previous-releases#release-schedule) are supported by this package.

## Contributing

This project has adopted the [Amazon Open Source Code of
Conduct](https://aws.github.io/code-of-conduct).

We welcome community contributions and pull requests. See our [contribution
guide](./CONTRIBUTING.md) for more information on how to report issues, set up a
development environment and submit code.

## License

This project is distributed under the [Apache License, Version 2.0](./LICENSE).