semvec/pypi-packages huggingface dataset:
poetry-codeartifact-login 0.3.0
Poetry plugin for logging in to AWS CodeArtifact.
Requires Python: <4.0,>=3.7

# Poetry AWS CodeArtifact Login
A Poetry plugin for authenticating with AWS CodeArtifact.

## Requirements
- `poetry >= 1.2.0`
Install using the dedicated installation script. See [here](https://python-poetry.org/docs/#installation). 

- `AWS CLI v2`
See [here](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html) for installation guide.


## Intallation
```
poetry self add poetry-codeartifact-login
```

## Usage
AWS credentials will need to be configured on the system prior to usage. Typically this is done using the `aws configure` command and/or directly modifying the configuration files. See [here](https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-files.html) for more info. They can also be set through [environment variables](https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-envvars.html), which will take precedence over any configuration file values.

Once credentials have been configured, you can log in to CodeArtifact:
```
poetry aws-login <source_name>
```

Assuming the credentials are configured properly and the identity they belong to has proper permissions, `poetry` will be configured with a short-lived authentication token that will automatically be used for installation of any packages in the authenticated source. See [here](https://python-poetry.org/docs/repositories/#private-repository-example) for more information on working with private repositories through `poetry`.

If want to log in with a profile other than the default, you can do:
```
poetry aws-login <source_name> --profile <profile_name>
```

## CLI Reference
```
poetry aws-login --help
```
zappix 1.2.3
A Python replacement for Zabbix sender and get.
Keywords: zabbix get sender agent active

# zappix - a package for Zabbix sender and get.

zappix aims to be a drop-in replacement for zabbix_get as well as zabbix_sender.
Its components are available not only as a module but from the command line as well.

zappix requires Python3 and is guaranteed to work with 3.6.

## Instalation 

zappix is not dependant on any third party modules.
The easiest way to install it with pip:
```sh
pip install zappix
```

# Usage

As mentioned earlier - zappix can be used both as a module inside of an application, as well as from the Command Line Interface.

## As a module

At the moment zappix has two classes: Sender and Get. Both of which can be imported in the following manner:
```python
>>> from zappix.sender import Sender
>>> from zappix.get import Get
```

Then you can send or get some data. Asuming both Zabbix Agent and Server run on localhost and default ports:

```python
>>> getter = Get("127.0.0.1")
>>> getter.get_value("agent.ping")
1
>>> sender = Sender("127.0.0.1")
>>> sender.send_value('testhost', 'test', 1)
{"processed": 1, "failed": 0, "total": 1, "seconds spent": 0.005}

```

## CLI

To use this utility from the command line, you need to invoke python with the -m flag, followed by the module name and required parameters:

```sh
python -m zappix.sender -z 127.0.0.1 -s testhost -k testkey -o 1
```

## Testing

If you wish to contribute it's good to know how to conduct tests.
You can go with mocked tests only or add integration tests as well.

To enable integration tests, set the envvar `ZAPPIX_TEST_INTEGRATION=yes`

After if you wish to proceed with services in docker containers run the following:

```shell
docker run -d -e "ZBX_CACHEUPDATEFREQUENCY=1" -p 10051:10051 -p 80:80 zabbix/zabbix-appliance
docker run -d -e "ZBX_SERVER_HOST=0.0.0.0/0" -p 10050:10050 zabbix/zabbox-agent
```

Note that the zabbix-appliance might take a while to start. Once both containers are up and running, just run `tox`.

If you have your custom Zabbix services, it is possible to configure tests via envvars to connect to those:

| envvar          | usage                                                                                                              |
| --------------- | ------------------------------------------------------------------------------------------------------------------ |
| ZAPPIX_AGENT    | IP address or DNS name of running Zabbix agent                                                                     |
| ZAPPIX_SERVER   | IP address or DNS name of running Zabbix Server                                                                    |
| ZAPPIX_API      | URL of Zabbix fronted. Schema is required                                                                          |
| ZAPPIX_API_USER | User for creating entities via API. Should have RW permissions to a Host group with ID=2 - Usually 'Linux Servers' |
| ZAPPIX_API_PASS | Password for that user                                                                                             |
proxly 0.1.4
HTTP proxy library for Python using CroxyProxy infrastructure
Requires Python: >=3.9

# proxly

[![Python](https://img.shields.io/badge/python-3.9+-blue.svg)](https://www.python.org/downloads/)
[![License](https://img.shields.io/badge/license-GPL%20v3-blue.svg)](LICENSE)

HTTP proxy library for Python using CroxyProxy infrastructure.

## Installation

```bash
pip install proxly
```

## Usage

```python
import proxly

# Simple usage
response = proxly.get("https://example.com")
print(response.text)

# Session-based
proxy = proxly.proxly()
response = proxy.get("https://example.com/api")
proxy.close()

# Context manager
with proxly.proxly() as proxy:
    response = proxy.get("https://example.com")

# Get available servers
servers = proxly.get_server_list()
print(f"Available servers: {len(servers)}")
```

## API

### proxly Class

```python
proxly(timeout=30, max_retries=3)
```

**Methods:**
- `get(url, **kwargs)`
- `post(url, **kwargs)`  
- `put(url, **kwargs)`
- `delete(url, **kwargs)`
- `head(url, **kwargs)`
- `patch(url, **kwargs)`
- `get_session_info()`
- `close()`

### Convenience Functions

```python
proxly.get(url, **kwargs)
proxly.post(url, **kwargs)
proxly.put(url, **kwargs)
proxly.delete(url, **kwargs)
proxly.head(url, **kwargs)
proxly.patch(url, **kwargs)
```

### Server Management

```python
proxly.get_server_list()     # Get list of available proxy servers
proxly.clear_server_cache()  # Clear cached server list
```

## Error Handling

```python
try:
    response = proxly.get("https://example.com")
except proxly.ProxyError as e:
    print(f"Proxy error: {e}")
```

## Requirements

- Python 3.9+
- curl-cffi

## License

GNU General Public License v3.0
llmpy-lib 0.0.8
Easily interact with all main LLMs
Requires Python: >=3.10

Supported large language models:
the one hosted on groq

The rest is to come:
- anthropic (claude...)
- deepseek (deepseek-70b...)
- google (gemini...)
- meta (llama3.1-7b...)
- openai (gpt3.5...)
- qwen (34b...)


Usage example:

```python
import llmpy as lm

question = 'how many r\'s in strawberry'

model = Model.LLAMA_3_3_70B
models = [
    Model.LLAMA_3_3_70B,
    Model.Deepseek
]

lm.ask(model, question)
lm.ask_many(models, question)
```
llmpy-models 0.0.19
Automatically generated LLM models for llmpy-lib
Requires Python: >=3.10

# llmpy-models Auto Generator

This project includes a script to regenerate and publish the `llmpy_models.py` file automatically.

## Requirements

To run `scripts/publish.sh`, ensure the following are available:

- **Python** ≥ 3.10
- **Virtual environment** in `.venv/` with dependencies installed
- **macOS** (due to `sed -i ''` syntax)
- **Tools installed**:
  - `twine`
  - `build`
  - `diff`
  - `sed`

Make sure the update.sh script is executable:
`chmod +x scripts/update.sh`
nfflr 0.4.1
neural force field learning toolkit
Requires Python: <3.13,>=3.8

# NFFLr - Neural Force Field Learning toolkit
[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](https://makeapullrequest.com)
![GitHub tag (latest by date)](https://img.shields.io/github/v/tag/usnistgov/nfflr)
![GitHub commit activity](https://img.shields.io/github/commit-activity/y/usnistgov/nfflr)
[![General badge](https://img.shields.io/badge/docs-main-blue.svg)](https://pages.nist.gov/nfflr)


# Table of Contents
* [Introduction](#intro)
* [Installation](#install)
* [Examples](#example)
* [How to contribute](#contrib)
* [Correspondence](#corres)
* [Funding support](#fund)

<a name="intro"></a>
# NFFLr (Introduction)
The Neural Force Field Learning library ([docs](https://pages.nist.gov/nfflr)) is intended to be a flexible toolkit for developing and deploying atomistic machine learning systems, with a particular focus on crystalline material property and energy models.

The initial codebase is a fork of [ALIGNN](https://github.com/usnistgov/alignn), with modified configuration and modeling interfaces for performance.

<a name="install"></a>
Installation
------------

We recommend using a per-project [pyenv-virtualenv](https://github.com/pyenv/pyenv-virtualenv) or [conda](https://docs.conda.io/projects/conda/en/latest/user-guide/concepts/environments.html) environment.

To ensure proper CUDA support, make sure to install the GPU versions of [PyTorch](https://pytorch.org/get-started/locally/) and [DGL](https://www.dgl.ai/pages/start.html). For example, to set up a conda environment on linux with with python 3.10 and CUDA 12.1:

```
conda create --name myproject python=3.10
conda activate myproject
conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
conda install -c dglteam/label/cu121 dgl
python -m pip install nfflr
```

<a name="example"></a>
Examples
--------
[Under construction here.](https://pages.nist.gov/nfflr/tutorials)


<a name="contrib"></a>
How to contribute
-----------------

We gladly accept [pull requests](https://makeapullrequest.com).

For detailed instructions, please see [Contributing.md](Contributing.md)

<a name="corres"></a>
Correspondence
--------------------

Please report bugs as Github issues (https://github.com/usnistgov/nfflr/issues) or email to brian.decost@nist.gov.

<a name="fund"></a>
Funding support
--------------------

NIST-MGI (https://www.nist.gov/mgi).

Code of conduct
--------------------

Please see [Code of conduct](https://github.com/usnistgov/jarvis/blob/master/CODE_OF_CONDUCT.md)