semvec/pypi-packages huggingface dataset:
greptime-cloud-quick-start 1.0.2
A quick start demo for GreptimeCloud
Requires Python: >=3.10

# Introduction

This is a quick start demo for [GreptimeCloud](https://greptime.cloud/). It collects the system metric data such as CPU and memory usage through Opentelemetry and sends the metrics to GreptimeCloud. You can view the metrics on the GreptimeCloud dashboard.

## Quick Start

Use the following command line to start it in Python 3.10+ without cloning the repo:

```shell
pipx run --no-cache greptime-cloud-quick-start -e <endpoint-url> -db <dbname> -u <username> -p <password>
```

Or you can clone the repo and run it:

```shell
pip install -r requirements.txt
python start/main.py -e <endpoint-url> -db <dbname> -u <username> -p <password>
```

## Release

1. Change the version in `pyproject.toml`.
2. Commit and push the changes.
3. Create a tag with the version and push it to the remote repository.

    ```shell
    git tag v<major>.<minor>.<patch>
    git push origin v<major>.<minor>.<patch>
    ```

4. Build and publish the package to PyPI:

    ```shell
    python -m build
    python -m twine upload dist/*
    ```
tir-cli 0.1.1
This a E2E CLI tool for TIR AI-ML

# TIR CLI

## Stable Release : version - 0.1.1
The  TIR  Command  Line  Interface is a unified tool to manage all your tir services
A command line tool developed by tir Networks Ltd


## Getting started

Just Login to your [E2E myAccount](https://myaccount.tirnetworks.com/) and get your access/project tokens.
For more on access token refer [E2E Tokens](https://docs.tirnetworks.com/guides/create_API_access_token.html)
Add this to your system and you are all set to go.


## Requirements

The tir-cli package works on Python versions:

    3.x and greater
    setuptools 45.2.0 or greater
    requests 2.22.0 or greater


## Notices

Attention!
We recommend that all customers regularly monitor the [TIR docs](https://docs.e2enetworks.com/AI_ML/index.html) website for any important update bulletins related to tir-cli.


## Installation
Installation of the TIR CLI and its dependencies use a range of packaging features provided by pip and setuptools. To ensure smooth installation, it’s recommended to use:

pip: 21.0 or greater
requests: 2.22.0 or greater
setuptools: 45.2.0 or greater

The safest way to install the tir CLI is to use pip in a virtualenv:
        pip install tir-cli


## Configuration

Before using the tir CLI, you need to configure your tir credentials/Tokens
This can be done by running the following commands to add token, [more]() :

    tir config add      ->   To add project

Further set default project by using :
    tir config set      ->   To set default project for system


## Basic Commands

An tir CLI command has the following structure:

    tir <command> <subcommand> [options and parameters]

For example, to list buckets, the command would be:

    tir datasets list 

To view help/man documentation, use one of the following:
    
    tir --help

To get the version of the tir CLI:

    tir --version/-v

To get the package info of the tir CLI:

    tir --info

To turn on debugging :

    tir --debug  <command> <subcommand> 

To get  arguments info :

    tir <command> <subcommand> --help


## Support

For support/help refer [TIR CLI docs](https://docs.e2enetworks.com/AI_ML/index.html) or visit [tir Networks](https://gpu-notebooks.e2enetworks.com/)


## Authors and acknowledgment

Aman Mishra


## Project status
magellantools 0.0.2
Tools to parse and manipulate data from the Magellan mission stored on NASA's PDS
Requires Python: >=3.6

# Magellan PDS Tools
[![Documentation Status](https://readthedocs.org/projects/magellantools/badge/?version=latest)](https://magellantools.readthedocs.io/en/latest/?badge=latest)
[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)
[![DOI](https://zenodo.org/badge/430485608.svg)](https://zenodo.org/doi/10.5281/zenodo.10041646)

<p align="center">
  <img src="docs/source/img/logo.png" />
</p>

magellantools is a small Python library and set of command line tools to read, manipulate, and export (to more convenient formats) radar and radiometry data acquired by NASA's Magellan mission to Venus that is archived on the [Planetary Data System](https://pds-geosciences.wustl.edu/missions/magellan/index.htm).

We do not currently support all of the data types on the PDS (see list below). Requests to add support for a specific data type are welcome, but contributing to the code to add support for that data type is even more welcome.

Supported data types:  
- [ ] ARCDR  
	- [x] ADF  
	- [x] RDF  

---

- Documentation, including install instructions, example problems and API, can 
  be found on [Read the Docs](https://magellantools.readthedocs.io).


- If you find any issues, have questions, or would like to join the community, 
  please feel free to open up a [GitHub Issue](https://github.com/iganache/magellantools/issues) 

---
dark-emulator 1.1.2
dark emulator package
Keywords: cosmology,large scale structure,halo,gaussian process,machine learning

# Dark Emulator
[![Anaconda-Server Badge](https://anaconda.org/nishimichi/dark_emulator/badges/version.svg)](https://anaconda.org/nishimichi/dark_emulator)
[![Anaconda-Server Badge](https://anaconda.org/nishimichi/dark_emulator/badges/latest_release_date.svg)](https://anaconda.org/nishimichi/dark_emulator)
[![Anaconda-Server Badge](https://anaconda.org/nishimichi/dark_emulator/badges/license.svg)](https://anaconda.org/nishimichi/dark_emulator)
[![Anaconda-Server Badge](https://anaconda.org/nishimichi/dark_emulator/badges/downloads.svg)](https://anaconda.org/nishimichi/dark_emulator)

A repository for a cosmology tool `dark_emulator` to emulate halo clustering statistics. The code is developed based on Dark Quest simulation suite (https://darkquestcosmology.github.io/). The current version supports the halo mass function and two point correlation function (both halo-halo and halo-matter cross).

## Install
In order to install dark emulator package, use pip:
```
   pip install dark_emulator
```
or use conda:
```
   conda install -c nishimichi dark_emulator
```
Please note that updates on conda are currently halted due to an unresolved issue in conda build. Therefore, we recommend using the version in pip or installing from the source using the following command.

If the above does not work for you, you may download the source files from this repository and install via
```
python -m pip install -e .
```
after moving to the top directory of the source tree.
In that case, you need to install `george` (a software package for the Gaussian process) and colossus
```
conda install -c conda-forge george
pip install colossus
```
From version 1.1.0, `dark_emulator` uses FFTLog implementation by [Fang et al (2019); arXiv:1911.11947](https://arxiv.org/abs/1911.11947).

## Usage
You can then check how Dark Emulator works by running a tutorial notebook at
```
docs/tutorial.ipynb
docs/tutorial-hod.ipynb
```
See also the documentation on [readthedocs](https://dark-emulator.readthedocs.io/en/latest/).

## Code Paper
The main reference for our halo emulation strategy is: "Dark Quest. I. Fast and Accurate Emulation of Halo Clustering Statistics and Its Application to Galaxy Clustering", by T. Nishimichi et al., [ApJ 884, 29 (2019)](https://iopscience.iop.org/article/10.3847/1538-4357/ab3719/meta), [arXiv:1811.09504](https://arxiv.org/abs/1811.09504). Please also refer to the paper "Cosmological inference from emulator based halo model I: Validation tests with HSC and SDSS mock catalogs", by H. Miyatake et al.,  [arXiv:2101.00113](https://arxiv.org/abs/2101.00113) for the implementation and performance of the halo-galaxy connection routines.
hyp3-sbas 0.1.0
HyP3 product generation for SBAS processing
Requires Python: >=3.8

# colorem

# Description

COLOR mEets Munsell or colorem (from latin word for color), is an open-source toolbox programmed in Python for soil color applications.

# Installation

The colorem package can be installed directly from [PyPi](https://pypi.org/) running the pip command 
on the system shell:

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Python 
>>> pip install colorem
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
NameVariablePrint 1.0.0.4
Print variable name and value when you debugging
Requires Python: >=3.6
Keywords: pypi,NameVariablePrint,debugprint,print

<div align="center">
	<img src="https://capsule-render.vercel.app/api?type=rounded&color=0:0091ff,100:00f6fa&height=120&text=NameVariablePrint&animation=twinkling&fontColor=001580&fontSize=50"/>
</div>
<div style="text-align: left;">
	<h1 style="border-bottom: 1px solid #d8dee4; color: #282d33;"> NameVariablePrint - nvprint </h1>
	<div style="font-weight: 700; font-size: 15px; text-align: left; color: #282d33;"> This Python package improves your variable debugging. </div>
</div>
<div style="text-align: left;">
	<br>
		<br>
			<h1 style="border-bottom: 1px solid #d8dee4; color: #282d33;">📄 How to Use </h1>
			<h3>🔗Download PyPI Package</h3>
			<li>pip install NameVariablePrint</li>
			<br>
				<h3>🪄Package Import</h3>
				<li>import NameVariablePrint.nvprint</li>
				<br>
					<h3>✔️Usage</h3>
					<li>nvprint.nvprint(var1, var2, ...)</li>
					<br>
						<h3>❤️Parameters</h3>
						<li>All type Variables you want to print with.</li>
						<li>Variable Type Print : t</li>
						<li>t's type : boolean</li>
						<br>
</div>
polyprops 1.0.2
A Python package used for the analysis of polygon properties with a focus on performance.
Requires Python: >=3.10

# polyprops

polyprops is a Python package written in Rust used for the analysis of polygon properties with a focus on performance.

## Features

- Fast and efficient calculation of polygon properties using algorithms written in Rust

## Installation

Install polyprops with pip:

```bash
  pip install polyprops
```

## Usage/Examples

```python
import polyprops as pp

# Create a polygon
polygon = pp.Polygon([
    0, 0,
    10, 0,
    10, 10,
])

# Calculate the area
area = polygon.area()

# Calculate the centroid
centroid = polygon.centroid()
```
notifyall 1.0
A multi-channel notification library


# NotifyAll

NotifyAll is a Python library designed to simplify sending notifications across various platforms like Telegram and SMS via Amazon SNS. It provides a unified API to manage and dispatch notifications, making it an ideal solution for applications requiring multi-channel communication.

## Features

- **Multi-Channel Support**: Seamlessly integrate with various services like Telegram and Amazon SNS.
- **Easy to Use**: Simplified API for sending notifications with minimal setup.
- **Customizable**: Extensible to support additional notification services as needed.
- **Asynchronous Support**: Capable of handling notification sending asynchronously for better performance.

## Installation

Install NotifyAll using pip:

```bash
pip install notifyall
```

## Dependencies
- **PyYAML==6.0.1**
- **boto3==1.29.3**
- **boto3==1.29.3**
- **requests==2.31.0**
- **requests-toolbelt==1.0.**

To install these dependencies, run:

```bash
pip install -r requirements.txt
```


## Quick Start

Here's a quick example of how to send a notification using NotifyAll:


# Initialize the notifier
```python
from notifyall import NotifyAll
from notifyall.params import TelegramParams

# Initialize the notifier
notifier = NotifyAll(config_file='path/to/config.yaml')

```


# Send notification
```python
# Prepare parameters for the Telegram notification
params = TelegramParams(chat_id="123456789")

# Send a notification
notifier.send("Hello from NotifyAll!", params)

```

Replace `"path/to/config.yaml"` with the path to your configuration file. 
The TelegramParams class is used to specify parameters for the Telegram notifier.

## Documentation

For more detailed information about installation, configuration, and usage, please refer to the [Documentation](/docs).

## Configuring Logging

`NotifyAll` uses Python's standard logging library. To configure logging for `NotifyAll`, set up logging in your application as desired. For example:

```python
import logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
```

## Exceptions:
- **ConfigurationError**: Raised when the configuration file is missing or invalid.
- **UnsupportedChannelError**: Raised when an unsupported notification channel is used.
- **NotificationSendError**: Raised when there is an error in sending the notification.



## Contributing

Contributions to NotifyAll are welcome! Please refer to the [Contributing Guide](/CONTRIBUTING.md) for guidelines on how to contribute.

## License

NotifyAll is released under the [MIT License](/LICENSE).