semvec/pypi-packages huggingface dataset:
cdshealpix 0.8.0
A healpix manipulation library.
Requires Python: >=3.8
Keywords: astronomy, healpix

# CDSHealpix

[![Build Status](https://github.com/cds-astro/cds-healpix-python/actions/workflows/test.yml/badge.svg)](https://github.com/cds-astro/cds-healpix-python/actions/workflows/test.yml)
[![Deploy status](https://github.com/cds-astro/cds-healpix-python/actions/workflows/deploy_pypi.yml/badge.svg?branch=master)](https://github.com/cds-astro/cds-healpix-python/actions/workflows/deploy_pypi.yml)
[![PyPI version](https://badge.fury.io/py/cdshealpix.svg)](https://badge.fury.io/py/cdshealpix)
[![Documentation](https://img.shields.io/badge/Documentation-link-green.svg)](https://cds-astro.github.io/cds-healpix-python/)

This is a BSD-licensed HEALPix package which is wrapped around the [cdshealpix Rust crate](https://github.com/cds-astro/cds-healpix-rust).

[cdshealpix](https://pypi.org/project/cdshealpix/) is multi-platform and is currently deployed on PyPI for i686, x86_64 and aarch64 archs.

```bash
pip install cdshealpix
```

Or

```bash
conda install -c conda-forge cdshealpix
```

Reminder on conda activation/deactivation:

```bash
conda config --set auto_activate_base false
conda activate base
conda deactivate
```

Test:

```python
import cdshealpix
from cdshealpix import healpix_to_lonlat
lon, lat = healpix_to_lonlat(0, 0)
assert lon.rad[0] == 0.7853981633974483
```

## Features

* [Nested and Ring HEALPix notation](https://cds-astro.github.io/cds-healpix-python/api.html#cdshealpix) supported
* [Cone search](https://cds-astro.github.io/cds-healpix-python/stubs/cdshealpix.nested.cone_search.html#cdshealpix.nested.cone_search)
* [Elliptical-Cone search](https://cds-astro.github.io/cds-healpix-python/stubs/cdshealpix.nested.elliptical_cone_search.html#cdshealpix.nested.elliptical_cone_search)
* [Polygon search](https://cds-astro.github.io/cds-healpix-python/stubs/cdshealpix.nested.polygon_search.html#cdshealpix.nested.polygon_search)
* [Bilinear interpolation](https://cds-astro.github.io/cds-healpix-python/stubs/cdshealpix.nested.bilinear_interpolation.html#cdshealpix.nested.bilinear_interpolation)
* [lonlat_to_healpix](https://cds-astro.github.io/cds-healpix-python/stubs/cdshealpix.nested.lonlat_to_healpix.html#cdshealpix.nested.lonlat_to_healpix) and [healpix_to_lonlat](https://cds-astro.github.io/cds-healpix-python/stubs/cdshealpix.nested.healpix_to_lonlat.html#cdshealpix.nested.healpix_to_lonlat) supports numpy broadcasting
* Rust allows easy concurrency. A ``num_threads`` optional parameter can be used to allow parallelism. By default, concurrency is disabled.
* Get the [world vertices corresponding to an HEALPix cell](https://cds-astro.github.io/cds-healpix-python/stubs/cdshealpix.nested.vertices.html#cdshealpix.nested.vertices)
* Get the [neighbours of an HEALPix cell](https://cds-astro.github.io/cds-healpix-python/stubs/cdshealpix.nested.neighbours.html#cdshealpix.nested.neighbours)

## Documentation

Here is the link to the [documentation](https://cds-astro.github.io/cds-healpix-python/) for informations about how to use this package.
fabriform 0.0.1
A declarative infrastructure-as-code framework built on Fabric for automating bare-metal provisioning, VM orchestration, and service deployment.
Requires Python: >=3.14

# Fabriform

A declarative infrastructure-as-code framework built on Fabric for automating bare-metal provisioning, VM orchestration, and service deployment.

## Building, Developing, and Testing

This requires a compatible version of Python in your path from which the path to the interpreter can be gleaned by running `which python<version>`.  See the `requires-python` entry in `pyproject.toml` at the root of the repo for the currently required version of Python.

### Building a Distribution

```bash
python -m build && twine check dist/*
```

### Dependency Management

First-order dependencies for `requirements.txt`, `requirements_test.txt`, are defined in the respective `.in` files.  If you make updates to the first order dependencies you need to "compile" the full dependency list.  First, ensure that `pip-tools` is installed in your dev virtual environment.  `dev` dependendies are just defined in `requirements_dev.txt`.
```bash
pip install .[dev]
pip install .[test]
```

Then run the following
```bash
pip-compile -v --no-emit-trusted-host --no-emit-index-url requirements.in
pip-compile -v --no-emit-trusted-host --no-emit-index-url requirements_test.in
cube-compress 0.1.0
Compress and decompress Gaussian CUBE files using 24-bit float packing.
Requires Python: >=3.8

# cube_compress.py

一个用于将 Gaussian CUBE 体数据文件压缩为 `.cubexs`，并可解压回 `.cube` 的小工具。核心思路是把 `float32` 数据压缩为 24-bit（1 位符号 + 8 位指数 + 15 位尾数），再用 gzip 进行二次压缩。

## 依赖

- Python 3.x
- numpy

> `gzip` 为 Python 标准库，无需额外安装。

## 功能概览

- `float32_to_24bit(data_array)`  
  将 `float32` 数组压缩为 24-bit（3 字节）表示。

- `uint8_from_24bit(byte_array, num_values)`  
  将 24-bit 数据还原为 `float32` 数组。

- `compress(input_file, output_file)`  
  读取 `.cube` 文件，压缩数据并写入 `.cubexs`。

- `decompress(input_file, output_file)`  
  读取 `.cubexs` 文件，解压并输出 `.cube`。

## 使用示例

```python
from cube_compress import compress, decompress, compress_cube_file

# 压缩
compress("input.cube", "output.cubexs")

# 解压
decompress("output.cubexs", "restored.cube")

```

## 安装（本地开发）

在项目根目录执行：

```bash
pip install -e .
```

然后即可通过 `import cube_compress` 使用。

## 文件结构说明

`.cubexs` 的结构为：

1. 原 `.cube` 的头部文本（UTF-8，逐行写入）
2. 三行元数据：
   - `compressed_size=...`
   - `original_size=...`
   - `num_values=...`
3. gzip 压缩后的二进制数据（24-bit 数据重排后压缩）

## 注意事项

- 该压缩是**有损**的（尾数从 23 位缩减为 15 位）。
- `.cube` 文件头部必须符合标准格式（前几行标题、Fermi 信息、原子数与网格信息）。
egrobots-sa-client 2.0.1
Python client for Egrobots Arabic Speech Analysis service
Requires Python: >=3.9
Keywords: arabic, audio, conversation, analysis, speech, nlp

# Egrobots SA Client

Python client for Egrobots Arabic Speech Analysis service.

## Installation

```bash
pip install egrobots-sa-client
```

## Quick Start

```python
from egrobots_sa_client import EgrobotsSSAClient

client = EgrobotsSSAClient()

# Conversation analysis
result = client.analyze(
    audio="audio.mp3",
    enable_translation=False  # Set True for EN + AR
)
```

## Configuration

Create a `.env` file:

```env
BASE_URL=https://your-service.com
```

## Features

- **Conversation Analysis**: Analyze audio conversations with speaker diarization
- **Bilingual Support**: Get responses in both English and Arabic
- **Progress Tracking**: Monitor upload and processing progress
- **Retry Logic**: Automatic retries for failed requests

## Usage

### Basic Analysis

```python
from egrobots_sa_client import EgrobotsSSAClient

client = EgrobotsSSAClient()

# Analyze audio file
result = client.analyze(audio="audio.mp3")
print(result)
```

### With Bilingual Support

```python
result = client.analyze(
    audio="audio.mp3",
    enable_translation=True
)

# Check if bilingual
if client.is_bilingual_response(result):
    en_result = client.extract_language_version(result, 'EN')
    ar_result = client.extract_language_version(result, 'AR')
```

### Using Audio Bytes

```python
with open("audio.mp3", "rb") as f:
    audio_bytes = f.read()

result = client.analyze(
    audio=audio_bytes,
    file_name="audio.mp3"
)
```

### Progress Monitoring

```python
def progress_handler(event_type, data):
    print(f"[{event_type}] {data}")

result = client.analyze(
    audio="audio.mp3",
    progress_callback=progress_handler
)
```

## API Reference

### `analyze()`

Main method for conversation analysis.

**Parameters:**
- `audio` (str | bytes): Path to audio file or audio bytes
- `file_name` (str): Filename when using bytes (default: "audio.wav")
- `enable_translation` (bool): Enable EN + AR bilingual response (default: False)
- `progress_callback` (Callable): Progress handler function
- `max_retries` (int): Maximum retry attempts (default: 3)
- `retry_delay` (int): Delay between retries in seconds (default: 2)

**Returns:** Dict containing analysis results

### Helper Methods

- `is_bilingual_response(result)` - Check if response has EN/AR keys
- `extract_language_version(result, language)` - Extract 'EN' or 'AR' version

## Documentation

See [CLIENT_USAGE.md](https://github.com/Mox301/egrobots-audio-analysis-agent-demo/blob/main/backend_client/CLIENT_USAGE.md) for full documentation.

## License

MIT
model-munger 0.3.4
Extract vertical profiles from NWP models and output netCDF files
Requires Python: >=3.10

# Model Munger

[![Run tests](https://github.com/actris-cloudnet/model-munger/actions/workflows/test.yml/badge.svg)](https://github.com/actris-cloudnet/model-munger/actions/workflows/test.yml)
[![PyPI version](https://badge.fury.io/py/model-munger.svg)](https://badge.fury.io/py/model-munger)

Extract vertical profiles from numerical weather prediction (NWP) models and
output netCDF files.

## Supported models

| Model                                                                    | Horizontal resolution | Vertical resolution | Temporal resolution | Download                                 |
| ------------------------------------------------------------------------ | --------------------- | ------------------- | ------------------- | ---------------------------------------- |
| AROME                                                                    | Native                | 90 model levels     | 1 hour              | Not supported                            |
| [ARPEGE](https://www.umr-cnrm.fr/spip.php?article121&lang=en)            | Native                | 105 model levels    | 1 hour              | Not supported                            |
| [ECMWF open data](https://www.ecmwf.int/en/forecasts/datasets/open-data) | 0.25 degrees          | 13 pressure levels  | 3 hours             | Last days from ECMWF, few years from AWS |
| [GDAS1](https://www.ready.noaa.gov/gdas1.php)                            | 1 degree              | 23 pressure levels  | 3 hours             | Since December 2004                      |

## Processing steps

Model Munger deals with three types of files:

- **Raw data** is model output stored for example as GRIB files. Model Munger
  can download the raw data for some models.
- **Intermediate files** are netCDF files containing vertical profiles in a
  single fixed or moving location. There may be multiple intermediate files, for
  example one for each model run. For some models, Model Munger extracts
  intermediate files from the raw data, but for other models, it uses the output
  from other tools.
- **Output file** is a harmonized netCDF file generated from one or more
  intermediate files. The output file contains up to 24 hours of data from a
  single fixed or moving location, possibly combined from different model runs.

## License

MIT
divein 1.0.9
A simple, secure, and modern SSH connection manager
Requires Python: >=3.6

# DiveIn 🌊

DiveIn is a secure, modern, and user-friendly CLI tool for managing and connecting to your SSH hosts. It serves as a robust alternative to managing a complex `~/.ssh/config` file, offering features like encrypted password storage and an interactive interface.

## Features

-   **Secure Storage**: SSH passwords are encrypted using AES (Fernet) with a master password.
-   **Interactive UI**: Beautiful terminal interface powered by `Rich` and `Typer`.
-   **Quick Connect**: Connect to hosts by ID (`divein 1`) or nickname (`divein my-server`).
-   **Bulk Management**: Delete multiple hosts at once with range support (`divein rm 1-3,5`).
-   **Native Experience**: Seamless SSH integration without external dependencies like `sshpass`.

## Installation

Clone the repository and install it locally:

```bash
git clone https://github.com/yourusername/divein.git
cd divein
pip install -e .
```

## Usage

### Add a Host
Add a new SSH host. You will be prompted for a Master Password to encrypt your SSH password.

```bash
divein add
```

### List Hosts
View all your managed hosts in a table. You can interactively connect or delete hosts from this view.

```bash
divein list
```

### Connect
Connect to a host directly using its ID or nickname.

```bash
divein 1
# or
divein production-server
```

### View Details
See detailed information about a specific host.

```bash
divein show 1
```

### Remove Hosts
Delete hosts by ID, nickname, or range.

```bash
divein rm 1
divein rm 2-5,old-server
```

## Security

DiveIn uses PBKDF2HMAC for key derivation and Fernet (AES) for symmetric encryption. Your Master Password is used to unlock your SSH credentials only when needed and is never stored on disk.