semvec/pypi-packages huggingface dataset:
trieve 0.2.0
CLI for Trieve RAG Framework @ https://github.com/devflowinc/trieve
License: MIT
Requires Python: >=3.10,<4.0

# `trieve`

**Usage**:

```console
$ trieve [OPTIONS]
```

**Options**:

* `--install-completion`: Install completion for the current shell.
* `--show-completion`: Show completion for the current shell, to copy it or customize the installation.
* `--help`: Show this message and exit.
python-star 0.1.1
A command-line tool for simplifying project setup and development tasks.
License: MIT
Keywords: CLI,project setup,testing,development,automation,scripting,workflow,convenience,productivity,deployment,utility,developer tool,single command

# Star - Command Line Tool

Star is a command-line tool designed to simplify project setup, testing, and development tasks by providing a unified interface for running scripts and commands. It allows you to define and manage scripts in a configuration file, making it easy to execute complex workflows with a single command.

## Features

-   **Script Configuration**: Define scripts in a configuration file (`star.json`) to specify tasks for setup, testing, or development.

-   **Unified Interface**: Run scripts using a single command, reducing the need to remember complex command sequences.

-   **Flexibility**: Execute both single commands and sequences of commands defined in the configuration file.

-   **Easy to Use**: Simplify your workflow by streamlining common tasks with predefined scripts.

## Installation

Star can be installed using `pip`. Open a terminal and run:

```bash
pip install python-star
```

## Documentation (Usage)

#### Adding Commands

Define your custom scripts in the star.json file located in the root directory of your project. Example:

```json
{
	"scripts": {
		"custom_script": "echo 'Running custom script'",
		"test": ["echo 'Test 1 Pass'", "echo 'Test 1 Pass'"]
	}
}
```

### Running Commands

To run a script, use the following command:

```bash
star <script-name>
```

Replace `<script-name>` with the name of the script defined in your star.json file.

### Example

Assuming you have a star.json file with the following content:

```json
{
	"scripts": {
		"setup": "python setup.py",
		"test": ["pytest", "flake8"]
	}
}
```

You can run the "setup" script using

```bash
star setup
```

Or run the "test" script sequence using:

```bash
star test
```

### Other Command

| Short Form | Long Form | Description                     |
| ---------- | --------- | ------------------------------- |
| -h         | --help    | Show this help message and exit |
| -v         | --version | Display the version of Star     |
| -l         | --list    | List all available scripts      |

## Contributing

For guidance on setting up a development environment and how to make a contribution to Star, see the
device-picker 0.1.2
A device picker for machine learning frameworks like PyTorch, TensorFlow, and JAX.
License: MIT
Requires Python: >=3.7,<4.0

# Device Picker
<p align="center"><img width="250" height="250" margin-right="100%" src="https://raw.githubusercontent.com/YaoYinYing/device_picker/main/image/logo.png"></p>

## Description

Device Picker is a Python package designed to automatically select the appropriate computational device for machine learning tasks. It supports various frameworks like PyTorch, TensorFlow, and JAX. This tool is particularly useful in environments where multiple computational backends are available, as it simplifies the process of device selection based on the user's preferences and system capabilities.

## Installation

To install Device Picker, use the following pip command:

```bash
pip install device-picker
```

For users on macOS with Apple Silicon (M1, M2 chips), to enable Metal support:

```bash
# for jax
pip install device-picker[jax_metal_support] 
# for tensorflow
pip install device-picker[tensorflow_metal_support] 
```

## Usage

To use the Device Picker in your project, import the `DevicePicker` class and create an instance of it. The class methods `pytorch_device`, `tensorflow_device`, and `jax_device` can optionally take a device name as an argument. If a device name is given, the Device Picker will attempt to use the specified device if it is available. If no device name is provided or if the specified device is not available, the Device Picker will automatically select a suitable default device.

```python
from device_picker import DevicePicker

# Create an instance of DevicePicker
device_picker = DevicePicker()

# Select a specific device for PyTorch, or let the picker choose automatically
pytorch_device = device_picker.pytorch_device('cuda') # You can specify 'cuda', 'mps', or leave it empty

# Select a specific device for TensorFlow
tensorflow_device = device_picker.tensorflow_device('GPU') # Options could be 'GPU', 'CPU', etc.

# Select a specific device for JAX
jax_device = device_picker.jax_device('gpu') # Choose 'gpu', 'tpu', or others

```

## Running Tests

To run the unit tests for Device Picker, execute the following command in the root directory of the project:

```bash
make test
```

## Contributing

Contributions to Device Picker are welcome! Please feel free to submit pull requests, open issues, or suggest improvements.

## License

Device Picker is released under the MIT License. See the [LICENSE](LICENSE) file for more details.
WassersteinWormhole 0.1.0
Efficient and scalable image registration (alignment) for multiplexed imaging data
License: MIT
Requires Python: >=3.9,<4.0

WassersteinWormhole for Python3
======================

Embedding point-clouds by presering Wasserstein distancse with the Wormhole.

This implementation is written in Python3 and relies on FLAX, JAX, JAX-OTT.


To install JAX, simply run the command:

    pip install --upgrade "jax[cuda11_pip]" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html

And to install WassersteinWormhole along with the rest of the requirements: 

    pip install WassersteinWormhole

And running the Womrhole on your own set of point-clouds is as simple as: