semvec/pypi-packages huggingface dataset:
gpubackendtools-cpu 0.0.15
GPU Backend Tools
Requires Python: >=3.9

# GPUBackendTools: Backend tools for GPU/CPU agnostic codes.


## Getting Started


### Prerequisites


### Installing


## Running the Tests


## Versioning

We use [SemVer](http://semver.org/) for versioning. For the versions available, see the [tags on this repository](https://github.com/mikekatz04/GPUBackendTools/tags).

Current Version: 0.0.1

## Authors

* Michael Katz
* Maxime Pigou
* Mathieu Dubois

## Contributors


## License

This project is licensed under the Apache License - see the [LICENSE](https://github.com/mikekatz04/GPUBackendTools/blob/master/LICENSE) file for details.
muspi-merol 0.2.5
CLI utilities for personal use
Requires Python: >=3.12

# `m`

`m` is a simple CLI application that I personally use when developing projects.
It is written in Python and is designed to be easy to extend.

## Installation

Since this package is a CLI application, it is recommended to install it
globally with `uv` or `pipx`:

```sh
uv tool install muspi-merol[all]
```

or

```sh
pipx install muspi-merol[all]
```

You can also install it with `pip`:

```sh
pip install muspi-merol[all]
```

## Usage

You can find the usage information by running:

```sh
m --help
```
rcabench 1.1.55
RCABench - A comprehensive root cause analysis benchmarking platform for microservices
Requires Python: >=3.10

# RCABench SDK

A Python SDK for interacting with RCABench services.

## Installation

### From PyPI

```bash
pip install rcabench
```

### From Source

```bash
# Clone the repository
git clone https://github.com/your-username/rcabench.git
cd rcabench/sdk/python

# Install the package
pip install -e .
```

## Building the Package

To build the package for distribution:

```bash
# Install build dependencies
pip install build

# Build the package
python -m build

# This will create distribution files in the dist/ directory
```

## Usage

```python
from rcabench import RCABenchSDK

# Initialize the SDK
sdk = RCABenchSDK("http://localhost:8082")

# Get available algorithms
algorithms = sdk.algorithm.list()
print(algorithms)

# Submit an injection task
injection_payload = [{
    "duration": 1,
    "faultType": 5,
    "injectNamespace": "ts",
    "injectPod": "ts-preserve-service",
    "spec": {"CPULoad": 1, "CPUWorker": 3},
    "benchmark": "clickhouse",
}]
response = sdk.injection.execute(injection_payload)
print(response)

# Run an algorithm
algorithm_payload = [{
    "benchmark": "clickhouse",
    "algorithm": "e-diagnose", 
    "dataset": "dataset-name",
}]
response = sdk.algorithm.execute(algorithm_payload)
print(response)
```

## API Reference

The SDK provides the following main components:

- `RCABenchSDK`: The main entry point for the SDK
  - `algorithm`: For interacting with algorithm endpoints
  - `evaluation`: For interacting with evaluation endpoints
  - `injection`: For interacting with injection endpoints

For detailed API documentation, please refer to the code docstrings.

## Requirements

- Python 3.8 or higher
- `requests` and `aiohttp` libraries
scGCA 0.1.1
Single-Cell Genome-Wide Chromatin Accessibility
Requires Python: >=3.9

# scGCA
 Genomewide chromatin accessibility for single-cell data.

## Installation
1. Create a virtual environment
```bash
conda create -n scGCA python=3.10 scipy numpy pandas scikit-learn && conda activate scGCA
```

2. Install [PyTorch](https://pytorch.org/get-started/locally/) following the official instruction. 
```bash
pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu126
```

3. Install scGCA
```bash
pip3 install scGCA
```
unidata-blocks 0.0.24
A library that helps query Unicode blocks by Blocks.txt
Requires Python: >=3.10
Keywords: unicode

# Unidata Blocks

[![Python](https://img.shields.io/badge/python-3.10-brightgreen)](https://www.python.org)
[![PyPI](https://img.shields.io/pypi/v/unidata-blocks)](https://pypi.org/project/unidata-blocks/)

A library that helps query Unicode blocks by [Blocks.txt](https://www.unicode.org/Public/UNIDATA/Blocks.txt).

## Installation

```shell
pip install unidata-blocks
```

## Usage

```python
import unidata_blocks

block = unidata_blocks.get_block_by_chr('A')
assert block.code_start == 0x0000
assert block.code_end == 0x007F
assert block.name == 'Basic Latin'
```

## Dependencies

- [Langcodes](https://github.com/rspeer/langcodes)

## License

[MIT License](LICENSE)