semvec/pypi-packages huggingface dataset:
data-genie 1.4.1
A small genie to generate test data

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# Data Genie

Genie that can satisfy your data wish. **Python 3.5+**

## QuickStart

- `python3 -m pip install data-genie`
- Detailed [Documentation](https://data-genie.readthedocs.io)

## Supported Formats

- Fixed Width
- Delimited (CSV)
- JSON

## Data quality

`dqc` module allows to write data quality checks on pandas data frame.
sharktank 3.8.0
SHARK layers and inference models for genai

# SHARK Tank

**WARNING: This is an early preview that is in progress. It is not ready for
general use.**

Light weight inference optimized layers and models for popular genai
applications.

This sub-project is a work in progress. It is intended to be a repository of
layers, model recipes, and conversion tools from popular LLM quantization
tooling.

## Project Status

[![CI - sharktank nightly](https://github.com/nod-ai/shark-ai/actions/workflows/ci-sharktank-nightly.yml/badge.svg?branch=main)](https://github.com/nod-ai/shark-ai/actions/workflows/ci-sharktank-nightly.yml)

## Examples

The repository will ultimately grow a curated set of models and tools for
constructing them, but for the moment, it largely contains some CLI examples.
These are all under active development and should not yet be expected to work.


### Perform batched inference in PyTorch on a paged llama derived LLM:

Note: Use `--device='cuda:0'` to run this inference on an AMD GPU.

```shell
python -m sharktank.examples.paged_llm_v1 \
  --hf-dataset=open_llama_3b_v2_f16_gguf \
  --device='cuda:0' \
  "Prompt 1" \
  "Prompt 2" ...
```

### Export an IREE compilable batched LLM for serving:

```shell
python -m sharktank.examples.export_paged_llm_v1 \
  --hf-dataset=open_llama_3b_v2_f16_gguf \
  --output-mlir=/tmp/open_llama_3b_v2_f16.mlir \
  --output-config=/tmp/open_llama_3b_v2_f16.json
```

### Generate sample input tokens for IREE inference/tracy:Add commentMore actions

```shell
python -m sharktank.examples.paged_llm_v1 \
  --irpa-file=open_llama_3b_v2_f16.irpa \
  --tokenizer-config-json=tokenizer_config.json \
  --prompt-seq-len=128 \
  --bs=4 \
  --dump-decode-steps=1 \
  --max-decode-steps=1 \
  --dump-path='/tmp' \
  --device='cuda:0'
```

### Dump parsed information about a model from a gguf file:

```shell
python -m sharktank.tools.dump_gguf --hf-dataset=open_llama_3b_v2_f16_gguf
```

## Package Python Release Builds

* To build wheels for Linux:

    ```bash
    ./build_tools/build_linux_package.sh
    ```

    That should produce
    `build_tools/wheelhouse/sharktank-{X.Y.Z}.dev0-py3-none-any.whl`, which can
    then be installed with

    ```bash
    python3 -m pip install build_tools/wheelhouse/sharktank-{X.Y.Z}.dev0-py3-none-any.whl
    ```

* To build a wheel for your host OS/arch manually:

    ```bash
    # Build sharktank.*.whl into the dist/ directory
    #   e.g. `sharktank-3.0.0.dev0-py3-none-any.whl`
    python3 -m pip wheel -v -w dist .

    # Install the built wheel.
    python3 -m pip install dist/*.whl
    ```
bssl 1.0.0a0
Modern and flexible TLS for Python, built on BoringSSL
Requires Python: >=3.12
Keywords: tls, ja3, ja4, fingerprint

# BSSL

[![Made in Ukraine](https://img.shields.io/badge/made_in-ukraine-ffd700.svg?labelColor=0057b7)](https://stand-with-ukraine.pp.ua)
[![license](https://img.shields.io/github/license/somespecialone/bssl)](https://github.com/somespecialone/bssl/blob/main/LICENSE)
[![pypi](https://img.shields.io/pypi/v/bssl)](https://pypi.org/project/bssl)
[![python versions](https://img.shields.io/pypi/pyversions/bssl)](https://pypi.org/project/bssl)
[![CI](https://github.com/somespecialone/bssl/actions/workflows/ci.yml/badge.svg)](https://github.com/somespecialone/bssl/actions/workflows/ci.yml)

Modern and flexible TLS for Python, built on **BoringSSL**

> This project is an early attempt to implement the idea of [PEP-748](https://peps.python.org/pep-0748/) in practice,
> with main goal is to provide a clean, extensible, and flexible alternative to Python’s built-in `ssl` module

## Learning resources

* 🐍 [Python API source code](./bssl)
* 📖 [DeepWiki](https://deepwiki.com/somespecialone/bssl)
* 📑 [PEP-748](https://peps.python.org/pep-0748/)
* [Integrations](https://github.com/somespecialone/bssl-integrations)

## Supported platforms

- **Linux** (glibc/musl):
    - x86_64
    - x86 (i686)
    - aarch64
    - armv7

- **Windows**:
    - x86_64
    - x86 (i686)
    - aarch64

- **macOS**:
    - x86_64
    - aarch64 (Apple Silicon)

## Installation

While project listed on [PyPI](https://pypi.org/project/bssl) it is in _prerelease_ state,
so consider allowing _prereleases_ during installation:

```sh
pip install --pre bssl
poetry add --allow-prereleases bssl
uv add --prerelease if-necessary bssl  # optional as uv must allow prereleases by default for prerelease-only packages
```

## Integrations and usage examples

See [bssl-integrations](https://github.com/somespecialone/bssl-integrations) repo.

## Building

Package is built using [maturin](https://github.com/PyO3/maturin).

Refer to [boring crate ci](https://github.com/cloudflare/boring/blob/master/.github/workflows/ci.yml) and
[BoringSSL build docs](https://github.com/google/boringssl/blob/main/BUILDING.md) to build `boring` crate.

You can look at [project ci](./.github/workflows/ci.yml) build steps and
🐋 [Docker image for musl cross-building](https://github.com/somespecialone/rust-musl-cross-gcc)
to see how it is done.

### Development

1) Ensure build dependencies from above are installed
2) Create and activate a `Python` virtual environment by _your_ choice
3) Install project in editable mode with:
   ```sh
   maturin develop
   ```

For example, on `Windows` you may need `Perl`, `CMake`, and `LLVM`.

[//]: # (TODO ubuntu build instruments example)

## Credits

* [cloudflare/boring](https://github.com/cloudflare/boring)
* [0x676e67/boring2](https://github.com/0x676e67/boring2)
* [0x676e67/wreq](https://github.com/0x676e67/wreq) - certificate compressors code
* [0x676e67/rnet](https://github.com/0x676e67/rnet) - building reference