semvec/pypi-packages huggingface dataset:
ninjaexi 0.0.1
A professional-grade AI utility for automated data synchronization and backend management.
Requires Python: >=3.8
Keywords: automation, api-client, sync, tooling



# Installation


To install requirements: `python -m pip install requirements.txt`

To save requirements: `python -m pip list --format=freeze --exclude-editable -f https://download.pytorch.org/whl/torch_stable.html > requirements.txt`

* Note we use Python 3.9.4 for our experiments

# Running the code 

For remaining experiments: 

Navigate to the corresponding directory, then execute: `python run.py -m` with the corresponding `config.yaml` file (which stores experiment configs).

# License

Consult License.md
dlt-runtime 0.21.2a0
CLI tool for accessing dltHub runtime
Requires Python: <3.15,>=3.9.2
Keywords: etl

<h1 align="center">
    <strong>dlt-runtime</strong>
</h1>

<div align="center">
  <a target="_blank" href="https://dlthub.com/community" style="background:none">
    <img src="https://img.shields.io/badge/slack-join-dlt.svg?labelColor=191937&color=6F6FF7&logo=slack" style="width: 260px;"  />
  </a>
</div>
<div align="center">
  <a target="_blank" href="https://pypi.org/project/dlt-runtime/" style="background:none">
    <img src="https://img.shields.io/pypi/v/dlt-runtime?labelColor=191937&color=6F6FF7">
  </a>
  <a target="_blank" href="https://pypi.org/project/dlt-runtime/" style="background:none">
    <img src="https://img.shields.io/pypi/pyversions/dlt-runtime?labelColor=191937&color=6F6FF7">
  </a>
</div>

`dlt-runtime` is an extension to the open source data load tool ([dlt]((https://dlthub.com/docs/))) that implements
**dltHub Runtime** API Client and extends the `dlt` command line with `dlt runtime` command. Overall it enables `dlt` users
to quickly deploy and run their pipelines, datasets, notebooks and mcp servers.


## Installation

`dlt-runtime` supports Python 3.10 and above and is a plugin (based on [pluggy](https://github.com/pytest-dev/pluggy)) Use `hub` extra on `dlt` to pick the matching plugin version:

```sh
pip install "dlt[hub]"
```


## Documentation

Learn more in the [dlthub docs](https://dlthub.com/docs/hub/intro).
posecheck-fast 0.1.13
Fast docking evaluation metrics: symmetry-corrected RMSD and PoseBusters filters
Requires Python: >=3.10
Keywords: docking, rmsd, posebusters, molecular-docking, benchmark

# posecheck-fast

[![PyPI version](https://badge.fury.io/py/posecheck-fast.svg)](https://pypi.org/project/posecheck-fast/)
[![CI](https://github.com/LigandPro/posecheck-fast/actions/workflows/ci.yml/badge.svg)](https://github.com/LigandPro/posecheck-fast/actions/workflows/ci.yml)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg)](https://www.python.org/downloads/)

Fast docking evaluation metrics: symmetry-corrected RMSD and lightweight PoseBusters filters.

## Installation

```bash
uv pip install posecheck-fast
```

## Features

- **Symmetry-corrected RMSD** — accounts for molecular symmetry (benzene, carboxylates, etc.)
- **Fast PoseBusters filters** — 4 distance/clash checks optimized for throughput (auto-uses CUDA if available)

## Performance

Designed for throughput: **~0.03–0.12 ms/pose** on the fast filter set (CPU/GPU depending on batch size).

## Usage

```python
from posecheck_fast import compute_all_isomorphisms, get_symmetry_rmsd_with_isomorphisms

# Symmetry-corrected RMSD
isomorphisms = compute_all_isomorphisms(rdkit_mol)
rmsd = get_symmetry_rmsd_with_isomorphisms(true_coords, pred_coords, isomorphisms)
```

```python
from posecheck_fast import check_intermolecular_distance

# Fast filters: not_too_far_away, no_clashes, no_volume_clash, no_internal_clash
results = check_intermolecular_distance(
    mol_orig=rdkit_mol,
    pos_pred=pred_positions,      # (n_samples, n_atoms, 3)
    pos_cond=protein_positions,   # (n_protein_atoms, 3)
    atom_names_pred=lig_atoms,
    atom_names_cond=prot_atoms,
)
```

## Related

- [PoseBench](https://github.com/BioinfoMachineLearning/PoseBench) — full benchmark suite
- [PoseBusters](https://github.com/maabuu/posebusters) — full 27-test validation
- [spyrmsd](https://github.com/RMeli/spyrmsd) — symmetry RMSD algorithms

## License

MIT