semvec/pypi-packages huggingface dataset:
dartsort 0.3.6.5
DARTsort
Requires Python: >=3.11

[![badge](https://github.com/cwindolf/dartsort/actions/workflows/ci.yml/badge.svg?branch=main)](https://github.com/cwindolf/dartsort/actions/)
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# dartsort

## :warning: Work in progress code repository

We do not currently recommend DARTsort for production spike sorting purposes. We are in the process of implementing a robust and documented pipeline in [`src/dartsort`](src/dartsort), and we will update this page accordingly.

A workflow described in our preprint (https://www.biorxiv.org/content/10.1101/2023.08.11.553023v1) is in [uhd_pipeline.py](scripts/uhd_pipeline.py), which is implemented using the legacy code in [`src/spike_psvae`](src/spike_psvae).


## Suggested install steps

If you don't already have Python and PyTorch 2 installed, we recommend doing this with the Miniforge distribution of `conda`. You can find info and installers for your platform [at Miniforge's GitHub repository](https://github.com/conda-forge/miniforge). After installing Miniforge, `conda` will be available on your computer for installing Python packages, as well as the newer and faster conda replacement tool `mamba`. We recommend using `mamba` instead of `conda` below, since the installation tends to be a lot faster with `mamba`.

To install DARTsort, first clone this GitHub repository.

After cloning the repository, create and activate the `mamba`/`conda` environment from the configuration file provided as follows:

```bash
$ mamba env create -f environment.yml
$ mamba activate dartsort
```

Next, visit https://pytorch.org/get-started/locally/ and follow the `PyTorch` install instructions for your specific OS and hardware needs.
We also need to install `linear_operator` from the `gpytorch` channel.
For example, on a Linux workstation or cluster with NVIDIA GPUs available, one might use (dropping in `mamba` for `conda` commands):

```bash
# Example -- see https://pytorch.org/get-started/locally/ to find your platform's command.
(dartsort) $ mamba install pytorch torchvision torchaudio pytorch-cuda=11.8 linear_operator -c pytorch -c nvidia -c gpytorch
```

Finally, install the remaining `pip` dependencies and `dartsort` itself:

```bash
(dartsort) $ pip install -r requirements-full.txt
(dartsort) $ pip install -e .
```

To enable DARTsort's default motion correction algorithm [DREDge](https://www.biorxiv.org/content/10.1101/2023.10.24.563768), clone [its GitHub repository](https://github.com/evarol/dredge), and then `cd dredge/` and install the DREDge package with `pip install -e .`.

Soon we will have a package on PyPI so that these last steps will be just a `pip install dartsort`.

To make sure everything is working:

```bash
$ (dartsort) pytest tests/*
```
prelude-cli 2.6.13
For interacting with the Prelude SDK
Requires Python: >=3.10

# Prelude CLI

Interact with the full range of features in Prelude Detect, organized by:

- IAM: manage your account 
- Build: write and maintain your collection of security tests
- Detect: schedule security tests for your endpoints

## Quick start
```bash
pip install prelude-cli
prelude --help
prelude --interactive
```

## Documentation

https://docs.preludesecurity.com/docs/prelude-cli
prelude-sdk 2.6.44
For interacting with the Prelude API
Requires Python: >=3.10

# Prelude SDK

Interact with the Prelude Service API via Python. 

> The prelude-cli utility wraps around this SDK to provide a rich command line experience.

Install this package to write your own tooling that works with Build or Detect functionality.

- IAM: manage your account
- Build: write and maintain your collection of security tests
- Detect: schedule security tests for your endpoints

## Quick start

```bash
pip install prelude-sdk
```

## Documentation 

TBD

## Testing

To test the Python SDK and Probes, run the following commands from the python/sdk/ directory:

```bash
pip install -r tests/requirements.txt
pytest tests --api https://api.preludesecurity.com --email <EMAIL>
```