semvec/pypi-packages huggingface dataset:
coppice 0.2.0
A python and rust decision tree library
Requires Python: >=3.10

# coppice

A simple decision tree and random forest library using a Rust backend.

## Installation

```bash
pip install coppice
```

## Usage

### Python
```python
import numpy as np

from coppice import _coppice

x = ... # [w, n]
y = ... # [n]

x = x.astype(np.float32)
y = y.astype(np.uint32)

_coppice.train_tree_np(x, y, max_depth=5)

_coppice.train_forest_np(x, y, max_depth=5, num_trees=10)
```

### CLI

```bash
usage: coppice_ [-h] [--model-type {tree,forest}] [--num-trees NUM_TREES]
                [--max-depth MAX_DEPTH]
                x-path y-path

positional arguments:
  x-path
  y-path

options:
  -h, --help            show this help message and exit
  --model-type {tree,forest}
  --num-trees NUM_TREES
  --max-depth MAX_DEPTH
```

## Development

```bash
git clone git@github.com:JBwdn/coppice.git
cd coppice
pip install -e ".[dev]"
maturin develop
pre-commit install
```
ctpcrunch 0.0.1
A small package to compute coherence order transfer paths
Requires Python: >=3.10

# The ctpcrunch package

The ctpcrunch package is a collection of Python utilities to help understand and develop phase cycles for selecting coherence order transfer paths.

## What is a CTP?

A coherence order transfer path (CTP) describes what quantum mechanical coherence orders are present in a nuclear magnetic resonance experiment at a given point in time.


## Quickstart

## Generating and using a CTP object

```python
import ctpcrunch as cc

myctp = cc.CTP(3)

```

## Examples

### Finding the first cogwheel phase cycle

### Heteronuclear Experiment: INEPT


## Todos

- Get done.
digital-cortex 0.0.40
Python Client for Digital Cortex
Requires Python: <4.0,>=3.10

# digital-cortex

Python Client package for Digital Cortex

[# https://packaging.python.org/en/latest/tutorials/packaging-projects/]()

Aug-22-2023

### How to use:

``
pip install digital-cortex
``

```
import digital_cortex as dc

token = "get token from your digital-cortex account"

client = dc.client(token)

response = client.execute_function(......)
all_models_of_users = client.get_all_user_models()
dataset_details = client.get_particuler_dateset(dataset_id="data_set_id")
```
Repo2Prompt 0.1.2
Github repo -> prompt string
Requires Python: >=3.6

# repo2prompt

This is a simple package with minimal dependencies that turns a Github Repo's contents into a big prompt for long-context models.

this work for repos containing rust, python, javascript containing via the following file types:
'.py', '.ipynb', '.html', '.css', '.js', '.jsx', '.rst', '.md', '.rs'

Example Usage:

```python
from repo2prompt.extraction import extract_repo

extract_repo(github_url="https://github.com/vllm-project/vllm/tree/main", github_token="your_github_token")
```

Or 

```python
from repo2prompt.extraction import extract_repo

extract_repo(github_url="https://github.com/vllm-project/vllm/tree/main") # os.getenv("GITHUB_TOKEN") used internally
```

an important thing to note, github only allows 5000 requests per hour, so be careful