semvec/pypi-packages huggingface dataset:
jacaranda 0.0.1
Jacaranda Python Library
License: MIT
Requires Python: >=3.8.1

Jacaranda 
========================
[![PyPI version](https://badge.fury.io/py/jacaranda.svg)](https://badge.fury.io/py/jacaranda) [![GitHub version](https://badge.fury.io/gh/jacaranda-analytics%2Fjacaranda.svg)](https://badge.fury.io/gh/jacaranda-analytics%2Fjacaranda)[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)


<!-- markdown-toc start - Don't edit this section. Run M-x markdown-toc-refresh-toc -->
**Table of Contents**

- [Jacaranda ](#jacaranda)
- [Description](#description)
- [Examples](#examples)
- [Installation](#installation)
    - [GitHub](#github)
    - [Pip](#pip)
- [Examples](#examples-1)
- [License](#license)

<!-- markdown-toc end -->


# Description 

Jacaranda is a wrapper package around several Data Science and Machine Learning
librarys,  such as 

- [PyTorch](https://pytorch.org)
- [XGboost](https://xgboost.readthedocs.io/en/stable/)

which creates an easy interface to interact, and automatically tune models produced 
by these libraries. 


# Examples 

Examples for using the Jacaranda API to tune the following list of models is available in the examples folder. 

- Autoencoder 
- Variational Autoencode 
- Xgboost decicion tree
- 1D Convolutional Neural Network 
- Multilayer Perceptron 


# Installation 

Currently, there are various ways this package can be installed. 
These include 

- GitHub 
- pip

## GitHub 

To install from GitHub there are two options, 
the first option is to clone the repository and do a local installation from the cloned directory. 

```sh
git clone git@github.com:jacaranda-analytics/jacaranda.git
cd jacaranda/ && pip install . 
```

The second option is to install from GitHub without first cloning the repository, 
to install the latest master branch, run the command. 

```sh
pip install https://github.com/jacaranda-analytics/jacaranda/archive/master.zip
```

## Pip 

To install through pip, simply run 

```python 
pip install jacaranda
```



# License 

- [MIT](LICENSE.md)
genestack-client 0.35.5
Genestack Python Client Library
License: MIT
Requires Python: >2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*
Keywords: genestack,genomics,api


Python library that allows you to interact programmatically with an instance of
the Genestack platform.
XDMFWrite-h5py 0.2.0
Write XDMF files using h5py to open HDF5 file
License: MIT
Keywords: HDF5,h5py,XDMF,Paraview

[![CI](https://github.com/tdegeus/XDMFWrite_h5py/workflows/CI/badge.svg)](https://github.com/tdegeus/XDMFWrite_h5py/actions)
[![readthedocs](https://readthedocs.org/projects/xdmfwrite_h5py/badge/?version=latest)](https://readthedocs.org/projects/xdmfwrite_h5py/badge/?version=latest)

Module to write XDMF files for HDF5 files. For example:

```python
with h5py.File(root.with_suffix(".h5")) as file, xh.Grid(root.with_suffix(".xdmf")) as xdmf:

    xdmf += xh.Unstructured(file["coor"], file["conn"], "Quadrilateral")
    xdmf += xh.Attribute(file["stress"], "Cell")
```

See
**Documentation: [xdmfwrite-h5py.readthedocs.io](https://xdmfwrite-h5py.readthedocs.io/en/latest/)**
for more information and examples.
Gsauce-pyds 1.0.0
Some useful and known data structure.
License: MIT
Keywords: python,linked list,singly linked list,Binary Search Tree,Binary Tree

# Data Structures for python
- Linked List
    - Singly Linked List
    - Circularly Singly Linked List
    - Doubly Linked List
    - Circularly Doubly Linked List
- Stack
    - Stack using list 
    - Stack using linked list   
- Queue
    - Queue using singly linked list
- Dequeue 
    - dequeue using doubly linked list
- Trees
    - Binary Trees
    - Binary search trees (BST)
    
## Installation
Latest Version : 0.3.0
```
pip install Gsauce-pyds
```

## License

© 2021 Rajarshi Banerjee

This repository is licensed under the MIT license. See Licence for details.

## Link to package

<a href="https://pypi.org/project/Gsauce-pyds/">Gsauce-pyds | pypi </a>

***