semvec/pypi-packages huggingface dataset:
alphatwirl 0.30.0
A Python library for summarizing event data

[![PyPI version](https://badge.fury.io/py/alphatwirl.svg)](https://badge.fury.io/py/alphatwirl) [![Anaconda-Server Badge](https://anaconda.org/conda-forge/alphatwirl/badges/version.svg)](https://anaconda.org/conda-forge/alphatwirl) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.597010.svg)](https://doi.org/10.5281/zenodo.597010) [![Build Status](https://travis-ci.org/alphatwirl/alphatwirl.svg?branch=master)](https://travis-ci.org/alphatwirl/alphatwirl) [![codecov](https://codecov.io/gh/alphatwirl/alphatwirl/branch/master/graph/badge.svg)](https://codecov.io/gh/alphatwirl/alphatwirl)

<br />

<img src="https://raw.githubusercontent.com/alphatwirl/alphatwirl/v0.11.0/images/AlphaTwirl_logo_black.png" width="500">

---

A Python library for summarizing event data into multivariate categorical data

### Description
_AlphaTwirl_ is a Python library that summarizes event data into multivariate categorical data as data frames. Event data, input to AlphaTwirl, are data with one entry (or row) for one event: for example, data in [ROOT](https://root.cern.ch/) [TTrees](https://root.cern.ch/doc/master/classTTree.html) with one entry per collision event of an [LHC](https://home.cern/topics/large-hadron-collider) experiment at [CERN](http://home.cern/). Event data are often large&mdash;too large to be loaded in memory&mdash;because they have as many entries as events. Multivariate categorical data, the output of AlphaTwirl, have one row for one category. They are usually small&mdash;small enough to be loaded in memory&mdash;because they only have as many rows as categories. Users can, for example, import them as data frames into [R](https://www.r-project.org/) and [pandas](http://pandas.pydata.org/), which usually load all data in memory, and can perform categorical data analyses with a rich set of data operations available in R and pandas.

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### Quick start

- Jupyter Notebook: [*Quick start of AlphaTwirl*](https://github.com/alphatwirl/notebook-tutorial-2019-02)<br />

&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/alphatwirl/notebook-tutorial-2019-02/master?filepath=tutorial_01.ipynb)

****

### Publication

- Tai Sakuma, *"AlphaTwirl: A Python library for summarizing event data into multivariate categorical data"*,
  EPJ Web of Conferences **214**, 02001 (2019), [doi:10.1051/epjconf/201921402001](https://doi.org/10.1051/epjconf/201921402001),
  [1905.06609](https://arxiv.org/abs/1905.06609)

****

### License

- AlphaTwirl is licensed under the BSD license.

*****

### Contact

- Tai Sakuma - tai.sakuma@gmail.com
django-quickstart 0.1
A tool for automating the Django project creation process.

# Django Quickstart

A command line interface for automating the Django project creation process.

# Operating System

These instructions are meant for Mac OS.

## Setup

1. Navigate to this directory and run `chmod +x quickstart.sh`
2. Run `./quickstart.sh` and the names for the project and app when prompted
3. Move project to desired directory.

## Virtual environment

1. Create a virtual environment `virtualenv venv`
2. Activate virtual environment `source venv/bin/activate`
3. Run `pip install -r requirements.txt`

## Database
2. Run `python manage.py migrate`
3. Run `python manage.py createsuperuser` then enter the requested information
4. Start the server `python manage.py runserver`

The app should now be viewable in a browser window at `http://localhost:8000/[APP NAME]/`.
snoop-tensor 0.2
Tensor extension for snoop

# snoop-tensor
Numpy/Pytorch Tensor extension for snoop. It's modified from [TorchSnooper](https://github.com/zasdfgbnm/TorchSnooper)

# Usage

```python
import snoop, snoop_tensor
snoop.install()
snoop_tensor.register() # need to be called after install()
```

## Features

- Display tensors in a beautiful way
- Profiling GPU memory usage and time usage
prcslib 4.1
Python API for PRCS.
Requires Python: >=2.7

# Introduction

The [`prcslib` package][prcslib] provides a <dfn>Python API for PRCS</dfn>.

[PRCS][] (Project Revision Control System) is a legacy version control system
that manages a *project* consisting of multiple files
and records related changes across them as a unit.

See the [home page][] for more information about the `prcslib` package.

[home page]: https://vx68k.bitbucket.io/prcslib.py/
[prcslib]: https://pypi.org/project/prcslib/
[PRCS]: http://prcs.sourceforge.net/

[![(Chat)](https://img.shields.io/gitter/room/vx68k/prcslib.py.svg)][Gitter room]
[![(Issues)](https://img.shields.io/bitbucket/issues/kazssym/prcslib.py.svg)][open issues]

[Gitter room]: https://gitter.im/vx68k/prcslib.py
[open issues]: https://bitbucket.org/kazssym/prcslib.py/issues?status=new&status=open

# License

This program is provided under the terms and conditions of the
[MIT License][MIT].

[![(License)](https://img.shields.io/badge/license-MIT-blue.svg)][MIT]

[MIT]: https://opensource.org/licenses/MIT "MIT License"

# Links

  - A [modified version of PRCS][downloads] that runs on recent Linux operating
    systems.

[downloads]: https://bitbucket.org/kazssym/prcs/downloads/
ndexr-redditor 0.0.2
A simple package for gathering Reddit data
Requires Python: >=3.4
Keywords: package numbers calculations

# Installation

```
python setup.py install
```

```
python3 -m pip install --upgrade setuptools wheel
```

```
python3 setup.py sdist bdist_wheel
```

```
python3 -m pip install --upgrade twine
```

```
twine upload --repository-url https://test.pypi.org/legacy/ dist/*
```
```
pip install ndexr_redditor
```

```
python3 -m twine upload dist/*
```

# Usage

Initialization is not required for using methods in ndexr_numdata
```
from ndexr_numdata import calculate
calculate.calculate_cube(3)
```
ndexr-reddit 0.0.2
A simple package for gathering Reddit data
Requires Python: >=3.4
Keywords: package numbers calculations

# Installation

```
sudo python setup.py install
```

```
python3 -m pip install --upgrade setuptools wheel
```

```
sudo python3 setup.py sdist bdist_wheel
```

```
python3 -m pip install --upgrade twine
```

```
twine upload --repository-url https://test.pypi.org/legacy/ dist/*
```
```
pip install ndexr_numdata
```

```
python3 -m twine upload dist/*
```

# Usage

Initialization is not required for using methods in ndexr_numdata
```
from ndexr_numdata import calculate
calculate.calculate_cube(3)
```