semvec/pypi-packages huggingface dataset:
petrify-bdt 1.1.0
Convert Scikit-learn and TMVA boosted decision trees (BDTs) to dependency-free C++ or Python
Requires Python: >=2.7

![](petrified-forest.jpg)

> "They took all the trees, and put em in a tree museum...
>  And they charged the people a dollar and a half to see them"
>    — Joni Mitchell, "Big Yellow Taxi"

Boosted decision trees are widely used in HEP, particularly in data analyses for
making complex, multivariate nested cuts to separate signal events from background ones.

While powerful, the complexity of their training makes BDT (and therefore
analysis) preservation troublesome: BDTs get stored in different formats, which
may not be forwards-compatible with future versions of their framework
libraries. So now we start talking about dragging around Docker containers just
to make sure the right _version_ of the right framework is used. Plus those
libraries have to be included in any user code, adding unwelcome dependencies
and complexity, and perhaps even being incompatible with the target language
(e.g. applying a BDT from a Python framework in a C++ application).

This is ridiculous, because BDTs are actually absurdly simple objects. The
framework complexity is needed for training, but not for execution. This package
provideds a set of utilities for converting sklearn and TMVA boosted decision
trees, for either classification or regression, from their custom formats to
vanilla C++ and Python code that has _no_ dependencies, can be safely used
forever without risk of format or framework breaking-changes, and by virtue of
being static code can execute more quickly and with less memory overhead than
the original form.
mendec 0.0.6
Message encrytion using RSA algorithm
Requires Python: >=3.6

# MEnDec
![Python Logo](https://www.python.org/static/community_logos/python-logo.png "Sample inline image")
![Python package](https://github.com/biojet1/mendec/workflows/Python%20package/badge.svg)
![Upload Python Package](https://github.com/biojet1/mendec/workflows/Upload%20Python%20Package/badge.svg)

[github.com/biojet1/mendec](https://github.com/biojet1/mendec)
[pypi.org/project/mendec](https://pypi.org/project/mendec/)

Python package for Message ENcryption and DEcryption

# Install
```
pip install mendec
```

# Usage

## Generate the secret key piar
```
> python -m mendec keygen --bits 384 --output SECRET_KEY
```

## Extract first key
```
> python -m mendec pick SECRET_KEY 1 KEY1
```

## Extract second key
```
> python -m mendec pick SECRET_KEY 2 KEY2
```

## Using the first key encrypt a message to CYPHER file
```
> printf 'Attack at Noon' | python -m mendec encrypt KEY1 -o CYPHER
```

## Using the second key decrypt the message
```
> python -m mendec decrypt KEY2 < CYPHER
Attack at Noon
```

## Using the second key encrypt the message, then the first key to decrypt the message
```
> printf Acknowledge | python -m mendec encrypt KEY2 | python -m mendec decrypt KEY1
Acknowledge
```

# Usage
praneethkarnenatest1 0.1.0
great app
Requires Python: >=3.7,<4.0

# MyApp Does Amazing Things!

## Installation

```
$ pip install -r requirements.txt

$ python setup.py install
```

## Development

This project includes a number of helpers in the `Makefile` to streamline common development tasks.

### Environment Setup

The following demonstrates setting up and working with a development environment:

```
### create a virtualenv for development

$ make virtualenv

$ source env/bin/activate


### run praneethkarnenatest1 cli application

$ praneethkarnenatest1 --help


### run pytest / coverage

$ make test
```


### Releasing to PyPi

Before releasing to PyPi, you must configure your login credentials:

**~/.pypirc**:

```
[pypi]
username = YOUR_USERNAME
password = YOUR_PASSWORD
```

Then use the included helper function via the `Makefile`:

```
$ make dist

$ make dist-upload
```

## Deployments

### Docker

Included is a basic `Dockerfile` for building and distributing `praneethkarnenatest1`,
and can be built with the included `make` helper:

```
$ make docker

$ docker run -it praneethkarnenatest1 --help
```
ether-addr 0.1.0
48 bit ethernet address

# 48 bit ethernet address

This package will help you in maintaining 48 bit ethernet address also known as MAC address.

## How to install it?

## On Linux

``` pip install ether_addr ```

## How to use it?

### Initialize Package

``` from ether_addr import ether_addr ```

# documentation is in it's script.


## On any issue.
### e-mail me on: skrab.sah@gmail.com
pandas-decimal 0.0.1
icy
Requires Python: >=3.8

# pandas-decimal

Extension array for pandas implementing fixed-precision decimal numbers.

Data is stored internally as integers and a dtype encoding the number of decimal
places. Operations are mostly implemented as integer arithmetic (i.e., fast!)
and always rounded to the required precision, meaning no floating point
quirks.

### Install

```bash
pip install git+//github.com/intake/pandas-decimal
```