semvec/pypi-packages huggingface dataset:
PermutationImportance 1.2.1.8
Important variables determined through data-based variable importance methods
License: MIT
Requires Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*
Keywords: predictor importance,variable importance,model evaluation

# <span class="permutationimportancetitle">PermutationImportance</span>

[![Build Status](https://travis-ci.com/gelijergensen/PermutationImportance.svg?branch=master)](https://travis-ci.com/gelijergensen/PermutationImportance)
[![Documentation Status](https://readthedocs.org/projects/permutationimportance/badge/?version=latest)](https://permutationimportance.readthedocs.io/en/latest/?badge=latest)

![PermutationImportance Logo](https://github.com/gelijergensen/PermutationImportance/blob/master/docs/images/favicon.png)

Welcome to the PermutationImportance library!

PermutationImportance is a Python package for Python 2.7 and 3.6+ which provides
several methods for computing data-based predictor importance. The methods
implemented are model-agnostic and can be used for any machine learning model in
many stages of development. The complete documentation can be found at our
[Read The Docs](https://permutationimportance.readthedocs.io/en/latest/).

## Version History

- 1.2.1.8: Shuffled pandas dataframes now retain the proper row indexing
- 1.2.1.7: Fixed a bug where pandas dataframes were being unshuffled when 
  concatenated
- 1.2.1.5: Added documentation and examples and ensured compatibility with
  Python 3.5+
- 1.2.1.4: Original scores are now also bootstrapped to match the other results
- 1.2.1.3: Corrected an issue with multithreading deadlock when returned scores
  were too large
- 1.2.1.1: Provided object to assist in constructing scoring strategies
  - Also added two new strategies with bootstrapping support
- 1.2.1.0: Metrics can now accept kwargs and support bootstrapping
- 1.2.0.0: Added support for Sequential Selection and completely revised backend
  for proper abstraction and extension
  - Return object now keeps track of `(context, result)` pairs
  - `abstract_variable_importance` enables implementation of custom variable
    importance methods
  - Backend is now correctly multithreaded (when specified) and is
    OS-independent
- 1.1.0.0: Revised return object of Permutation Importance to support easy
  retrieval of Breiman- and Lakshmanan-style importances
- 1.0.0.0: Published with `pip` support!
pyLivestatus 1.0.4
Python library for Livestatus Integration
License: MIT
Keywords: pyLivestatus,nagios,nagios socket

# pyLivestatus

This package allows to access [Check MK Livestatus](https://mathias-kettner.de/checkmk_livestatus.html) via python

# Usage

```python
from pyLivestatus import Livestatus

livestatus = Livestatus('127.0.0.1', '6557') # host and port of livestatus socket

livestatus.get_hosts() # return array with details for all hosts
livestatus.get_host('my_host') # return details for host 'my_host'
livestatus.get_services('my_host') # return details for every service of host 'my_host'
```