semvec/pypi-packages huggingface dataset:
anomalyHTM 1.0.0
Numenta Platform for Intelligent Computing

Numenta Platform for Intelligent Computing: a machine intelligence platform that implements the HTM learning algorithms. HTM is a detailed computational theory of the neocortex. At the core of HTM are time-based continuous learning algorithms that store and recall spatial and temporal patterns. NuPIC is suited to a variety of problems, particularly anomaly detection and prediction of streaming data sources.

For more information, see http://numenta.org or the NuPIC wiki at https://github.com/numenta/nupic/wiki.
Flask-Mux 0.0.3
Minimal routing extension for Flask
Requires Python: >=3.6

Flask-Mux
================

|Build Status| |Downloads| |Latest Version| |Supported Python versions|
|License|

**Flask-Mux** is a lightweight Flask_ extension that provides a routing 
system similar to that of Express.js_. It basically wraps Flask's 
url route registrations API to add more flexibility.

.. _Flask: https://palletsprojects.com/p/flask/
.. _Express.js: https://www.expressjs.com


Installing
----------
Install using `pip`_:

.. code-block:: text

  $ pip install Flask-Mux

.. _pip: https://pip.pypa.io/en/stable/quickstart/


A Simple Example
----------------

.. code-block:: python

    from flask import Flask
    from flask_mux import Mux, Router

    app = Flask(__name__)
    mux = Mux(app)

    def home():
        return 'home'

    def about():
        return 'about'

    index_router = Router()
    index_router.get('/', home)
    index_router.get('/about', about)

    mux.use('/', index_router)


User's Guide
------------
You'll find the user guide and all documentation here_

.. _here: https://emr-flask-mux.readthedocs-hosted.com/en/latest/

Links
-----

-   Documentation: https://emr-flask-mux.readthedocs-hosted.com/en/latest/ 
-   PyPI Releases: https://pypi.org/project/Flask-Mux/
-   Source Code: https://github.com/ElMehdi19/flask-mux/
-   Issue Tracker: https://github.com/ElMehdi19/flask-mux/issues/


.. |Build Status| image:: https://github.com/ElMehdi19/flask-mux/actions/workflows/tests.yml/badge.svg
   :target: https://github.com/ElMehdi19/flask-mux/actions
.. |Latest Version| image:: https://img.shields.io/pypi/v/Flask-Mux.svg
   :target: https://pypi.python.org/pypi/Flask-Mux/
.. |Supported Python versions| image:: https://img.shields.io/pypi/pyversions/Flask-Mux.svg
   :target: https://img.shields.io/pypi/pyversions/Flask-Mux.svg
.. |License| image:: http://img.shields.io/:license-mit-blue.svg
   :target: https://pypi.python.org/pypi/Flask-Mux
.. |Downloads| image:: https://static.pepy.tech/personalized-badge/flask-mux?period=total&units=international_system&left_color=black&right_color=blue&left_text=Downloads 
   :target: https://pypi.python.org/pypi/Flask-Mux
hepynet 0.4.2
High energy physics, python based, neural network framework
Requires Python: <3.9,>=3.8

# **Hepynet**

**H**igh **e**nergy physics, **py**thon-based, neural-**net**work assistant framework

![forthebadge](https://img.shields.io/badge/hepynet-v0.4.2-blue)

## **Introduction**

The goal of the hepynet: perform DNN related high energy physics analysis tasks with simple config files

- for **ATLAS Analysis**: include supports for various ATLAS analysis jobs

- **Config Driven**: all tasks defined by a simple config file

- **Python Based**: codes are written in Python, which is the mainstream language for DNN studies

## **Installation**

```bash
pip install hepynet
```

### GPU support

- You can refer to [Tensorflow GPU support](https://www.tensorflow.org/install/gpu) to set up the environment to use GPU for training

- This is not mandatory, CPU alone is enough to run hepynet

## **Set Up the Workspace**

Please refer to [hepynet_example](https://github.com/Hepynet/hepynet_example) to see how to set up the workspace of hepynet.

## **Release Note - v0.4.2**

- Re-implement auto-tuning functions with [Ray](https://docs.ray.io/en/master/index.html) (currently, support three hyperparameter-tuning algorithms: [Ax](https://ax.dev/), [HyperOpt](http://hyperopt.github.io/hyperopt/) and [HEBO](https://github.com/huawei-noah/noah-research/tree/master/HEBO))
- Minor issues fixes and improvements
wiz-env 3.7.0
Environment management framework.

###
Wiz
###

.. image:: https://img.shields.io/pypi/v/wiz-env.svg
    :target: https://pypi.python.org/pypi/wiz-env
    :alt: PyPi Package Link

.. image:: https://github.com/themill/wiz/actions/workflows/main.yml/badge.svg?branch=master
    :target: https://github.com/themill/wiz/actions/workflows/main.yml
    :alt: Continuous Integration

.. image:: https://readthedocs.org/projects/wiz/badge/?version=stable
    :target: https://wiz.readthedocs.io/en/stable/
    :alt: Documentation Status

.. image:: https://img.shields.io/badge/group-join%20discussion-blue
    :target: https://groups.google.com/g/wiz-framework
    :alt: Google Group Page

.. image:: https://img.shields.io/badge/license-LGPL%20v3-blue.svg
    :target: https://www.gnu.org/licenses/lgpl-3.0
    :alt: License Link

Wiz is an environment management framework which consists of a Python API and a
command line tool. It can be used to run a command within a deterministic
environment resolved from one or several package requests.

The packages are defined in package definitions which are stored in one or
several registries.

The command line tool can be used as follows::

    >>> wiz use "app==2.*" my-plugin -- AppExe /path/to/script

Equivalent commands can be executed using the Python API:

.. code-block:: python

    import subprocess
    import wiz

    # Resolve context.
    context = wiz.resolve_context(["app==2.*", "my-plugin"])

    # Run command within environment.
    command = context["command"]["AppExe"]
    subprocess.call(command, environ=context["environ"])

*************
Documentation
*************

Full documentation, including installation and setup guides, can be found at
https://wiz.readthedocs.io/en/stable/

*********
Copyright
*********

Copyright (C) 2018, The Mill

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public License
along with this program.  If not, see <https://www.gnu.org/licenses/>.