semvec/pypi-packages huggingface dataset:
fusionsolar 0.0.6
A Python client for Huawei FusionSolar
License: MIT
Keywords: Huawei PV Solar FusionSolar API Python

# FusionSolar
Python client for Huawey FusionSolar API

## Example usage

```python
from fusionsolar import Client, PandasClient
import pandas as pd

date = pd.Timestamp('20200402', tz='Europe/Brussels')

with PandasClient(user_name=user, system_code=password) as client:
    sl = client.get_station_list()
    station_code = sl['data'][0]['stationCode']
    
    df = client.get_kpi_day(station_code=station_code, date=date)

print(df)
```
onnxcustom 0.4.293
Extends scikit-learn with a couple of new models, transformers, metrics, plotting.
License: MIT
Keywords: onnxcustom,Xavier Dupré

.. image:: https://circleci.com/gh/sdpython/onnxcustom/tree/master.svg?style=svg
    :target: https://circleci.com/gh/sdpython/onnxcustom/tree/master

.. image:: https://travis-ci.com/sdpython/onnxcustom.svg?branch=master
    :target: https://app.travis-ci.com/github/sdpython/onnxcustom
    :alt: Build status

.. image:: https://ci.appveyor.com/api/projects/status/a3sn45a2fayoxb5q?svg=true
    :target: https://ci.appveyor.com/project/sdpython/onnxcustom
    :alt: Build Status Windows

.. image:: https://codecov.io/gh/sdpython/onnxcustom/branch/master/graph/badge.svg
    :target: https://codecov.io/gh/sdpython/onnxcustom

.. image:: https://badge.fury.io/py/onnxcustom.svg
    :target: http://badge.fury.io/py/onnxcustom

.. image:: http://img.shields.io/github/issues/sdpython/onnxcustom.png
    :alt: GitHub Issues
    :target: https://github.com/sdpython/onnxcustom/issues

.. image:: https://img.shields.io/badge/license-MIT-blue.svg
    :alt: MIT License
    :target: http://opensource.org/licenses/MIT

.. image:: https://pepy.tech/badge/onnxcustom/month
    :target: https://pepy.tech/project/onnxcustom/month
    :alt: Downloads

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    :target: https://github.com/sdpython/onnxcustom/
    :alt: Forks

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    :target: https://github.com/sdpython/onnxcustom/
    :alt: Stars

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    :target: https://github.com/sdpython/onnxcustom/
    :alt: size

onnxcustom: custom ONNX
=======================

.. image:: https://raw.githubusercontent.com/sdpython/onnxcustom/master/_doc/sphinxdoc/source/phdoc_static/project_ico.png
    :width: 50

`documentation <http://www.xavierdupre.fr/app/onnxcustom/helpsphinx/index.html>`_

Examples, tutorial on how to convert machine learned models into ONNX,
implement your own converter or runtime, or even train with ONNX / onnxruntime.

The function *check* or the command line ``python -m onnxcustom check``
checks the module is properly installed and returns processing
time for a couple of functions or simply:

::

    import onnxcustom
    onnxcustom.check()

The documentation also introduces *onnx*, *onnxruntime* for
inference and training.
The tutorial related to *scikit-learn*
has been merged into `sklearn-onnx documentation
<http://onnx.ai/sklearn-onnx/index_tutorial.html>`_.
Among the tools this package implements, you may find:

* a tool to convert NVidia Profilder logs into a dataframe,
* a SGD optimizer similar to what *scikit-learn* implements but
  based on *onnxruntime-training* and able to train an CPU and GPU,
* functions to manipulate *onnx* graph.
zabbixsim 0.3.0
Zabbix Agent simulator
License: MIT

# zabbixsim

Zabbix Agent Simulator (active)

The Zabbix Agent Simulator is intended to be used instead of the regular Zabbix agent in scenarios, where the use of the real Zabbix Agnet is not partical or desirable. This includes testing scenarios that are not possible on a live system.

This is works well with the snmpsim to provide simulation data for Zabbix.
<https://github.com/etingof/snmpsim>
<https://pypi.org/project/snmpsim/>

The simulator is based on the protocol documented in the Zabbbix manual.
<https://www.zabbix.com/documentation/current/manual/appendix/items/activepassive>

## Installation

```bash
pip install zabbixsim
```

## Usage

### Record simulation file

Record a simulation file from a Zabbix Server

```bash
zabbixrec
```

### Run simulation file

Run a simulation file with a Zabbix Server

```bash
zabbixsim
```

Copyright (c) 2021, [Adam Leggo](mailto:adam@leggo.id.au). All rights reserved.
provablyfair 1.0.0
Provably fair for Python
License: MIT
Requires Python: >=3.6

# Provably fair

ref: <https://dicesites.com/provably-fair>

## Example

```python
from provablyfair import ProvablyFair

f = ProvablyFair("293d5d2ddd365f54759283a8097ab2640cbe6f8864adc2b1b31e65c14c999f04")
r = f.roll("ClientSeedForDiceSites.com")
print(r.roll % (10000) / 100)
```