semvec/pypi-packages huggingface dataset:
azure-mgmt-computelimit 1.0.0b1
Microsoft Azure Computelimit Management Client Library for Python
Requires Python: >=3.9
Keywords: azure, azure sdk

# Microsoft Azure SDK for Python

This is the Microsoft Azure Computelimit Management Client Library.
This package has been tested with Python 3.9+.
For a more complete view of Azure libraries, see the [azure sdk python release](https://aka.ms/azsdk/python/all).

## _Disclaimer_

_Azure SDK Python packages support for Python 2.7 has ended 01 January 2022. For more information and questions, please refer to https://github.com/Azure/azure-sdk-for-python/issues/20691_

## Getting started

### Prerequisites

- Python 3.9+ is required to use this package.
- [Azure subscription](https://azure.microsoft.com/free/)

### Install the package

```bash
pip install azure-mgmt-computelimit
pip install azure-identity
```

### Authentication

By default, [Azure Active Directory](https://aka.ms/awps/aad) token authentication depends on correct configuration of the following environment variables.

- `AZURE_CLIENT_ID` for Azure client ID.
- `AZURE_TENANT_ID` for Azure tenant ID.
- `AZURE_CLIENT_SECRET` for Azure client secret.

In addition, Azure subscription ID can be configured via environment variable `AZURE_SUBSCRIPTION_ID`.

With above configuration, client can be authenticated by following code:

```python
from azure.identity import DefaultAzureCredential
from azure.mgmt.computelimit import ComputeLimitClient
import os

sub_id = os.getenv("AZURE_SUBSCRIPTION_ID")
client = ComputeLimitClient(credential=DefaultAzureCredential(), subscription_id=sub_id)
```

## Examples

Code samples for this package can be found at:
- [Search Computelimit Management](https://docs.microsoft.com/samples/browse/?languages=python&term=Getting%20started%20-%20Managing&terms=Getting%20started%20-%20Managing) on docs.microsoft.com
- [Azure Python Mgmt SDK Samples Repo](https://aka.ms/azsdk/python/mgmt/samples)


## Troubleshooting

## Next steps

## Provide Feedback

If you encounter any bugs or have suggestions, please file an issue in the
[Issues](https://github.com/Azure/azure-sdk-for-python/issues)
section of the project. 

# Release History

## 1.0.0b1 (2025-11-14)

### Other Changes

  - Initial version
soliscloud 1.1.9
A small package to work with Solis Cloud API

# SolisCloud

A small library to work with the Solis Cloud API for some simple
data gathering and setting.

## Prerequisites

Usage of the API requires an active account on https://www.soliscloud.com and also requires an API key and secret, to be obtained via SolisCloud.

- Submit a service ticket and wait till it is resolved.
- Go to https://www.soliscloud.com/#/apiManage.
- Activate API management and agree with the usage conditions.
- After activation, click on view key tot get a pop-up window asking for the verification code.
- First click on "Verification code" after which you get an image with 2 puzzle pieces, which you need to overlap each other using the slider below.
- After that, you will receive an email with the verification code you need to enter (within 60 seconds).
- Once confirmed, you get the:
  - KEY_ID
  - KEY_SECRET
  - API URL


## Python use
### Instantiation and simple use
```
from soliscloud import SolisCloud


s = SolisCloud(key_id="KEY_ID", key_secret="KEY_SECRET")

status, stations = s.list_stations()

first_station = stations[0]
first_station_inverters = first_station.list_inverters()
first_station_first_inverter = first_station_inverters[0]
first_station_first_inverter_schedules first_station_first_inverter.get_charge_discharge_schedules()

```

### Charging schedules

For every inverter, there are three charging schedules.

One, two and three. Each one represents a charge and a discharge schedule.

Representation of each schedule consists of a charge start / end and current.

Just in case the schedule needs to be set on an individual inverter, the method ```set_charge_discharge_schedules``` is available on the inverter.

If you want to set the schedule at the SolisCloud level, this can be carried
out using the method ```set_inverter_charge_discharge_schedule```.

Managing schedules can be done using individual schedules or using the
same schedule across all inverters.
NuMPI 0.9.0
Numerical tools for MPI-parallelized code
Requires Python: >=3.8.0

NuMPI
=====

NuMPI is a collection of numerical tools for MPI-parallelized Python codes. NuMPI presently contains:

- An (incomplete) stub implementation of the [mpi4py](https://github.com/mpi4py/mpi4py) interface to the MPI libraries. This allows running serial versions of MPI parallel code  without having `mpi4py` (and hence a full MPI stack) installed.
- Parallel file IO in numpy's [.npy](https://docs.scipy.org/doc/numpy/reference/generated/numpy.save.html) format using MPI I/O.
- An MPI-parallel implementation of the L-BFGS optimizer.
- An MPI-parallel bound constrained conjugate gradients algorithm.

Build status
------------

[![Tests](https://github.com/IMTEK-Simulation/NuMPI/actions/workflows/tests.yml/badge.svg?branch=master)](https://github.com/IMTEK-Simulation/NuMPI/actions/workflows/tests.yml) [![Flake8](https://github.com/IMTEK-Simulation/NuMPI/actions/workflows/flake8.yml/badge.svg?branch=master)](https://github.com/IMTEK-Simulation/NuMPI/actions/workflows/flake8.yml)

Installation
------------

```
python3 -m pip install NuMPI
```

Development Installation
------------------------

Clone the repository.

To use the code, install the current package as editable:

```
pip install -e .[test]
```

Testing
-------

You have to do a development installation to be able to run the tests.

We use [runtests](https://github.com/bccp/runtests). 

From the main installation directory:
```bash
python run-tests.py
```

If you want to use NuMPI without mpi4py, you can simply run the tests with pytest. 

```bash
pytest tests/
```

Testing on the cluster
----------------------
On NEMO for example

```bash
msub -q express -l walltime=15:00,nodes=1:ppn=20 NEMO_test_job.sh -m bea
```

Development & Funding
---------------------

Development of this project is funded by the [European Research Council](https://erc.europa.eu) within [Starting Grant 757343](https://cordis.europa.eu/project/id/757343) and by the [Deutsche Forschungsgemeinschaft](https://www.dfg.de/en) within project [EXC 2193](https://gepris.dfg.de/gepris/projekt/390951807).