semvec/pypi-packages huggingface dataset:
SymEnergy 1.0.7
Lagrange multiplier based energy market toy modeling framework

=============================
SymEnergy 
=============================

Symbolic modelling of energy systems, based on SymPy.

SymEnergy provides a framework for the structured solution of cost-optimization of energy systems using 
the standard Lagrange multiplier approach. The result consists in the close-form
analytical solutions to the optimization problem. For example, the energy production
from a power plant is expressed as
a function of the vector of symbolic parameters. These solutions are evaluated
for certain parameters in order to identify relevant constraint combinations.

============
Installation
============

``pip install symenergy``

=============
Documentation
=============

`<https://symenergy.readthedocs.io/>`_

=============
Source
=============

`<https://github.com/mcsoini/symenergy>`_
tamarco 0.1.1
Microservices framework designed for asyncio and Python
Keywords: tamarco

# Tamarco

[![Build Status](https://travis-ci.com/System73/tamarco.svg?branch=master)](https://travis-ci.com/System73/tamarco)
[![Build Documentation](https://readthedocs.org/projects/tamarco/badge/?version=latest)](https://tamarco.readthedocs.io/en/latest/)
[![Coverage](https://sonarcloud.io/api/project_badges/measure?project=System73_tamarco&metric=coverage)](https://sonarcloud.io/dashboard?id=System73_tamarco)
[![Quality Gate Status](https://sonarcloud.io/api/project_badges/measure?project=System73_tamarco&metric=alert_status)](https://sonarcloud.io/dashboard?id=System73_tamarco)

Microservices framework designed for asyncio and Python.

## Features

* Lifecycle management.
* Standardized settings via etcd.
* Automatic logging configuration. Support for sending logs to an ELK stack.
* Application metrics via Prometheus. 
* Designed for asyncio.
* Messaging patterns. The framework comes with support for AMQP and Kafka via external resources. The AMQP resource has 
implemented publish/subscribe, request/response and push/pull patterns. 
* Custom encoders and decoders. 
* Pluging oriented architecture. Anyone can create a new resource to add new functionality. External resources are integrated 
into the framework transparently for the user.
* Graceful shutdown.

## Resources

The framework allows to write external resources and integrate them in the lifecycle of a microservice easily. List with
 the available resources:

* Metrics
* Registry
* Status
* Profiler
* Memory analizer
* HTTP
* [Kafka][kafka_resource]
* [AMQP][amqp_resource]
* Postgres (not released yet)
* Influxdb (not released yet)
* Redis (not released yet)
* Websocket (not released yet)

[kafka_resource]: https://github.com/System73/tamarco-kafka
[amqp_resource]: https://github.com/System73/tamarco-amqp

Let us know if you have written a resource.

## Documentation

The documentation is available [here][readthedocs_latest].

[readthedocs_latest]: https://tamarco.readthedocs.io/en/latest/

## Examples

There are several examples in the `examples` folder.

To run them, install tamarco, launch the docker-compose (not necessary for all the examples) and run it.

```python3
pip install tamarco
docker-compose up -d
python examples/http_resource/microservice.py
```

## Requirements

Support for Python >= 3.6.
udk-configparser 1.0.2
Config parser for UDK .ini files
Requires Python: >=3.5
Keywords: ue3 udk configparser

# udk_configparser

Like CPython standard configparser but adjusted for UDK config files.

## Example usage

```python
from udk_configparser import UDKConfigParser

cg = UDKConfigParser()

cg.read("Engine.ini")
cg["Section"]["Key"] = "NewValue"

with open("Engine.ini", "w") as config_file:
    cg.write(config_file, space_around_delimiters=False)
```