semvec/pypi-packages huggingface dataset:
plankton 0.1.2
Plankton - wkhtmltopdf REST service
License: MIT
Keywords: html to pdf,wkhtmltopdf,pdf,rest

# Plankton - html to pdf REST service

Uses wkhtmltopdf as backend.
Only works with python 3.5 or greater.

Enspired by:
https://github.com/openlabs/docker-wkhtmltopdf and https://github.com/incuna/django-wkhtmltopdf.

## Installation
1. ```pip install plankton``` 
2. download and install wkhtmltopdf http://wkhtmltopdf.org/downloads.html.
3. Run server```plankton-server``` 

If you want to run in docker container:

1. Clone repo ```git clone git@github.com:django-stars/plankton.git```
2. ```cd plankton```
3. Build docker image ```docker build -t plankton .```
4. Run container  ```docker run -p 9003:8080  plankton```.

You can specify wkhtmltopdf command and port:
```plankton-server --wkhtmltopdf_command '/usr/local/bin/wkhtmltopdf' --port 9000```


## Usage

POST ```http://127.0.0.1:9003/html-to-pdf/```

DATA ```{"page": "http://google.com.ua"}```

You can provide wkhtmltopdf options:

DATA ```{"page": "http://google.com.ua", "options": {"javascript-delay": 2000, "cookie": [["key1","val1"], ["key2", "val2"]]}}```


## TODO
Project currently under developing and there are lot of things to do:

1. debug mode
2. HTTP OPTIONS
3. logging
4. security
5. ...
cini 0.2.4
Librería para calcular de forma automática el código de identificación normalizado de instalaciones
License: MIT

CINI
====

.. image:: https://travis-ci.org/gisce/cini.svg?branch=master
    :target: https://travis-ci.org/gisce/cini
.. image:: https://readthedocs.org/projects/cini/badge/?version=latest
    :target: http://cini.readthedocs.io/es/latest/?badge=latest
    :alt: Documentation Status
.. image:: https://coveralls.io/repos/github/gisce/cini/badge.svg?branch=master
    :target: https://coveralls.io/github/gisce/cini?branch=master


Libreria para calcular de forma automática el código de identificación normalizado
de instalaciones (CINI)

https://www.boe.es/diario_boe/txt.php?id=BOE-A-2016-4131

Instalaciones soportadas
-------------------------

- Lineas
- Transformadores
- CT’s
- Subestacions
- Posicions y parques de distribución
- Celdas y elementos de corte
- Aparatos de medidas

Para desarrollar
----------------

Para cualquier cambio en el comportamiento **debe haber** un test que implemente este
comportamiento **antes** de desarrollar el cambio (metodología `TDD <https://en.wikipedia.org/wiki/Test-driven_development>`_)

- Crear un virtualenv

.. code-block:: shell

    $ mkvirtualenv cini
    $ workon cini


- Clonar el repositorio

.. code-block:: shell

    $ git clone https://github.com/gisce/cini.git


- Instalar dependencias desarrollo

.. code-block:: shell

    $ cd cini
    $ pip install -r requirements-dev.txt
    $ pip install -e .
    
Ejecutar tests
--------------
Utilizamos el sistema de tests `Mamba <http://nestorsalceda.github.io/mamba/>`_

Con el virtualenv activado y situados en la raíz del repositorio ejecutamos:

.. code-block:: shell

    $ mamba --format=documentation
dympy 0.0.3
Python-Dymola communication on windows
License: MIT

dympy
=====

A tool to communicate with Dymola from python on Windows
dympy communicates with dymola through DDE (Dynamic Data Exchange).
After a connection with an open Dymola window is established, commands can be sent as if they were typed in the Dymola command line.
Several usefull commands (opening models, setting model parameters, compiling, writing a dsin.txt file, simulating, and loading results,...) have been predefined for ease of use.

Check the example below for a quickstart or the docstrings for a more complete guide.

Installation
------------
requires:

- ``numpy``
- ``scipy``
- ``pywin32`` `available here <http://sourceforge.net/projects/pywin32/files/pywin32/>`_.

To install download the latest `release <https://github.com/BrechtBa/dympy/releases>`_., unpack, cd to the unpacked folder and run::

	python setup.py install


Example
-------

First initialize the Dymola connection. It is good practice to clear all open models from Dymola after initialization to avoid redefinition conflicts, however this is not necessary::

	dymola = dympy.Dymola()
	dymola.clear()

Next we'll open a model and compile it::

	dymola.openModel('example.mo')
	dymola.compile('example')

Parameters can be changed using the ``set_parameters`` method. The method takes a dictionary with name, value pairs as input.
Inputs can be written to a dsu.txt file  using the ``write_dsu`` method. The method again takes a dictionary with name, value pairs as input, ``time`` must always be one of the inputs::

	dymola.set_parameters({'C_in.C':5e6,'C_em.C':10e6,'UA_em_in.G':1600,'UA_in_amb.G':200})
	dymola.set_parameters({'C_em.T':300})
	dymola.write_dsu({'time':[0,43200,86400],'Q_flow_hp':[1000,5000,2000],'T_amb':[273.15,278.15,273.15]})


The simulation can now be started within a certain time range::

	dymola.simulate(StopTime=86400)


After the simulation is finished you can load the results as a dictionary using ``get_result()``.
The result is a dictionary with the variable names in dot notation as keys::

	res = dymola.get_result()
	print(res.keys())

There is also a ``get_res`` method implemented which will return all result keys which are children of the supplied argument key.
If the argument has no children it's value is returned::

	dymola.get_res('UA_em_in')