semvec/pypi-packages huggingface dataset:
xslproxy 1.2.0
Xsl transforming reverse proxy based on twisted
Requires Python: >=3.5

XSL Proxy
=========

.. image:: https://travis-ci.com/znerol/xslproxy.svg?branch=master
    :target: https://travis-ci.com/znerol/xslproxy


Xsl transforming reverse proxy based on twisted_ and lxml_

.. _twisted: https://twistedmatrix.com/
.. _lxml: https://lxml.de/


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

::

   python3 -m pip install xslproxy


Usage
-----

::

   Usage: twist [options] plugin [plugin_options] xslproxy [options]
   Options:
         --backend=  Url to backend, no trailing slash [default: http://localhost]
         --help      Display this help and exit.
         --listen=   Listen port (strports syntax) [default: tcp:8080]
         --path=      [default: A directory with xsl files]
         --version   Display Twisted version and exit.


Requests to one of the proxy endpoints will be forwarded to the backend. When a
successful result is returned from the backend, content is transformed using
the specified XSL stylesheets and sent to the client. The following proxy
endpoints are available:

/transform/{XSLPARAMS}
  All stylesheets and parameters specified in XSLPARAMS are applied and to the
  backend response and the result is returned to the client with
  ``Content-Type`` header set to ``application/xml``, ``text/html`` or
  ``text/plain`` according to the ``method`` specified in the ``<xsl:output>``
  element of the last stylesheet in the chain.

The ``XSLPARAMS`` path segement takes the following ``key=value`` pairs. Each
pair separated by the ampersand (``&``) character:

xsl[]
  Relative path to a stylesheet on the server (without ``.xsl`` or ``.xslt``
  extension). This parameter can be specified multiple times.
xa[stylesheet-key]
  Stylesheet alias. Relative path to a stylesheet on the server (without
  ``.xsl`` or ``.xslt``. This parameter is usefull if the same stylesheet should
  be applied multiple times with different parameters.
xp[stylesheet-key][param-key]
  XPath parameter with the name ``param-key`` for the stylesheet specified in
  ``stylesheet-key``. The latter need to match one of the values specified via
  ``xsl[]`` parameter.
sp[stylesheet-key][param-key]
  String parameter with the name ``param-key`` for the stylesheet specified in
  ``stylesheet-key``. The latter need to match one of the values specified via
  ``xsl[]`` parameter.


License
-------

The software is subject to the AGPLv3_ or later license.

.. _AGPLv3: https://www.gnu.org/licenses/agpl-3.0.en.html
dataframe-logger 0.0.1
Logger for iterative processes.

# DataFrameLogger

[![Docs](https://readthedocs.org/projects/docs/badge/?version=latest)](https://dataframelogger.readthedocs.io/en/latest/?badge=latest)


A basic Logger based on [Pandas](https://pandas.pydata.org) useful specifically for training neural networks or other iterative processes that log data sequentially.

Required packages are in `requirements.txt`.

Usage:

- Import the logger class from the `logger.py` file as follows:

  `from logger import DFLogger`

- Initialize the logger in your code providing the names of the dataframe columns (e.g. in your component `__init__` method) and the separator to use:

  `df_logger = DFLogger(column_names='epoch | batch | lr | loss | accuracy | flag', sep='|')`

- In your training/evaluation code, you can pass the logged values one by one or as a list (same size as the number of columns provided at inistantiation of the logger):

  `df_logger.log_values_list([epoch_number, batch_number, current_lr, loss_value, accuracy_value, 'train'])`


- A call to the plotting function will generate plots for all the numerical columns with some options as grouping per flag. This call can be added for example when training neural networks at the end of each epoch.

  `df_logger.plot_columns(epoch=epoch_number, batches_per_epoch=train_data_size // batch_size, log_interval=logging_interval)`