semvec/pypi-packages huggingface dataset:
gunicorn-console 0.1.16
A curses application for managing gunicorn processes.
License: BSD

================
gunicorn-console
================

Created by `Stephen McDonald <http://twitter.com/stephen_mcd>`_

A curses application for managing gunicorn processes. The ``ps`` command is 
polled for gunicorn processes named with the ``setproctitle`` package and its 
output is parsed to display a list of gunicorn processes showing the process 
ID, port, name, rough memory used and number of workers for each gunicorn. 
A gunicorn in the list can then be selected and several operations are 
supported via keypresses such as modifying the number of worker process per 
gunicorn as well as reloading or shutting down the master gunicorn process.

Dependencies
============

  * `setproctitle <http://pypi.python.org/pypi/setproctitle>`_

.. image:: http://media.tumblr.com/tumblr_l35pgbDlII1qa0qji.gif
ezjson 1.0
Ezjson (means easy json) is a simple python module to encode and decode json.
License: BSD

ezjson
-------------

Ezjson (means easy json) is a simple python module to encode and decode json.
The reason by which I did this module, is because i dont like the way as anothers modules, works .
There is some python objects (like datetime.date) that isn't JSON serializable and it often generates errors.
Encode and decode JSON it should be an simple task, like in PHP way.
logplex 0.0.3
A Logplex client for Python.
License: BSD

Python-Logplex
==============

Python-Logplex is a fast & efficient client for sending log messages to
Heroku's `Logplex project <http://github.com/heroku/logplex>`_. It uses keep-alive
connections to enable high-throughput with little overhead.

Usage
-----

First, install the library::

    $ pip install logplex

Then, send some sample data::

    from logplex import Logplex

    logplex = Logplex(token='SECRETSAUCE')

    logplex.puts('\o/')
tradingmachine 0.1.7
A backtester for financial algorithms.
License: BSD

TradingMachine
=======

TradingMachine is intend to bring optimization and machine techniques into finance algorithmic trading.

Discussion and Help
===================

TODO

Features
========

* Optimization on strategy parameters.
* PyBrain Integration (Reinforcement Learning, Neural Network ...).
* TA-Lib Integration (Most common technical analysis available.)
* Pandas (High speed time series data analysis)


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

# You will first need to install TALib. ta-lib is a python wrapper for that. Please refer [TA-Lib](http://ta-lib.org/hdr_doc.html)

TradingMachine can be installed via pip

```
pip install numpy
pip install matplotlib
pip install pandas
pip install ta-lib		
pip install tradingmachine
```

If there are problems installing the dependencies, please consider install scipy stack.
For Windows, the [Enthought Python Distribution](http://www.enthought.com/products/epd.php)
includes most of the necessary dependencies. 
On OSX, the [Scipy Superpack](http://fonnesbeck.github.com/ScipySuperpack/) works very well.
Other platforms, the [Scipy Stack](http://www.lfd.uci.edu/~gohlke/pythonlibs/) has binary available to install.

After installation, you will need to create a configuration file in home directory named ".tmconfig.ini".

Example:
```
  1 [DEFAULT]
  2 HistoricalDataPath = /Users/chen/Repository/historicaldata
```

Configuration file is intended to point to the historical data folder.
A copy of historical data can be downloaded from: [historicalata](https://github.com/chinux23/historicaldata)

Dependencies
------------

* Python (>= 3.3.1)
* numpy (>= 1.7.1)
* pandas (>= 0.11.0)
* pytz
* ta-lib

Contact
=======

For other questions, please contact Chen Huang <chinux@gmail.com>.