Metadata-Version: 2.1
Name: pymarket
Version: 0.7.5
Summary: A simple library for simulating markets in Python
Home-page: https://github.com/gus0k/pymarket
Author: Diego Kiedanki
Author-email: gusok@protonmail.com
License: MIT license
Description: 
        # PyMarket
        
        [![Build Status](https://travis-ci.org/gus0k/pymarket.svg?branch=master)](https://travis-ci.org/gus0k/pymarket)
        
        [![Documentation Status](https://readthedocs.org/projects/pymarket/badge/?version=latest)](https://pymarket.readthedocs.io/en/latest/?badge=latest)
        
        [![PyPI version](https://badge.fury.io/py/pymarket.svg)](https://badge.fury.io/py/pymarket)
        
        PyMarket is a python library designed to ease the simulation and
        comparison of different market mechanisms.
        
        Marketplaces can be proposed to solve a diverse array of problems. They
        are used to sell ads online, bandwith spectrum, energy, etc.
        PyMarket provides a simple environment to try, simulate and compare different
        market mechanisms, a task that is inherent to the process of establishing a new
        market.
        
        As an example, Local Energy Markets (LEMs) have been proposed to syncronize energy consumption
        with surplus of renewable generation. Several mechanisms have been proposed for such a market:
        from double sided auctions to p2p trading. 
        
        This library aims to provide a simple interface for such process, making results reproducible.
        
        ## Getting Started
        
        
        ```python
        import pymarket as pm
        import numpy as np
        
        r = np.random.RandomState(1234)
        
        mar = pm.Market()
        bids = pm.datasets.uniform_bidders.generate(20, 20, 1, 1, r)
        for b in bids:
            mar.accept_bid(*b)
            
        mar.plot()
        ```
        
        
        ![png](README_files/README_4_0.png)
        
        
        ### Access the bids
        
        
        ```python
        bids = mar.bm.get_df()
        bids.head()
        ```
        
        
        
        
               quantity   price  user  buying  time  divisible
            0    0.2374  1.0234     0    True     0       True
            1    0.1784  1.1770     1    True     0       True
            2    0.6301  1.5789     2    True     0       True
            3    0.1600  1.8008     3    True     0       True
            4    0.7920  1.5478     4    True     0       True
        
        
        
        ### Run a market algorithm
        
        
        ```python
        transactions, extra = mar.run('p2p', r=r)
        transactions = transactions.get_df()
        transactions.head()
        ```
        
        
        
        
               bid  quantity   price  source  active
            0   16    0.0000  0.0000      34    True
            1   34    0.0000  0.0000      16    True
            2    0    0.0000  0.0000      23    True
            3   23    0.0000  0.0000       0    True
            4   12    0.0786  1.3828      26   False
        
        
        
        ## Documentation and Examples
        
        [Docs can be found here (click me!)](https://pymarket.readthedocs.io)
        
        # Installation
        
        ```python
        pip install pymarket
        ```
        
Keywords: pymarket
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
