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https://github.com/gus0k/pymarket

PyMarket is a python library aimed to ease the design, simulation and comparison of different market mechanisms.
https://github.com/gus0k/pymarket

auctions energy game-theory market market-mechanisms simulation

Last synced: about 2 months ago
JSON representation

PyMarket is a python library aimed to ease the design, simulation and comparison of different market mechanisms.

Host: GitHub
URL: https://github.com/gus0k/pymarket
Owner: kiedanski
License: mit
Created: 2019-06-19T09:25:16.000Z (over 5 years ago)
Default Branch: master
Last Pushed: 2022-12-26T20:47:41.000Z (almost 2 years ago)
Last Synced: 2024-05-28T16:30:24.972Z (4 months ago)
Topics: auctions, energy, game-theory, market, market-mechanisms, simulation
Language: Python
Homepage: https://pymarket.readthedocs.io/en/latest/
Size: 649 KB
Stars: 25
Watchers: 1
Forks: 4
Open Issues: 8
Metadata Files:
- Readme: README.ipynb
- Contributing: CONTRIBUTING.rst
- License: LICENSE

Awesome Lists containing this project

README

{
"cells": [
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"tags": [
"remove_cell"
]
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import pandas as pd\n",
"pd.set_option('display.notebook_repr_html', False)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# PyMarket"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[![Build Status](https://travis-ci.org/gus0k/pymarket.svg?branch=master)](https://travis-ci.org/gus0k/pymarket)\n",
"\n",
"[![Documentation Status](https://readthedocs.org/projects/pymarket/badge/?version=latest)](https://pymarket.readthedocs.io/en/latest/?badge=latest)\n",
"\n",
"[![PyPI version](https://badge.fury.io/py/pymarket.svg)](https://badge.fury.io/py/pymarket)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"PyMarket is a python library designed to ease the simulation and\n",
"comparison of different market mechanisms.\n",
"\n",
"Marketplaces can be proposed to solve a diverse array of problems. They\n",
"are used to sell ads online, bandwith spectrum, energy, etc.\n",
"PyMarket provides a simple environment to try, simulate and compare different\n",
"market mechanisms, a task that is inherent to the process of establishing a new\n",
"market.\n",
"\n",
"As an example, Local Energy Markets (LEMs) have been proposed to syncronize energy consumption\n",
"with surplus of renewable generation. Several mechanisms have been proposed for such a market:\n",
"from double sided auctions to p2p trading. \n",
"\n",
"This library aims to provide a simple interface for such process, making results reproducible."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Getting Started"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
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Ku5DczLqb2X1AXYx1ScLi6vtXH71Ifsu0pTAbWAAMAOqBVcA34ipKciubb/2N3+jV9y9SXDIKhfC6yX8fcy0Sk8Zv/W3pttE3epHilOnso8XA3e7+Ubj9N8Aj7n57nMVJ7uhbv4hkItMxhdGNgQDg7n8BxsRTkoiIJCXTUOgStg4AMLMz0NnQIiIFJ9MP9keA35jZ8nD7ZuCheEoqPEkv7aBpoHmu8bKcqWbM0NXYJBGZDjQ/Y2bVwBWAATe6++ZYK4tBUh/Ob7wR/J44sePfGzRonNea+w+jS3RKgszdW37Q7DR3/zjsLjqJu/85tspaUF5e7tXV1Vk9t3FN/CS+NeuLn2SssdWgmQGSQ2ZW4+7l6fZL11JYCtwA1ACp6WHh9rCsK0yIZuGIiLSs1VBw9xssWNtioru/30E1iYhIQtLOPvKgf+nFDqhFREQSlumU1DVmNi7WSkREJHGZTkm9HJhtZjuBTwjHFNx9dFyFiYhIx8s0FK6LtQoREckLrYaCmfUkWCH1bOBd4Cl3P94RhYkUteZOaEuS5lQXjXQthcXAMeBNgtbCSODuuIsSKWr5dqbhG28EP+0581Oh0mmkC4WR7j4KwMyeAtbGX5JIkauszK8P0PYuBZCLUGmOgiYW6ULhWOMNdz/e5HKcrTKzpwlOfNvj7l9u5nEjuHDP9cBfgdvcfX3GbyAiHaO9IRXH+jJaCiQ26ULhfDP7OLxtQK9wu3H20WmtPHcRsBB4poXHrwOGhz8TgMfD3yJSSOJo+TSuWdPcuItaEO2S7ozmkmxf2N1/bWalrewyFXgmPDlujZmdbmZnuvvubN9TRIpES+MuakG0W5LXRBgA7ErZrg/viyUU7rkn6NZMaqVSEcmhllof+TRjq5PK9IzmODQ3QNHskq1mVmlm1WZWvXfv3qzfcOLE/JvYISKST5JsKdQDg1K2BwIfNLeju1cBVRAsnZ3Nm82fn82zRESKS5IthRXAP1rgQuCAxhNERJIVW0vBzJ4FKoC+ZlYPfBfoBuDuTwCvEkxH3U4wJfXrcdUiIiKZiS0U3P3WNI878I243l9ERNouye4jERHJMwoFERGJKBRERCSiUBARkYhCQUREIgoFERGJKBRERCSiUBARkYhCQUREIgoFERGJKBRERCSiUBARkYhCQUREIgoFERGJKBRERCSiUBARkYhCQUREIgoFERGJKBRERCSiUBARkYhCQUREIgoFERGJKBRERCSiUBARkYhCQUREIgoFERGJKBRERCSiUBARkYhCQUREIgoFERGJKBRERCSiUBARkYhCQUREIrGGgplda2ZbzGy7mc1t5vHbzGyvmdWGP7PirEdERFrXNa4XNrMS4MfAVUA9sM7MVrj75ia7Pufuc+KqQ0REMhdnS2E8sN3dd7j7UWAZMDXG9xMRkXaKMxQGALtStuvD+5r6OzPbaGbLzWxQcy9kZpVmVm1m1Xv37o2jVhERId5QsGbu8ybbK4FSdx8N/B9gcXMv5O5V7l7u7uX9+vXLcZkiItIozlCoB1K/+Q8EPkjdwd33u/un4eZPgQtirEdERNKIMxTWAcPNbKiZdQduAVak7mBmZ6ZsTgHqYqxHRETSiG32kbsfN7M5wC+BEuBpd99kZg8C1e6+AvgnM5sCHAf+DNwWVz0iIpJebKEA4O6vAq82ue87Kbe/DXw7zhpERCRzOqNZREQiCgUREYkoFEREJKJQEBGRiEJBREQiCgUREYkoFEREJKJQEBGRiEJBREQiCgUREYkoFEREJKJQEBGRiEJBREQiCgUREYkoFEREJKJQEBGRiEJBREQiCgUREYkoFEREJKJQEBGRiEJBREQiCgUREYkoFEREJKJQEBGRiEJBREQiCgUREYkoFEREJKJQEBGRiEJBREQiCgUREYkoFEREJKJQEBGRSKyhYGbXmtkWM9tuZnObebyHmT0XPv62mZXGWY+IiLQutlAwsxLgx8B1wEjgVjMb2WS3O4C/uPvZwA+B/x5XPSIikl6cLYXxwHZ33+HuR4FlwNQm+0wFFoe3lwNXmpnFWJOIiLSia4yvPQDYlbJdD0xoaR93P25mB4A+wL4Y6xKRQlZbCxUVSVcRj7IymD8/1reIMxSa+8bvWeyDmVUClQCDBw9uf2UiUphmzEi6gk4vzlCoBwalbA8EPmhhn3oz6wp8Hvhz0xdy9yqgCqC8vPyk0BARAaCyMviRrMU5prAOGG5mQ82sO3ALsKLJPiuAr4W3bwL+1d31oS8ikpDYWgrhGMEc4JdACfC0u28ysweBandfATwF/IuZbSdoIdwSVz0iIpJenN1HuPurwKtN7vtOyu0jwM1x1iAiIpnTGc0iIhJRKIiISEShICIiEYWCiIhEFAoiIhKxznZagJntBf6Y5dP7UhhLaBTCcRTCMUBhHEchHAMUxnHEeQxD3L1fup06XSi0h5lVu3t50nW0VyEcRyEcAxTGcRTCMUBhHEc+HIO6j0REJKJQEBGRSLGFQlXSBeRIIRxHIRwDFMZxFMIxQGEcR+LHUFRjCiIi0rpiaymIiEgriiYUzOxaM9tiZtvNbG7S9bSVmQ0ys9fNrM7MNpnZ3UnX1B5mVmJmG8zslaRryYaZnW5my83s9+F/k4uSrikbZvafwr+n35nZs2bWM+ma0jGzp81sj5n9LuW+M8zsNTPbFv7+myRrzEQLx/E/wr+pjWb2opmd3tF1FUUomFkJ8GPgOmAkcKuZjUy2qjY7DnzT3c8FLgS+0QmPIdXdQF3SRbTDAuAX7v63wPl0wmMxswHAPwHl7v5lgiXuO8Py9YuAa5vcNxf4lbsPB34Vbue7RZx8HK8BX3b30cBW4NsdXVRRhAIwHtju7jvc/SiwDJiacE1t4u673X19ePsgwYfQgGSryo6ZDQQmA08mXUs2zOw04DKC64Hg7kfd/aNkq8paV6BXeOXD3px8dcS84+6/5uQrNE4FFoe3FwP/vkOLykJzx+Huq9z9eLi5huCKlR2qWEJhALArZbueTvqBCmBmpcAY4O1kK8nafOA/Aw1JF5KlYcBe4GdhF9iTZva5pItqK3f/N+Bh4H1gN3DA3VclW1XWvuDuuyH4AgX0T7ieXLgd+N8d/abFEgrWzH2dctqVmZ0CPA/c4+4fJ11PW5nZDcAed69JupZ26AqMBR539zHAJ3SO7ooThP3uU4GhwFnA58zsH5KtSgDM7H6CLuMlHf3exRIK9cCglO2BdIJmclNm1o0gEJa4+wtJ15Oli4EpZraToBvvCjP7n8mW1Gb1QL27N7bUlhOERGczCXjP3fe6+zHgBeArCdeUrQ/N7EyA8PeehOvJmpl9DbgB+PskrllfLKGwDhhuZkPNrDvBYNqKhGtqEzMzgj7sOnd/NOl6suXu33b3ge5eSvDf4V/dvVN9O3X3PwG7zOyc8K4rgc0JlpSt94ELzax3+Pd1JZ1wwDy0AvhaePtrwMsJ1pI1M7sW+C/AFHf/axI1FEUohAM3c4BfEvzR/y9335RsVW12MTCT4Jt1bfhzfdJFFbG7gCVmthEoA76fcD1tFrZ0lgPrgXcJPg8SP6M2HTN7FvgtcI6Z1ZvZHcB/A64ys23AVeF2XmvhOBYCpwKvhf+PP9HhdemMZhERaVQULQUREcmMQkFERCIKBRERiSgUREQkolAQEZGIQkGKmpkNNLOXw9U1d5jZQjPrkeP3qDCzr6Rszzazfwxv32ZmZ+Xy/UTaQ6EgRSs8YesF4KVwdc3hQC/gBzl+qwpSzhR29yfc/Zlw8zaCJSZE8oLOU5CiZWZXAt9198tS7jsN+CPwAPC37j4nvP8V4GF3X21mjwPjCAJkubt/N9xnJ8EKnf8O6AbcDBwhWO3yM4JF9O4iOHP4ELCTYPnkfwMOA/cDs9x9Wvh6VwF3uvuNsf0jiDShloIUs/OAExbmCxcZ3Emw6F1L7nf3cmA0MNHMRqc8ts/dxwKPA/e5+07gCeCH7l7m7m+mvNdyoJpgjZsy4FXgXDPrF+7ydeBn7Tg+kTZTKEgxM5pfLbe5VXVTfdXM1gMbCIIl9WJHjQsV1gClbSkmXPzsX4B/CK+4dREJLJ0sxa21b0MihW4T8Hepd4TdR18A9gMjUh7qGT4+FLgPGOfufzGzRY2PhT4Nf39Gdv9//QxYSdDt9POUC66IdAi1FKSY/QronTITqAR4hGBRsveAMjPrYmaDCK7eB3AawfUTDpjZFwgu8ZrOQYJFztI+5u4fECzr/l8JxhtEOpRCQYpW2F0zDbgpXF1zP9Dg7g8B/5cgGN4luDpZ46VQ3yHoNtoEPB3ul85KYFq46uWlTR5bBDwRPtYrvG8JsMvdO+Ny3NLJafaRSCg8l+BZ4MYkrwxnZguBDe7+VFI1SPFSKIjkETOrIeieusrdP023v0iuKRRERCSiMQUREYkoFEREJKJQEBGRiEJBREQiCgUREYkoFEREJPL/AGgkGDkE73FcAAAAAElFTkSuQmCC\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"import pymarket as pm\n",
"import numpy as np\n",
"\n",
"r = np.random.RandomState(1234)\n",
"\n",
"mar = pm.Market()\n",
"bids = pm.datasets.uniform_bidders.generate(20, 20, 1, 1, r)\n",
"for b in bids:\n",
" mar.accept_bid(*b)\n",
" \n",
"mar.plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Access the bids"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
" quantity price user buying time divisible\n",
"0 0.2374 1.0234 0 True 0 True\n",
"1 0.1784 1.1770 1 True 0 True\n",
"2 0.6301 1.5789 2 True 0 True\n",
"3 0.1600 1.8008 3 True 0 True\n",
"4 0.7920 1.5478 4 True 0 True"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bids = mar.bm.get_df()\n",
"bids.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Run a market algorithm"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
" bid quantity price source active\n",
"0 16 0.0000 0.0000 34 True\n",
"1 34 0.0000 0.0000 16 True\n",
"2 0 0.0000 0.0000 23 True\n",
"3 23 0.0000 0.0000 0 True\n",
"4 12 0.0786 1.3828 26 False"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"transactions, extra = mar.run('p2p', r=r)\n",
"transactions = transactions.get_df()\n",
"transactions.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Documentation and Examples\n",
"\n",
"[Docs can be found here (click me!)](https://pymarket.readthedocs.io)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Installation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"```python\n",
"pip install pymarket\n",
"```"
]
}
],
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