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        "description": "ABCE the Agent-Based Computational Economy platform that makes modeling easier\n//////////////////////////////////////////////////////////////////////////////\n\nABCE is a Python based modeling platform for economic simulations.\nABCE comes with standard functions to simulations of trade, production\nand consumption. The modeler can concentrate on implementing\nthe logic and decisions of an agents; ABCE takes care of all exchange\nof goods and production and consumption.\n\n.. figure:: http://abce.readthedocs.io/en/0.9b/_images/cheesegrater.png\n   :target: http://35.176.189.179/ABCE/\n   :scale: 20 %\n   :align: right\n\nIn ABCE  goods have the physical properties of\ngoods in reality in the sense that if agent A gives a good to agent B, then\n- unlike information - agent B receives the good and agent B does not have\nthe good anymore.\nThe ownership and transformations (production or consumption) of goods are\nautomatically handled by the platform.\n\nABCE models are programmed in standard Python, stock functions of agents\ncan be inherited from archetype classes (Firm or Household). The only\nnot-so-standard Python is that agents are executed in parallel by the\nSimulation class (in start.py).\n\nABCE allows the modeler to program agents as ordinary Python class-objects,\nbut run the simulation on a multi-core/processor computer. It takes no\neffort or intervention from the modeler to run the simulation on a\nmulti-core system.\nThe speed advantages of using ABCE with multi-processes enabled.\nABCE are typically only observed for 10000 agents and more. Below, it\nmight be slower than pure python implementation. ABCE supports pypy3,\nwhich is approximately 10 times faster than CPython.\n\nABCE is a scheduler and a set of agent classes.\nAccording to the schedule the simulation class calls - each sub-round - agents\nto execute some actions. Each agent executes these actions\nusing some of the build-in functions, such as trade, production and\nconsumption of ABCE. The agents can use the full set of commands of the\nPython general purpose language.\n\nThe audience of ABCE are economists that want to model agent-based\nmodels of trade and production.\n\nABCE does support an accounting framework\nfor financial simulations. `ESL can be downloaded here <https://github.com/AB-CE/ABCESL>`_.\n\nABCE runs on macOS, Windows, and Linux. ABCE runs 10x faster on pypy!\n\n.. image:: https://zenodo.org/badge/4157636.svg\n   :target: https://zenodo.org/badge/latestdoi/4157636\n\n.. image:: https://travis-ci.org/AB-CE/abce.svg?branch=master\n   :alt: ABCE build status on Travis CI\n   :target: https://travis-ci.org/AB-CE/abce\n\n.. image:: https://ci.appveyor.com/api/projects/status/c2w73u9im2b87reb?svg=true\n   :alt: ABCE build status on Appveyor CI\n   :target: https://ci.appveyor.com/project/AB-CE/abce\n\n.. image:: https://img.shields.io/pypi/v/abce.svg\n   :alt:  Pypi version\n   :target: https://pypi.python.org/pypi/abce\n\n.. image:: https://readthedocs.org/projects/abce/badge/?version=master\n   :alt:  readthedocs\n   :target: https://abce.readthedocs.io\n\n\nInstall with::\n\n    pip3 install abce\n\nThe documentation is here:\n\n    http://abce.readthedocs.io/\n\nAn example is here:\n\n    `Insurance Market <http://35.176.189.179/ABCE/>`_\n\nA code example is here:\n\n    `Jupyter Tutorial <https://github.com/AB-CE/examples/tree/master/examples/jupyter_tutorial>`_\n\nMore code examples are here:\n\nhttps://github.com/AB-CE/examples\n\n",
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