sfctools 1.0.5.3

Framework for stock-flow consistent agent-based modeling, being developed at the German Aerospace Center (DLR) for and in the scientific context of energy systems analysis, however, it is widely applicable in other scientific fields.

sfctools - A toolbox for stock-flow consistent, agent-based models

Sfctools is a lightweight and easy-to-use Python framework for agent-based macroeconomic, stock-flow consistent (ABM-SFC) modeling. It concentrates on agents in economics and helps you to construct agents, helps you to manage and document your model parameters, assures stock-flow consistency, and facilitates basic economic data structures (such as the balance sheet).

Installation

We recommend to install sfctools in a fresh Python 3.8 environment. For example, with conda, do

conda create --name sfcenv python=3.8
conda activate sfcenv
conda install pip

Then, in a terminal of your choice, type:

pip install sfctools

see https://pypi.org/project/sfctools/

Usage with Graphical User Interface 'Attune'

Type

python -m sfctools attune

to start the GUI.

Usage inside Python

from sfctools import Agent,World
class MyAgent(Agent):
    def __init__(self, a):
        super().__init__(self)
        self.some_attribute = a
my_agent = MyAgent()
print(my_agent)
print(World().get_agents_of_type("MyAgent"))

Running examples

| Author Thomas Baldauf, German Aerospace Center (DLR), Curiestr. 4 70563 Stuttgart | [e-mail] |