{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# swmmio \n", "_Programmatic pre and post processing for EPA Stormwater Management Model (SWMM)_\n", "\n", "![image](_static/img/flooded_anno_example.png)\n", "\n", "\n", "## Introduction\n", "`swmmio` is a Python tool for engineers and hydrologists who need to supercharge their ability to modify and analyze EPA SWMM models and results. Using a familiar Pandas interface, users can replace manual procesess that used to live in spreadsheets with scripts and automation.\n", "\n", "The core {py:class}`~swmmio.core.Model` object provides accessors to related elements in the INP and RPT. For example, the {py:obj}`Model.subcatchments ` property provides a {py:obj}`~pandas.DataFrame` (or GeoDataFrame) accessor joining data from the `[SUBCATCHMENTS]` and `[SUBAREAS]` tables in the model.inp file and, if available, the `Subcatchment Runoff Summary` from the model.rpt file. \n", "\n", "Additionally, `swmmio` provides a lower-level {py:class}`~swmmio.core.inp` API for reading and writing (almost) all of the sections of the model.inp file which is useful for programmatically modifying EPA SWMM models.\n", "\n", "\n", "## Installation\n", "```bash\n", "pip install swmmio\n", "``` \n", "\n", "For more examples and tutorials, see the [User Guide](usage/index.md) section." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```{toctree}\n", "---\n", "maxdepth: 2\n", "hidden: \n", "---\n", "usage/index\n", "reference/index\n", "changelog\n", "```" ] } ], "metadata": { "kernelspec": { "display_name": "venv", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.4" } }, "nbformat": 4, "nbformat_minor": 2 }