Skip to main content

Solid Waste Optimization Life-cycle Framework in Python(SwolfPy)

Project description

Solid Waste Optimization Life-cycle Framework in Python(swolfpy)

https://img.shields.io/pypi/v/swolfpy.svg Supported Python Versions License Format Documentation Status

Features

  • Life cycle assessment of Municipal Solid Waste (MSW) systems. Process models include Landfill, Waste-to-Energy (WTE), Composting, Anaerobic Digestion (AD), Single Stream Material Recovery Facility (MRF), Reprocessing, and Collection.

  • Monte Carlo simulation

  • Optimization

Installation

1- Download and install miniconda from: https://docs.conda.io/en/latest/miniconda.html

2- Update conda in a terminal window or anaconda prompt:

conda update conda

3- Add conda channels:

conda config --append channels conda-forge
conda config --append channels cmutel
conda config --append channels haasad

4- Create a new environment for PySWOLF:

conda create --name swolfpy python=3.7

5- Activate the environment:

conda activate swolfpy

6- Install PySWOLF in the environment:

pip install swolfpy

7- Open python to run swolfpy:

ipython

8- Run swolfpy in python:

from swolfpy import *
swolfpy()

History

0.1.6 (2020-04-11)

  • Add Reporcessing. Revise Functional units. Reivse parameters class.

0.1.0 (2020-02-27)

  • First release on PyPI. Main functionality: LCA, Monte-Carlo, and Optimization. Process Models include LF, WTE, Composting, AD, SS_MRF nd Collection.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

swolfpy-0.1.7.tar.gz (698.0 kB view details)

Uploaded Source

Built Distribution

swolfpy-0.1.7-py3-none-any.whl (639.7 kB view details)

Uploaded Python 3

File details

Details for the file swolfpy-0.1.7.tar.gz.

File metadata

  • Download URL: swolfpy-0.1.7.tar.gz
  • Upload date:
  • Size: 698.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.1.3.post20200330 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.6.9

File hashes

Hashes for swolfpy-0.1.7.tar.gz
Algorithm Hash digest
SHA256 fa6a3e3c2d98bac54dfb9289cd403e6b2f14503765fcec9b3f7f54c2e64f2221
MD5 a50ae4ffa5b9d3f7ae6d7d87d7ac8092
BLAKE2b-256 c8dd221f363ed0af45c20cc5f660421a6b979a185c333d6fd16b0bd71d34e0d1

See more details on using hashes here.

File details

Details for the file swolfpy-0.1.7-py3-none-any.whl.

File metadata

  • Download URL: swolfpy-0.1.7-py3-none-any.whl
  • Upload date:
  • Size: 639.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.1.3.post20200330 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.6.9

File hashes

Hashes for swolfpy-0.1.7-py3-none-any.whl
Algorithm Hash digest
SHA256 6846f544e36e57cebc787862f4cb76b72fb329b68575a930d2829fc04a37ca8e
MD5 0fa39ed927825debb43bf962725743a8
BLAKE2b-256 2c3f7ac9997cdaec758a3b18fd7096880343296728059ce6ff2cf58361b5fd21

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page