Skip to main content

Software to (re)produce burning ember diagrams of the style used in IPCC reports.

Project description

The Ember Factory

Objective

The purpose of this software is to facilitate the (re)production of burning ember diagrams of the style used in IPCC reports. An example is figure 2 from the Summary for Policymakers of the Special Report on a global warming of 1.5°C: SR15 Figure SPM.2.

The Ember Factory is a small web application ('the factory') that relies on the related EmberMaker project (...'the machine') to produce the diagrams. While the EmberFactory produces diagrams in just a few clicks, EmberMaker can be integrated into other applications as a library.

The ability of this software to reproduce many of the figures published to date by the IPCC has been carefully tested (however, the IPCC would not be responsible for any errors in this software).

How to use

This software (hereafter 'the EF') is designed to work as a web application. However, it is relatively easy to run it "locally":

  • The application is publicly available here: https://climrisk.org/emberfactory

  • To run it on your own computer, you need to have Python >= 3.10 installed, then install the EF with pip: pip3 install emberfactory Then set the environment variable needed by flask: export FLASK_APP=emberfactory (for Windows: $env:FLASK_APP = "emberfactory") and start with flask run. You should receive an url to open in your browser and access the EF, such as for example http://127.0.0.1:5000/

  • To run the app on a server, you need a WSGI server such as Gunicorn (not included in the required packages because you do not need it to run the EF locally, and you may have another WSGI server).
    If you want a root path such as /emberfactory, the EF is written so that you should set this path in the APPLICATION_ROOT variable within a file called emberfactory.cfg that needs to be located in your /instance folder (this is not entirely standard).

Development history

This software was created by philippe.marbaix -at- uclouvain.be at the end of 2019. The first objective was to produce figure 3 of Zommers et al. 2020 (doi.org/10/gg985p). Improvements were regularly provided during 2020 and this will likely continue if there are needs. Some aspects of the coding may still reflect the logic of the first versions rather than what would be done if starting from scratch; changes are done when they become useful, as experience also drives further development. Any feedback is thus very helpful!

Help is welcome to further improve the application. All contributions will be recognised :-).

No tracking

I am making efforts to avoid anything that could result in user tracking: no fonts, icons or libraries downloaded from third-parties by the user. I would like this to continue in the future. Advice would be welcome. It is also why the code is hosted by framasoft using gitlab. I thank them both.

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

emberfactory-2.1.0.tar.gz (1.1 MB view details)

Uploaded Source

Built Distribution

EmberFactory-2.1.0-py3-none-any.whl (1.1 MB view details)

Uploaded Python 3

File details

Details for the file emberfactory-2.1.0.tar.gz.

File metadata

  • Download URL: emberfactory-2.1.0.tar.gz
  • Upload date:
  • Size: 1.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.9

File hashes

Hashes for emberfactory-2.1.0.tar.gz
Algorithm Hash digest
SHA256 46f1fc69afc98107d0e884fbd8e22e033ccc2b5ae85e28100f588677935189ec
MD5 78f9a7010bf838e2bead233a3c503aec
BLAKE2b-256 1516c232ca700dc0250e28c39490113d83665f736b22f3f357bb79fb22b460e9

See more details on using hashes here.

File details

Details for the file EmberFactory-2.1.0-py3-none-any.whl.

File metadata

File hashes

Hashes for EmberFactory-2.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 95ac6d953e29dea24ec0196db7c2f3bf1713a41bd658a261bec1f9bd262ea7a7
MD5 247bf125c09986c29d238c56a0d22b61
BLAKE2b-256 f58241963c19a53871c90aa95b52e22df58b772e02db53d9549454c682679ae7

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