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SBTi-finance-tool

This toolkit helps companies and financial institutions to assess the temperature alignment of current targets, commitments, and investment and lending portfolios, and to use this information to develop targets for official validation by the SBTi. See the wiki for a change log.

https://github.com/ScienceBasedTargets/SBTi-finance-tool

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (13.0%) to scientific vocabulary

Keywords

climate-data climate-model climate-science finance portfolio suistainable

Keywords from Contributors

projection interactive serializer measurement cycles packaging charts network-simulation archival shellcodes
Last synced: 6 months ago · JSON representation

Repository

This toolkit helps companies and financial institutions to assess the temperature alignment of current targets, commitments, and investment and lending portfolios, and to use this information to develop targets for official validation by the SBTi. See the wiki for a change log.

Basic Info
Statistics
  • Stars: 55
  • Watchers: 7
  • Forks: 42
  • Open Issues: 24
  • Releases: 16
Topics
climate-data climate-model climate-science finance portfolio suistainable
Created over 5 years ago · Last pushed 8 months ago
Metadata Files
Readme Contributing License Code of conduct

README.md

Visit https://sciencebasedtargets.github.io/SBTi-finance-tool/ for the full documentation

If you have any additional questions or comments send a mail to: financialinstitutions@sciencebasedtargets.org

SBTi Temperature Alignment tool

This package helps companies and financial institutions to assess the temperature alignment of current targets, commitments, and investment and lending portfolios, and to use this information to develop targets for official validation by the SBTi.

This tool can be used either as a standalone Python package, a REST API or as a simple webapp which provides a simple skin on the API. So, the SBTi toolkit caters for three types of usage:

  • Users can integrate the Python package in their codebase
  • The tool can be included as a Microservice (containerised REST API) in any IT infrastructure (in the cloud or on premise)
  • As an webapp, exposing the functionality with a simple user interface.

To following diagram provides an overview of the different parts of the toolkit:

+-------------------------------------------------+
|   UI     : Simple user interface on top of API  |
|   Install: via dockerhub                        |
|            docker.io/sbti/ui:latest             |
|                                                 |
| +-----------------------------------------+     |
| | REST API: Dockerized FastAPI/NGINX      |     |
| | Source : github.com/OFBDABV/SBTi_api    |     |
| | Install: via source or dockerhub        |     |
| |          docker.io/sbti/sbti/api:latest |     |
| |                                         |     |
| | +---------------------------------+     |     |
| | |                                 |     |     |
| | |Core   : Python Module           |     |     |
| | |Source : github.com/ScienceBasedTargets/     |
| | |               SBTi-finance-tool |     |     |
| | |Install: via source or PyPi      |     |     |
| | |                                 |     |     |
| | +---------------------------------+     |     |
| +-----------------------------------------+     |
+-------------------------------------------------+

As shown above the API is dependent on the Python Repo, in the same way the UI requires the API backend. These dependencies are scripted in the Docker files.

This repository only contains the Python module. If you'd like to use the REST API, please refer to this repository or the same repository on Dockerhub.

Structure

The folder structure for this project is as follows:

.
├── .github                 # Github specific files (Github Actions workflows)
├── app                     # FastAPI app files for the API endpoints
├── docs                    # Documentation files (Sphinx)
├── config                  # Config files for the Docker container
├── SBTi                    # The main Python package for the temperature alignment tool
└── test                    # Automated unit tests for the SBTi package (Nose2 tests)

Installation

The SBTi package may be installed using PIP. If you'd like to install it locally use the following command. For testing or production please see the deployment section for further instructions

bash pip install -e .

For installing the latest stable release in PyPi run:

bash pip install sbti-finance-tool

Development

To set up the local dev environment with all dependencies, install poetry and run

bash poetry install

This will create a virtual environment inside the project folder under .venv.

SBTi Companies Taking Action (CTA) Data

The tool supports multiple formats of the SBTi CTA file: - Per-company format (default, recommended): One row per company with aggregated target status - Per-target format: Multiple rows per company with detailed target information - Legacy format: Original Title Case column format

The tool automatically detects and handles all formats, defaulting to the per-company format for consistency.

Testing

Each class should be unit tested. The unit tests are written using the Nose2 framework. The setup.py script should have already installed Nose2, so now you may run the tests as follows:

bash nose2 -v

Publish to PyPi

The package should be published to PyPi when any changes to main are merged.

Update package

  1. bump version in pyproject.toml based on semantic versioning principles
  2. run poetry build
  3. run poetry publish
  4. check whether package has been successfully uploaded

Initial Setup

  • Create account on PyPi

Owner

  • Name: Science Based Targets initiative
  • Login: ScienceBasedTargets
  • Kind: organization

GitHub Events

Total
  • Issues event: 3
  • Watch event: 4
  • Delete event: 2
  • Issue comment event: 2
  • Push event: 8
  • Pull request event: 8
  • Create event: 3
Last Year
  • Issues event: 3
  • Watch event: 4
  • Delete event: 2
  • Issue comment event: 2
  • Push event: 8
  • Pull request event: 8
  • Create event: 3

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 678
  • Total Committers: 18
  • Avg Commits per committer: 37.667
  • Development Distribution Score (DDS): 0.676
Past Year
  • Commits: 7
  • Committers: 1
  • Avg Commits per committer: 7.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
OFJanPostema j****a@o****m 220
David Kroon d****n@o****m 144
VitoMurillo A****o@o****m 90
Joris Cramwinckel j****l@o****m 61
LEDdeBruijn l****n@o****m 47
Daan van de Meeberg d****g@o****m 29
Peter Nystroem 4****r 23
dependabot[bot] 4****] 12
Christian Schmidli c****i@g****m 10
David Kroon 3****0 9
MikeM M****s@O****m 9
hbsbti h****l@s****g 9
Christian Schmidli c****i@k****m 7
max-tikehaucapital 1****l 2
Daniel 3****I 2
Joris Cramwinckel j****1@h****m 2
Piotr Jankowski p****s@g****m 1
aleks-sch 1****h 1
Committer Domains (Top 20 + Academic)
ortec-finance.com: 4 ofdataanalytics.com: 3 king.com: 1 sciencebasedtargets.org: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 161
  • Total pull requests: 173
  • Average time to close issues: 28 days
  • Average time to close pull requests: 8 days
  • Total issue authors: 21
  • Total pull request authors: 17
  • Average comments per issue: 0.27
  • Average comments per pull request: 0.24
  • Merged pull requests: 144
  • Bot issues: 0
  • Bot pull requests: 23
Past Year
  • Issues: 1
  • Pull requests: 5
  • Average time to close issues: 2 days
  • Average time to close pull requests: 2 days
  • Issue authors: 1
  • Pull request authors: 2
  • Average comments per issue: 2.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • DaanvdMeeberg (95)
  • ofjpostema (22)
  • cschmidli (11)
  • joriscram (10)
  • LEDdeBruijn (5)
  • aleks-sch (2)
  • pjankows (2)
  • VerdureClimateLtd (1)
  • ogibbo (1)
  • JohnAdders (1)
  • lukasdenkstatt (1)
  • dependabot[bot] (1)
  • trev0rwright (1)
  • babetsdasha (1)
  • brookeann2015 (1)
Pull Request Authors
  • ofjpostema (44)
  • dependabot[bot] (28)
  • dp90 (21)
  • LEDdeBruijn (20)
  • mountainrambler (16)
  • joriscram (14)
  • cschmidli (10)
  • hubell (6)
  • max-tikehaucapital (4)
  • VitoMurillo (4)
  • hbsbti (3)
  • Waterstraal (2)
  • aleks-sch (2)
  • DaanvdMeeberg (2)
  • Warkanlock (2)
Top Labels
Issue Labels
bug (13) documentation (1) dependencies (1)
Pull Request Labels
dependencies (29) enhancement (1)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 37 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 11
  • Total maintainers: 2
pypi.org: sbti-finance-tool

This package helps companies and financial institutions to assess the temperature alignment of current targets, commitments, and investment and lending portfolios, and to use this information to develop targets for official validation by the SBTi.'

  • Versions: 11
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 37 Last month
Rankings
Forks count: 6.4%
Stargazers count: 9.8%
Dependent packages count: 10.1%
Average: 12.3%
Downloads: 13.7%
Dependent repos count: 21.5%
Maintainers (2)
cschmidli mountainrambler
Last synced: 6 months ago

Dependencies

examples/requirements.txt pypi
  • jupyter ==1.0.0
  • matplotlib ==3.2.2
  • openpyxl ==2.5.9
  • pandas ==1.0.3
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poetry.lock pypi
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  • idna 2.10
  • numpy 1.22.0
  • openpyxl 3.0.9
  • pandas 1.3.4
  • pydantic 1.8.2
  • python-dateutil 2.8.2
  • pytz 2022.1
  • requests 2.28.1
  • six 1.15.0
  • typing-extensions 4.3.0
  • urllib3 1.26.10
  • xlrd 1.2.0
pyproject.toml pypi
  • Sphinx 4.3.2 develop
  • black 21.10b0 develop
  • ipykernel 6.5.0 develop
  • pylint ^2.10.2 develop
  • sphinx-autoapi 1.8.4 develop
  • sphinx-rtd-theme 1.0.0 develop
  • openpyxl 3.0.9
  • pandas 1.3.4
  • pydantic 1.8.2
  • python >=3.7.1,<4
  • requests 2.28.1
  • six 1.15.0
  • xlrd 1.2.0
requirements.txt pypi
  • certifi ==2021.10.8
  • charset-normalizer ==2.0.12
  • et-xmlfile ==1.1.0
  • idna ==3.3
  • numpy ==1.22.0
  • openpyxl ==3.0.9
  • pandas ==1.3.4
  • pydantic ==1.8.2
  • python-dateutil ==2.8.2
  • pytz ==2021.3
  • requests ==2.23.0
  • six ==1.15.0
  • typing-extensions ==4.1.1
  • urllib3 ==1.22
  • xlrd ==1.2.0
setup.py pypi
  • openpyxl ==3.0.9
  • pandas ==1.3.4
  • pydantic ==1.8.2
  • requests ==2.28.1
  • six ==1.15.0
  • xlrd ==1.2.0
.github/workflows/docs2pages.yaml actions
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  • actions/checkout v2 composite
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.github/workflows/notebooks.yml actions
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.github/workflows/ossaudit.yml actions
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examples/environment.yml pypi