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Open Sustainable Technology

SBTi Temperature Alignment tool

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

Category: Sustainable Development
Sub Category: Sustainable Investment

Keywords

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

Keywords from Contributors

climate-data-analysis

Last synced: about 5 hours ago
JSON representation

Repository metadata

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.

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

Note: This tool implements Version 1.0 of the CDP/WWF Temperature Rating Methodology, for setting and reporting on SBTi Financial Institutions Near-Term Targets. For Version 1.5 of the methodology, please refer to the CDP-WWF Temperature Scoring Methodology.

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 as a standalone Python package or as a containerised REST API.

  • Python package: Integrate directly into your codebase or run via Jupyter notebooks
  • REST API: Deploy as a microservice using the SBTi Finance Tool API

This repository contains the Python package. For the REST API, see the API repository.

Structure

The folder structure for this project is as follows:

.
├── .github                 # Github specific files (Github Actions workflows)
├── docs                    # Documentation files (Sphinx)
├── examples                # Jupyter notebook examples
├── 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

pip install -e .

For installing the latest stable release in PyPi run:

pip install sbti-finance-tool

Development

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

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:

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 metadata

GitHub Events

Total
Last Year

Committers metadata

Last synced: 5 months ago

Total Commits: 679
Total Committers: 18
Avg Commits per committer: 37.722
Development Distribution Score (DDS): 0.676

Commits in past year: 8
Committers in past year: 1
Avg Commits per committer in past year: 8.0
Development Distribution Score (DDS) in past year: 0.0

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
hbsbti h****l@s****g 10
Christian Schmidli c****i@g****m 10
David Kroon 3****0 9
MikeM M****s@O****m 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:

Issue and Pull Request metadata

Last synced: 7 months ago

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 request: 144
Bot issues: 0
Bot pull requests: 23

Past year issues: 1
Past year pull requests: 5
Past year average time to close issues: 2 days
Past year average time to close pull requests: 2 days
Past year issue authors: 1
Past year pull request authors: 2
Past year average comments per issue: 2.0
Past year average comments per pull request: 0.0
Past year merged pull request: 3
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/ScienceBasedTargets/SBTi-finance-tool

Top 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)

Top 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 Issue Labels

  • bug (13)
  • documentation (1)
  • dependencies (1)

Top Pull Request Labels

  • dependencies (29)
  • enhancement (1)

Package metadata

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.'

  • Homepage:
  • Documentation: https://sciencebasedtargets.github.io/SBTi-finance-tool
  • Licenses: MIT
  • Latest release: 1.1.0 (published 8 months ago)
  • Last Synced: 2025-10-29T20:15:56.500Z (5 months ago)
  • Versions: 11
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 100 Last month
  • Rankings:
    • Forks count: 6.378%
    • Stargazers count: 9.818%
    • Dependent packages count: 10.126%
    • Average: 12.318%
    • Downloads: 13.732%
    • Dependent repos count: 21.535%
  • Maintainers (2)

Dependencies

examples/requirements.txt pypi
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poetry.lock pypi
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pyproject.toml pypi
  • Sphinx 4.3.2 develop
  • black 21.10b0 develop
  • ipykernel 6.5.0 develop
  • pylint ^2.10.2 develop
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  • pydantic 1.8.2
  • python >=3.7.1,<4
  • requests 2.28.1
  • six 1.15.0
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requirements.txt pypi
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  • charset-normalizer ==2.0.12
  • et-xmlfile ==1.1.0
  • idna ==3.3
  • numpy ==1.22.0
  • openpyxl ==3.0.9
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  • pydantic ==1.8.2
  • python-dateutil ==2.8.2
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  • requests ==2.23.0
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setup.py pypi
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  • pydantic ==1.8.2
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examples/environment.yml pypi

Score: 11.881809572815392