a data warehouse for scenario analysis
Project description
The ixmp4 package for scenario data management
Copyright (c) 2023-2024 IIASA - Energy, Climate, and Environment Program (ECE)
Overview
The ixmp4 package is a data warehouse for high-powered scenario analysis in the domain of integrated assessment of climate change and energy systems modeling.
License
The ixmp4 package is released under the MIT license.
Install from pypi
You can install ixmp4 using pip:
pip install ixmp4
Install from GitHub
For installing the latest version directly from GitHub do the following.
Requirements
This project requires Python 3.10 (or higher) and poetry (>= 1.2).
Setup
# Install Poetry, minimum version >=1.2 required
curl -sSL https://install.python-poetry.org | python -
# You may have to reinitialize your shell at this point.
source ~/.bashrc
# Activate in-project virtualenvs
poetry config virtualenvs.in-project true
# Add dynamic versioning plugin
poetry self add "poetry-dynamic-versioning[plugin]"
# Install dependencies
# (using "--with dev,docs,server" if dev and docs dependencies should be installed as well)
poetry install --with dev,docs,server
# Activate virtual environment
poetry shell
# Copy the template environment configuration
cp template.env .env
# Add a test platform
ixmp4 platforms add test
# Start the asgi server
ixmp4 server start
CLI
ixmp4 --help
Docs
Read doc/README.md to build and serve the documentation locally.
Docker Image
Check docker/README.md to build and publish docker images.
Developing
See DEVELOPING.md for guidance. When contributing to this project via
a Pull Request, add your name to the "authors" section in the pyproject.toml
file.
Compatibility
This project mainly targets postgres version 16 but we test version 15 continously also. Tests with pyarrow installed alongside are also run due to its effect on pandas etc.
python | postgres | with pyarrow |
---|---|---|
3.10 | 16 | false |
3.11 | 16 | false |
3.12 | 16 | false |
3.12 | 16 | true |
3.12 | 15 | false |
Funding ackownledgement
The development of the ixmp4 package was funded from the EU Horizon 2020 projects openENTRANCE and ECEMF as well as the BMBF Kopernikus project ARIADNE (FKZ 03SFK5A by the German Federal Ministry of Education and Research).
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 835896 and 101022622.
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