WATTS
WATTS (Workflow and Template Toolkit for Simulation) consists of a set of Python classes that can manage simulation workflows for one or multiple codes. It provides the following capabilities:
- An isolated execution environment when running a code;
- The ability to use placeholder values in input files that are filled in programmatically;
- Seamless unit conversions when working with multiple codes;
- A managed database that simulation inputs and outputs are automatically saved to; and
- Python classes that provide extra post-processing and analysis capabilities for each code.
Installation
To install watts, run:
python -m pip install watts
Documentation
Documentation for WATTS can be found here.
Citing
If you use WATTS in your research, please consider giving proper attribution by citing the following publication:
- Paul K. Romano, Nicolas E. Stauff, Zhiee Jhia Ooi, Yinbin Miao, Amanda Lund, and Ling Zou, "WATTS: Workflow and template toolkit for simulation," Journal of Open Source Software, 7 (79), 4735 (2022). doi:10.21105/joss.04735
Sponsors
WATTS is being developed with support from Argonne National Laboratory. For any questions, please contact watts@anl.gov.
1 maintainer
Metadata
1 maintainer
Release files for watts 0.5.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| watts-0.5.2.tar.gz | 177.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| watts-0.5.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 372.8 kB
Release files / watts-0.5.2.tar.gz
| Download URL | watts-0.5.2.tar.gz |
|---|---|
| Size | 177.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
f4e41c10e0abca7222a1db9a167e87ac413246009a4d0e9a27cccb0cc3b82f06
|
|
BLAKE2b-256 checksum How to use checksums |
e5dd799c6b3c3724448d7e1f7389a676e4be5dcd10024e00fc9b6d668292835a
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.12.9
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Apr 14, 2025.
Transparency logRelease files / watts-0.5.2-py3-none-any.whl
| Download URL | watts-0.5.2-py3-none-any.whl |
|---|---|
| Size | 194.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
474e329d0a64e70aed746a7551034fabb05f7987601fc4acb8e31ace750c4a13
|
|
BLAKE2b-256 checksum How to use checksums |
6af78824efa287d0ada6d2a00b0e4a61723b63872db314fea003c1683a65eff0
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.12.9
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Apr 14, 2025.
Transparency log
