PASTA electronic lab notebook (ELN) | The favorite ELN for experimental scientists
PASTA-ELN (adaPtive mAterials Science meTadatA - Electronic Lab Notebook) provides a streamlined and efficient solution for experimental scientists to manage and organize raw data alongside associated metadata. By leveraging extractors that automate the processing of raw measurement files, PASTA-ELN facilitates the seamless integration of thumbnails, data, and metadata into a centralized database. These extractors can be customized and shared by users, empowering researchers to tailor their workflows to their specific needs.
Location of information
More information, incl. detailed installation instructions, for users can be found on the Github-pages.
While people that are interested into the development are guided to github.
Short installation instructions
pip install pasta-eln
To start PASTA-ELN, use:
pastaELN
which will automatically open the graphical user interface (GUI) to finish the setup.
More detail are found at the install-page.
1 maintainer
Release files for pasta-eln 3.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pasta_eln-3.3.0.tar.gz | 1.2 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pasta_eln-3.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.7 MB
Release files / pasta_eln-3.3.0.tar.gz
| Download URL | pasta_eln-3.3.0.tar.gz |
|---|---|
| Size | 1.2 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / pasta_eln-3.3.0-py3-none-any.whl
| Download URL | pasta_eln-3.3.0-py3-none-any.whl |
|---|---|
| Size | 460.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
e0b82ffc1e70b1f6f8f470bf9073cbf98d6e02e362c45cecdcb32fdf90b778d1
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|
BLAKE2b-256 checksum How to use checksums |
a79de958817f3c0ce229af7ae539fb98049de1ce542986d86c35e0a5f455d9f5
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
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 Sep 24, 2026.
Transparency log
