Sefara is a Python library for managing your datasets. It provides a way to specify once what your datasets are (usually fileystem paths) and any metadata (e.g. which experiment they came from), then refer to them conveniently in analysis scripts and notebooks.
Sefara doesn’t assume anything about what your datasets are, what format they’re in, or are how they are accessed.
Define a “resource collection” by making a file like this, which we’ll call datasets.sefara.py:
from sefara import export export( "my_first_dataset.hdf5", path="/path/to/file1.hdf5", tags=["first", "important"], ) export( "my_second_dataset.csv", path="/path/to/file2.csv", tags=["second", "unimportant"], )
Then, use Sefara to open it in Python:
>>> import sefara >>> datasets = sefara.load("datasets.sefara.py") >>> print(datasets.filter("tags.important").path) /path/to/file1.hdf5
Available at: http://timodonnell.github.io/sefara/docs/html
pip install sefara
To run the tests:
To build the documentation:
pip install -e . pip install Sphinx cd docs make clean setup rst html
The docs will be written to the _build/html directory.
TODO: Figure out how to actually get changelog content.
Changelog content for this version goes here.