Skip to content
forked from glotzerlab/signac

Manage large and heterogeneous data spaces on the file system.

License

Notifications You must be signed in to change notification settings

rosecers/signac

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

signac - simple data management

PyPI conda-forge CircleCI RTD License PyPI-downloads Gitter

The signac framework helps users manage and scale file-based workflows, facilitating data reuse, sharing, and reproducibility.

It provides a simple and robust data model to create a well-defined indexable storage layout for data and metadata. This makes it easier to operate on large data spaces, streamlines post-processing and analysis and makes data collectively accessible.

Resources

Installation

The recommended installation method for signac is through conda or pip. The software is tested for Python versions 2.7 and 3.4+ and is built for all major platforms.

To install signac via the conda-forge channel, execute:

conda install -c conda-forge signac

To install signac via pip, execute:

pip install signac

Detailed information about alternative installation methods can be found in the documentation.

Quickstart

The framework facilitates a project-based workflow. Set up a new project:

$ mkdir my_project
$ cd my_project
$ signac init MyProject

and access the project handle:

>>> project = signac.get_project()

Testing

You can test this package by executing:

$ python -m unittest discover tests/

Acknowledgment

When using signac as part of your work towards a publication, we would really appreciate that you acknowledge signac appropriately. We have prepared examples on how to do that here. Thank you very much!

About

Manage large and heterogeneous data spaces on the file system.

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 99.3%
  • Other 0.7%