The bdbag
utilities are a collection of software programs for working with
BagIt packages that conform to the BDBag and Bagit/RO profiles.
The bdbag
profiles specify the use of the fetch.txt
file, require serialization, and specify what manifests must be provided with a bdbag
.
The bdbag
utilities incorporate functions from various other Python-based bagit
components (such as the
Bagit-Python bag creation utility and the
Bagit-Profiles-Validator
utility) and wraps them in a single, easy to use software package with additional features.
Enhanced bag support includes:
- Update-in-place functionality for existing bags.
- Automatic archiving and extraction of bags using ZIP, TAR, and TGZ formats.
- Automatic generation of file manifest entries and
fetch.txt
for remote files via configuration file. - Automatic file retrieval based on the contents of a bag's
fetch.txt
file with multiple protocol support. Transport handlers forhttp(s)
,ftp
,s3
,gs
, andglobus
are provided, along with an extensibility mechanism for adding externally developed transports. - Built-in
bagit-profile
validation. - Built-in support for creation of bags with Bagit/RO profile compatibility.
An experimental Graphical User Interface (GUI) for bdbag
can be found here.
"I'll take that to go: Big data bags and minimal identifiers for exchange of large, complex datasets" explains the motivation for BDBags and the related Minid construct, provides details on design and implementation, and gives examples of use.
"Reproducible big data science: A case study in continuous FAIRness" presents a data analysis use case in which BDBags and Minids are used to capture a transcription factor binding site analysis.
- Python 2.7 is the minimum Python version required. Please note however that Python 2.7 is officially end-of-life and ongoing compatibility between Python 2.7 and
bdbag
(and its dependencies) is not officially supported and cannot be guaranteed. - Python 3, versions 3.8 through 3.12 are the current officially supported releases.
The latest bdbag
release is available on PyPi and can be installed using pip
:
pip install bdbag
Note that the above command will install bdbag
with only the minimal dependencies required to run.
If you wish to install bdbag
with the extra fetch transport handler support provided by boto
(for AWS S3)
and globus
(for Globus Transfer) packages, use the following command:
pip install bdbag[boto,globus]
You can use pip
to install bdbag
directly from GitHub:
sudo pip install git+https://github.com/fair-research/bdbag
or:
pip install --user git+https://github.com/fair-research/bdbag
You can also download the current bdbag
source code from GitHub or
alternatively clone the source from GitHub if you have git installed:
git clone https://github.com/fair-research/bdbag
From the root of the bdbag
source code directory execute the following command:
sudo pip install .
or:
pip install --user .
Note that if you want to install the extra dependencies from a local source directory you would use the following command:
pip install .[boto,globus]
The unit tests can be run by invoking the following command from the root of the bdbag
source code directory:
python setup.py test
This software can be used from the command-line environment by running the bdbag
script. For detailed usage
instructions, see the CLI Guide.
Some components of the bdbag
software can be configured via JSON-formatted configuration files.
See the Configuration Guide for further details.
It is also possible to use bdbag
from within other Python programs via an API.
See the API Guide for further details.
A CLI utility module is provided for various ancillary tasks commonly involved with authoring bdbags. See the Utility Guide for further details.
The change log is located here.