Merge tag 'pybis-1.7.2' into develop

Support for DataSet containers

pybis/src/python/CHANGELOG.md

 ## Changes with pybis-1.7.2
 
-* pyBIS now allows to create dataset-containers
+* pyBIS now allows to create dataset-containers that contain no data themselves
 * datasets now show a «kind» attribute, which can be either PHYSICAL, LINK or CONTAINER
 * PropertyAssignments and other internal data are now finally nicely presented in Jupyter
+* various bugfixes
 
 ## Changes with pybis-1.7.1
 

pybis/src/python/README.md

@@ -246,6 +246,16 @@ ds_new = o.new_dataset(
     files      = ['my_analyzed_data.dat'], 
     props      = {'name': 'some good name', 'description': '...' })
 )
+
+# DataSet CONTAINER (contains other DataSets, but no files)
+ds_new = o.new_dataset(
+    type       = 'ANALYZED_DATA', 
+    experiment = '/SPACE/PROJECT/EXP1', 
+    sample     = '/SPACE/SAMP1',
+    kind       = 'CONTAINER',
+    props      = {'name': 'some good name', 'description': '...' })
+)
+
 ds_new.save()
 
 dataset.get_parents()
@@ -258,14 +268,14 @@ dataset.set_children(['20170115220259155-412'])
 dataset.add_children(['20170115220259155-412'])
 dataset.del_children(['20170115220259155-412'])
 
-# A DataSet may belong to other DataSets, which then act as containers.
-# As opposed to Samples, DataSets may belong (contained) to more than one container-DataSet
+# A DataSet may belong to other DataSets, which must be of kind=CONTAINER
+# As opposed to Samples, DataSets may belong (contained) to more than one DataSet-container
 dataset.get_containers()
 dataset.set_containers(['20170115220259155-412'])
 dataset.add_containers(['20170115220259155-412'])
 dataset.del_containers(['20170115220259155-412'])
 
-# A DataSet may contain other DataSets, to act like a container (see above)
+# A DataSet of kind=CONTAINER may contain other DataSets, to act like a folder (see above)
 # The DataSet-objects inside that DataSet are called components or contained DataSets
 # You may also use the xxx_contained() functions, which are just aliases.
 dataset.get_components()

pybis/src/python/README.rst

@@ -263,6 +263,16 @@ Datasets
        files      = ['my_analyzed_data.dat'], 
        props      = {'name': 'some good name', 'description': '...' })
    )
+
+   # DataSet CONTAINER (contains other DataSets, but no files)
+   ds_new = o.new_dataset(
+       type       = 'ANALYZED_DATA', 
+       experiment = '/SPACE/PROJECT/EXP1', 
+       sample     = '/SPACE/SAMP1',
+       kind       = 'CONTAINER',
+       props      = {'name': 'some good name', 'description': '...' })
+   )
+
    ds_new.save()
 
    dataset.get_parents()
@@ -275,14 +285,14 @@ Datasets
    dataset.add_children(['20170115220259155-412'])
    dataset.del_children(['20170115220259155-412'])
 
-   # A DataSet may belong to other DataSets, which then act as containers.
-   # As opposed to Samples, DataSets may belong (contained) to more than one container-DataSet
+   # A DataSet may belong to other DataSets, which must be of kind=CONTAINER
+   # As opposed to Samples, DataSets may belong (contained) to more than one DataSet-container
    dataset.get_containers()
    dataset.set_containers(['20170115220259155-412'])
    dataset.add_containers(['20170115220259155-412'])
    dataset.del_containers(['20170115220259155-412'])
 
-   # A DataSet may contain other DataSets, to act like a container (see above)
+   # A DataSet of kind=CONTAINER may contain other DataSets, to act like a folder (see above)
    # The DataSet-objects inside that DataSet are called components or contained DataSets
    # You may also use the xxx_contained() functions, which are just aliases.
    dataset.get_components()

pybis/src/python/pybis/__init__.py

 __author__ = 'Swen Vermeul'
 __email__ = 'swen@ethz.ch'
-__version__ = '1.7.1'
+__version__ = '1.7.2'
 
 from . import pybis
 from .pybis import Openbis

pybis/src/python/setup.py

@@ -9,7 +9,7 @@ from setuptools import setup
 
 setup(
     name='PyBIS',
-    version= '1.7.1',
+    version= '1.7.2',
     description='openBIS connection and interaction, optimized for using with Jupyter',
     url='https://sissource.ethz.ch/sispub/pybis/',
     author='Swen Vermeul |  ID SIS | ETH Zürich',