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Convert iRODS Metadata into a Python dictionary

The md2dict module of mango_mdconverter creates Python dictionaries by flattening namespaced iRODS metadata items. This can be done:

  • naively with regards to the semantics, simply unnesting the namespacing
    • also ignoring units
    • returning value-units tuples if units exist
  • reorganizing the dictionary to bring ManGO schemas together and “analysis” metadata together

The module can be imported like so:

from mango_mdconverter import md2dict

Example

To understand this better, let’s look at some examples. We’ll simulate a set of metadata from an iRODS item, and it looks like so:

from irods.meta import iRODSMeta

metadata_items = [
    iRODSMeta("mgs.book.author.name", "Fulano De Tal", "1"),
    iRODSMeta("mgs.book.author.age", "50", "1"),
    iRODSMeta("mgs.book.author.pet", "cat", "1"),
    iRODSMeta("mgs.book.author.name", "Jane Doe", "2"),
    iRODSMeta("mgs.book.author.age", "29", "2"),
    iRODSMeta("mgs.book.author.pet", "cat", "2"),
    iRODSMeta("mgs.book.author.pet", "parrot", "2"),
    iRODSMeta("mgs.book.title", "A random book title"),
    iRODSMeta("mg.mime_type", "text/plain"),
    iRODSMeta("page_n", "567", "analysis/reading"),
    iRODSMeta("chapter_n", "15", "analysis/reading"),
]

Naive conversion

The unflatten_namespace_into_dict() function updates a dictionary with the name-value pairs of an AVU, and optionally with the units as well. Given a dictionary metadict, we can provide it an AVU name and value to either add the respective keys and values to the dictionary or, if the key already exists, to append the value to the list of values.

metadict = {}
md2dict.unflatten_namespace_into_dict(metadict, "AVU_name", "AVU_value")
metadict
{'AVU_name': 'AVU_value'}

Metadata names with dots will be assumed to be namespaced: they will be split and their values will become dictionaries themselves.

metadict = {}
md2dict.unflatten_namespace_into_dict(metadict, "level1.level2.level3", "AVU_value")
metadict
{'level1': {'level2': {'level3': 'AVU_value'}}}

For a full list of metadata items, such as the output of the .metadata.items() method of an iRODS data object or collection, we could loop over the iterable:

metadict = {}
for avu in metadata_items:
    md2dict.unflatten_namespace_into_dict(metadict, avu.name, avu.value)
metadict
{'mgs': {'book': {'author': {'name': ['Fulano De Tal', 'Jane Doe'],
    'age': ['50', '29'],
    'pet': ['cat', 'cat', 'parrot']},
   'title': 'A random book title'}},
 'mg': {'mime_type': 'text/plain'},
 'page_n': '567',
 'chapter_n': '15'}

As you can see from the example, the function can work ignoring units. This functionality is sufficient for the opensearch indexing.

For ManGO schemas, however, we want to use the units to keep track of repeatable composite fields. In order to achieve that, we just have to also provide the unit and set the use_units argument to True.

The unpack_metadata_to_dict() is a wrapper around this function that always uses units and takes the whole irods.meta.iRODSMeta object as an argument instead of the name, value and units separately.

metadict = {}
for avu in metadata_items:
    md2dict.unpack_metadata_into_dict(metadict, avu)
metadict
{'mgs': {'book': {'author': {'name': [('Fulano De Tal', '1'),
     ('Jane Doe', '2')],
    'age': [('50', '1'), ('29', '2')],
    'pet': [('cat', '1'), ('cat', '2'), ('parrot', '2')]},
   'title': 'A random book title'}},
 'mg': {'mime_type': 'text/plain'},
 'page_n': ('567', 'analysis/reading'),
 'chapter_n': ('15', 'analysis/reading')}

Now items with units are rendered as tuples of values and units, but these are not interpreted in the context of ManGO. This is why this approach is the “naïve” one: in order to reorganize this dictionary into something that makes sense given how ManGO uses schemas and units, we need to use another function.

ManGO-specific conversion

The convert_metadata_to_dict() function takes an iterable of irods.meta.iRODSMeta instances and returns a nested dictionary based on the namespacing of the metadata names as well as the units. It works upon the result of unpack_metadata_into_dict() and then reformats the dictionary to group all metadata schemas under the “schemas” key (instead of “mgs”) and to group all items with units starting with “analysis/” under the “analysis” key. In addition, the repeatable composite fields of schemas are reorganized properly based on their units.

reorganized_dict = md2dict.convert_metadata_to_dict(metadata_items)
reorganized_dict
{'schema': {'book': {'author': [{'age': '50',
     'name': 'Fulano De Tal',
     'pet': 'cat'},
    {'age': '29', 'name': 'Jane Doe', 'pet': ['cat', 'parrot']}],
   'title': 'A random book title'}},
 'mg': {'mime_type': 'text/plain'},
 'analysis': {'reading': {'page_n': '567', 'chapter_n': '15'}}}

This function is to be used when converting ManGO metadata into a dictionary, in order to export it to a sidecar file, for downloading, or in the context of cold storage.