Samples are normally annotated with the use of AnnotationFields and AnnotationValues. However in some cases the available AnnotationFields do not suffice and it comes handy to upload sample annotations in a table where each row holds information about some sample in collection. In general, there can be multiple rows referring to the same sample in the collection (for example one sample received two or more distinct treatments). In such cases one can upload this tables with the process Metadata table. However, quite often there is exactly one-on-one mapping between rows in such table and samples in collection. In such case, please use the “unique” flavour of the above process, Metadata table (one-to-one).

Metadata in ReSDK is just a special kind of Data resource that simplifies retrieval of the above mentioned tables. In addition to all of the functionality of Data, it also has two additional attributes: df and unique:

# The "df" attribute is pandas.DataFrame of the output named "table"
# The index of df are sample ID's
# Attribute "unique" is signalling if this is metadata is unique or not


Behind the scenes, df is not an attribute but rather a property. So it has getter and setter methods (get_df and set_df). This comes handy if the default parsing logic does not suffice. In such cases you can provide your own parser and keyword arguments for it. Example:

import pandas
m.get_df(parser=pandas.read_csv, sep="\t", skiprows=[1, 2, 3])

In the most common case, Metadata objects exist somewhere on Resolwe server and user just fetches them:

# Get one metadata by slug
m = res.metadata.get("my-slug")

# Filter metadata by some conditions, e.g. get all metadata
# from a given collection:
ms = res.metadata.filter(collection=<my-collection>):

Sometimes, these objects need to be updated, and one can easily do that. However, df and unique are upload protected - they can be set during object creation but cannot be set afterwards:

m.unique = False  # Will fail on already existing object
m.df = <new-df>  # Will fail on already existing object

Sometimes one wishes to create a new Metadata. This can be achieved in the same manner as for other ReSDK resources:

m = res.metadata.create(df=<my-df>, collection=<my-collection>)

# Creating metadata without specifying  df / collection will fail
m = res.metdata.create()  # Fail
m = res.metdata.create(collection=<my-collection>)  # Fail
m = res.metdata.create(df=<my-df>)  # Fail

Alternatively, one can also build this object gradually from scratch and than call save():

m = Metadata(resolwe=<resolwe>)
m.collection = <my-collection>
my_df = m.set_index(<my-df>)
m.df = my_df

where m.set_index(<my-df>) is a helper function that finds Sample name/slug/ID column or index name, maps it to Sample ID and sets it as index. This function is recommended to use because the validation step is trying to match m.df index with m.collection sample ID’s.

Deleting Metadata works the same as for any other resource. Be careful, this cannot be undone and you need to have sufficient permissions: