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Examples

Reading and writing CLDF data

As an extended example for reading and writing CLDF data with pycldf, we will extract a single WALS feature as "stand-alone" CLDF dataset from the full WALS Online v2020 data at https://doi.org/10.5281/zenodo.3731125 .

The same data is also available from GitHub in a form that pycldf can access directly, i.e. without first downloading and unzipping the packed version of the dataset.

Now we can run the script wals2cldf.py as follows:

$ python wals2cldf.py 1A

Please inspect the heavily documented, short script wals2cldf.py for idiomatic use of pycldf functionalties.

This packages the values of feature 1A as CLDF StructureDataset and we can now inspect the directory it created:

$ ls -ks1 wals_1A_cldf/
total 212
 12 StructureDataset-metadata.json
  4 codes.csv
 40 languages.csv
  4 parameters.csv
124 sources.bib
 28 values.csv

For further inspection we can use the cldf command:

$ cldf validate wals_1A_cldf/StructureDataset-metadata.json
$ cldf stats wals_1A_cldf/StructureDataset-metadata.json
<cldf:v1.0:StructureDataset at wals_1A_cldf>
key            value
-------------  ----------------------------------------------------
dc:conformsTo  http://cldf.clld.org/v1.0/terms.rdf#StructureDataset
dc:source      sources.bib

Path            Type              Rows
--------------  --------------  ------
values.csv      ValueTable         563
languages.csv   LanguageTable      563
parameters.csv  ParameterTable       1
codes.csv       CodeTable            5
sources.bib     Sources            947