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Python implementation of CSV on the Web

Project description

About

csvwlib is a Python implementation of the W3C CSV on the Web recommendations.

This enables converting tabular data, and optionally its associated metadata, to a semantic graph in RDF or JSON-LD format.

Tabular data includes CSV files, TSV files, and upstream may be coming from spreadsheets, RDBMS export, etc.

Requires Python 3.6 or later.

Installation

pip install csvwlib

Usage

The library exposes one class - CSVWConverter which has methods to_json() and to_rdf()

Both of these methods have similar API, and require 3+ parameters:

  • csv_url - URL of a CSV file; default None
  • metadata_url - optional URL of a metadata file; default None
  • mode - conversion mode; default standard, or minimal

The are three ways of starting the conversion process:

  • pass only csv_url - corresponding metadata will be looked up based on csv_url as described in Locating Metadata

  • pass both csv_url and metadata_url - metadata by user will be used. If url field is set in metadata, the CSV file will be retrieved from that location which can cause, that passed csv_url will be ignored

  • pass only metadata_url - associated CSV files will be retrieved based on metadata url field

You can also specify the conversion mode - standard or minimal, the default is standard. From the W3C documentation:

Standard mode conversion frames the information gleaned from the cells of the tabular data with details of the rows, tables, and a group of tables within which that information is provided.
Minimal mode conversion includes only the information gleaned from the cells of the tabular data.

After conversion to JSON, you receive a dict object, when converting to RDF it is more complex. If you pass format parameter, graph will be serialized to this format and returned as string. From the rdflib docs:

Format support can be extended with plugins, but "xml", "n3", "turtle", "nt", "pretty-xml", "trix", "trig" and "nquads" are built in.

If you don't specify the format, you will receive a rdflib.Graph object.

Examples

Example data+metadata files can be found at http://w3c.github.io/csvw/tests/

Starting with CSV:

from csvwlib import CSVWConverter

CSVWConverter.to_rdf("http://w3c.github.io/csvw/tests/test001.csv", format="ttl")

Minimal mode:

from csvwlib import CSVWConverter

CSVWConverter.to_rdf("http://w3c.github.io/csvw/tests/tree-ops.csv", mode="minimal", format="ttl")

Starting with metadata only:

from csvwlib import CSVWConverter

CSVWConverter.to_rdf(metadata_url="http://w3c.github.io/csvw/tests/test188-metadata.json", format="ttl")

Both CSV and metadata URL specified:

from csvwlib import CSVWConverter

CSVWConverter.to_rdf("http://w3c.github.io/csvw/tests/tree-ops.csv", "http://w3c.github.io/csvw/tests/tree-ops.csv", format="ttl")

Starting with metadata:

from csvwlib import CSVWConverter

CSVWConverter.to_json("http://w3c.github.io/csvw/tests/countries.json")

Starting with CSV:

from csvwlib import CSVWConverter

CSVWConverter.to_json("http://w3c.github.io/csvw/tests/test001.csv")

Contributors

Authored by @Aleksander-Drozd

Maintained by @DerwenAI

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