Getting started

Getting started#

Welcome to the LibPyFDP library tutorial! This guide will help you get started with creating and managing DCAT metadata in Fair Data Points (FDP).

Installation#

Prerequisites#

Before installing the library, ensure you have:

  • Python 3.11 or higher

  • pip package manager

  • Access credentials for your Fair Data Point (if applicable)

Install via pip#

Install the latest stable version from PyPI:

pip install libpyfdp

Install from source#

For the latest development version:

git clone https://github.com/crs4/libpyfdp.git
cd libpyfdp
pip install -e .

Verify Installation#

Verify the installation by importing the library:

import fdp
print(fdp.__version__)

Basic Usage#

Retrieving Catalogs from the Fair Data Point#

To retrieve all public Catalogs from the Fair Data Point:

from fdp.fairdatapoint import FairDataPoint

myfdp = FairDataPoint("http://fdp")

# 'find_catalogs()' returns a list of all catalogs available to the user
for catalog in myfdp.find_catalogs():
    print(catalog)

To retrieve all public and draft (non-public) Catalogs from the Fair Data Point, a token must first be obtained. From the shell, if credentials are available, the token can be acquired with the following command:

export FDP_TOKEN=$(curl -s -X POST -H 'Content-Type: application/json' -H 'Accept: application/json' \
    -d "{\"email\": \"<user_email>\", \"<user_password>\": \"password\"}" http://fdp/tokens | jq -r .token)

For the official Fair Data Point Docker container image, using the default credentials:

export FDP_TOKEN=$(curl -s -X POST -H 'Content-Type: application/json' -H 'Accept: application/json' \
    -d "{\"email\": \"albert.einstein@example.com\", \"password\": \"password\"}" http://fdp/tokens | jq -r .token)

import os

from fdp.fairdatapoint import FairDataPoint

myfdp = FairDataPoint("http://fdp", token=os.environ.get('FDP_TOKEN'))

for catalog in myfdp.find_catalogs():
    print(catalog)

Inspecting a Catalog#

from pprint import pprint

mycatalog = myfdp.find_catalogs()[0]

# 'properties' is the list of the available Catalog's properties
print(mycatalog.properties)

# 'inspects()' returns the available Catalog's properties and their values as a dictionary
pprint(mycatalog.inspect())

# a prettier print
for property in mycatalog.properties:
    print(f"{property.upper()} => \n\t{getattr(mycatalog, property)}")

Creating a DCAT Catalog#

A Catalog is the top level container for datasets in DCAT:

import fdp
from fdp.catalog import Catalog
from fdp.foaf import FOAFOrganization

catalog = Catalog(
    title="My Research Data Catalog",
    description="Collection of datasets from our research project",
    publisher=FOAFOrganization(
        name="Research Institution",
        homepage="https://www.example.com/research_institution",
    ),
    language="en",
    license="https://creativecommons.org/licenses/by/4.0/"
)
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