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DaniFdezAlvarezDaniFdezAlvarez
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Add some example notebooks
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‎doc/input_types.ipynb‎

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{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"provenance": []
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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}
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},
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "tgDn9FgB09vu"
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},
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"outputs": [],
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"source": [
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"!pip install shexer"
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"sheXer can handle different types of inputs:\n",
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"\n",
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"* Local/remote files.\n",
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"* in-memory string content.\n",
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"* SPARQL endpoints.\n",
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"* Compressed files.\n",
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"* RDFlib graphs.\n",
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"\n",
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"In this notebook, you'll find examples on how to provide such inputs to sheXer\n"
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],
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"metadata": {
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"id": "8FnmPwt91Dxn"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"from shexer.shaper import Shaper\n",
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"\n",
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"def default_namespaces():\n",
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" return {\"http://example.org/\": \"ex\",\n",
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" \"http://www.w3.org/XML/1998/namespace/\": \"xml\",\n",
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" \"http://www.w3.org/1999/02/22-rdf-syntax-ns#\": \"rdf\",\n",
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" \"http://www.w3.org/2000/01/rdf-schema#\": \"rdfs\",\n",
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" \"http://www.w3.org/2001/XMLSchema#\": \"xsd\",\n",
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" \"http://xmlns.com/foaf/0.1/\": \"foaf\"\n",
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" }"
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],
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"metadata": {
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"id": "atpnK9s82Q5o"
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},
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"execution_count": 3,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"# Getting some shapes for a graph in an str object\n",
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"\n",
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"raw_graph_turtle = \"\"\"@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .\n",
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"@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .\n",
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"@prefix ex: <http://example.org/> .\n",
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"@prefix foaf: <http://xmlns.com/foaf/0.1/> .\n",
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"@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .\n",
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"\n",
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"ex:Jimmy a foaf:Person ; # Complete\n",
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"\tfoaf:age \"23\"^^xsd:integer ;\n",
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"\tfoaf:name \"Jimmy\" ;\n",
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"\tfoaf:familyName \"Jones\" .\n",
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"\n",
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"ex:Sarah a foaf:Person ; # Complete implicit type for age\n",
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"\tfoaf:age 22 ;\n",
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"\tfoaf:name \"Sarah\" ;\n",
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"\tfoaf:familyName \"Salem\" .\n",
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"\n",
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"ex:Bella a foaf:Person ; # Missing familyName\n",
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"\tfoaf:age \"56\"^^xsd:integer ;\n",
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"\tfoaf:name \"Isabella\" .\n",
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"\n",
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"ex:David a foaf:Person ; # Missing age and use knows\n",
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"\tfoaf:name \"David\" ;\n",
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"\tfoaf:familyName \"Doulofeau\" ;\n",
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"\tfoaf:knows ex:Sarah .\n",
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"\n",
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"ex:HumanLike foaf:name \"Person\" ; # foaf properties, but not explicit type.\n",
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"\tfoaf:familyName \"Maybe\" ;\n",
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"\tfoaf:age 99 ;\n",
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"\tfoaf:knows ex:David .\n",
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"\n",
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"\n",
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"ex:x1 rdf:type foaf:Document ;\n",
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"\tfoaf:depiction \"A thing that is nice\" ;\n",
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"\tfoaf:title \"A nice thing\" .\n",
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"\n",
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"\n",
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"ex:x2 rdf:type foaf:Document ;\n",
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"\tfoaf:title \"Another thing\" .\"\"\"\n",
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"\n",
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"from shexer.consts import TURTLE_ITER, TURTLE\n",
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"\n",
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"shaper = Shaper(\n",
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" raw_graph=raw_graph_turtle, # parameter to pass the input str\n",
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" namespaces_dict=default_namespaces(), # some namespaces to pretify the result\n",
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" all_classes_mode=True, # get a shape for each class with instances\n",
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" input_format=TURTLE_ITER) # input format should be indicated. Available options in shexer.const\n",
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" # TURTLE_ITER is turtle, but the parser used in implemented within sheXer\n",
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" # TURTLE input format in available. Such option uses rdflib's parser\n",
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"\n",
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"str_result = shaper.shex_graph(string_output=True)\n",
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"print(str_result)\n"
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],
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"metadata": {
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"id": "pXcChiaB7gUU"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"# Same case, same content. But now the input is in a remote file\n",
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"\n",
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"shaper = Shaper(\n",
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" graph_file_input=\"https://raw.githubusercontent.com/weso/shexer/refs/heads/master/test/t_files/t_graph_1.ttl\", # parameter to pass a path for a remote file\n",
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" namespaces_dict=default_namespaces(),\n",
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" all_classes_mode=True,\n",
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" input_format=TURTLE) # using rdflib's parser, some more namespaces appear in the results (precharged ones in an rdflig.Graph() object)\n",
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"\n",
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"str_result = shaper.shex_graph(string_output=True)\n",
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"print(str_result)"
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],
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"metadata": {
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"id": "k-nBQyCr9m6i"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"# Same case, but now the file is local\n",
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"\n",
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"import requests\n",
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"\n",
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"def remote_to_local(url, local_path):\n",
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" response = requests.get(url)\n",
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" if response.status_code == 200:\n",
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" with open(local_path, \"w\", encoding=\"utf-8\") as out_stream:\n",
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" out_stream.write(response.text)\n",
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"\n",
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"remote_to_local(\"https://raw.githubusercontent.com/weso/shexer/refs/heads/master/test/t_files/t_graph_1.ttl\",\n",
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" \"local_file.ttl\")\n",
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"\n",
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"shaper = Shaper(\n",
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" graph_file_input=\"./local_file.ttl\", # the parameter for local and remote files is the same\n",
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" namespaces_dict=default_namespaces(),\n",
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" all_classes_mode=True,\n",
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" input_format=TURTLE)\n",
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"\n",
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"str_result = shaper.shex_graph(string_output=True)\n",
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"print(str_result)"
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],
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"metadata": {
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"id": "R1tORPF5_VKy"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"# Same case, but now the parsed content if N-Triples instead. This format uses an internal parser too\n",
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"from shexer.consts import NT\n",
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"\n",
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"remote_to_local(\"https://raw.githubusercontent.com/weso/shexer/refs/heads/master/test/t_files/t_graph_1.nt\",\n",
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" \"local_file.nt\")\n",
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"\n",
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"shaper = Shaper(\n",
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" graph_file_input=\"./local_file.nt\", # the parameter for local and remote files is the same\n",
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" namespaces_dict=default_namespaces(),\n",
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" all_classes_mode=True,\n",
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" input_format=NT)\n",
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"\n",
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"str_result = shaper.shex_graph(string_output=True)\n",
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"print(str_result)"
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],
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"metadata": {
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"id": "yJNPlCTWFmc_"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"#Same case, but now the content is split in two different files that should be parsed as a single dataset\n",
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"\n",
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"remote_to_local(\"https://raw.githubusercontent.com/weso/shexer/refs/heads/master/test/t_files/t_graph_1.nt\",\n",
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" \"local_file.nt\")\n",
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"\n",
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"with open(\"local_file.nt\") as in_stream:\n",
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" lines = in_stream.readlines()\n",
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" with open(\"local_file_pt1.nt\", \"w\") as out_1: # Writing 7 first lines to \"local_file_pt1.nt\"\n",
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" out_1.write(\"\".join(lines[:7]))\n",
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" with open(\"local_file_pt2.nt\", \"w\") as out_2: # Writing the rest of lines to to \"local_file_pt2.nt\"\n",
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" out_2.write(\"\".join(lines[7:]))\n",
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"\n",
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"shaper = Shaper(\n",
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" graph_list_of_files_input=[\"./local_file_pt1.nt\", \"./local_file_pt2.nt\"], # Use this parameter to parse a list of files instead of a single file\n",
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" namespaces_dict=default_namespaces(),\n",
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" all_classes_mode=True,\n",
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" input_format=NT)\n",
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"\n",
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"str_result = shaper.shex_graph(string_output=True)\n",
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"print(str_result)\n"
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],
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"metadata": {
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"id": "e6dWseCJGCEE"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"# Same case, but now we process an rdflib graph object\n",
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"\n",
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"from rdflib import Graph\n",
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"\n",
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"remote_to_local(\"https://raw.githubusercontent.com/weso/shexer/refs/heads/master/test/t_files/t_graph_1.ttl\",\n",
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" \"local_file.ttl\")\n",
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"\n",
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"g = Graph()\n",
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"g.parse(\"./local_file.ttl\")\n",
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"\n",
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"shaper = Shaper(\n",
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" rdflib_graph=g, # Use this parameter for rdflib inputs\n",
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" namespaces_dict=default_namespaces(),\n",
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" all_classes_mode=True,\n",
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" input_format=TURTLE)\n",
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"\n",
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"str_result = shaper.shex_graph(string_output=True)\n",
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"print(str_result)"
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],
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"metadata": {
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"id": "NabS5L4u0kuc"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"# Same target content, but not it is compressed in a ZIP file\n",
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"# In this case,t he file consist of a single file. But in case the file\n",
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"# zips more files, the setting would be the same and all files woul be parsed\n",
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"# parsed as a single data source\n",
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"\n",
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"from shexer.consts import ZIP, TURTLE_ITER\n",
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"import urllib.request\n",
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"\n",
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"urllib.request.urlretrieve(\"https://github.com/weso/shexer/raw/refs/heads/master/test/t_files/compression/t_graph_1.ttl.zip\",\n",
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" \"local_file.zip\")\n",
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"\n",
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"shaper = Shaper(\n",
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" graph_file_input=\"./local_file.zip\", # as it is a file input, we still use this parameter to declare the path\n",
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" namespaces_dict=default_namespaces(),\n",
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" all_classes_mode=True,\n",
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" input_format=TURTLE_ITER,\n",
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" compression_mode=ZIP)\n",
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"\n",
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"str_result = shaper.shex_graph(string_output=True)\n",
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"print(str_result)"
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],
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"metadata": {
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"id": "_6gQPxMa2G-2"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"# Example to generate a shape for some nodes exposed in DBpedia endpoint.\n",
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"# With this setting, only 4 nodes (result of the SPARQL query) will be used\n",
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"# as example. Only exploring direct connections with those nodes. No other\n",
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"# chape than the specified in the shape map will be generated\n",
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"\n",
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"\n",
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"\n",
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"shape_map_raw = \"SPARQL'select ?s where {?s a <http://dbpedia.org/ontology/Person>} LIMIT 4'@<ShapePerson>\"\n",
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"shaper = Shaper(shape_map_raw=shape_map_raw, # indicates target shapes and nodes as a shape map\n",
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" url_endpoint=\"https://dbpedia.org/sparql\", # target url\n",
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" namespaces_dict=default_namespaces(), #some namespaces to pretify results.\n",
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" depth_for_building_subgraph=1, # distance fo exploration from seed nodes\n",
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" track_classes_for_entities_at_last_depth_level=False, # no exception for the previous rule\n",
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" all_classes_mode=False) # no class out of the content specified in the shape map will generate a shape\n",
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"str_result = shaper.shex_graph(string_output=True,\n",
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" acceptance_threshold=0.9) # Only accept very frequent observations\n",
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"print(str_result)"
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],
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"metadata": {
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"id": "S0fEjGgf1RQX"
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},
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"execution_count": null,
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"outputs": []
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}
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]
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}

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