thehardwarestore.ai

This repository is a pure, generic microformats2 parser for PHP that makes HTML as easy to consume as a JSON API. It provides both functional and object-oriented interfaces for parsing microformats2 structured data from HTML documents. The parser handles all standard microformats2 property types (p-, u-, dt-, e-), implements implied property parsing, resolves relative URLs according to HTML and URI specifications, and includes backward compatibility for classic microformats markup. It features a robust test suite and follows PSR-0 autoloading standards.

This repository is a Python library and command-line tool for extracting structured data from HTML documents. It supports multiple formats including W3C HTML Microdata, JSON-LD, Microformat, Open Graph, RDFa, and Dublin Core. The project provides a main extract function that runs all enabled extractors and returns the results in a dictionary, with an option to convert the output to a uniform JSON-LD-like structure for easier consumption. The architecture is modular, with each format handled by a separate extractor class. The main orchestration function in `_extruct.py` manages the extraction process, error handling, and result aggregation. The command-line interface allows users to extract data from a URL or file and output JSON directly. The project includes an extensive test suite with sample HTML files and expected outputs for each format, covering valid cases, edge cases, and invalid inputs. Key reusable components include the uniform output transformation module (`extruct/uniform.py`), which normalizes data from different formats into a common structure, and the error handling pattern used throughout the extraction pipeline. The project is actively maintained, with recent updates adding support for newer Python versions and maintaining compatibility with dependencies. Technical drift is low due to regular updates and a focus on compatibility.

DeepOnto is a Python package for ontology engineering with deep learning, centered on ontology alignment (BERTMap) and subsumption inference (BERTSubs, OntoLAMA). It wraps the OWLAPI Java library through JPype to load, query, reason over, and prune OWL ontologies, and uses PyTorch/Hugging Face Transformers to train or apply BERT-based classifiers for mapping prediction and refinement. The package exposes config-driven pipelines (BERTMapPipeline, BERTSubs pipelines, OntoLAMA inference) plus evaluation utilities for OAEI-style benchmarks.