Results for “parsing”

Parse PDFs, Office files, and images locally with layout-preserved text, bounding boxes, OCR, and page screenshots for RAG and multimodal agents.

Pythonic wrapper around RDKit for cheminformatics, simplifying SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, and parallel processing while returning native rdkit.Chem.Mol objects.

Consume and produce STIX/TAXII 2.1 cyber threat intelligence feeds using Python, including server discovery, collection polling, object parsing, and SIEM/TIP integration.

Read, extract, merge, split, rotate, watermark, encrypt, and OCR PDF files using Python libraries and command-line tools.

Parse Windows forensic artifacts including registry, prefetch, shellbags, MFT, and event logs using Eric Zimmerman's tools and analyze results in Timeline Explorer.

Provides guidance for using python-xxhash to implement fast non-cryptographic hashing, including algorithm selection, byte encoding, streaming updates, digest representation, and collision-aware identity for checksums, bucketing, and sampling.

Detect suspicious Windows service installations (MITRE ATT&CK T1543.003) by parsing System event logs for Event ID 7045, analyzing service binary paths, and identifying indicators of persistence mechanisms.

Analyze Windows LNK shortcut files and Jump List artifacts to establish evidence of file access, program execution, and user activity using LECmd, JLECmd, and manual binary parsing.

Reference for MariaDB's built-in date and time functions, covering current time, arithmetic, differences, extraction, parsing, formatting, Unix time, time-zone conversion, construction, and Oracle-compatible helpers, with guidance on version-specific behavior and common pitfalls.

Analyzes a target job description and a Chinese resume to map evidence, identify gaps, rewrite the resume for ATS/HR/interview consistency, and generate application materials for the Chinese job market.

Explains MariaDB-specific syntax and behavior for LOAD DATA [LOCAL] INFILE and LOAD XML, including LOCAL vs server-side file handling, security and privilege requirements, default tab/newline parsing, duplicate and strict-mode caveats, IGNORE n LINES, user-variable SET transforms, CHARACTER SET clause, and priority.

Provides the RDKit cheminformatics toolkit for low-level, fine-grained molecular primitives — SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure/SMARTS search, 2D/3D coordinate generation, similarity, and reaction handling. Use when custom sanitization, specialized fingerprint or descriptor algorithms, reaction enumeration, or conformer generation demand direct API control; for a high-level pandas-friendly wrapper over RDKit prefer alterlab-datamol, and for turning molecules into ML feature vectors prefer alterlab-molfeat. Part of the AlterLab Academic Skills suite.