Bulk Public PDF Text Extraction
Budget: $750 – $1,500 USD
I have a sizeable collection of publicly available PDFs that all follow the same template, and I need their text contents extracted in bulk for research. The job is straightforward: crawl or batch-download the files, parse each document, and return clean, structured text that I can drop directly into my analysis pipeline.
Because the layout is consistent across every PDF, you can rely on positional cues or pattern-based parsing rather than complex heuristics. OCR should be unnecessary—native text extraction with a Python stack (pdfminer.six, PyPDF2, or similar) or a Java/Node alternative is fine as long as the output is accurate.
Deliverables
• A reusable script or small utility with clear instructions
• Sample output (JSON or CSV) showing the full text from at least a handful of PDFs
• A brief README explaining dependencies, how to run the tool, and any edge-case considerations
I will validate by comparing random extractions against the source documents; accuracy and reliability are the key success metrics.
Because the layout is consistent across every PDF, you can rely on positional cues or pattern-based parsing rather than complex heuristics. OCR should be unnecessary—native text extraction with a Python stack (pdfminer.six, PyPDF2, or similar) or a Java/Node alternative is fine as long as the output is accurate.
Deliverables
• A reusable script or small utility with clear instructions
• Sample output (JSON or CSV) showing the full text from at least a handful of PDFs
• A brief README explaining dependencies, how to run the tool, and any edge-case considerations
I will validate by comparing random extractions against the source documents; accuracy and reliability are the key success metrics.