Issue #1: Large Dataroom Performance - PDF Page Count Extraction (2025-11-30)
Status: Open - Needs Fix
Severity: High
Discovered: 2025-11-30 during Star-Catcher dataroom analysis
Problem Description
When processing large datarooms (100+ files, especially with many PDFs), the analyzer becomes extremely slow during the initial scan phase. The root cause is that _get_page_count() is called synchronously for every PDF file during inventory building.
Observed behavior with Star-Catcher dataroom:
- 218 total files (152 PDFs, 10 Excel files)
- Scanner opens every PDF with
pypdf.PdfReader just to count pages
- Malformed PDFs trigger hundreds of
"Ignoring wrong pointing object" warnings
- Each PDF open/parse adds latency
- Total scan time: Several minutes for just the inventory phase
Issue #1: Large Dataroom Performance - PDF Page Count Extraction (2025-11-30)
Status: Open - Needs Fix
Severity: High
Discovered: 2025-11-30 during Star-Catcher dataroom analysis
Problem Description
When processing large datarooms (100+ files, especially with many PDFs), the analyzer becomes extremely slow during the initial scan phase. The root cause is that
_get_page_count()is called synchronously for every PDF file during inventory building.Observed behavior with Star-Catcher dataroom:
pypdf.PdfReaderjust to count pages"Ignoring wrong pointing object"warnings