I m excited to share TenTags 2.0.2, a new release of my Python library for generating HTML, Excel, and PDF documents from a compact declarative syntax.
TenTags was created to make document generation easier for Python developers and AI systems. Instead of manually building tables, styles, merges, alignment, and formatting in different output formats, you describe the structure once and render it into the format you need.
TenTags v1.1.1 is out: Multi-Table Reports & Template Decoupling!
Our declarative table generator for backend engines and AI agents just got a major upgrade. TenTags can now orchestrate complex multi-table reports and dashboard layouts from a single runner.
Key Updates:
Multi-Table Rendering: Group independent tables into a single HTML Grid, a multi-page PDF (ReportLab), or an Excel workbook (either on separate sheets or stacked vertically on one sheet).
Decoupled Templates: Preamble configurations and styles are now completely detached from the raw datasets. Design one layout template and apply it dynamically to any data.
The idea behind TenTags is to describe complex table structures (cell spans, text styles, alignment, and background colors) in a single, compact declarative string. This format serves as a universal source (AST), which the library compiles into an identical visual representation for HTML, Excel (.xlsx), and PDF, eliminating the need for the backend to maintain separate templates and write hundreds of lines of boilerplate code for each format.
TenTags is an open-source declarative document language and Intermediate Representation (IR) for generating structured documents. Instead of embedding programming logic into templates, TenTags uses a compact semantic syntax that can be generated by Python applications and AI agents. Compile the same document definition into HTML, PDF, Excel (.xlsx), and future output formats while keeping business logic separate from presentation.
