# elapouya/python-docx-template

Use a docx as a jinja2 template

Repository: https://github.com/elapouya/python-docx-template
Canonical: https://ross.abutalabs.com/products/python-docx-template
Language: Python
License: LGPL-2.1
License Family: copyleft
Last push: 2026-07-07T12:13:00+00:00

## Health v2 (maintenance only)
Score: 73/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 91, release rhythm 35, longevity 100
- inputs: {"age_days": 4192, "days_push": 57, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2697, forks 451 (observed 2026-08-28T04:07:11.251204+00:00)

## What it is
A Python library that lets you use Microsoft Word .docx files as Jinja2 templates to generate documents. It combines python-docx with Jinja2 so you can design documents in Word and fill them programmatically with context variables.

## Use cases
- generate word documents from a template
- fill docx templates with data in python
- create reports as docx from python
- mail merge with word templates
- render jinja2 tags inside a docx file
- automate invoice or contract document generation

## When to choose
- you want to design complex Word documents visually and fill them with data
- you need to modify or generate .docx files from Python
- you prefer authoring templates in Microsoft Word rather than code

## When to avoid
- you need to generate PDF or non-Word formats directly
- you only need to create simple documents from scratch without templates
- you work outside the Python ecosystem

## Facets
- artifact type: library
- maturity: stable
- function: templating, pdf, serialization
- domain: files, developer-tools
- platform: python, cross-platform
- tags: docx, jinja2, word-documents, document-generation, template-engine, automation

## Member repositories
- elapouya/python-docx-template (main) score 73

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:11.251204+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:16:12.647343+00:00, confidence not recorded.
  - readme: https://github.com/elapouya/python-docx-template (fetched 2026-08-28T04:07:11.251204+00:00, sha bfb5068b9ec1)
- Data as of 2026-08-30T08:39:29.467469+00:00.