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Author SHA1 Message Date
egutierrez 048781df3f feat(eda): portada — tamaño grande + descripción/granularidad reales
El capítulo PORTADA ahora muestra SIEMPRE el tamaño del dataset (N filas ×
M columnas) en grande, como heading junto al nombre y agrupado con él
(Group keep-together), en lugar de enterrarlo en la tabla de metadatos.

La Descripción y la Granularidad ya no salen vacías ni con placeholders:
se resuelven por cascada — ctx explícito > bloque LLM (profile['llm'].summary
/ row_meaning de eda_llm_insights) > derivación del propio perfil (forma,
mezcla de tipos y score de calidad para la descripción; columnas
key_candidates o la forma de la tabla para una frase 'Cada fila es…').
Las derivaciones son honestas (declaran que vienen del perfil) y nunca
inventan significado de negocio.

Añade chapters/portada_test.py: golden (tamaño grande + textos del LLM,
sin fila 'Tamaño' duplicada), fallbacks sin LLM (keys / forma), prioridad
de ctx, edge de perfil vacío sin lanzar, y render a PDF + PPTX.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-30 18:04:05 +02:00
egutierrez c6d9bc26da merge: Fase 4a AutomaticEDA motor+glosario (verificado met)
- fix negrita-pisa PDF, zebra striping (PDF+PPT), keep-together (Group: heading+figura+texto misma pagina/slide), imagenes con caption en PPT
- portada construida-al-final mostrada en posicion 1 (con resumen agregado del cuerpo)
- capitulo glosario al final + terminos clicables REALES: PDF link annotation (add_pdf_internal_links, PyMuPDF) + PPT hyperlink nativo (pptx_link_run_to_slide); entropia enganchado en cat_distr como ejemplo E2E
- contrato docs/automatic_eda_contract.md §11 (glosario + keep-together + zebra)
- pymupdf>=1.28.0
2026-06-30 17:45:30 +02:00
egutierrez d1a3d58a6b feat(eda): motor AutomaticEDA fase 4a — render fixes + keep-together + glosario clicable
Mejoras transversales del motor de render (no del contenido de capítulos):

1. Fix negrita pisa texto (PDF): _place_rich_lines mide el ancho REAL de cada
   span con las métricas de fuente del renderer (peso correcto) en vez del
   grid de ancho medio; negrita y normal en la misma línea ya no se solapan.
2. Zebra striping: filas pares sombreadas (#f6f8fa) en DataTable (PDF + PPTX),
   coherente al partir tablas largas (índice de fila lógico, no por página).
3. Keep-together: bloque Group nuevo; el renderer mide el grupo entero y lo
   mueve completo a la página/slide siguiente si no cabe, y encoge la figura
   (height_in) para dejar sitio a su título y texto. num_distr lo usa.
4. Caption siempre visible en toda figura PPTX (fallback al heading); la figura
   reserva el alto de su caption para que ambos quepan en el mismo slide.
5. Portada construida al final (con resumen agregado del análisis vía
   ctx['document_summary']) pero colocada primera por build_document.
6. Glosario: capítulo nuevo (último) + GlossaryCollector en ctx; los capítulos
   registran términos y marcan apariciones con [[term:key]]...[[/term]]. Links
   clicables reales: PDF (PyMuPDF, link GOTO) y PPTX (slide-jump nativo).
   Enganchado "entropía" en cat_distr como ejemplo end-to-end.

Funciones reutilizables delegadas a fn-constructor (tag eda):
- add_pdf_internal_links_py_datascience (PyMuPDF)
- pptx_link_run_to_slide_py_datascience (slide-jump)

Contrato docs/automatic_eda_contract.md actualizado (§1/§3/§5 + §11 nueva) con
la API de glosario, keep-together y zebra para la siguiente fase. PyMuPDF
declarado en pyproject. Suite verde (90 tests); golden titanic verificado.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-30 17:35:19 +02:00
egutierrez b5334a2e97 merge: Fase 3 AutomaticEDA wiring (verificado met)
- build_eda_render_ctx: arma ctx (raw_numeric, timeseries_raw, geo_points, db_path+table) desde tabla DuckDB
- pipeline render_automatic_eda: perfila + ctx + build_document -> PDF + PPTX (11 capitulos poblados)
- profile_table: flag emit_automatic emite el report AutomaticEDA (PDF+PPT) sin romper render_eda_pdf
- text_layout: render real de **negrita** en PDF y PPTX
- .claude/commands/eda.md actualizado

Los 4 capitulos que degradaban (modelos/timeseries/geospatial/agregacion) ahora salen POBLADOS end-to-end.
2026-06-30 16:19:52 +02:00
22 changed files with 2431 additions and 121 deletions
+123 -3
View File
@@ -25,7 +25,8 @@ cabecera, y figuras/imágenes se escalan para caber enteras.
```
Document = list[Chapter]
Chapter = { id: str, title: str, version: str, blocks: list[Block] }
Block = Heading | Markdown | KVTable | DataTable | Figure | Image | Caption | Note
Block = Heading | Markdown | KVTable | DataTable | Figure | Image | Caption
| Note | Group | GlossaryEntry
```
Importa el modelo desde `datascience.automatic_eda.model` (o
@@ -44,6 +45,10 @@ reconocido se degrada a `Note`, nunca lanza).
| `Figure(fig=None, make=None, caption=None, height_in=None)` | una `matplotlib.figure.Figure` ya construida (`fig`) o un callable `make()->Figure` (perezoso) | se rasteriza y escala para caber entera (nunca recortada) |
| `Image(path, caption=None, height_in=None)` | ruta a PNG/JPG | se escala para caber entera |
| `Caption(text)` / `Note(text)` | texto auxiliar pequeño | pie/nota en gris; `Note` es además el fallback de lo desconocido |
| `Group(blocks, title=None)` | unidad **keep-together**: sus bloques se mantienen juntos | el renderer mide el grupo entero y lo mueve completo a la página/slide siguiente si no cabe; encoge la figura para dejar sitio al título+texto. Ver §11 |
| `GlossaryEntry(key, label, definition)` | una entrada del glosario (destino clicable) | la genera el capítulo `glosario`; registra su posición como destino de los términos marcados. Ver §11 |
`Figure`/`Image` aceptan `height_in` (hint): el renderer **clampa** la figura a esa altura máxima (lo usa `Group` para encoger la figura). Toda figura escala dejando sitio a su caption en la misma página/slide; en PPTX el caption es **siempre** visible (si no se da `caption`, cae al último heading o a "Figura").
### Subset de markdown soportado (`Markdown`)
@@ -84,8 +89,9 @@ El orden canónico está **pre-declarado** en
```python
CHAPTER_ORDER = [
"portada", "overview", "num_distr", "cat_distr", "calidad", "correlacion",
"modelos", "analisis_llm", "timeseries", "geospatial", "agregacion",
"portada", "overview", "analisis_llm", "num_distr", "cat_distr", "calidad",
"correlacion", "modelos", "timeseries", "geospatial", "agregacion",
"glosario",
]
```
@@ -95,6 +101,15 @@ CHAPTER_ORDER = [
`CHAPTER_ORDER`) y aparecerá automáticamente en su posición. Esto permite que muchos
agentes trabajen **en paralelo** sin contención: cada uno toca solo su archivo.
**Dos capítulos tienen posición especial** (los gestiona `build_document`, no toques esto):
- `portada`: se **construye el último** (después del cuerpo) para poder resumir el
análisis, pero se **coloca el primero**. Recibe `ctx['document_summary']` (ver §5) con
un resumen agregado del resto. Decisión del usuario: la portada refleja hallazgos.
- `glosario`: se construye y se **coloca el último**. Lee los términos que los demás
capítulos registraron en `ctx['glossary']` (ver §11). Si no se registró ninguno, el
capítulo devuelve `None` y desaparece.
Si tu capítulo usa un `<id>` que aún no está en `CHAPTER_ORDER`, añádelo en la posición
correcta (única edición compartida; coordínala con el orquestador).
@@ -143,6 +158,8 @@ defensivo). Esto habilita el **seguimiento y la mejora continua por capítulo**.
| `granularity` | "Cada fila es…" (portada). Default: derivado de `key_candidates` |
| `quality_criteria` | criterios del score de calidad (portada) |
| `head_rows` | `list[dict]` con `df.head` (overview). Ver §7 |
| `glossary` | `GlossaryCollector` compartido — los capítulos registran términos en él. Lo crea `build_document`; ver §11 |
| `document_summary` | dict con el resumen agregado del cuerpo (n_rows, n_cols, quality_score, n_numeric, n_categorical, chapter_titles, …). Lo calcula `build_document` y lo consume la portada |
Un capítulo puede definir y consumir sus propias claves `ctx` — documenta cuáles en su
docstring.
@@ -279,6 +296,109 @@ sus bloques presentes y el no-corte (texto largo intacto en la salida). Patrón:
---
## 11. Glosario, keep-together y zebra (motor, fase 4a)
Tres capacidades transversales del motor que **todos** los capítulos pueden usar. La 6.1
(glosario) requiere que el capítulo coopere (registrar + marcar términos); la 6.2
(keep-together) es opt-in por capítulo (envolver bloques en `Group`); la 6.3 (zebra) es
automática (no hay nada que hacer).
### 11.1 Glosario con términos clicables
El glosario es un capítulo nuevo (`chapters/glosario.py`) que se renderiza **siempre el
último** y lista cada término técnico que algún capítulo haya registrado. Cada aparición
del término en el texto se vuelve un **clic real** que salta a su entrada: en PDF como
*link annotation* interno (post-proceso con PyMuPDF, porque `PdfPages` no soporta
hyperlinks internos), en PPTX como *slide-jump* nativo (`ppaction://hlinksldjump`).
**API exacta para un capítulo (dos pasos):**
1. **Registrar el término** en el colector compartido `ctx['glossary']` (un
`model.GlossaryCollector`, creado por `build_document` y pasado a todos los capítulos):
```python
glossary = ctx.get("glossary")
if isinstance(glossary, model.GlossaryCollector):
glossary.add("entropia", "Entropía (de Shannon)", "Medida, en bits, de …")
```
`add(key, label, definition)` es idempotente (la primera definición de cada `key` gana).
`key` debe ser `[A-Za-z0-9_]+`. Si no hay colector en `ctx` (renderizado suelto), el
capítulo simplemente no marca términos — degrada sin romper.
2. **Marcar cada aparición** en el texto de un bloque `Markdown` con el span inline
`[[term:KEY]]texto visible[[/term]]`. El texto visible puede llevar `**negrita**`. El
marcador no altera el texto visible (se elimina como cualquier marcador inline); solo
añade el destino clicable.
```python
# En cat_distr (ejemplo real ya implementado):
"La [[term:entropia]]**entropía de Shannon**[[/term]] mide cómo de repartidos…"
```
Eso es todo: el capítulo `glosario` recoge los términos (orden alfabético por `label`),
emite un `GlossaryEntry` por término, y los renderers cablean los enlaces automáticamente.
Si ningún capítulo registró términos, el glosario no aparece.
**Helpers de `text_layout` (no reimplementar):** `parse_inline_rich(text)` →
`[(texto, is_bold, term_key), …]`; `wrap_rich_terms(text, max_chars)` → líneas de esos
spans sin corte. `strip_inline_md` ya elimina los marcadores `[[term:…]]`/`[[/term]]`.
(Las funciones previas `parse_inline_bold` / `wrap_rich` siguen existiendo, sin términos.)
**Funciones del registry que cablean los enlaces** (grupo `eda`, ya invocadas por los
renderers; degradan en silencio si faltan): `add_pdf_internal_links_py_datascience`
(PyMuPDF, link GOTO) y `pptx_link_run_to_slide_py_datascience` (salto a slide nativo).
Dependencia: `pymupdf` (declarada en `python/pyproject.toml`).
**Trabajo de la siguiente fase — enganchar más términos.** El mecanismo está hecho y
probado de extremo a extremo con `entropia` (en `cat_distr`). Cada capítulo debe registrar
y marcar SUS términos con el mismo patrón de dos pasos. Candidatos por capítulo:
| Capítulo | Términos a enganchar (key sugerida) |
|---|---|
| `cat_distr` | `entropia` ✅ (hecho) |
| `calidad` | `completitud`, `validez`, `consistencia` |
| `correlacion` | `cramers_v`, `fdr` (comparaciones múltiples), método de correlación usado |
| `modelos` | `pca`, `silhouette`, `isolation_forest` |
| `timeseries` | `estacionariedad`, `acf_pacf`, `stl` |
| `num_distr` | `iqr`, `curtosis`, `outlier` (vallas de Tukey) |
Define la definición de cada término en su capítulo (constante local, como
`_TERM_ENTROPIA_DEF` en `cat_distr`) y márcalo en su primera aparición.
### 11.2 Keep-together: gráfico junto a su título y texto (`Group`)
Para que un encabezado no quede en una página/slide y su figura en la siguiente, envuelve
los bloques de una misma idea en un `model.Group`:
```python
blocks.append(model.Group(blocks=[
model.Heading(text=str(name), level=2),
model.Figure(make=_figura_perezosa(...), caption="…"),
model.Markdown(text="explicación…"),
]))
```
El renderer **mide el grupo entero** antes de dibujar nada: si no cabe en lo que queda de
página/slide pero cabe en una entera, lo mueve **completo** a la siguiente; y **encoge la
figura** (vía `height_in`) lo justo para que el título + texto + figura quepan juntos. Si
el grupo es más alto que una página entera, empieza en una nueva y fluye (degradación
honesta, nunca corta). Ejemplo real implementado: `num_distr` envuelve cada columna
(heading + figura histograma/boxplot + nota) en un `Group`.
Recomendado para `agregacion` y cualquier capítulo donde una figura deba ir pegada a su
título/explicación. Coste: si un capítulo inspecciona `chapter.blocks` en sus tests, ahora
encontrará `Group`s — aplana con un helper recursivo (ver `num_distr_test.py::_flatten`).
### 11.3 Zebra striping en tablas (automático)
Todo `DataTable` se renderiza con **filas pares sombreadas** (gris muy suave `#f6f8fa`) y
cabecera con su fondo propio. Es automático en PDF y PPTX; el patrón se mantiene coherente
cuando una tabla larga se parte y repite cabecera (el índice de fila es lógico, no por
página). No hay nada que hacer en los capítulos.
---
## 10. Integración futura con `profile_table` (siguiente fase)
`profile_table(emit_pdf=True)` usa hoy `render_eda_pdf` (intacto). En la siguiente fase
+2
View File
@@ -68,11 +68,13 @@ from .extract_timeseries_raw import extract_timeseries_raw
from .build_eda_render_ctx import build_eda_render_ctx
from .profile_datetime import profile_datetime
from .resample_timeseries import resample_timeseries
from .add_pdf_internal_links import add_pdf_internal_links
__all__ = [
"detect_time_column",
"extract_timeseries_raw",
"build_eda_render_ctx",
"add_pdf_internal_links",
"profile_datetime",
"resample_timeseries",
"render_automatic_eda_pdf",
@@ -0,0 +1,85 @@
---
name: add_pdf_internal_links
kind: function
lang: py
domain: datascience
version: "1.0.0"
purity: impure
signature: "def add_pdf_internal_links(pdf_path: str, links: list) -> dict"
description: "Postprocesa un PDF YA escrito insertando link annotations internos de tipo GOTO ('ir a') con PyMuPDF (import fitz). Pensado para PDFs generados por matplotlib PdfPages, que NO soporta hyperlinks internos: tras escribir el PDF se reabre y, por cada entrada de `links`, se añade una anotacion clicable desde un rectangulo de una pagina origen (src_page + src_rect en puntos top-left) hasta un punto de una pagina destino (dst_page + dst_point). Caso de uso tipico del grupo eda: hacer clicables los terminos de un AutomaticEDA que apuntan a su entrada en el glosario al final del documento. Estilo dict-no-throw: NUNCA lanza; valida cada link y SALTA (n_skipped++) los malformados o fuera de rango en vez de fallar. Guarda de forma segura escribiendo a un temporal en el mismo directorio y haciendo os.replace atomico (evita corromper el original). Devuelve {status:ok,n_links,n_skipped} o {status:error,error}; si pymupdf no esta disponible o el archivo no existe devuelve status error."
tags: [eda, datascience, pdf, links, glossary, pymupdf, fitz, postprocess, python]
uses_functions: []
uses_types: []
returns: []
returns_optional: false
error_type: "error_go_core"
imports: []
params:
- name: pdf_path
desc: "ruta al PDF existente (str no vacio). Se reescribe IN SITU (in-place) tras añadir los links: se guarda a un temporal `.<base>.tmp_links` en el mismo directorio y se reemplaza atomicamente con os.replace. Si no es str o no existe el archivo -> {status:error}."
- name: links
desc: "lista de dicts, uno por link a insertar. Cada dict: src_page (int 0-based de la pagina origen), src_rect ([x0,y0,x1,y1] del rectangulo clicable en PUNTOS PDF 1/72\" con origen ARRIBA-IZQUIERDA), dst_page (int 0-based de la pagina destino), dst_point ([x,y] punto destino, mismos puntos top-left). Las entradas que no son dict, con page fuera de rango [0,page_count), src_rect que no tenga 4 numeros o dst_point que no tenga 2 numeros se SALTAN (n_skipped++), no lanzan. None se trata como lista vacia."
output: "dict (NUNCA lanza): en exito {\"status\":\"ok\",\"n_links\":int,\"n_skipped\":int} con n_links = anotaciones GOTO insertadas y n_skipped = entradas invalidas saltadas. En fallo {\"status\":\"error\",\"error\":str}: pymupdf no disponible, pdf_path no es str / no existe, links no es lista, o cualquier excepcion global (el PDF original queda intacto porque el replace solo ocurre tras un save correcto)."
tested: true
tests: ["test_add_goto_link_basico", "test_links_invalidos_se_saltan", "test_archivo_inexistente_devuelve_error"]
test_file_path: "python/functions/datascience/add_pdf_internal_links_test.py"
file_path: "python/functions/datascience/add_pdf_internal_links.py"
---
## Ejemplo
```python
import sys, os
sys.path.insert(0, os.path.join("python", "functions"))
from datascience import add_pdf_internal_links
# Tienes un PDF ya escrito por matplotlib PdfPages (sin hyperlinks internos).
# Quieres que el texto "Margen bruto" de la pagina 0 (rectangulo en puntos
# top-left) salte a su entrada del glosario en la ultima pagina (indice 7).
res = add_pdf_internal_links(
"reports/eda.pdf",
[
{"src_page": 0, "src_rect": [72, 120, 180, 134], "dst_page": 7, "dst_point": [72, 200]},
{"src_page": 0, "src_rect": [72, 140, 180, 154], "dst_page": 7, "dst_point": [72, 260]},
],
)
# res == {"status": "ok", "n_links": 2, "n_skipped": 0}
```
## Cuando usarla
Justo DESPUES de escribir un PDF con matplotlib `PdfPages` (o cualquier motor
que no genere hyperlinks internos) cuando necesitas que ciertos terminos o
referencias sean clicables y salten a otra pagina del mismo documento — el caso
canonico es enlazar los terminos de un AutomaticEDA con su entrada de glosario
al final. Es un paso de postproceso: primero generas el PDF y calculas en que
rectangulo quedo cada termino (en puntos PDF), luego pasas esa lista a esta
funcion para inyectar las anotaciones GOTO.
## Gotchas
- **Impura — reescribe el archivo IN SITU.** El PDF en `pdf_path` se reemplaza
por la version con los links. El guardado es seguro: escribe a un temporal
`.<base>.tmp_links` en el MISMO directorio y hace `os.replace` atomico tras
cerrar el documento, asi un fallo a mitad no corrompe el original. Aun asi,
conserva una copia si el PDF es valioso.
- **Sistema de coordenadas: puntos top-left, igual que matplotlib.** PyMuPDF y
matplotlib (PdfPages) usan ambos PUNTOS PDF (1/72") con el origen ARRIBA-
IZQUIERDA, asi que los rectangulos/puntos COINCIDEN: el `src_rect` que calcules
con la geometria de la figura matplotlib se pasa tal cual, sin invertir el eje
Y. (Ojo: el espacio de datos de matplotlib SI tiene el origen abajo; lo que
coincide es el espacio de la PAGINA en puntos.)
- **Indices de pagina 0-based.** `src_page` / `dst_page` son indices base 0
(la primera pagina es 0). Fuera del rango `[0, page_count)` el link se SALTA
(cuenta en `n_skipped`), no lanza.
- **dict-no-throw, validacion por-link.** Las entradas malformadas (no dict,
page fuera de rango, `src_rect` sin 4 numeros, `dst_point` sin 2 numeros) se
saltan individualmente e incrementan `n_skipped`; el resto de links validos se
insertan igual. La funcion solo devuelve `{status:error}` ante fallos globales
(pymupdf ausente, archivo inexistente, `links` no es lista).
- **`error_type: error_go_core` es metadata del registry, no comportamiento.**
Toda funcion impura debe declararlo y el indexer lo exige, pero el codigo NUNCA
lanza esa excepcion: degrada al dict de estado.
- **Requiere PyMuPDF (`import fitz`).** Si no esta instalado devuelve
`{"status":"error","error":"pymupdf no disponible: ..."}`. En el registry el
venv `python/.venv` ya lo trae.
@@ -0,0 +1,132 @@
"""Postprocesa un PDF existente insertando link annotations internos (GOTO).
Motor: PyMuPDF (``import fitz``). Pensado para PDFs generados por matplotlib
``PdfPages``, que no soporta hyperlinks internos: tras escribir el PDF, esta
funcion lo reabre y le añade anotaciones "ir a" (GOTO) desde un rectangulo de
una pagina origen hasta un punto de una pagina destino. Util para hacer
clicables terminos que apuntan a su entrada en un glosario al final del
documento.
Estilo dict-no-throw del grupo `eda`: NUNCA lanza; devuelve un dict de estado.
"""
import os
def add_pdf_internal_links(pdf_path: str, links: list) -> dict:
"""Añade link annotations internos (GOTO) a un PDF ya escrito.
Postprocesa un PDF (p.ej. generado por matplotlib PdfPages, que NO soporta
hyperlinks internos) insertando, por cada entrada de ``links``, una
anotacion de tipo "ir a" desde un rectangulo de una pagina origen hasta un
punto de una pagina destino. Sirve para hacer clicables terminos que apuntan
a su entrada en un glosario al final del documento.
Args:
pdf_path: ruta al PDF existente (se reescribe in situ).
links: lista de dicts, cada uno:
{
"src_page": int, # indice 0-based de la pagina origen
"src_rect": [x0,y0,x1,y1], # rectangulo clicable, en PUNTOS PDF
# (1/72") con origen ARRIBA-IZQUIERDA
"dst_page": int, # indice 0-based de la pagina destino
"dst_point": [x, y], # punto destino, mismos puntos top-left
}
Returns:
dict (NUNCA lanza): {"status":"ok","n_links":int,"n_skipped":int}
o {"status":"error","error":str}. Si pymupdf no esta disponible o el
archivo no existe -> {"status":"error", ...}.
"""
try:
try:
import fitz # PyMuPDF
except Exception as exc: # ImportError u otro fallo de carga
return {"status": "error", "error": f"pymupdf no disponible: {exc}"}
if not isinstance(pdf_path, str) or not pdf_path:
return {"status": "error", "error": "pdf_path debe ser una ruta no vacia"}
if not os.path.isfile(pdf_path):
return {"status": "error", "error": f"el archivo no existe: {pdf_path}"}
if links is None:
links = []
if not isinstance(links, (list, tuple)):
return {"status": "error", "error": "links debe ser una lista de dicts"}
doc = fitz.open(pdf_path)
try:
n_pages = doc.page_count
n_ok = 0
n_skipped = 0
for link in links:
if not isinstance(link, dict):
n_skipped += 1
continue
src_page = link.get("src_page")
dst_page = link.get("dst_page")
src_rect = link.get("src_rect")
dst_point = link.get("dst_point")
# src_page / dst_page: enteros 0-based en rango.
if not _is_int(src_page) or not _is_int(dst_page):
n_skipped += 1
continue
if not (0 <= src_page < n_pages) or not (0 <= dst_page < n_pages):
n_skipped += 1
continue
# src_rect: 4 numeros.
if not _is_num_seq(src_rect, 4):
n_skipped += 1
continue
# dst_point: 2 numeros.
if not _is_num_seq(dst_point, 2):
n_skipped += 1
continue
try:
doc[int(src_page)].insert_link(
{
"kind": fitz.LINK_GOTO,
"from": fitz.Rect(*[float(v) for v in src_rect]),
"page": int(dst_page),
"to": fitz.Point(*[float(v) for v in dst_point]),
}
)
n_ok += 1
except Exception:
n_skipped += 1
continue
# Guardado seguro: escribir a temporal en el mismo directorio y
# reemplazar atomicamente (evita corromper el PDF original).
directory = os.path.dirname(os.path.abspath(pdf_path)) or "."
base = os.path.basename(pdf_path)
tmp_path = os.path.join(directory, f".{base}.tmp_links")
doc.save(tmp_path)
finally:
doc.close()
os.replace(tmp_path, pdf_path)
return {"status": "ok", "n_links": n_ok, "n_skipped": n_skipped}
except Exception as exc: # degrada cualquier fallo a dict de error
return {"status": "error", "error": str(exc)}
def _is_int(value) -> bool:
"""True si value es un entero (no bool)."""
return isinstance(value, int) and not isinstance(value, bool)
def _is_num_seq(value, length: int) -> bool:
"""True si value es una secuencia de `length` numeros (int/float, no bool)."""
if not isinstance(value, (list, tuple)) or len(value) != length:
return False
for v in value:
if isinstance(v, bool) or not isinstance(v, (int, float)):
return False
return True
@@ -0,0 +1,77 @@
"""Tests para add_pdf_internal_links."""
import os
import sys
import pytest
sys.path.insert(0, os.path.dirname(__file__))
from add_pdf_internal_links import add_pdf_internal_links
def test_add_goto_link_basico(tmp_path):
"""Golden: un PDF de 2 paginas recibe un link GOTO de la pag 0 a la pag 1."""
fitz = pytest.importorskip("fitz")
# 1) PDF temporal de 2 paginas A5 (~419x595 puntos).
pdf = str(tmp_path / "doc.pdf")
doc = fitz.open()
doc.new_page(width=419, height=595)
doc.new_page(width=419, height=595)
doc.save(pdf)
doc.close()
# 2) Insertar un link interno desde la pag 0 hacia la pag 1.
res = add_pdf_internal_links(
pdf,
[{"src_page": 0, "src_rect": [50, 50, 200, 70], "dst_page": 1, "dst_point": [40, 40]}],
)
assert res["status"] == "ok"
assert res["n_links"] == 1
assert res["n_skipped"] == 0
# 3) Reabrir y verificar que la pag 0 tiene un link GOTO a la pag 1.
doc = fitz.open(pdf)
try:
links = doc[0].get_links()
goto = [l for l in links if l.get("kind") == fitz.LINK_GOTO and l.get("page") == 1]
assert len(goto) >= 1
finally:
doc.close()
def test_links_invalidos_se_saltan(tmp_path):
"""Edge: entradas malformadas o fuera de rango incrementan n_skipped, no lanzan."""
fitz = pytest.importorskip("fitz")
pdf = str(tmp_path / "doc.pdf")
doc = fitz.open()
doc.new_page(width=419, height=595)
doc.new_page(width=419, height=595)
doc.save(pdf)
doc.close()
res = add_pdf_internal_links(
pdf,
[
# valido
{"src_page": 0, "src_rect": [10, 10, 90, 30], "dst_page": 1, "dst_point": [20, 20]},
# dst_page fuera de rango
{"src_page": 0, "src_rect": [10, 40, 90, 60], "dst_page": 9, "dst_point": [20, 20]},
# src_rect con 3 numeros
{"src_page": 0, "src_rect": [10, 70, 90], "dst_page": 1, "dst_point": [20, 20]},
# no es dict
"no-soy-un-dict",
],
)
assert res["status"] == "ok"
assert res["n_links"] == 1
assert res["n_skipped"] == 3
def test_archivo_inexistente_devuelve_error():
"""Error path: pdf_path inexistente -> status error sin lanzar."""
res = add_pdf_internal_links("/ruta/que/no/existe_xyz.pdf", [])
assert res["status"] == "error"
assert "error" in res
@@ -21,6 +21,9 @@ from .model import ( # noqa: F401
Chapter,
DataTable,
Figure,
GlossaryCollector,
GlossaryEntry,
Group,
Heading,
Image,
KVTable,
@@ -45,6 +48,9 @@ __all__ = [
"Image",
"Caption",
"Note",
"Group",
"GlossaryEntry",
"GlossaryCollector",
"Chapter",
"as_blocks",
"as_chapters",
@@ -33,10 +33,23 @@ import math
from .. import model
CHAPTER_VERSION = "1.0.0"
CHAPTER_VERSION = "1.1.0"
CHAPTER_ID = "cat_distr"
CHAPTER_TITLE = "Distribuciones categóricas"
# Glossary term this chapter explains. Registered in the shared collector and
# marked clickable on its first appearance (end-to-end glossary example —
# mejora 6). Other chapters hook their own terms the same way (see the contract).
_TERM_ENTROPIA_KEY = "entropia"
_TERM_ENTROPIA_LABEL = "Entropía (de Shannon)"
_TERM_ENTROPIA_DEF = (
"Medida, en bits, de cómo de repartidos están los valores de una columna "
"categórica. Vale 0 cuando una sola categoría concentra todas las filas "
"(máxima previsibilidad) y alcanza su máximo, log2(k) para k categorías "
"distintas, cuando todas aparecen por igual (máxima diversidad). La entropía "
"normalizada (entropía dividida por su máximo) la lleva al rango 01 para "
"comparar columnas con distinto número de categorías.")
# Cap the number of categorical columns rendered to keep the document bounded;
# the rest are summarized in a closing note (no silent truncation).
MAX_COLS = 40
@@ -337,10 +350,14 @@ def _topk_table(cat: dict):
note=note)
def _intro_blocks(n_rows):
def _intro_blocks(n_rows, mark_term: bool = False):
total = _fmt_int(n_rows)
# Mark the first appearance of the term as a clickable glossary jump when the
# term was registered (mark_term). The visible text is identical either way.
entropia = ("[[term:entropia]]**entropía de Shannon**[[/term]]" if mark_term
else "**entropía de Shannon**")
text = (
"La **entropía de Shannon** mide cómo de repartidos están los valores de "
f"La {entropia} mide cómo de repartidos están los valores de "
"una columna categórica, en bits. Vale 0 cuando una sola categoría "
"concentra todas las filas (máxima previsibilidad) y alcanza su máximo, "
"log2(k) para k categorías distintas, cuando todas aparecen por igual "
@@ -370,7 +387,15 @@ def build_cat_distr(profile: dict, ctx: dict):
return None
n_rows = profile.get("n_rows")
blocks = list(_intro_blocks(n_rows))
# Register "entropía" in the shared glossary collector (if present) and mark
# its first appearance clickable. End-to-end glossary example (mejora 6).
glossary = ctx.get("glossary")
mark_term = False
if isinstance(glossary, model.GlossaryCollector):
glossary.add(_TERM_ENTROPIA_KEY, _TERM_ENTROPIA_LABEL,
_TERM_ENTROPIA_DEF)
mark_term = True
blocks = list(_intro_blocks(n_rows, mark_term=mark_term))
rendered = cat_cols[:MAX_COLS]
for col in rendered:
@@ -0,0 +1,47 @@
"""Glossary chapter (GLOSARIO) — always the last chapter, clickable terms.
Renders one entry per glossary term that the other chapters registered during
the document build through ``ctx['glossary'].add(key, label, definition)`` (see
``GlossaryCollector`` in ``model.py``). Each entry is a clickable destination:
every in-text appearance a chapter marked with ``[[term:key]]texto[[/term]]``
becomes a real jump to its entry here — PDF link annotations (PyMuPDF) and PPTX
native slide jumps, both wired by the renderers.
Returns ``None`` when no term was registered (there is nothing to show), so the
chapter simply disappears from documents that did not mark any term.
Contract: build_<id>(profile, ctx) -> Chapter | None ; CHAPTER_VERSION = "x.y.z".
"""
from __future__ import annotations
from .. import model
CHAPTER_VERSION = "1.0.0"
CHAPTER_ID = "glosario"
CHAPTER_TITLE = "Glosario"
def build_glosario(profile: dict, ctx: dict):
"""Build the glossary Chapter from the shared collector, or None if empty."""
ctx = ctx or {}
glossary = ctx.get("glossary")
if not isinstance(glossary, model.GlossaryCollector) or not glossary:
return None
blocks = [
model.Heading(text="Glosario de términos", level=1),
model.Markdown(text=(
"Definición de los términos técnicos que aparecen en el informe. "
"Cada término va resaltado en el texto y, al pulsarlo, salta a su "
"definición en esta sección.")),
]
# One clickable destination per term, alphabetically by visible label.
for term in glossary.terms(by="label"):
blocks.append(model.GlossaryEntry(
key=model._safe_str(term.get("key")),
label=model._safe_str(term.get("label")),
definition=model._safe_str(term.get("definition"))))
return model.Chapter(id=CHAPTER_ID, title=CHAPTER_TITLE,
version=CHAPTER_VERSION, blocks=blocks)
@@ -34,7 +34,7 @@ try:
except Exception: # noqa: BLE001 — keep the chapter importable no matter what.
build_boxplot_stats = None # type: ignore[assignment]
CHAPTER_VERSION = "1.0.0"
CHAPTER_VERSION = "1.1.0"
CHAPTER_ID = "num_distr"
CHAPTER_TITLE = "Distribuciones numéricas"
@@ -278,12 +278,17 @@ def build_num_distr(profile: dict, ctx: dict):
box = build_boxplot_stats(numeric) or {}
except Exception: # noqa: BLE001 — degrade, never raise.
box = {}
blocks.append(model.Heading(text=str(name), level=2))
blocks.append(model.Figure(
make=_figure_maker(name, numeric, box),
caption=f"Distribución de «{name}» — histograma (media/mediana/±σ) "
f"y boxplot."))
blocks.append(model.Markdown(text=_stats_note(name, numeric, box)))
# Keep the column heading, its figure and its stats note together on the
# same page/slide (mejora 3 — keep-together): the renderers measure the
# whole Group and move it whole when it would not fit.
blocks.append(model.Group(blocks=[
model.Heading(text=str(name), level=2),
model.Figure(
make=_figure_maker(name, numeric, box),
caption=f"Distribución de «{name}» — histograma "
f"(media/mediana/±σ) y boxplot."),
model.Markdown(text=_stats_note(name, numeric, box)),
]))
return model.Chapter(id=CHAPTER_ID, title=CHAPTER_TITLE,
version=CHAPTER_VERSION, blocks=blocks)
@@ -65,19 +65,33 @@ def _pdf_text(path: str) -> str:
return re.sub(r"\s+", " ", txt)
def _flatten(blocks):
"""Expand keep-together Groups so the per-column heading/figure/markdown are
inspectable as a flat block list (the chapter wraps each column in a Group)."""
out = []
for b in blocks:
if getattr(b, "kind", "") == "group":
out.extend(_flatten(getattr(b, "blocks", []) or []))
else:
out.append(b)
return out
def test_golden_chapter_estructura_y_bloques():
ch = build_num_distr(_profile(n_numeric=2), {})
assert ch is not None
assert ch.id == "num_distr"
assert ch.version == CHAPTER_VERSION
kinds = [b.kind for b in ch.blocks]
# Per-column blocks are wrapped in keep-together Groups: flatten to inspect.
flat = _flatten(ch.blocks)
kinds = [b.kind for b in flat]
# Heading + intro Markdown, then per column: Heading + Figure + Markdown.
assert kinds[0] == "heading"
assert kinds[1] == "markdown"
assert kinds.count("figure") == 2 # one figure per numeric column.
assert kinds.count("heading") == 1 + 2 # chapter title + one per column.
# Each figure has a lazy maker that produces a real matplotlib figure.
figs = [b for b in ch.blocks if b.kind == "figure"]
figs = [b for b in flat if b.kind == "figure"]
fig = figs[0].make()
assert fig is not None
# Two stacked axes: histogram + boxplot share the figure.
@@ -90,7 +104,8 @@ def test_golden_media_mediana_sigma_y_boxplot_presentes():
# The intro documents the three reference lines and the Tukey boxplot; the
# per-column note carries the actual mean/median/σ numbers and the shape.
ch = build_num_distr(_profile(n_numeric=1, extra_categorical=False), {})
md_texts = " ".join(b.text for b in ch.blocks if b.kind == "markdown")
md_texts = " ".join(b.text for b in _flatten(ch.blocks)
if b.kind == "markdown")
assert "media" in md_texts and "mediana" in md_texts
assert "±1σ" in md_texts or "σ" in md_texts
assert "boxplot" in md_texts.lower()
@@ -126,7 +141,8 @@ def test_anti_corte_muchas_columnas_pdf_y_pptx():
# 8 numeric columns + long note text: nothing may be cut. Every column
# heading must survive in both the PDF text and the PPTX deck.
ch = build_num_distr(_profile(n_numeric=8), {})
names = [b.text for b in ch.blocks if b.kind == "heading" and b.level == 2]
names = [b.text for b in _flatten(ch.blocks)
if b.kind == "heading" and b.level == 2]
assert len(names) == 8
with tempfile.TemporaryDirectory() as d:
pdf = os.path.join(d, "num.pdf")
@@ -2,8 +2,17 @@
Builds the document cover from a TableProfile plus an optional ``ctx`` of
presentation metadata. Reads everything defensively (``.get``) and degrades
honestly: a field that is neither in the profile nor in ``ctx`` is shown as a
placeholder rather than invented, leaving a hook for the LLM layer to fill it.
honestly.
The dataset size (N rows x M columns) is always shown big, as a heading right
under the dataset name (kept together in a ``Group``), not buried in the
metadata table. The Description and Granularity are resolved through a cascade
so they are never empty: an explicit ``ctx`` value wins; otherwise the LLM block
(``profile['llm']`` from ``eda_llm_insights``) provides ``summary`` /
``row_meaning``; otherwise a short summary is derived from the profile itself
(shape, column-type mix, quality score) and a "Cada fila es…" sentence from the
key-candidate columns or the table shape. Nothing is invented: the derived
fallbacks state that they come from the profile.
Contract for chapter authors (see ``docs/capabilities/automatic_eda.md``):
build_<id>(profile: dict, ctx: dict) -> Chapter | None
@@ -17,10 +26,15 @@ from datetime import datetime, timezone
from .. import model
CHAPTER_VERSION = "1.0.0"
CHAPTER_VERSION = "1.2.0"
CHAPTER_ID = "portada"
CHAPTER_TITLE = "Portada"
# Key under which eda_llm_insights stores its interpretive block in the profile.
# The cover reads ``summary`` (what the table is) and ``row_meaning`` (what one
# row represents) from it when the LLM layer ran (``run_llm``).
_LLM_KEY = "llm"
# Default human description of what the table quality score measures. Chapters
# can override it via ctx["quality_criteria"].
_DEFAULT_QUALITY_CRITERIA = (
@@ -67,6 +81,53 @@ def _fmt_int(v) -> str:
return str(v)
def _fmt_pct(value) -> str:
"""Format a percentage that may arrive as a 01 fraction or a 0100 number."""
if value is None:
return ""
try:
v = float(value)
except (TypeError, ValueError):
return str(value)
if 0 < v <= 1.0:
v *= 100.0
return f"{v:.1f}%"
def _summary_blocks(summary) -> list:
"""Mini-summary of the rest of the analysis, shown on the cover (mejora 5).
The cover is built AFTER the body (``build_document`` passes the aggregated
``ctx['document_summary']``), so it can reflect what the analysis found:
shape, column types, quality flags and which chapters were included. Returns
an empty list when there is no summary (the cover degrades to its metadata
table only)."""
if not isinstance(summary, dict) or not summary:
return []
rows = []
n_num = summary.get("n_numeric")
n_cat = summary.get("n_categorical")
if n_num is not None or n_cat is not None:
rows.append(("Columnas numéricas / categóricas",
f"{_fmt_int(n_num)} / {_fmt_int(n_cat)}"))
if summary.get("duplicate_pct") is not None:
rows.append(("Filas duplicadas", _fmt_pct(summary.get("duplicate_pct"))))
if summary.get("null_cell_pct") is not None:
rows.append(("Celdas nulas", _fmt_pct(summary.get("null_cell_pct"))))
titles = summary.get("chapter_titles") or []
if titles:
rows.append(("Capítulos del informe", _fmt_int(len(titles))))
blocks = [model.Heading(text="Resumen del análisis", level=2)]
if rows:
blocks.append(model.KVTable(rows=rows))
if titles:
bullets = "\n".join(f"- {model._safe_str(t)}" for t in titles)
blocks.append(model.Markdown(
text="Este informe incluye los siguientes capítulos:\n" + bullets))
return blocks
def _fmt_date_eu(value) -> str:
"""Format a date/ISO string as European DD/MM/AAAA HH:mm (UI convention).
@@ -95,6 +156,88 @@ def _fmt_date_eu(value) -> str:
return s
def _llm_block(profile: dict, ctx: dict) -> dict:
"""Return the interpretive LLM block (``eda_llm_insights`` output), or {}.
It is stored under ``profile['llm']`` by ``profile_table(run_llm=True)`` and
may also be forwarded in ``ctx['llm']``. Read defensively: anything that is
not a dict degrades to an empty dict so the cover never raises.
"""
block = profile.get(_LLM_KEY)
if not isinstance(block, dict):
block = ctx.get(_LLM_KEY)
return block if isinstance(block, dict) else {}
def _count_column_types(profile: dict, ctx: dict):
"""Best-effort (n_numeric, n_categorical) for the dataset.
Prefers the aggregated ``ctx['document_summary']`` (computed by the engine
over the whole body); falls back to counting the profile columns directly so
the cover still has the numbers when no summary was passed.
"""
summary = ctx.get("document_summary")
if isinstance(summary, dict):
n_num = summary.get("n_numeric")
n_cat = summary.get("n_categorical")
if n_num is not None or n_cat is not None:
return n_num, n_cat
cols = profile.get("columns") or []
n_num = sum(1 for c in cols if isinstance(c, dict)
and c.get("inferred_type") == "numeric")
n_cat = sum(1 for c in cols if isinstance(c, dict)
and isinstance(c.get("categorical"), dict)
and c.get("categorical", {}).get("top")
and c.get("inferred_type") != "numeric")
return n_num, n_cat
def _derive_description(profile: dict, ctx: dict) -> str:
"""A short, honest description of the dataset from the profile.
Used only when no explicit ``ctx['description']`` and no LLM ``summary`` are
available. Summarizes shape, column-type mix and quality score; never empty,
never invents business meaning (it states the description was derived)."""
n_rows = profile.get("n_rows")
n_cols = profile.get("n_cols")
n_num, n_cat = _count_column_types(profile, ctx)
head = f"Conjunto de datos con {_fmt_int(n_rows)} filas y {_fmt_int(n_cols)} columnas"
type_bits = []
if n_num:
type_bits.append(f"{_fmt_int(n_num)} numéricas")
if n_cat:
type_bits.append(f"{_fmt_int(n_cat)} categóricas")
if type_bits:
head += " (" + ", ".join(type_bits) + ")"
parts = [head + "."]
score = profile.get("quality_score")
if score is not None:
parts.append(f"Calidad media estimada: {score}/100.")
parts.append(
"Resumen derivado del perfil; active la interpretación LLM (`run_llm`) "
"para una descripción de negocio más rica.")
return " ".join(parts)
def _derive_granularity(profile: dict, dataset_name: str) -> str:
"""A ``Cada fila es…`` granularity sentence from the profile.
Prefers the key-candidate columns (a row is identified by them); when no key
is detected, falls back to the table shape so the line is always meaningful
and starts with ``Cada fila es`` as the user requested."""
keys = profile.get("key_candidates") or []
if keys:
shown = ", ".join(str(k) for k in keys[:3])
more = "" if len(keys) <= 3 else f" (y {len(keys) - 3} más)"
return (f"Cada fila es un registro identificado por {shown}{more}, "
"candidata(s) a clave por ser únicas y sin nulos.")
n_rows = profile.get("n_rows")
tail = f" El dataset tiene {_fmt_int(n_rows)} filas en total." if n_rows else ""
return (f"Cada fila es un registro de «{dataset_name}». No se detectó una "
"columna identificadora única, así que la granularidad se infiere "
"de la forma de la tabla." + tail)
def build_portada(profile: dict, ctx: dict):
"""Build the cover Chapter, or None if there is truly nothing to show."""
profile = profile or {}
@@ -119,30 +262,38 @@ def build_portada(profile: dict, ctx: dict):
quality_criteria = ctx.get("quality_criteria") or _DEFAULT_QUALITY_CRITERIA
quality_value = "" if score is None else f"{score} / 100"
# Granularity: ctx wins; else derive from key candidates; else be honest.
llm = _llm_block(profile, ctx)
# Granularity: explicit ctx wins; then the LLM "row_meaning"; then the key
# candidates; finally a shape-based fallback. Always a real "Cada fila es…".
granularity = ctx.get("granularity")
if not granularity:
keys = profile.get("key_candidates") or []
if keys:
granularity = ("Cada fila parece identificada por "
+ ", ".join(str(k) for k in keys[:3]) + ".")
else:
granularity = ("Cada fila es… (granularidad no determinada — "
"pendiente de la capa de cálculo/LLM).")
granularity = (llm.get("row_meaning") or "").strip() or None
if not granularity:
granularity = _derive_granularity(profile, str(dataset_name))
# Description: explicit ctx wins; then the LLM "summary"; finally a short
# profile-derived summary. Never the old empty placeholder.
description = ctx.get("description")
if not description:
description = ("Descripción no provista — pendiente de la capa LLM "
"(`run_llm`) o de `ctx['description']`.")
description = (llm.get("summary") or "").strip() or None
if not description:
description = _derive_description(profile, ctx)
blocks = [
# Title + dataset size shown together and BIG (Heading) at the top, kept on
# the same page (Group). The size is no longer buried in the metadata table.
cover = [
model.Heading(text=str(dataset_name), level=1),
model.Markdown(text="**Automatic-EDA** · informe exploratorio automático"),
model.Heading(text=shape, level=2),
]
blocks = [
model.Group(blocks=cover),
model.KVTable(rows=[
("Fuente", source_origin),
("Almacenamiento", storage),
("Generado", when),
("Tamaño", shape),
("Calidad", quality_value),
("Criterios de calidad", quality_criteria),
]),
@@ -152,5 +303,8 @@ def build_portada(profile: dict, ctx: dict):
model.Markdown(text=str(granularity)),
]
# Mini-summary of the rest of the analysis (built last, shown on the cover).
blocks.extend(_summary_blocks(ctx.get("document_summary")))
return model.Chapter(id=CHAPTER_ID, title=CHAPTER_TITLE,
version=CHAPTER_VERSION, blocks=blocks)
@@ -0,0 +1,197 @@
"""Tests for the PORTADA (cover) chapter — DoD: golden + edges + render.
Self-contained: builds synthetic TableProfiles (no DuckDB) so the suite is fast
and deterministic. Verifies the Fase 4b improvements:
1. The dataset size (N rows x M columns) is always shown BIG — as a level-2
heading kept together with the dataset name in a ``Group`` — and is no longer
a row of the metadata table.
2. Description and Granularity are resolved through a real cascade and are never
the old empty placeholders: an explicit ``ctx`` value wins; otherwise the LLM
block (``profile['llm']``) provides ``summary`` / ``row_meaning``; otherwise a
short summary is derived from the profile and a "Cada fila es…" sentence from
the key-candidate columns or the table shape.
3. The chapter degrades without raising on empty/None input.
4. It renders inside the full document to both PDF and PPTX showing that content.
"""
import os
import re
import tempfile
from pypdf import PdfReader
from pptx import Presentation
from datascience.automatic_eda.model import Group, Heading, KVTable, Markdown
from datascience.automatic_eda.chapters.portada import (
CHAPTER_ID, CHAPTER_VERSION, build_portada,
)
from datascience.render_automatic_eda_pdf import render_automatic_eda_pdf
from datascience.render_automatic_eda_pptx import render_automatic_eda_pptx
def _profile(with_llm: bool = True, with_keys: bool = True) -> dict:
prof = {
"table": "titanic",
"source": "/data/titanic.csv",
"profiled_at": "2026-06-30T10:00:00+00:00",
"n_rows": 891,
"n_cols": 12,
"quality_score": 78.0,
"columns": [
{"name": "PassengerId", "inferred_type": "numeric",
"null_pct": 0.0, "numeric": {"mean": 446.0, "min": 1.0,
"max": 891.0, "std": 257.0}},
{"name": "Survived", "inferred_type": "numeric",
"null_pct": 0.0, "numeric": {"mean": 0.38, "min": 0.0,
"max": 1.0, "std": 0.49}},
{"name": "Sex", "inferred_type": "categorical", "null_pct": 0.0,
"categorical": {"top": [{"value": "male", "count": 577, "pct": 0.65},
{"value": "female", "count": 314,
"pct": 0.35}],
"mode": "male", "n_distinct": 2, "entropy": 0.93}},
],
}
if with_keys:
prof["key_candidates"] = ["PassengerId"]
if with_llm:
prof["llm"] = {
"summary": "Pasajeros del Titanic con su supervivencia y datos de viaje.",
"row_meaning": "Cada fila es un pasajero del Titanic.",
"dictionary": [], "pii": [], "cleaning": [], "analyses": [],
}
return prof
def _pdf_text(path: str) -> str:
txt = "".join((pg.extract_text() or "") for pg in PdfReader(path).pages)
return re.sub(r"\s+", " ", txt)
def _pptx_text(path: str) -> str:
prs = Presentation(path)
parts = []
for sl in prs.slides:
for sh in sl.shapes:
if sh.has_text_frame:
parts.append(sh.text_frame.text)
if sh.has_table:
tb = sh.table
for r in range(len(tb.rows)):
for c in range(len(tb.columns)):
parts.append(tb.cell(r, c).text)
return re.sub(r"\s+", " ", " ".join(parts))
def _markdown_after(blocks, heading_text):
"""Return the Markdown block that follows a Heading whose text matches."""
for i, b in enumerate(blocks):
if isinstance(b, Heading) and heading_text.lower() in b.text.lower():
for nb in blocks[i + 1:]:
if isinstance(nb, Markdown):
return nb
return None
def test_golden_tamano_grande_y_textos_llm():
ch = build_portada(_profile(), {})
assert ch is not None
assert ch.id == CHAPTER_ID
assert ch.version == CHAPTER_VERSION
# 1) Title + size kept together in a Group; size is a BIG level-2 heading.
group = next(b for b in ch.blocks if isinstance(b, Group))
inner = group.blocks
assert isinstance(inner[0], Heading) and inner[0].level == 1
assert inner[0].text == "titanic"
size_h = next(b for b in inner if isinstance(b, Heading) and b.level == 2)
assert "891" in size_h.text and "12" in size_h.text
assert "filas" in size_h.text and "columnas" in size_h.text
# 2) Size is no longer a row of the metadata table.
kv = next(b for b in ch.blocks if isinstance(b, KVTable))
labels = [r[0] for r in kv.rows]
assert "Tamaño" not in labels
assert "Fuente" in labels and "Calidad" in labels
# 3) Description and Granularity come from the LLM block.
desc = _markdown_after(ch.blocks, "Descripción")
gran = _markdown_after(ch.blocks, "Granularidad")
assert desc is not None and "Titanic" in desc.text
assert gran is not None and gran.text.startswith("Cada fila es")
assert "pasajero" in gran.text.lower()
def test_fallback_sin_llm_usa_keys_y_perfil():
# No LLM block: description derived from the profile, granularity from keys.
ch = build_portada(_profile(with_llm=False, with_keys=True), {})
desc = _markdown_after(ch.blocks, "Descripción")
gran = _markdown_after(ch.blocks, "Granularidad")
# Description is the derived summary, never the old "pendiente" placeholder.
assert "pendiente" not in desc.text.lower()
assert "891" in desc.text and "columnas" in desc.text
assert "numéricas" in desc.text or "categóricas" in desc.text
# Granularity mentions the key candidate and starts with "Cada fila es".
assert gran.text.startswith("Cada fila es")
assert "PassengerId" in gran.text
assert "" not in gran.text # the old ellipsis placeholder is gone.
def test_fallback_sin_llm_sin_keys_usa_forma():
ch = build_portada(_profile(with_llm=False, with_keys=False), {})
gran = _markdown_after(ch.blocks, "Granularidad")
assert gran.text.startswith("Cada fila es")
assert "titanic" in gran.text.lower()
assert "pendiente" not in gran.text.lower()
def test_ctx_explicito_gana_sobre_llm():
ctx = {"description": "Descripción manual.",
"granularity": "Cada fila es una unidad manual."}
ch = build_portada(_profile(), ctx)
desc = _markdown_after(ch.blocks, "Descripción")
gran = _markdown_after(ch.blocks, "Granularidad")
assert desc.text == "Descripción manual."
assert gran.text == "Cada fila es una unidad manual."
def test_edge_perfil_vacio_no_lanza():
# Empty / None never raise; the cover still shows a size and real texts.
for prof, ctx in (({}, {}), (None, None)):
ch = build_portada(prof, ctx)
assert ch is not None
group = next(b for b in ch.blocks if isinstance(b, Group))
size_h = next(b for b in group.blocks
if isinstance(b, Heading) and b.level == 2)
assert "filas" in size_h.text and "columnas" in size_h.text
desc = _markdown_after(ch.blocks, "Descripción")
gran = _markdown_after(ch.blocks, "Granularidad")
assert desc.text and "pendiente" not in desc.text.lower()
assert gran.text.startswith("Cada fila es")
def test_golden_render_pdf_muestra_portada():
prof = _profile()
with tempfile.TemporaryDirectory() as d:
out = os.path.join(d, "eda.pdf")
res = render_automatic_eda_pdf(prof, out, {"title": "EDA"})
assert res["path"] == out and os.path.exists(out)
assert CHAPTER_ID in [c["id"] for c in res["chapters"]]
txt = _pdf_text(out)
assert "titanic" in txt.lower()
assert "891" in txt and "filas" in txt and "columnas" in txt
assert "Titanic" in txt # LLM summary in the Description.
assert "Cada fila es" in txt # granularity sentence.
def test_golden_render_pptx_muestra_portada():
prof = _profile()
with tempfile.TemporaryDirectory() as d:
out = os.path.join(d, "eda.pptx")
res = render_automatic_eda_pptx(prof, out, {"title": "EDA"})
assert res["path"] == out and os.path.exists(out)
assert CHAPTER_ID in [c["id"] for c in res["chapters"]]
txt = _pptx_text(out)
assert "titanic" in txt.lower()
assert "891" in txt and "columnas" in txt
assert "Cada fila es" in txt
@@ -26,7 +26,7 @@ from . import model
# placeholders other agents will fill by creating chapters/<id>.py — they will
# appear in this exact position automatically once their module exists.
CHAPTER_ORDER = [
"portada", # cover
"portada", # cover — BUILT LAST, PLACED FIRST (see build_document).
"overview", # df.head + columns/types/nulls/examples + describe
"analisis_llm", # LLM interpretation — sits next to overview (user request)
"num_distr", # numeric distributions
@@ -37,8 +37,15 @@ CHAPTER_ORDER = [
"timeseries", # time-series analysis
"geospatial", # geospatial
"agregacion", # aggregations / pivots
"glosario", # glossary — ALWAYS LAST; clickable term destinations.
]
# Chapters whose position is special-cased by build_document: portada is built
# last (so it can summarize the rest) but placed first; glosario is built and
# placed last (it reads the terms every other chapter registered).
_PORTADA = "portada"
_GLOSARIO = "glosario"
def build_chapter(chapter_id: str, profile: dict, ctx: dict):
"""Build a single chapter by id, or None if absent/not-applicable/error.
@@ -75,15 +82,72 @@ def build_document(profile: dict, ctx: dict = None) -> list:
list[Chapter] in canonical order, containing only the chapters that are
implemented and applicable. Never raises.
"""
if profile is None:
profile = {}
if not isinstance(profile, dict):
profile = {}
if ctx is None:
ctx = {}
chapters = []
# Copy ctx so the shared collector / summary we add do not leak to the caller.
ctx = dict(ctx) if isinstance(ctx, dict) else {}
# A single glossary collector is shared by every chapter via ctx['glossary'].
# Chapters call ctx['glossary'].add(key, label, definition) and mark in-text
# appearances with [[term:key]]…[[/term]]; the glosario chapter renders the
# registered terms and the renderers wire the clickable links.
glossary = ctx.get("glossary")
if not isinstance(glossary, model.GlossaryCollector):
glossary = model.GlossaryCollector()
ctx["glossary"] = glossary
# 1) Body: every chapter except portada (built last) and glosario (placed
# last), in canonical order. This also fills the glossary collector.
body = []
for cid in CHAPTER_ORDER:
if cid in (_PORTADA, _GLOSARIO):
continue
ch = build_chapter(cid, profile, ctx)
if ch is not None and ch.blocks:
chapters.append(ch)
body.append(ch)
# 2) Aggregated summary of the rest, for the cover (user decision: the cover
# is BUILT after the body so it can reflect what the analysis found).
ctx["document_summary"] = _summarize_document(profile, body)
# 3) Build the cover last, place it FIRST.
portada = build_chapter(_PORTADA, profile, ctx)
# 4) Build the glossary last (reads the terms the body registered), place LAST.
glosario = build_chapter(_GLOSARIO, profile, ctx)
chapters = []
if portada is not None and portada.blocks:
chapters.append(portada)
chapters.extend(body)
if glosario is not None and glosario.blocks:
chapters.append(glosario)
return chapters
def _summarize_document(profile: dict, body: list) -> dict:
"""Aggregate a tiny findings summary of the body for the cover. Never raises.
Returns a dict with dataset shape, quality, column-type counts and the list
of chapters actually included — enough for the cover to show a mini-summary
of the analysis without re-deriving anything."""
try:
cols = profile.get("columns") or []
n_num = sum(1 for c in cols if isinstance(c, dict)
and c.get("inferred_type") == "numeric")
n_cat = sum(1 for c in cols if isinstance(c, dict)
and isinstance(c.get("categorical"), dict)
and c.get("categorical", {}).get("top")
and c.get("inferred_type") != "numeric")
return {
"n_chapters": len(body),
"chapter_titles": [getattr(c, "title", "") for c in body],
"n_rows": profile.get("n_rows"),
"n_cols": profile.get("n_cols"),
"quality_score": profile.get("quality_score"),
"n_numeric": n_num,
"n_categorical": n_cat,
"duplicate_pct": profile.get("duplicate_pct"),
"null_cell_pct": profile.get("null_cell_pct"),
}
except Exception: # noqa: BLE001 — the summary is best-effort.
return {"n_chapters": len(body) if isinstance(body, list) else 0}
@@ -128,6 +128,39 @@ class Note:
kind: str = field(default="note", init=False)
@dataclass
class Group:
"""A keep-together unit: its blocks render on the SAME page/slide.
Renderers measure the whole group first; if it does not fit in the remaining
space they move it *whole* to the next page (PDF) or slide (PPTX) before
drawing anything — so a heading never gets stranded apart from the figure and
text it introduces. If the group is taller than a full page even on its own,
it starts on a fresh page and flows (honest degradation, never cut). Use it to
bind ``Heading`` + ``Markdown`` + ``Figure`` of one idea together (see the
DISTR NUM / AGREGACION chapters).
"""
blocks: list = field(default_factory=list)
title: Optional[str] = None
kind: str = field(default="group", init=False)
@dataclass
class GlossaryEntry:
"""One glossary term: a clickable destination at the end of the document.
Rendered as the term ``label`` (heading) plus its ``definition`` (markdown).
The renderers register its page/slide position as the link target so every
in-text appearance of the same ``key`` becomes a real clickable jump (PDF link
annotation via PyMuPDF; PPTX internal slide jump)."""
key: str = ""
label: str = ""
definition: str = ""
kind: str = field(default="glossary_entry", init=False)
@dataclass
class Chapter:
"""An ordered set of blocks with an id, a title and a generation version."""
@@ -150,13 +183,17 @@ _BLOCK_BY_KIND = {
"image": Image,
"caption": Caption,
"note": Note,
"group": Group,
"glossary_entry": GlossaryEntry,
}
def as_block(obj: Any):
"""Coerce a value into a block dataclass. Unknown values become a Note."""
if isinstance(obj, (Heading, Markdown, KVTable, DataTable, Figure, Image,
Caption, Note)):
Caption, Note, Group, GlossaryEntry)):
if isinstance(obj, Group):
obj.blocks = as_blocks(obj.blocks)
return obj
if isinstance(obj, dict):
kind = obj.get("kind")
@@ -189,6 +226,13 @@ def as_block(obj: Any):
return Caption(text=_safe_str(obj.get("text")))
if cls is Note:
return Note(text=_safe_str(obj.get("text")))
if cls is Group:
return Group(blocks=as_blocks(obj.get("blocks")),
title=obj.get("title"))
if cls is GlossaryEntry:
return GlossaryEntry(key=_safe_str(obj.get("key")),
label=_safe_str(obj.get("label")),
definition=_safe_str(obj.get("definition")))
except Exception: # noqa: BLE001 — never raise on a malformed block.
return Note(text=_safe_str(obj))
return Note(text=_safe_str(obj))
@@ -246,6 +290,67 @@ def _safe_str(v: Any) -> str:
return ""
# --------------------------------------------------------------------------- #
# Glossary collector — chapters register the terms they use; the glosario
# chapter renders them at the end and the renderers wire the clickable links.
# --------------------------------------------------------------------------- #
class GlossaryCollector:
"""Accumulates glossary terms registered by chapters during document build.
A single instance is created by :func:`build_document` and passed to every
chapter via ``ctx['glossary']``. A chapter calls ``add(key, label,
definition)`` to declare a term it explains (e.g. ``"entropia"`` →
"Entropía"), and marks each in-text appearance with the inline span
``[[term:key]]texto visible[[/term]]`` (see ``text_layout.parse_inline_rich``).
The ``glosario`` chapter reads ``terms()`` to emit one :class:`GlossaryEntry`
per term; the renderers turn every marked appearance into a real click that
jumps to that entry. First registration of a key wins (idempotent); never
raises."""
def __init__(self):
self._terms: dict = {}
self._order: list = []
def add(self, key: Any, label: Any = None, definition: Any = "") -> str:
"""Register a term and return its normalized key (''. if invalid)."""
try:
k = _safe_str(key).strip()
if not k:
return ""
if k not in self._terms:
self._terms[k] = {
"key": k,
"label": _safe_str(label).strip() or k,
"definition": _safe_str(definition),
}
self._order.append(k)
return k
except Exception: # noqa: BLE001 — collecting a term never breaks a build.
return ""
def has(self, key: Any) -> bool:
return _safe_str(key).strip() in self._terms
def get(self, key: Any) -> Optional[dict]:
return self._terms.get(_safe_str(key).strip())
def terms(self, by: str = "label") -> list:
"""Return the registered terms as dicts.
``by='label'`` (default) sorts alphabetically by visible label;
``by='order'`` keeps first-appearance order."""
if by == "order":
return [self._terms[k] for k in self._order]
return sorted(self._terms.values(),
key=lambda t: _safe_str(t.get("label")).lower())
def __len__(self) -> int:
return len(self._terms)
def __bool__(self) -> bool:
return bool(self._terms)
# --------------------------------------------------------------------------- #
# Manifest — per-chapter versions and page/slide counts for tracking.
# --------------------------------------------------------------------------- #
@@ -0,0 +1,354 @@
"""Tests for the AutomaticEDA engine features added in phase 4a.
Covers, with executable evidence, the six render-engine improvements:
1. Bold no longer overlaps the following text in the PDF (real width measured).
2. Zebra striping on data tables (PDF Rectangle fills + PPTX cell fills).
3. Keep-together: a Group moves whole to the next page/slide (heading never gets
stranded from its figure).
4. Every PPTX figure carries a visible caption/title (fallback to the heading).
5. Cover is built last but placed first and reflects an aggregated summary.
6. Glossary is the last chapter; the term "entropía" is a real clickable link in
the PDF (PyMuPDF GOTO annotation) and in the PPTX (native slide-jump run).
Self-contained: synthetic profiles, no DuckDB. Heavy renderer checks (fitz/pptx)
skip cleanly when the optional engine is missing.
"""
import os
import sys
import pytest
_HERE = os.path.dirname(os.path.abspath(__file__))
_FUNCTIONS = os.path.abspath(os.path.join(_HERE, "..", "..", "..")) # python/functions
if _FUNCTIONS not in sys.path:
sys.path.insert(0, _FUNCTIONS)
import matplotlib # noqa: E402
matplotlib.use("Agg")
import matplotlib.colors as mcolors # noqa: E402
import matplotlib.pyplot as plt # noqa: E402
from matplotlib.patches import Rectangle # noqa: E402
from datascience.automatic_eda import model # noqa: E402
from datascience.automatic_eda import render_pdf_impl as RP # noqa: E402
from datascience.automatic_eda import render_pptx_impl as RX # noqa: E402
from datascience.automatic_eda import build_document # noqa: E402
from datascience.render_automatic_eda_pdf import render_automatic_eda_pdf # noqa: E402
from datascience.render_automatic_eda_pptx import render_automatic_eda_pptx # noqa: E402
class _FakePdf:
"""Stand-in for PdfPages so the placers can call _new_page in unit tests."""
def savefig(self, fig): # noqa: D401
pass
def _small_fig():
fig = plt.figure(figsize=(4.0, 1.5))
ax = fig.add_subplot(111)
ax.plot([0, 1, 2], [1, 3, 2])
return fig
def _profile_with_cat_and_num():
"""A tiny profile that triggers cat_distr (→ entropía term) and num_distr."""
return {
"table": "ventas", "n_rows": 120, "n_cols": 2, "quality_score": 91,
"duplicate_pct": 1.5, "null_cell_pct": 0.8,
"columns": [
{"name": "region", "inferred_type": "categorical",
"categorical": {
"top": [{"value": "norte", "count": 50, "pct": 0.42},
{"value": "sur", "count": 40, "pct": 0.33},
{"value": "este", "count": 30, "pct": 0.25}],
"mode": "norte", "n_distinct": 3, "entropy": 1.55,
"imbalance": 0.1}},
{"name": "importe", "inferred_type": "numeric",
"numeric": {"mean": 50.0, "median": 48.0, "std": 10.0,
"min": 10, "max": 99, "iqr": 15,
"histogram": [{"lo": 0, "hi": 50, "count": 40},
{"lo": 50, "hi": 100, "count": 80}]}},
],
}
# --------------------------------------------------------------------------- #
# 1) Bold does not overlap the following text (PDF).
# --------------------------------------------------------------------------- #
def test_pdf_bold_span_does_not_overlap_following_text():
fig = plt.figure(figsize=(RP._W, RP._H))
st = RP._PdfState(_FakePdf(), "t")
st.fig = fig
st.page = 1
# A wide bold token immediately followed by normal text on the SAME line.
rich = [[("PALABRAMUYANCHAENNEGRITA", True, None),
(" texto normal justo después", False, None)]]
RP._place_rich_lines(st, rich, RP._FS_BODY, RP._INK)
renderer = fig.canvas.get_renderer()
boxes = sorted((t.get_window_extent(renderer) for t in fig.texts),
key=lambda b: b.x0)
assert len(boxes) == 2, "se esperaban dos spans dibujados"
# The bold span ends before the normal span starts (no overlap). 1px slack.
assert boxes[0].x1 <= boxes[1].x0 + 1.0, \
"la negrita se solapa con el texto siguiente"
plt.close(fig)
# --------------------------------------------------------------------------- #
# 2) Zebra striping.
# --------------------------------------------------------------------------- #
def _facecolor_eq(artist, hexcolor) -> bool:
want = mcolors.to_rgba(hexcolor)
got = artist.get_facecolor()
return all(abs(a - b) < 0.02 for a, b in zip(got[:3], want[:3]))
def test_pdf_table_has_zebra_striping():
fig = plt.figure(figsize=(RP._W, RP._H))
st = RP._PdfState(_FakePdf(), "t")
st.fig = fig
st.page = 1
st.chapter = model.Chapter(id="c", title="C", version="1.0.0")
dt = model.DataTable(header=["A", "B"],
rows=[["1", "x"], ["2", "y"], ["3", "z"], ["4", "w"]])
RP._place_data_table(st, dt)
zebra = [a for a in fig.findobj(Rectangle) if _facecolor_eq(a, RP._ZEBRA)]
# 4 data rows → even rows (1-based 2 and 4) shaded = 2 zebra rectangles.
assert len(zebra) == 2, f"esperadas 2 filas zebra, hay {len(zebra)}"
plt.close(fig)
def test_pptx_table_has_zebra_striping(tmp_path):
pptx = pytest.importorskip("pptx")
from pptx import Presentation
from pptx.dml.color import RGBColor
doc = [model.Chapter(id="c", title="Tabla", version="1.0.0", blocks=[
model.DataTable(header=["A", "B"],
rows=[["1", "x"], ["2", "y"], ["3", "z"], ["4", "w"]])])]
out = str(tmp_path / "zebra.pptx")
assert render_automatic_eda_pptx(doc, out, {"write_manifest": False})["path"]
prs = Presentation(out)
table = None
for slide in prs.slides:
for sh in slide.shapes:
if sh.has_table:
table = sh.table
break
assert table is not None, "no se encontró la tabla en el deck"
zebra = RGBColor(0xF6, 0xF8, 0xFA)
white = RGBColor(0xFF, 0xFF, 0xFF)
# Row 0 = header; data rows follow. Even data rows (table rows 2, 4) shaded.
assert table.cell(1, 0).fill.fore_color.rgb == white
assert table.cell(2, 0).fill.fore_color.rgb == zebra
assert table.cell(4, 0).fill.fore_color.rgb == zebra
# --------------------------------------------------------------------------- #
# 3) Keep-together (Group): heading + figure never split.
# --------------------------------------------------------------------------- #
def test_pdf_group_moves_whole_to_next_page_when_it_does_not_fit():
fig = plt.figure(figsize=(RP._W, RP._H))
st = RP._PdfState(_FakePdf(), "t")
st.fig = fig
st.page = 1
st.chapter = model.Chapter(id="c", title="C", version="1.0.0")
grp = model.Group(blocks=[
model.Heading(text="Sección con figura", level=2),
model.Figure(make=_small_fig, caption="cap"),
model.Markdown(text="Descripción breve de la figura."),
])
# Only ~0.4in left: the group does not fit here but fits on a fresh page.
st.y = RP._CONTENT_BOTTOM - 0.4
page_before = st.page
RP._place_group(st, grp)
# Exactly one page break: the whole group (heading+figure+text) stays
# together on the new page — no second break inside it.
assert st.page == page_before + 1
plt.close(st.fig)
def test_pdf_group_does_not_break_when_it_fits():
fig = plt.figure(figsize=(RP._W, RP._H))
st = RP._PdfState(_FakePdf(), "t")
st.fig = fig
st.page = 1
st.chapter = model.Chapter(id="c", title="C", version="1.0.0")
grp = model.Group(blocks=[
model.Heading(text="Cabe entera", level=2),
model.Figure(make=_small_fig, caption="cap"),
])
st.y = RP._CONTENT_TOP # empty page → fits, must not break.
page_before = st.page
RP._place_group(st, grp)
assert st.page == page_before
plt.close(st.fig)
def test_pptx_group_moves_whole_to_next_slide(tmp_path):
pytest.importorskip("pptx")
from pptx import Presentation
from pptx.util import Inches
prs = Presentation()
prs.slide_width = Inches(RX._W)
prs.slide_height = Inches(RX._H)
st = RX._PptxState(prs, "t")
st.chapter = model.Chapter(id="c", title="C", version="1.0.0")
RX._new_slide(st, cont=False)
grp = model.Group(blocks=[
model.Heading(text="Sección con figura", level=2),
model.Figure(make=_small_fig, caption="cap"),
model.Markdown(text="Descripción breve."),
])
st.y = RX._CONTENT_BOTTOM - 0.4 # does not fit here.
slide_before = st.slide_no
RX._place_group(st, grp)
assert st.slide_no == slide_before + 1 # one jump; group kept together.
# --------------------------------------------------------------------------- #
# 4) Every PPTX figure carries a visible caption/title.
# --------------------------------------------------------------------------- #
def test_pptx_figure_without_caption_gets_heading_title(tmp_path):
pytest.importorskip("pptx")
from pptx import Presentation
from pptx.enum.shapes import MSO_SHAPE_TYPE
doc = [model.Chapter(id="c", title="Cap", version="1.0.0", blocks=[
model.Heading(text="Mi sección gráfica", level=2),
model.Figure(make=_small_fig), # NO caption provided.
])]
out = str(tmp_path / "cap.pptx")
assert render_automatic_eda_pptx(doc, out, {"write_manifest": False})["path"]
prs = Presentation(out)
for slide in prs.slides:
has_pic = any(sh.shape_type == MSO_SHAPE_TYPE.PICTURE
for sh in slide.shapes)
if not has_pic:
continue
italic = [r.text for sh in slide.shapes if sh.has_text_frame
for p in sh.text_frame.paragraphs for r in p.runs
if r.font.italic and r.text.strip()]
assert italic, "la figura no lleva caption visible en su slide"
assert any("Mi sección gráfica" in t for t in italic), \
"el caption no cayó al título de la sección"
return
pytest.fail("no se encontró ningún slide con imagen")
def test_pptx_no_figure_slide_is_ever_untitled(tmp_path):
"""Invariant: across many figures (incl. tall ones), NO slide with an image
lacks a visible caption — the caption never spills to the next slide."""
pytest.importorskip("pptx")
from pptx import Presentation
from pptx.enum.shapes import MSO_SHAPE_TYPE
def _tall_fig():
fig = plt.figure(figsize=(5.0, 4.6)) # nearly square → fills the slide.
fig.add_subplot(111).bar([1, 2, 3], [4, 5, 6])
return fig
blocks = []
for i in range(6):
blocks.append(model.Heading(text=f"Gráfico {i}", level=2))
blocks.append(model.Figure(
make=_tall_fig,
caption=("Una descripción de la figura deliberadamente larga para "
"que el caption ocupe más de una línea al envolverse en el "
f"ancho del slide — figura número {i} del bloque.")))
doc = [model.Chapter(id="c", title="Muchas figuras", version="1.0.0",
blocks=blocks)]
out = str(tmp_path / "many.pptx")
assert render_automatic_eda_pptx(doc, out, {"write_manifest": False})["path"]
prs = Presentation(out)
missing = []
pics = 0
for i, slide in enumerate(prs.slides):
if not any(sh.shape_type == MSO_SHAPE_TYPE.PICTURE
for sh in slide.shapes):
continue
pics += 1
italic = [r.text for sh in slide.shapes if sh.has_text_frame
for p in sh.text_frame.paragraphs for r in p.runs
if r.font.italic and r.text.strip()]
if not italic:
missing.append(i)
assert pics >= 6, f"esperadas >=6 figuras, hay {pics}"
assert not missing, f"slides con imagen sin caption: {missing}"
# --------------------------------------------------------------------------- #
# 5) Cover built last, placed first, with an aggregated summary.
# --------------------------------------------------------------------------- #
def test_cover_first_glossary_last_with_summary():
chs = build_document(_profile_with_cat_and_num(), ctx={"dataset_name": "v"})
ids = [c.id for c in chs]
assert ids[0] == "portada", f"la portada no es la primera: {ids}"
assert ids[-1] == "glosario", f"el glosario no es el último: {ids}"
cover = chs[0]
headings = [b.text for b in cover.blocks if b.kind == "heading"]
assert any("Resumen" in h for h in headings), \
"la portada no incluye el resumen agregado"
# The summary reflects the body chapters (e.g. the numeric/categorical ones).
cover_text = " ".join(
b.text for b in cover.blocks if getattr(b, "kind", "") == "markdown")
assert "Distribuciones" in cover_text, \
"el resumen de portada no menciona los capítulos del cuerpo"
# --------------------------------------------------------------------------- #
# 6) Glossary clickable in PDF (PyMuPDF GOTO) and PPTX (native slide jump).
# --------------------------------------------------------------------------- #
def test_pdf_glossary_term_is_clickable(tmp_path):
fitz = pytest.importorskip("fitz")
out = str(tmp_path / "glos.pdf")
res = render_automatic_eda_pdf(_profile_with_cat_and_num(), out,
{"ctx": {"dataset_name": "v"},
"write_manifest": False})
assert res["path"] == out and os.path.exists(out)
doc = fitz.open(out)
goto = [(pno, l) for pno in range(doc.page_count)
for l in doc[pno].get_links() if l.get("kind") == fitz.LINK_GOTO]
doc.close()
assert goto, "no hay ningún enlace interno (entropía → glosario) en el PDF"
# Destination must be a real page in the document (the glossary page).
assert all(0 <= l.get("page", -1) for _p, l in goto)
def test_pptx_glossary_term_is_clickable(tmp_path):
pytest.importorskip("pptx")
from pptx import Presentation
from pptx.oxml.ns import qn
out = str(tmp_path / "glos.pptx")
res = render_automatic_eda_pptx(_profile_with_cat_and_num(), out,
{"ctx": {"dataset_name": "v"},
"write_manifest": False})
assert res["path"] == out and os.path.exists(out)
prs = Presentation(out)
found = False
for slide in prs.slides:
for sh in slide.shapes:
if not sh.has_text_frame:
continue
for p in sh.text_frame.paragraphs:
for r in p.runs:
rpr = r._r.find(qn("a:rPr"))
if rpr is None:
continue
hl = rpr.find(qn("a:hlinkClick"))
if hl is not None and \
hl.get("action") == "ppaction://hlinksldjump":
found = True
assert found, "ningún término tiene hyperlink de salto a slide en el PPTX"
@@ -60,6 +60,8 @@ _FS_BODY, _FS_CELL, _FS_NOTE = 10.5, 9.0, 9.0
_GAP = 0.12 # vertical gap after a block, inches.
_CELL_PAD = 0.06 # horizontal padding inside a table cell, inches.
_ROW_VPAD = 0.05 # vertical padding inside a table row, inches.
_ZEBRA = "#f6f8fa" # very light grey for zebra-striped (even) table rows.
_LINK = "#2a6f97" # accent colour for clickable glossary terms.
class _PdfState:
@@ -73,6 +75,11 @@ class _PdfState:
self.page = 0 # global page counter.
self.chapter = None # current Chapter (for the footer).
self.chapter_pages = 0 # pages produced for the current chapter.
self.last_heading = "" # text of the most recent heading.
# Glossary wiring (mejora 6). Pages are 0-based; rects/points are in PDF
# points (1/72") with a top-left origin — same convention as PyMuPDF.
self.term_sources = [] # [{key, page, rect:[x0,y0,x1,y1]}]
self.term_dests = {} # key -> {page, point:[x,y]}
# --------------------------------------------------------------------------- #
@@ -121,6 +128,35 @@ def _draw_footer(st: _PdfState) -> None:
transform=st.fig.transFigure, color=_RULE, lw=0.6))
def _text_width_in(st: _PdfState, s: str, fs: float, bold: bool) -> float:
"""Real rendered width (inches) of ``s`` at ``fs`` with the given weight.
Measured with the Agg renderer's own font metrics (the same TrueType the PDF
backend embeds), so a **bold** span advances the cursor by its ACTUAL width —
fixing the bug where bold text overlapped the following normal text because
the cursor advanced by the normal-weight average-glyph estimate. Falls back to
the deterministic character grid if the renderer is unavailable, so it never
raises.
"""
if not s:
return 0.0
try:
from matplotlib.font_manager import FontProperties
renderer = st.fig.canvas.get_renderer()
prop = FontProperties(family="sans-serif", size=fs,
weight="bold" if bold else "normal")
w_px, _h, _d = renderer.get_text_width_height_descent(s, prop, False)
return w_px / float(st.fig.dpi)
except Exception: # noqa: BLE001 — fall back to the conservative grid metric.
return tl.avg_char_width_in(fs) * len(s)
def _pt_rect(x0_in: float, y_top_in: float, x1_in: float,
y_bottom_in: float) -> list:
"""An inches box (top-left origin) → a PDF-points rect for PyMuPDF links."""
return [x0_in * 72.0, y_top_in * 72.0, x1_in * 72.0, y_bottom_in * 72.0]
def _remaining(st: _PdfState) -> float:
return _CONTENT_BOTTOM - st.y
@@ -138,6 +174,7 @@ def _place_heading(st: _PdfState, block) -> None:
level = max(1, min(3, int(getattr(block, "level", 1) or 1)))
fs = {1: _FS_H1, 2: _FS_H2, 3: _FS_H3}[level]
text = tl.strip_inline_md(getattr(block, "text", ""))
st.last_heading = text or st.last_heading
max_chars = tl.chars_per_line(_USABLE_W, fs)
lines = tl.wrap(text, max_chars)
lh = tl.line_height_in(fs, leading=1.2)
@@ -171,17 +208,19 @@ def _place_text_lines(st: _PdfState, lines: list, fs: float, color: str,
def _place_rich_lines(st: _PdfState, rich_lines: list, fs: float, color: str,
indent: float = 0.0, prefixes=None) -> None:
"""Draw pre-wrapped lines of styled segments (bold spans rendered bold).
"""Draw pre-wrapped lines of styled segments (bold + clickable term spans).
Each line is ``[(text, is_bold), ...]``. Segments are placed left-to-right,
advancing x by the deterministic character grid (same metric the wrapper
used), so a bold span is rendered with ``fontweight='bold'`` without
changing the line's measured width — the no-cut guarantee is preserved.
Each line is a list of ``(text, is_bold)`` or ``(text, is_bold, term_key)``
segments. Segments are placed left-to-right, advancing x by the segment's
REAL rendered width (measured with the renderer's font metrics for the actual
weight) — this is what stops a bold span from overlapping the following text:
the cursor no longer advances by the normal-weight estimate. A segment with a
``term_key`` is drawn in the accent colour and its rectangle is recorded in
``st.term_sources`` so it becomes a clickable jump to the glossary entry.
``prefixes`` is an optional ``(first_line, other_lines)`` pair (e.g. a
bullet) drawn before the segments.
"""
lh = tl.line_height_in(fs)
cw = tl.avg_char_width_in(fs)
for idx, segs in enumerate(rich_lines):
_ensure_space(st, lh)
x = _ML + indent
@@ -190,14 +229,23 @@ def _place_rich_lines(st: _PdfState, rich_lines: list, fs: float, color: str,
if prefix:
st.fig.text(_xf(x), _yf(st.y), prefix, fontsize=fs, color=color,
ha="left", va="top")
x += cw * len(prefix)
for seg_text, is_bold in segs:
x += _text_width_in(st, prefix, fs, False)
for seg in segs:
if len(seg) == 3:
seg_text, is_bold, term = seg
else:
seg_text, is_bold, term = seg[0], seg[1], None
if seg_text == "":
continue
st.fig.text(_xf(x), _yf(st.y), seg_text, fontsize=fs, color=color,
ha="left", va="top",
w = _text_width_in(st, seg_text, fs, bool(is_bold))
st.fig.text(_xf(x), _yf(st.y), seg_text, fontsize=fs,
color=(_LINK if term else color), ha="left", va="top",
fontweight="bold" if is_bold else "normal")
x += cw * len(seg_text)
if term:
st.term_sources.append({
"key": term, "page": st.page - 1,
"rect": _pt_rect(x, st.y, x + w, st.y + lh)})
x += w
st.y += lh
@@ -242,7 +290,7 @@ def _place_markdown(st: _PdfState, block) -> None:
if stripped.startswith("- ") or stripped.startswith("* "):
content = stripped[2:] # keep inline markers for bold rendering.
bullet_chars = tl.chars_per_line(_USABLE_W - 0.22, _FS_BODY)
rich = tl.wrap_rich(content, bullet_chars)
rich = tl.wrap_rich_terms(content, bullet_chars)
_place_rich_lines(st, rich, _FS_BODY, _INK,
prefixes=("", " "))
i += 1
@@ -258,7 +306,8 @@ def _place_markdown(st: _PdfState, block) -> None:
j += 1
text = " ".join(para)
max_chars = tl.chars_per_line(_USABLE_W, _FS_BODY)
_place_rich_lines(st, tl.wrap_rich(text, max_chars), _FS_BODY, _INK)
_place_rich_lines(st, tl.wrap_rich_terms(text, max_chars), _FS_BODY,
_INK)
i = j
st.y += _GAP
@@ -325,15 +374,18 @@ def _wrap_row(cells: list, widths: list, fs: float) -> list:
def _draw_table_row(st: _PdfState, cells_lines: list, widths: list, fs: float,
y0: float, header: bool) -> float:
y0: float, header: bool, zebra: bool = False) -> float:
lh = tl.line_height_in(fs)
nlines = max((len(c) for c in cells_lines), default=1)
row_h = lh * nlines + _ROW_VPAD * 2
if header:
# Background: header band, or a faint zebra fill for even data rows. Drawn
# below the text/rule (zorder 0) so striping never hides cell content.
bg = _HEAD_BG if header else (_ZEBRA if zebra else None)
if bg is not None:
st.fig.add_artist(Rectangle(
(_xf(_ML), _yf(y0 + row_h)), _xf(_ML + _USABLE_W) - _xf(_ML),
_yf(y0) - _yf(y0 + row_h), transform=st.fig.transFigure,
color=_HEAD_BG, lw=0, zorder=0))
color=bg, lw=0, zorder=0))
x = _ML
for c, lines in enumerate(cells_lines):
for k, ln in enumerate(lines):
@@ -378,14 +430,18 @@ def _place_data_table(st: _PdfState, block) -> None:
+ _ROW_VPAD * 2
_ensure_space(st, header_h() + max(first_row_h, lh))
draw_header()
for r in rows:
# ``data_idx`` is the LOGICAL row index (not reset across page breaks) so the
# zebra pattern stays coherent when a long table splits and repeats the
# header: even rows (1-based) are shaded → 0-based odd indices.
for data_idx, r in enumerate(rows):
cells_lines = _wrap_row(r, widths, fs)
row_h = lh * max((len(c) for c in cells_lines), default=1) \
+ _ROW_VPAD * 2
if _remaining(st) < row_h:
_new_page(st)
draw_header() # repeat header on the continuation page.
st.y += _draw_table_row(st, cells_lines, widths, fs, st.y, header=False)
st.y += _draw_table_row(st, cells_lines, widths, fs, st.y,
header=False, zebra=(data_idx % 2 == 1))
note = getattr(block, "note", None)
if note:
_place_text_lines(st, tl.wrap(model._safe_str(note),
@@ -414,53 +470,98 @@ def _png_from_figure(fig) -> bytes:
return buf.read()
def _place_image_array(st: _PdfState, arr, caption) -> None:
def _figure_png_cached(block):
"""Rasterize a Figure to PNG bytes ONCE and cache (bytes, aspect).
Measuring (keep-together) and drawing must agree on the REAL aspect ratio:
``bbox_inches='tight'`` changes it vs ``figsize``, so we rasterize once and
reuse the bytes for both. Cached on the block; never raises."""
cached = getattr(block, "_aeda_png", None)
if cached is not None:
return cached
fig, owned = _resolve_figure(block)
data = None
if fig is not None:
try:
data = _png_from_figure(fig)
finally:
if owned:
try:
plt.close(fig)
except Exception: # noqa: BLE001
pass
aspect = 0.66
if data is not None:
try:
arr = mpimg.imread(io.BytesIO(data))
aspect = (arr.shape[0] / arr.shape[1]) if arr.shape[1] else 0.66
except Exception: # noqa: BLE001
aspect = 0.66
try:
block._aeda_png = (data, aspect)
return block._aeda_png
except Exception: # noqa: BLE001 — block may reject attributes; degrade.
return (data, aspect)
def _image_aspect(block) -> float:
"""Real aspect (h/w) of an Image block by path, for measurement."""
path = getattr(block, "path", "")
if path and os.path.exists(path):
try:
arr = mpimg.imread(path)
return (arr.shape[0] / arr.shape[1]) if arr.shape[1] else 0.66
except Exception: # noqa: BLE001
pass
return 0.66
def _place_image_array(st: _PdfState, arr, caption, max_h_in=None) -> None:
h_px, w_px = arr.shape[0], arr.shape[1]
aspect = (h_px / w_px) if w_px else 1.0
# Reserve the caption's REAL (possibly multi-line) height FIRST, then scale
# the image to (max_h - cap_reserve) so figure + caption always fit the same
# page. cap_reserve adds a cushion so the caption never spills to next page.
cap_lines = (tl.wrap(model._safe_str(caption),
tl.chars_per_line(_USABLE_W, _FS_NOTE))
if caption else [])
cap_real = tl.line_height_in(_FS_NOTE) * len(cap_lines) if caption else 0.0
cap_reserve = (cap_real + 0.04 + 0.08) if caption else 0.0
max_h = _CONTENT_BOTTOM - _CONTENT_TOP
# height_in hint (model.Figure/Image): cap the height so a figure in a
# keep-together Group shrinks to leave room for its heading and text.
if isinstance(max_h_in, (int, float)) and max_h_in > 0:
max_h = min(max_h, float(max_h_in))
max_img_h = max(max_h - cap_reserve, 0.6)
target_w = _USABLE_W
target_h = target_w * aspect
if target_h > max_h:
target_h = max_h
if target_h > max_img_h:
target_h = max_img_h
target_w = target_h / aspect if aspect else _USABLE_W
cap_h = tl.line_height_in(_FS_NOTE) + 0.04 if caption else 0.0
# Move whole image to next page if it does not fit in remaining space.
if _remaining(st) < target_h + cap_h:
if (max_h) >= target_h + cap_h:
_new_page(st)
else:
# Taller than a full page even at min — already clamped to max_h.
_new_page(st)
if _remaining(st) < target_h + cap_reserve:
_new_page(st)
left_frac = _xf(_ML + (_USABLE_W - target_w) / 2.0)
bottom_frac = _yf(st.y + target_h)
ax = st.fig.add_axes([left_frac, bottom_frac, target_w / _W, target_h / _H])
ax.imshow(arr)
ax.axis("off")
st.y += target_h + 0.04
if caption:
_place_text_lines(st, tl.wrap(model._safe_str(caption),
tl.chars_per_line(_USABLE_W, _FS_NOTE)),
_FS_NOTE, _MUTED, style="italic")
if cap_lines:
_place_text_lines(st, cap_lines, _FS_NOTE, _MUTED, style="italic")
st.y += _GAP
def _place_figure(st: _PdfState, block) -> None:
fig, owned = _resolve_figure(block)
if fig is None:
png, _aspect = _figure_png_cached(block)
if png is None:
_place_text_lines(st, ["(figura no disponible)"], _FS_NOTE, _MUTED,
style="italic")
st.y += _GAP
return
try:
png = _png_from_figure(fig)
finally:
if owned:
try:
plt.close(fig)
except Exception: # noqa: BLE001
pass
arr = mpimg.imread(io.BytesIO(png))
_place_image_array(st, arr, getattr(block, "caption", None))
_place_image_array(st, arr, getattr(block, "caption", None),
max_h_in=getattr(block, "height_in", None))
def _place_image(st: _PdfState, block) -> None:
@@ -471,7 +572,8 @@ def _place_image(st: _PdfState, block) -> None:
st.y += _GAP
return
arr = mpimg.imread(path)
_place_image_array(st, arr, getattr(block, "caption", None))
_place_image_array(st, arr, getattr(block, "caption", None),
max_h_in=getattr(block, "height_in", None))
def _place_caption(st: _PdfState, block) -> None:
@@ -488,6 +590,189 @@ def _place_note(st: _PdfState, block) -> None:
st.y += _GAP
# --------------------------------------------------------------------------- #
# Block measurement (mejora 3 — keep-together). These estimate a block's height
# WITHOUT drawing it, so a Group can decide to move whole to the next page before
# anything is drawn. Over-estimating is safe: it only triggers an earlier page
# break, never a content cut (the placers keep their own no-cut pagination).
# --------------------------------------------------------------------------- #
def _measure_heading_text(text: str, level: int) -> float:
level = max(1, min(3, int(level or 1)))
fs = {1: _FS_H1, 2: _FS_H2, 3: _FS_H3}[level]
lines = tl.wrap(tl.strip_inline_md(text), tl.chars_per_line(_USABLE_W, fs))
h = tl.line_height_in(fs, leading=1.2) * len(lines) + 0.06
if level == 1:
h += 0.10
return h + _GAP
def _measure_markdown(block) -> float:
raw = str(getattr(block, "text", "") or "")
md_lines = raw.split("\n")
h = 0.0
i, n = 0, len(md_lines)
while i < n:
stripped = md_lines[i].strip()
if stripped.startswith("|") and stripped.endswith("|"):
j = i
while j < n and md_lines[j].strip().startswith("|") \
and md_lines[j].strip().endswith("|"):
j += 1
h += (tl.line_height_in(_FS_CELL) + _ROW_VPAD * 2) * (j - i) + _GAP
i = j
continue
if stripped == "":
h += tl.line_height_in(_FS_BODY) * 0.5
i += 1
continue
if stripped.startswith("### "):
h += _measure_heading_text(stripped[4:], 3)
i += 1
continue
if stripped.startswith("## "):
h += _measure_heading_text(stripped[3:], 2)
i += 1
continue
if stripped.startswith("# "):
h += _measure_heading_text(stripped[2:], 1)
i += 1
continue
if stripped.startswith("- ") or stripped.startswith("* "):
lines = tl.wrap_rich_terms(
stripped[2:], tl.chars_per_line(_USABLE_W - 0.22, _FS_BODY))
h += tl.line_height_in(_FS_BODY) * len(lines)
i += 1
continue
para = [stripped]
j = i + 1
while j < n:
nxt = md_lines[j].strip()
if nxt == "" or nxt.startswith(("|", "#", "- ", "* ")):
break
para.append(nxt)
j += 1
lines = tl.wrap_rich_terms(" ".join(para),
tl.chars_per_line(_USABLE_W, _FS_BODY))
h += tl.line_height_in(_FS_BODY) * len(lines)
i = j
return h + _GAP
def _measure_figure_like(block) -> float:
max_h = _CONTENT_BOTTOM - _CONTENT_TOP
hint = getattr(block, "height_in", None)
if isinstance(hint, (int, float)) and hint > 0:
target_h = min(float(hint), max_h)
else:
# Real rasterized aspect (cached) so measuring matches drawing.
if getattr(block, "kind", "") == "image":
aspect = _image_aspect(block)
else:
_data, aspect = _figure_png_cached(block)
target_h = min(_USABLE_W * aspect, max_h)
cap = getattr(block, "caption", None)
cap_h = tl.line_height_in(_FS_NOTE) + 0.04 if cap else 0.0
return target_h + 0.04 + cap_h + _GAP
def _measure_block(st: _PdfState, block) -> float:
kind = getattr(block, "kind", "")
try:
if kind == "heading":
return _measure_heading_text(getattr(block, "text", ""),
getattr(block, "level", 1))
if kind == "markdown":
return _measure_markdown(block)
if kind in ("figure", "image"):
return _measure_figure_like(block)
if kind in ("caption", "note"):
lines = tl.wrap(getattr(block, "text", ""),
tl.chars_per_line(_USABLE_W, _FS_NOTE))
return tl.line_height_in(_FS_NOTE) * len(lines) + _GAP
if kind == "kv_table":
rows = getattr(block, "rows", []) or []
return (tl.line_height_in(_FS_BODY) + _ROW_VPAD) * (len(rows) + 1) \
+ _GAP
if kind == "data_table":
rows = getattr(block, "rows", []) or []
return (tl.line_height_in(_FS_CELL) + _ROW_VPAD * 2) \
* (len(rows) + 1) + _GAP
if kind == "group":
return sum(_measure_block(st, b)
for b in (getattr(block, "blocks", []) or []))
except Exception: # noqa: BLE001 — a measurement never aborts rendering.
pass
return tl.line_height_in(_FS_BODY)
def _shrink_group_figures(st: _PdfState, blocks: list, avail_full: float) -> None:
"""Cap each figure's height (via height_in) so the whole group fits a page.
The figure shrinks just enough to leave room for its heading, text and
caption — keep-together puts the chart on the SAME page as its title and
description instead of pushing it to the next page."""
fig_blocks = [b for b in blocks
if getattr(b, "kind", "") in ("figure", "image")]
if not fig_blocks:
return
nonfig_h = sum(_measure_block(st, b) for b in blocks
if getattr(b, "kind", "") not in ("figure", "image"))
fig_overhead = tl.line_height_in(_FS_NOTE) + 0.04 + 0.04 + _GAP
budget = avail_full - nonfig_h - 0.08 * len(fig_blocks)
if budget <= 0.8:
return
per = budget / len(fig_blocks) - fig_overhead
if per <= 0.6:
return
for fb in fig_blocks:
cur = getattr(fb, "height_in", None)
fb.height_in = (min(float(cur), per)
if isinstance(cur, (int, float)) and cur > 0 else per)
def _place_group(st: _PdfState, block) -> None:
"""Render a keep-together Group: move it whole to the next page if needed."""
blocks = getattr(block, "blocks", []) or []
if not blocks:
return
avail_full = _CONTENT_BOTTOM - _CONTENT_TOP
_shrink_group_figures(st, blocks, avail_full)
total = sum(_measure_block(st, b) for b in blocks)
if total <= avail_full:
# Fits on one page: keep it together by moving whole when it won't fit.
if total > _remaining(st):
_new_page(st)
elif st.y > _CONTENT_TOP + 1e-6:
# Taller than a full page: at least start it on a fresh page, then flow.
_new_page(st)
for b in blocks:
placer = _PLACERS.get(getattr(b, "kind", ""), _place_note)
try:
placer(st, b)
except Exception: # noqa: BLE001 — a bad block never aborts the group.
pass
def _place_glossary_entry(st: _PdfState, block) -> None:
"""Render one glossary term and register it as a clickable link target."""
key = getattr(block, "key", "")
label = getattr(block, "label", "") or key
definition = getattr(block, "definition", "")
# Reserve the term + its first definition line together, then anchor the
# destination at the resolved page/position before drawing.
_ensure_space(st, tl.line_height_in(_FS_H3, leading=1.2)
+ tl.line_height_in(_FS_BODY) * 2)
if key:
st.term_dests[key] = {"page": st.page - 1,
"point": [_ML * 72.0, st.y * 72.0]}
_place_heading(st, model.Heading(text=str(label), level=3))
if definition:
_place_text_lines(st, tl.wrap(model._safe_str(definition),
tl.chars_per_line(_USABLE_W, _FS_BODY)),
_FS_BODY, _INK)
st.y += _GAP * 0.5
_PLACERS = {
"heading": _place_heading,
"markdown": _place_markdown,
@@ -497,6 +782,8 @@ _PLACERS = {
"image": _place_image,
"caption": _place_caption,
"note": _place_note,
"group": _place_group,
"glossary_entry": _place_glossary_entry,
}
@@ -553,8 +840,42 @@ def render_pdf(chapters: list, out_path: str, meta: dict = None) -> dict:
return {"path": None, "n_pages": 0, "chapters": [],
"note": f"fallo al escribir el PDF: {e}"}
# Mejora 6 — wire clickable glossary links now the PDF is closed on disk.
# PdfPages cannot emit internal hyperlinks, so we post-process with PyMuPDF
# (delegated registry function). Degrades silently if it is unavailable.
n_links = _wire_glossary_links(st, out_path, notes)
note = f"{n_pages} páginas"
if n_links:
note += f" · {n_links} enlaces de glosario"
if notes:
note += " · " + "; ".join(notes)
return {"path": out_path, "n_pages": n_pages, "chapters": chapters_meta,
"note": note}
def _wire_glossary_links(st: _PdfState, out_path: str, notes: list) -> int:
"""Build {source rect → glossary dest} links and apply them via PyMuPDF.
Returns the number of links applied (0 if there is nothing to wire or the
post-processor is unavailable). Never raises."""
try:
links = []
for src in st.term_sources:
dest = st.term_dests.get(src.get("key"))
if not dest:
continue
links.append({
"src_page": src["page"], "src_rect": src["rect"],
"dst_page": dest["page"], "dst_point": dest["point"]})
if not links:
return 0
from datascience.add_pdf_internal_links import add_pdf_internal_links
res = add_pdf_internal_links(out_path, links)
if isinstance(res, dict) and res.get("status") == "ok":
return int(res.get("n_links") or 0)
if isinstance(res, dict) and res.get("error"):
notes.append(f"glosario sin enlaces: {res.get('error')}")
except Exception as e: # noqa: BLE001 — links are best-effort.
notes.append(f"glosario sin enlaces: {e}")
return 0
@@ -43,6 +43,8 @@ _ACCENT = (0x2A, 0x6F, 0x97)
_MUTED = (0x8A, 0x8A, 0x8A)
_HEAD_BG = (0xEE, 0xF3, 0xF6)
_WHITE = (0xFF, 0xFF, 0xFF)
_ZEBRA = (0xF6, 0xF8, 0xFA) # faint grey for even (zebra) data rows.
_LINK = (0x2A, 0x6F, 0x97) # accent colour for clickable glossary terms.
_FS_TITLE = 26
_FS_H1, _FS_H2, _FS_H3 = 20, 16, 13
@@ -59,6 +61,10 @@ class _PptxState:
self.chapter = None
self.slide_no = 0
self.chapter_slides = 0
self.last_heading = "" # text of the most recent heading.
# Glossary wiring (mejora 6): runs to link and per-term target slide.
self.term_runs = [] # [(key, run)]
self.term_anchor_slide = {} # key -> Slide (glossary entry)
def _rgb(c):
@@ -155,9 +161,13 @@ def _add_rich_text(st: _PptxState, rich_lines: list, fs: float, color,
indent=0.0, bullet=False) -> None:
"""Add pre-wrapped lines of styled segments as one paragraph per line.
Each line is ``[(text, is_bold), ...]``; every segment becomes its own run
so ``**bold**`` spans render with native PowerPoint bold (``run.font.bold``)
without affecting the measured height (one paragraph per pre-wrapped line).
Each line is a list of ``(text, is_bold)`` or ``(text, is_bold, term_key)``
segments; every segment becomes its own run so ``**bold**`` spans render with
native PowerPoint bold (``run.font.bold``) without affecting the measured
height (one paragraph per pre-wrapped line). A segment carrying a
``term_key`` is drawn in the accent colour and its run is recorded in
``st.term_runs`` so it later becomes a native hyperlink jumping to the
glossary slide of that term.
"""
lh = tl.line_height_in(fs)
height = lh * len(rich_lines) + 0.05
@@ -176,14 +186,20 @@ def _add_rich_text(st: _PptxState, rich_lines: list, fs: float, color,
r0.text = ""
r0.font.size = Pt(fs)
r0.font.color.rgb = _rgb(color)
for seg_text, is_bold in segs:
for seg in segs:
if len(seg) == 3:
seg_text, is_bold, term = seg
else:
seg_text, is_bold, term = seg[0], seg[1], None
if seg_text == "":
continue
run = p.add_run()
run.text = seg_text
run.font.size = Pt(fs)
run.font.bold = bool(is_bold)
run.font.color.rgb = _rgb(color)
run.font.color.rgb = _rgb(_LINK if term else color)
if term:
st.term_runs.append((term, run, st.slide))
st.y += height
@@ -191,6 +207,7 @@ def _place_heading(st: _PptxState, block) -> None:
level = max(1, min(3, int(getattr(block, "level", 1) or 1)))
fs = {1: _FS_H1, 2: _FS_H2, 3: _FS_H3}[level]
text = tl.strip_inline_md(getattr(block, "text", ""))
st.last_heading = text or st.last_heading
lines = tl.wrap(text, tl.chars_per_line(_USABLE_W, fs))
_add_text(st, lines, fs, _INK, bold=True)
st.y += 0.04
@@ -233,12 +250,12 @@ def _place_markdown(st: _PptxState, block) -> None:
continue
if stripped.startswith("- ") or stripped.startswith("* "):
content = stripped[2:] # keep inline markers for bold rendering.
rich = tl.wrap_rich(content,
tl.chars_per_line(_USABLE_W - 0.3, _FS_BODY))
rich = tl.wrap_rich_terms(content,
tl.chars_per_line(_USABLE_W - 0.3, _FS_BODY))
_add_rich_text(st, rich, _FS_BODY, _INK, bullet=True)
i += 1
continue
para = [stripped] # keep inline markers; wrap_rich renders **bold**.
para = [stripped] # keep inline markers; wrap_rich_terms renders **bold**.
j = i + 1
while j < n:
nxt = md_lines[j].strip()
@@ -247,8 +264,8 @@ def _place_markdown(st: _PptxState, block) -> None:
para.append(nxt)
j += 1
text = " ".join(para)
_add_rich_text(st, tl.wrap_rich(text, tl.chars_per_line(_USABLE_W, _FS_BODY)),
_FS_BODY, _INK)
_add_rich_text(st, tl.wrap_rich_terms(
text, tl.chars_per_line(_USABLE_W, _FS_BODY)), _FS_BODY, _INK)
i = j
st.y += _GAP
@@ -295,7 +312,8 @@ def _row_height_in(cells, widths, fs) -> float:
return lh * maxlines + 0.10
def _emit_table(st: _PptxState, header, chunk, widths, fs) -> None:
def _emit_table(st: _PptxState, header, chunk, widths, fs,
start_index: int = 0) -> None:
nrows = len(chunk) + (1 if header else 0)
ncol = len(widths)
# Pre-measure total height to size the shape (pptx still auto-grows rows).
@@ -319,11 +337,14 @@ def _emit_table(st: _PptxState, header, chunk, widths, fs) -> None:
cell.text = model._safe_str(header[c]) if c < len(header) else ""
_style_cell(cell, fs, _INK, bold=True, fill=_HEAD_BG)
ridx = 1
for r in chunk:
# Zebra striping: shade even data rows (1-based) using the GLOBAL row index
# (start_index offset) so the pattern stays coherent across split chunks.
for k, r in enumerate(chunk):
fill = _ZEBRA if (start_index + k) % 2 == 1 else _WHITE
for c in range(ncol):
cell = gtable.cell(ridx, c)
cell.text = model._safe_str(r[c]) if c < len(r) else ""
_style_cell(cell, fs, _INK, bold=False, fill=_WHITE)
_style_cell(cell, fs, _INK, bold=False, fill=fill)
ridx += 1
st.y += total_h + _GAP
@@ -367,6 +388,7 @@ def _place_data_table(st: _PptxState, block, shaded_header=True,
avail = _remaining(st) - header_h
chunk = []
used = 0.0
chunk_start = idx # global index of the first row in this chunk (zebra).
while idx < n:
rh = _row_height_in(rows[idx], widths, fs)
if used + rh > avail and chunk:
@@ -374,7 +396,7 @@ def _place_data_table(st: _PptxState, block, shaded_header=True,
chunk.append(rows[idx])
used += rh
idx += 1
_emit_table(st, header, chunk, widths, fs)
_emit_table(st, header, chunk, widths, fs, start_index=chunk_start)
note = getattr(block, "note", None)
if note:
_add_text(st, tl.wrap(model._safe_str(note),
@@ -421,54 +443,97 @@ def _resolve_png(block):
pass
def _place_picture_bytes(st: _PptxState, data: bytes, caption) -> None:
def _figure_bytes_cached(block):
"""Rasterize a figure/image to PNG bytes ONCE and cache (bytes, aspect).
Measuring (keep-together) and drawing must agree on the real aspect ratio
``bbox_inches='tight'`` changes it vs ``figsize``, so we rasterize once and
reuse the bytes for both. Cached on the block; never raises."""
cached = getattr(block, "_aeda_png", None)
if cached is not None:
return cached
kind = getattr(block, "kind", "")
data = None
if kind == "image":
path = getattr(block, "path", "")
if path and os.path.exists(path):
try:
with open(path, "rb") as fh:
data = fh.read()
except Exception: # noqa: BLE001
data = None
else:
data = _resolve_png(block)
aspect = 0.66
if data is not None:
w_px, h_px = _img_size_px(data)
aspect = (h_px / w_px) if w_px else 0.66
try:
block._aeda_png = (data, aspect)
return block._aeda_png
except Exception: # noqa: BLE001 — block may reject attributes; degrade.
return (data, aspect)
def _place_picture_bytes(st: _PptxState, data: bytes, caption,
max_h_in=None) -> None:
# Mejora 4 — every figure on a slide carries a visible caption/title. If the
# block has no caption, fall back to the current section heading, then to a
# generic label, so no image is ever shown untitled.
caption = (model._safe_str(caption).strip()
or model._safe_str(st.last_heading).strip() or "Figura")
w_px, h_px = _img_size_px(data)
aspect = (h_px / w_px) if w_px else 0.66
# Reserve the caption's REAL (possibly multi-line) height FIRST, then scale
# the image to (max_h - cap_reserve): a figure never fills the whole slide,
# so its caption always fits on the SAME slide and no image is untitled.
# cap_real = what _add_text consumes; cap_reserve adds the post-image gap and
# a small cushion so the caption never spills to the next slide.
cap_lines = tl.wrap(caption, tl.chars_per_line(_USABLE_W, _FS_NOTE))
cap_real = tl.line_height_in(_FS_NOTE) * len(cap_lines) + 0.05
cap_reserve = cap_real + 0.05 + 0.10
max_h = _CONTENT_BOTTOM - _CONTENT_TOP
# height_in hint (model.Figure/Image): cap the target height so a figure in a
# keep-together Group shrinks to leave room for its heading and text.
if isinstance(max_h_in, (int, float)) and max_h_in > 0:
max_h = min(max_h, float(max_h_in))
max_img_h = max(max_h - cap_reserve, 0.6)
target_w = _USABLE_W
target_h = target_w * aspect
if target_h > max_h:
target_h = max_h
if target_h > max_img_h:
target_h = max_img_h
target_w = target_h / aspect if aspect else _USABLE_W
cap_h = tl.line_height_in(_FS_NOTE) + 0.05 if caption else 0.0
if _remaining(st) < target_h + cap_h:
# Keep the image and its caption together on the same slide.
if _remaining(st) < target_h + cap_reserve:
_new_slide(st, cont=True)
left = _ML + (_USABLE_W - target_w) / 2.0
st.slide.shapes.add_picture(io.BytesIO(data), Inches(left), Inches(st.y),
width=Inches(target_w), height=Inches(target_h))
st.y += target_h + 0.05
if caption:
_add_text(st, tl.wrap(model._safe_str(caption),
tl.chars_per_line(_USABLE_W, _FS_NOTE)), _FS_NOTE, _MUTED,
italic=True)
_add_text(st, cap_lines, _FS_NOTE, _MUTED, italic=True)
st.y += _GAP
def _place_figure(st: _PptxState, block) -> None:
png = _resolve_png(block)
png, _aspect = _figure_bytes_cached(block)
if png is None:
_add_text(st, ["(figura no disponible)"], _FS_NOTE, _MUTED, italic=True)
st.y += _GAP
return
_place_picture_bytes(st, png, getattr(block, "caption", None))
_place_picture_bytes(st, png, getattr(block, "caption", None),
max_h_in=getattr(block, "height_in", None))
def _place_image(st: _PptxState, block) -> None:
path = getattr(block, "path", "")
if not path or not os.path.exists(path):
data, _aspect = _figure_bytes_cached(block)
if data is None:
path = getattr(block, "path", "")
_add_text(st, [f"(imagen no encontrada: {path})"], _FS_NOTE, _MUTED,
italic=True)
st.y += _GAP
return
try:
with open(path, "rb") as fh:
data = fh.read()
except Exception as e: # noqa: BLE001
_add_text(st, [f"(no se pudo leer la imagen: {e})"], _FS_NOTE, _MUTED,
italic=True)
st.y += _GAP
return
_place_picture_bytes(st, data, getattr(block, "caption", None))
_place_picture_bytes(st, data, getattr(block, "caption", None),
max_h_in=getattr(block, "height_in", None))
def _place_caption(st: _PptxState, block) -> None:
@@ -482,6 +547,170 @@ def _place_note(st: _PptxState, block) -> None:
_place_caption(st, block)
# --------------------------------------------------------------------------- #
# Block measurement (mejora 3 — keep-together). Estimate a block's slide height
# WITHOUT drawing it so a Group can move whole to the next slide before drawing.
# Over-estimating only triggers an earlier slide break, never a content cut.
# --------------------------------------------------------------------------- #
def _measure_heading_text(text: str, level: int) -> float:
level = max(1, min(3, int(level or 1)))
fs = {1: _FS_H1, 2: _FS_H2, 3: _FS_H3}[level]
lines = tl.wrap(tl.strip_inline_md(text), tl.chars_per_line(_USABLE_W, fs))
return tl.line_height_in(fs) * len(lines) + 0.05 + 0.04
def _measure_markdown(block) -> float:
raw = str(getattr(block, "text", "") or "")
md_lines = raw.split("\n")
h = 0.0
i, n = 0, len(md_lines)
while i < n:
stripped = md_lines[i].strip()
if stripped.startswith("|") and stripped.endswith("|"):
j = i
while j < n and md_lines[j].strip().startswith("|") \
and md_lines[j].strip().endswith("|"):
j += 1
h += (tl.line_height_in(_FS_CELL) + 0.10) * (j - i) + _GAP
i = j
continue
if stripped == "":
h += tl.line_height_in(_FS_BODY) * 0.4
i += 1
continue
if stripped.startswith("### "):
h += _measure_heading_text(stripped[4:], 3)
i += 1
continue
if stripped.startswith("## "):
h += _measure_heading_text(stripped[3:], 2)
i += 1
continue
if stripped.startswith("# "):
h += _measure_heading_text(stripped[2:], 1)
i += 1
continue
if stripped.startswith("- ") or stripped.startswith("* "):
lines = tl.wrap_rich_terms(
stripped[2:], tl.chars_per_line(_USABLE_W - 0.3, _FS_BODY))
h += tl.line_height_in(_FS_BODY) * len(lines) + 0.05
i += 1
continue
para = [stripped]
j = i + 1
while j < n:
nxt = md_lines[j].strip()
if nxt == "" or nxt.startswith(("|", "#", "- ", "* ")):
break
para.append(nxt)
j += 1
lines = tl.wrap_rich_terms(" ".join(para),
tl.chars_per_line(_USABLE_W, _FS_BODY))
h += tl.line_height_in(_FS_BODY) * len(lines) + 0.05
i = j
return h + _GAP
def _measure_figure_like(block) -> float:
max_h = _CONTENT_BOTTOM - _CONTENT_TOP
hint = getattr(block, "height_in", None)
if isinstance(hint, (int, float)) and hint > 0:
max_h = min(max_h, float(hint))
# Use the REAL rasterized aspect (cached) so measuring matches drawing — this
# is what keeps a figure together with its heading instead of splitting.
_data, aspect = _figure_bytes_cached(block)
target_h = min(_USABLE_W * aspect, max_h)
# Caption is always emitted now (mejora 4), so always reserve its line.
cap_h = tl.line_height_in(_FS_NOTE) + 0.05
return target_h + 0.05 + cap_h + _GAP
def _measure_block(st: _PptxState, block) -> float:
kind = getattr(block, "kind", "")
try:
if kind == "heading":
return _measure_heading_text(getattr(block, "text", ""),
getattr(block, "level", 1))
if kind == "markdown":
return _measure_markdown(block)
if kind in ("figure", "image"):
return _measure_figure_like(block)
if kind in ("caption", "note"):
lines = tl.wrap(getattr(block, "text", ""),
tl.chars_per_line(_USABLE_W, _FS_NOTE))
return tl.line_height_in(_FS_NOTE) * len(lines) + 0.05 + _GAP
if kind in ("kv_table", "data_table"):
rows = getattr(block, "rows", []) or []
return (tl.line_height_in(_FS_CELL) + 0.10) * (len(rows) + 1) + _GAP
if kind == "group":
return sum(_measure_block(st, b)
for b in (getattr(block, "blocks", []) or []))
except Exception: # noqa: BLE001 — a measurement never aborts rendering.
pass
return tl.line_height_in(_FS_BODY)
def _shrink_group_figures(st: _PptxState, blocks: list, avail_full: float) -> None:
"""Cap each figure's height (via height_in) so the whole group fits a slide.
The figure shrinks just enough to leave room for its heading, text and
caption that is how keep-together puts a chart on the SAME slide as its
title and description instead of pushing it to the next slide."""
fig_blocks = [b for b in blocks
if getattr(b, "kind", "") in ("figure", "image")]
if not fig_blocks:
return
nonfig_h = sum(_measure_block(st, b) for b in blocks
if getattr(b, "kind", "") not in ("figure", "image"))
fig_overhead = tl.line_height_in(_FS_NOTE) + 0.05 + 0.05 + _GAP
budget = avail_full - nonfig_h - 0.10 * len(fig_blocks)
if budget <= 1.0:
return # not enough room to keep together; let it flow (degrade).
per = budget / len(fig_blocks) - fig_overhead
if per <= 0.8:
return
for fb in fig_blocks:
cur = getattr(fb, "height_in", None)
fb.height_in = (min(float(cur), per)
if isinstance(cur, (int, float)) and cur > 0 else per)
def _place_group(st: _PptxState, block) -> None:
"""Render a keep-together Group: move it whole to the next slide if needed."""
blocks = getattr(block, "blocks", []) or []
if not blocks:
return
avail_full = _CONTENT_BOTTOM - _CONTENT_TOP
_shrink_group_figures(st, blocks, avail_full)
total = sum(_measure_block(st, b) for b in blocks)
if total <= avail_full:
if total > _remaining(st):
_new_slide(st, cont=True)
elif st.y > _CONTENT_TOP + 1e-6:
_new_slide(st, cont=True)
for b in blocks:
placer = _PLACERS.get(getattr(b, "kind", ""), _place_note)
try:
placer(st, b)
except Exception: # noqa: BLE001 — a bad block never aborts the group.
pass
def _place_glossary_entry(st: _PptxState, block) -> None:
"""Render one glossary term and register its slide as the link target."""
key = getattr(block, "key", "")
label = getattr(block, "label", "") or key
definition = getattr(block, "definition", "")
_ensure(st, tl.line_height_in(_FS_H3) + tl.line_height_in(_FS_BODY) * 2)
if key:
st.term_anchor_slide[key] = st.slide
_place_heading(st, model.Heading(text=str(label), level=3))
if definition:
_add_text(st, tl.wrap(model._safe_str(definition),
tl.chars_per_line(_USABLE_W, _FS_BODY)), _FS_BODY, _INK)
st.y += _GAP
_PLACERS = {
"heading": _place_heading,
"markdown": _place_markdown,
@@ -491,6 +720,8 @@ _PLACERS = {
"image": _place_image,
"caption": _place_caption,
"note": _place_note,
"group": _place_group,
"glossary_entry": _place_glossary_entry,
}
@@ -542,6 +773,9 @@ def render_pptx(chapters: list, out_path: str, meta: dict = None) -> dict:
_new_slide(st, cont=False)
_place_note(st, model.Note(
"(documento vacío — sin capítulos aplicables)"))
# Mejora 6 — wire clickable glossary terms to their entry slide (native
# PowerPoint slide-jump). Delegated registry function; degrades silently.
n_links = _wire_glossary_links(st, notes)
prs.save(out_path)
n_slides = st.slide_no
except Exception as e: # noqa: BLE001
@@ -549,7 +783,35 @@ def render_pptx(chapters: list, out_path: str, meta: dict = None) -> dict:
"note": f"fallo al escribir el PPTX: {e}"}
note = f"{n_slides} slides"
if n_links:
note += f" · {n_links} enlaces de glosario"
if notes:
note += " · " + "; ".join(notes)
return {"path": out_path, "n_slides": n_slides, "chapters": chapters_meta,
"note": note}
def _wire_glossary_links(st: _PptxState, notes: list) -> int:
"""Turn each recorded term run into a native jump to its glossary slide.
Returns the number of links applied. A term whose only appearance is inside
its own glossary entry (source slide == target slide) is skipped. Never
raises."""
if not st.term_runs or not st.term_anchor_slide:
return 0
linked = 0
try:
from datascience.pptx_link_run_to_slide import pptx_link_run_to_slide
except Exception as e: # noqa: BLE001
notes.append(f"glosario sin enlaces: {e}")
return 0
for key, run, src_slide in st.term_runs:
tgt = st.term_anchor_slide.get(key)
if tgt is None or tgt is src_slide:
continue
try:
if pptx_link_run_to_slide(run, src_slide, tgt):
linked += 1
except Exception: # noqa: BLE001 — links are best-effort.
pass
return linked
@@ -24,6 +24,13 @@ import textwrap
# the visible text matches ``strip_inline_md`` exactly.
_INLINE_SPAN_RE = re.compile(r"(\*\*.+?\*\*|__.+?__|`.+?`)")
# Glossary term span: ``[[term:key]]texto visible[[/term]]``. The visible text
# (which may itself contain ``**bold**``) is kept and tagged with ``key`` so the
# renderers can turn each appearance into a clickable jump to the glossary entry.
_TERM_SPAN_RE = re.compile(r"\[\[term:([A-Za-z0-9_]+)\]\](.*?)\[\[/term\]\]",
re.S)
_TERM_OPEN_RE = re.compile(r"\[\[term:[A-Za-z0-9_]+\]\]")
def avg_char_width_in(fontsize_pt: float) -> float:
"""Approximate average glyph width in inches for a sans-serif font.
@@ -86,11 +93,21 @@ def strip_inline_md(text: str) -> str:
if not text:
return ""
s = str(text)
# Drop glossary term markers, keeping the visible inner text.
s = _TERM_SPAN_RE.sub(lambda m: m.group(2), s)
s = _TERM_OPEN_RE.sub("", s) # leftover unbalanced open marker.
s = s.replace("[[/term]]", "") # leftover unbalanced close marker.
for marker in ("**", "__", "`"):
s = s.replace(marker, "")
return s
def _strip_term_markers(s: str) -> str:
"""Remove any (balanced or leftover) glossary term markers, keeping text."""
s = _TERM_OPEN_RE.sub("", s)
return s.replace("[[/term]]", "")
def _strip_leftover_markers(s: str) -> str:
"""Drop any unbalanced inline markers from a plain (non-span) fragment.
@@ -222,6 +239,118 @@ def wrap_rich(text: str, max_chars: int):
return lines or [[("", False)]]
def parse_inline_rich(text: str):
"""Split ``text`` into ``[(fragment, is_bold, term_key), ...]``.
Extends :func:`parse_inline_bold` with glossary term spans
``[[term:key]]visible[[/term]]``: the inner ``visible`` text is parsed for
``**bold**`` as usual and every resulting fragment carries ``term_key`` so the
renderers can make it clickable. Text outside a term span gets ``term_key =
None``. Unbalanced term markers are stripped (kept identical to
:func:`strip_inline_md`). The concatenation of all fragment texts equals
``strip_inline_md(text)`` visible characters and wrapping are unchanged; only
the bold flag and the term key are added. Adjacent fragments with the same
(bold, term) are merged.
"""
s = "" if text is None else str(text)
if not s:
return []
out = []
def _emit(fragment: str, bold: bool, term) -> None:
if fragment == "":
return
if out and out[-1][1] == bold and out[-1][2] == term:
out[-1] = (out[-1][0] + fragment, bold, term)
else:
out.append((fragment, bold, term))
def _emit_bolded(segment: str, term) -> None:
# Reuse the bold parser on a term-marker-free segment.
for frag, bold in parse_inline_bold(_strip_term_markers(segment)):
_emit(frag, bold, term)
pos = 0
for m in _TERM_SPAN_RE.finditer(s):
if m.start() > pos:
_emit_bolded(s[pos:m.start()], None)
_emit_bolded(m.group(2), m.group(1))
pos = m.end()
if pos < len(s):
_emit_bolded(s[pos:], None)
return out
def wrap_rich_terms(text: str, max_chars: int):
"""Like :func:`wrap_rich` but preserving glossary term keys per fragment.
Returns ``list[list[(fragment, is_bold, term_key)]]`` one inner list per
output line. Wrapping is word-aware and hard-splits over-long tokens so no
line exceeds ``max_chars`` (the renderers measure these very lines). Term and
bold flags never widen a line: the visible width matches :func:`wrap`.
"""
if max_chars < 1:
max_chars = 1
spans = parse_inline_rich(text)
if not spans:
return [[("", False, None)]]
tokens = [] # each: (word, bold, term) or ("\n", None, None)
for frag, bold, term in spans:
parts = frag.split("\n")
for pi, part in enumerate(parts):
if pi > 0:
tokens.append(("\n", None, None))
for word in part.split(" "):
if word == "":
continue
tokens.append((word, bold, term))
lines = []
cur = []
cur_len = 0
def _flush():
nonlocal cur, cur_len
merged = []
for k, (word, bold, term) in enumerate(cur):
piece = word if k == 0 else " " + word
if merged and merged[-1][1] == bold and merged[-1][2] == term:
merged[-1] = (merged[-1][0] + piece, bold, term)
else:
merged.append((piece, bold, term))
lines.append(merged or [("", False, None)])
cur = []
cur_len = 0
for word, bold, term in tokens:
if bold is None: # forced newline
_flush()
continue
if len(word) > max_chars:
if cur:
_flush()
chunks = _hard_split(word, max_chars)
for ci, chunk in enumerate(chunks):
if ci < len(chunks) - 1:
lines.append([(chunk, bold, term)])
else:
cur = [(chunk, bold, term)]
cur_len = len(chunk)
continue
add = len(word) if cur_len == 0 else cur_len + 1 + len(word)
if cur_len != 0 and add > max_chars:
_flush()
cur = [(word, bold, term)]
cur_len = len(word)
else:
cur.append((word, bold, term))
cur_len = add
if cur:
_flush()
return lines or [[("", False, None)]]
def parse_md_table(lines: list):
"""Parse consecutive ``| a | b |`` lines into ``(header, rows)`` or None.
@@ -0,0 +1,85 @@
---
name: pptx_link_run_to_slide
kind: function
lang: py
domain: datascience
version: "1.0.0"
purity: impure
signature: "def pptx_link_run_to_slide(run, source_slide, target_slide) -> bool"
description: "Convierte un run de texto de python-pptx en un hyperlink INTERNO 'ir a la diapositiva'. python-pptx soporta run.hyperlink.address para URLs externas pero NO para saltar a otra slide del mismo deck; esta función crea ese salto manipulando el XML: añade una relación slide->slide (RT.SLIDE) y un <a:hlinkClick> con action='ppaction://hlinksldjump' y el r:id de la relación, insertado como primer hijo del <a:rPr> del run (orden del schema CT_TextCharacterProperties). Idempotente (elimina un hlinkClick previo antes de insertar). Al pulsar el texto en PowerPoint o visores compatibles se navega a target_slide. Motor python-pptx. No lanza nunca: cualquier excepción -> return False."
tags: [eda, pptx, hyperlink, slide-jump, navigation, glossary, automatic-eda, python-pptx, xml, datascience, python]
uses_functions: []
uses_types: []
returns: []
returns_optional: false
error_type: "error_go_core"
imports: ["python-pptx"]
params:
- name: run
desc: "el pptx.text.text._Run cuyo texto se vuelve clicable. Debe pertenecer a un run real (expone ._r, el elemento <a:r>). Un objeto sin ._r hace que la función devuelva False sin lanzar."
- name: source_slide
desc: "la Slide que contiene el run. Su part recibe la relación slide->slide (relate_to con RELATIONSHIP_TYPE.SLIDE); el r:id resultante se referencia en el hlinkClick."
- name: target_slide
desc: "la Slide de destino del salto. Debe pertenecer al MISMO Presentation que source_slide para que la relación interna sea válida."
output: "bool. True si se aplicó el hyperlink interno (relación creada + <a:hlinkClick> insertado en el rPr del run); False si algo lo impidió (run inválido, slides de presentaciones distintas, etc.). Nunca lanza."
tested: true
tests: ["test_golden_run_se_vuelve_salto_a_otra_slide", "test_idempotente_reaplica_sin_duplicar_hlinkclick", "test_error_path_run_invalido_devuelve_false_sin_lanzar"]
test_file_path: "python/functions/datascience/pptx_link_run_to_slide_test.py"
file_path: "python/functions/datascience/pptx_link_run_to_slide.py"
---
## Ejemplo
```python
from pptx import Presentation
from pptx.util import Inches
from pptx.oxml.ns import qn
from datascience.pptx_link_run_to_slide import pptx_link_run_to_slide
prs = Presentation()
blank = prs.slide_layouts[6] # layout en blanco
slide0 = prs.slides.add_slide(blank)
slide1 = prs.slides.add_slide(blank) # destino del salto (p.ej. el glosario)
box = slide0.shapes.add_textbox(Inches(1), Inches(1), Inches(4), Inches(1))
run = box.text_frame.paragraphs[0].add_run()
run.text = "ir al glosario"
ok = pptx_link_run_to_slide(run, slide0, slide1)
print(ok) # -> True
# El run quedó con <a:rPr><a:hlinkClick action="ppaction://hlinksldjump" r:id="rIdN"/></a:rPr>
hlink = run._r.get_or_add_rPr().find(qn("a:hlinkClick"))
print(hlink.get("action")) # -> ppaction://hlinksldjump
prs.save("deck_con_salto.pptx")
```
## Cuando usarla
Cuando construyas un deck PPTX con **navegación interna** y quieras que un texto salte a
otra diapositiva al pulsarlo: un **glosario clicable** (cada término enlaza a su slide de
definición), un **índice/tabla de contenidos navegable**, botones "volver a la portada", o
referencias cruzadas entre capítulos. Es la pieza que `python-pptx` no cubre de fábrica —
úsala sobre los runs ya creados por renderers como `render_automatic_eda_pptx` del grupo
`eda` para enriquecer el deck con saltos sin reescribir el XML a mano cada vez.
## Gotchas
- **Impura**: muta el XML del run y crea una relación nueva en el part de `source_slide`.
- **Solo navega en visores que respetan `ppaction://hlinksldjump`**: PowerPoint y la
mayoría de visores compatibles lo siguen; algunos visores web/ligeros lo ignoran (el
texto se ve igual pero no salta).
- **Mismo Presentation**: `source_slide` y `target_slide` deben pertenecer al mismo deck.
Si son de presentaciones distintas, la relación interna no es válida y el salto no
funcionará (la función puede devolver True por crear la relación, pero el resultado en
el visor no será el esperado).
- **El `<a:hlinkClick>` vive en el `<a:rPr>` del run**, no como hijo directo del `<a:r>`.
Para localizarlo: `run._r.get_or_add_rPr().find(qn("a:hlinkClick"))` (un `find` sobre
`run._r` devuelve `None` porque solo mira hijos directos del `<a:r>`).
- **Idempotente**: si el run ya tenía un `hlinkClick` (p.ej. una URL externa o un salto
previo), se elimina antes de insertar el nuevo — un run tiene como mucho un click-link.
- **Nunca lanza**: cualquier excepción (run sin `._r`, slides incompatibles, etc.) se
traga y devuelve `False`. Comprobar el booleano si el salto es crítico.
- **Dependencia python-pptx**: declarada en `python/pyproject.toml`. Tests con
`~/fn_registry/python/.venv/bin/python3` (tiene `python-pptx` instalado).
@@ -0,0 +1,50 @@
"""Convierte un run de texto de python-pptx en un hyperlink interno "ir a la diapositiva".
python-pptx expone ``run.hyperlink.address`` para URLs externas, pero NO ofrece una
API pública para saltar a otra diapositiva del mismo deck. Esta función crea ese salto
interno manipulando el XML: añade una relación ``slide -> slide`` y un
``<a:hlinkClick>`` con la acción ``ppaction://hlinksldjump`` en el run, de modo que al
pulsar el texto en PowerPoint (o en visores que respetan esa acción) se navega a la
diapositiva de destino.
"""
from pptx.opc.constants import RELATIONSHIP_TYPE as RT
from pptx.oxml.ns import qn
def pptx_link_run_to_slide(run, source_slide, target_slide) -> bool:
"""Convierte un run de texto en un hyperlink interno "ir a la diapositiva".
Añade una relación ``slide -> slide`` desde la slide origen al part de la slide
destino y crea un ``<a:hlinkClick>`` con ``action="ppaction://hlinksldjump"`` como
primer hijo del ``<a:rPr>`` del run (orden válido del schema
``CT_TextCharacterProperties``). La operación es idempotente: un ``hlinkClick``
previo en el mismo run se elimina antes de insertar el nuevo.
Args:
run: el ``pptx.text.text._Run`` cuyo texto se vuelve clicable.
source_slide: la ``Slide`` que contiene el run.
target_slide: la ``Slide`` de destino del salto.
Returns:
True si se aplicó el hyperlink; False si algo impidió aplicarlo (no lanza).
"""
try:
rId = source_slide.part.relate_to(target_slide.part, RT.SLIDE)
rPr = run._r.get_or_add_rPr()
# Elimina un hlinkClick previo si lo hubiera (idempotente).
for existing in rPr.findall(qn("a:hlinkClick")):
rPr.remove(existing)
hlink = rPr.makeelement(
qn("a:hlinkClick"),
{
qn("r:id"): rId,
"action": "ppaction://hlinksldjump",
},
)
# a:hlinkClick debe ir como primer hijo de rPr
# (orden del schema CT_TextCharacterProperties).
rPr.insert(0, hlink)
return True
except Exception:
return False
@@ -0,0 +1,73 @@
"""Tests for pptx_link_run_to_slide — salto interno run -> diapositiva.
Self-contained: construye una Presentation en memoria con dos slides en blanco,
un textbox con un run en la slide 0, y verifica que la función inyecta un
``<a:hlinkClick>`` con ``action="ppaction://hlinksldjump"`` y un ``r:id`` que
resuelve al part de la slide 1.
"""
import pytest
pytest.importorskip("pptx")
from pptx import Presentation # noqa: E402
from pptx.oxml.ns import qn # noqa: E402
from pptx.util import Inches # noqa: E402
from datascience.pptx_link_run_to_slide import pptx_link_run_to_slide # noqa: E402
def _two_slide_deck_with_run():
prs = Presentation()
blank = prs.slide_layouts[6] # layout en blanco
slide0 = prs.slides.add_slide(blank)
slide1 = prs.slides.add_slide(blank)
box = slide0.shapes.add_textbox(Inches(1), Inches(1), Inches(4), Inches(1))
tf = box.text_frame
para = tf.paragraphs[0]
run = para.add_run()
run.text = "ir al glosario"
return prs, slide0, slide1, run
def test_golden_run_se_vuelve_salto_a_otra_slide():
prs, slide0, slide1, run = _two_slide_deck_with_run()
ok = pptx_link_run_to_slide(run, slide0, slide1)
assert ok is True
# El hlinkClick es hijo del rPr del run (orden del schema
# CT_TextCharacterProperties), no hijo directo del <a:r>.
rPr = run._r.get_or_add_rPr()
hlink = rPr.find(qn("a:hlinkClick"))
assert hlink is not None
assert hlink.get("action") == "ppaction://hlinksldjump"
rId = hlink.get(qn("r:id"))
assert rId, "el hlinkClick debe llevar un r:id no vacío"
# El rId debe existir en las relaciones de la slide origen y apuntar
# al part de la slide destino.
rels = slide0.part.rels
assert rId in rels
assert rels[rId].target_part is slide1.part
def test_idempotente_reaplica_sin_duplicar_hlinkclick():
prs, slide0, slide1, run = _two_slide_deck_with_run()
assert pptx_link_run_to_slide(run, slide0, slide1) is True
assert pptx_link_run_to_slide(run, slide0, slide1) is True
rPr = run._r.get_or_add_rPr()
hlinks = rPr.findall(qn("a:hlinkClick"))
assert len(hlinks) == 1
def test_error_path_run_invalido_devuelve_false_sin_lanzar():
prs, slide0, slide1, _run = _two_slide_deck_with_run()
# Un objeto sin ._r ni soporte de relación -> la función no lanza, devuelve False.
ok = pptx_link_run_to_slide(object(), slide0, slide1)
assert ok is False
+1
View File
@@ -25,6 +25,7 @@ dependencies = [
"polars>=1.40.1",
"pymeshlab>=2025.7.post1",
"pymssql>=2.3.13",
"pymupdf>=1.28.0",
"pypdf>=6.10.0",
"pyproj>=3.7.2",
"python-docx>=1.2.0",