Observed since 20 Oct, 20:09 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
DSL ultra-compacto para scraping, UI y APIs. Ahorra 95% de tokens en agentes de IA.
Save up to 95% of LLM Tokens. Reduce latency by 10x.
Why AeCode? • Quick Start • Syntax • Benchmarks • Examples
Current AI Coding Agents (Claude 3.5, GPT-4o, Gemini Pro) spend 90% of their output tokens writing:
import requests, BeautifulSoup boilerplate.<!DOCTYPE html>, Tailwind classes strings, and nested loop syntax.The result? Higher API bills, sluggish response times, context window exhaustion, and higher chances of hallucinated syntax.
AeCode compresses complex web workflows into high-density mathematical & functional primitives. An AI model writes 10 lines of AeCode; the engine compiles and executes it as 200+ lines of production Python + Tailwind CSS.
import csv, requests
from bs4 import BeautifulSoup
resp = requests.get("http://books.toscrape.com")
soup = BeautifulSoup(resp.text, 'html.parser')
books = []
for pod in soup.select(".product_pod"):
t = pod.select_one("h3 > a")["title"]
p = pod.select_one(".price_color").text
books.append({"title": t, "price": p})
html = """<!DOCTYPE html><html><head><script src="https://cdn.tailwindcss.com"></script></head><body class="bg-gray-900 text-white p-8"><div class="grid grid-cols-4 gap-6">"""
for b in books:
html += f"""<div class="bg-gray-800 p-4 rounded-xl border border-gray-700"><h3 class="font-bold">{b['title']}</h3><p class="text-amber-400 font-bold">{b['price']}</p></div>"""
html += "</div></body></html>"
with open("view.html", "w") as f: f.write(html)
import webbrowser; webbrowser.open("view.html")
DATA = SCRAPE("http://books.toscrape.com", ".product_pod", [title: "h3 > a" @ "title", price: ".price_color" @ "text"])
VIEW = GRID 4 > CARD(title, price) FROM DATA
RENDER VIEW
| Task | Traditional Python | AeCode | Token Savings |
|---|---|---|---|
| Basic Web Scraping | ~180 tokens | 48 tokens | -73% |
| Multithreaded Parallel FlatMap | ~280 tokens | 60 tokens | -78% |
| Auto-Pagination (Crawl) | ~320 tokens | 52 tokens | -84% |
| Tailwind Landing Page | ~500 tokens | 25 tokens | -95% |
| Live Scrape-to-UI Dashboard | ~600 tokens | 35 tokens | -94% |
pip install aecode
aecode doctor
aecode flow examples/dashboard.ae
Voilà! It automatically scrapes live data, builds an interactive Tailwind CSS UI, and opens it directly in your default browser.
doc = GET("http://books.toscrape.com")
items = doc > ".product_pod"
rows = items | λi. {title: (i > "h3 > a") @ "title", price: (i > ".price_color") @ "text"}
rows => "libros.csv"
aecode scrape examples/scraper.ae
PAGE /home
NAV [MiMarca, Links(Productos, Precios, Contacto)]
HERO "Bienvenido al futuro" center
GRID 3 > CARD(title, desc, price)
BTN "Empezar ahora"
FOOTER
aecode build examples/landing.ae --output index.html
DATA = SCRAPE("http://books.toscrape.com", ".product_pod", [title: "h3 > a" @ "title", price: ".price_color" @ "text"])
VIEW = GRID 4 > CARD(title, price) FROM DATA
RENDER VIEW
aecode flow examples/dashboard.ae
| Operator / Primitiva | Descripción | Ejemplo |
|---|---|---|
GET(url) | Petición HTTP + Parseo HTML | doc = GET("https://...") |
> | Selector CSS | items = doc > ".product_pod" |
@ | Extracción de atributo o texto | (el > "a") @ "href" o @ "text" |
| | Map funcional sobre colecciones | items | λi. { ... } |
|? | Filtro funcional booleano | items |? λi. num(i @ "text") > 50 |
|* | FlatMap concurrente multihilo | urls |* λu. (GET(u) > ".pod") |
CRAWL(url, fn, max) | Auto-paginación secuencial segura | CRAWL(url, λd. d > "li.next > a" @ "href", 5) |
SCRAPE(...) | Extracción masiva estructurada | SCRAPE(url, selector, [fields]) |
GRID n > CARD(...) | Cuadrícula responsiva Tailwind | GRID 4 > CARD(title, price) |
RENDER view | Compilación y apertura web | RENDER VIEW |
Programming languages designed in the 1990s were made for human keyboards. In 2026, code is generated by AI agents collaborating with humans.
AeCode treats code like mathematical equations: dense, declarative, composable, and crystal clear.
Distribuido bajo la Licencia MIT. Consulta LICENSE para más detalles.
Download counts and popularity will appear here as the collector receives them.
| Version | Published | Direct dependencies | Open version |
|---|---|---|---|
| 0.2.0 | 1 Oct 2026 | 4 |
This describes our collected data; it is not a security assessment.
Observed since 20 Oct, 20:09 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package:2208ee9bbacb2b7149ce682803c4b35963efae6d25182d9b1919b80d8f022f0f