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"""
Massive Web Render API client for seo-agi.
Massive (render.joinmassive.com) is used for COMPETITOR CONTENT PARSING --
fetching a URL and getting back clean rendered markdown that includes
JS-loaded content, which DataForSEO's content_parsing/live endpoint misses.
Scope intentionally narrow:
- Massive /browser endpoint: URL -> markdown (used here)
- Massive /search endpoint: NOT used. As of v1.9.0 it returns only
'also-searched' query suggestions, not organic SERP results. SERP
data continues to come from DataForSEO.
The client outputs the same shape as DataForSEOClient._extract_content
(`title`, `word_count`, `headings`, `plain_text_size`) so it is a
drop-in replacement for the content_parse() step in research.py.
"""
import json
import re
import urllib.parse
import urllib.request
import urllib.error
from typing import Optional
class MassiveClient:
"""Client for Massive Web Render API (render.joinmassive.com)."""
BASE_URL = "https://render.joinmassive.com"
def __init__(self, api_token: str, default_country: str = "US"):
self.api_token = api_token
self.default_country = default_country
def _headers(self) -> dict:
return {"Authorization": f"Bearer {self.api_token}"}
def _get(self, path: str, params: dict, timeout: int = 60) -> str:
"""Make a GET request and return the raw response body as text."""
qs = urllib.parse.urlencode(params)
url = f"{self.BASE_URL}{path}?{qs}"
req = urllib.request.Request(url, headers=self._headers())
try:
with urllib.request.urlopen(req, timeout=timeout) as resp:
return resp.read().decode("utf-8", errors="ignore")
except urllib.error.HTTPError as e:
body = e.read().decode("utf-8", errors="ignore") if e.fp else ""
raise RuntimeError(
f"Massive API error {e.code}: {body[:300]}"
) from e
except urllib.error.URLError as e:
raise RuntimeError(f"Massive connection error: {e.reason}") from e
def content_parse(
self, url: str, country: Optional[str] = None
) -> Optional[dict]:
"""Fetch a URL via Massive's renderer and extract content structure.
Returns the same shape as DataForSEOClient.content_parse():
{ "title": str, "word_count": int, "headings": [str],
"plain_text_size": int }
where each heading is formatted as "H{level}: {text}".
Returns None if the fetch returns empty content.
"""
try:
markdown = self._get(
"/browser",
{
"url": url,
"format": "markdown",
"country": country or self.default_country,
},
)
except RuntimeError:
return None
if not markdown or not markdown.strip():
return None
return self._parse_markdown(markdown)
@staticmethod
def _parse_markdown(md: str) -> dict:
"""Parse rendered markdown into the seo-agi content shape.
Headings: lines starting with `#`, `##`, ..., `######` -> H1..H6.
Title: first H1 found, otherwise empty.
Word count: rough split of body text after stripping markdown
syntax (consistent with how dataforseo.py counts).
Links: markdown `[text](url)` extraction for spoke detection.
"""
headings: list[str] = []
title = ""
for line in md.splitlines():
m = re.match(r"^(#{1,6})\s+(.+?)\s*$", line)
if not m:
continue
level = len(m.group(1))
text = m.group(2).strip()
if not text:
continue
if level == 1 and not title:
title = text
headings.append(f"H{level}: {text}")
# Word count: strip markdown punctuation, split on whitespace.
text = re.sub(r"[`*_#>\[\]()!|-]+", " ", md)
word_count = len([w for w in text.split() if w.strip()])
# Links (v1.9.1): standard markdown [text](url). Skip image links
# ![alt](src) -- those don't carry semantic anchor signal.
links: list[dict] = []
link_re = re.compile(r"(?<!!)\[([^\]]+)\]\(([^)\s]+)(?:\s+\"[^\"]*\")?\)")
for m in link_re.finditer(md):
anchor = m.group(1).strip()
url = m.group(2).strip()
if not anchor or not url:
continue
# Skip pure-hash/javascript/empty anchors -- no spoke value
if url.startswith(("#", "javascript:", "mailto:", "tel:")):
continue
links.append({"text": anchor, "url": url})
return {
"title": title,
"word_count": word_count,
"headings": headings,
"plain_text_size": len(md),
"links": links,
}