feat: v3.0.0 - intelligent search, GitHub person/project mode, ELI5, 13+ sources
v3 rewrites the search engine from the ground up: - Intelligent pre-research: resolves X handles, GitHub repos, subreddits, TikTok hashtags, and YouTube channels before searching - GitHub person-mode: PR velocity, top repos by stars, release notes - GitHub project-mode: live star counts, README, releases, top issues - ELI5 mode: plain language synthesis, no jargon - 13+ sources: Reddit, X, YouTube, TikTok, Instagram, HN, Polymarket, GitHub, Threads, Pinterest, Perplexity, Bluesky, Web - Free Reddit comments via public JSON (no API key needed) - Fun judge v2: humor scoring baked into narrative - Cookie consent before browser scanning - 10,000 free ScrapeCreators calls - 1,012 tests Thank you to the community contributors whose issues and PRs shaped v3: @uppinote20 (#143), @zerone0x (#134, #136), @thinkun (#116), @thomasmktong (#124), @fanispoulinakisai-boop (#100), @pejmanjohn (#78), @zl190 (#115), @hnshah (#84, #85, #86) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Matt Van Horn
+265
-65
@@ -9,7 +9,6 @@ API docs: https://scrapecreators.com/docs
|
||||
|
||||
import re
|
||||
import sys
|
||||
from datetime import datetime, timezone
|
||||
from typing import Any, Dict, List, Optional, Set
|
||||
|
||||
try:
|
||||
@@ -17,7 +16,7 @@ try:
|
||||
except ImportError:
|
||||
_requests = None
|
||||
|
||||
from . import http
|
||||
from . import dates, http, log
|
||||
|
||||
SCRAPECREATORS_BASE = "https://api.scrapecreators.com/v1/tiktok"
|
||||
|
||||
@@ -49,11 +48,65 @@ def _extract_core_subject(topic: str) -> str:
|
||||
return extract_core_subject(topic, noise=_TIKTOK_NOISE)
|
||||
|
||||
|
||||
def _infer_query_intent(topic: str) -> str:
|
||||
"""Tiny local intent classifier for TikTok query expansion."""
|
||||
text = topic.lower().strip()
|
||||
if re.search(r"\b(vs|versus|compare|difference between)\b", text):
|
||||
return "comparison"
|
||||
if re.search(r"\b(how to|tutorial|guide|setup|step by step|deploy|install)\b", text):
|
||||
return "how_to"
|
||||
if re.search(r"\b(thoughts on|worth it|should i|opinion|review)\b", text):
|
||||
return "opinion"
|
||||
if re.search(r"\b(pricing|feature|features|best .* for)\b", text):
|
||||
return "product"
|
||||
return "breaking_news"
|
||||
|
||||
|
||||
def expand_tiktok_queries(topic: str, depth: str) -> List[str]:
|
||||
"""Generate multiple TikTok search queries from a topic.
|
||||
|
||||
Mirrors reddit.py's expand_reddit_queries() pattern:
|
||||
1. Extract core subject (strip noise words)
|
||||
2. Include original topic if different from core
|
||||
3. Add intent-specific OR-joined content-type variants
|
||||
4. Cap by depth: 1 for quick, 2 for default, 3 for deep
|
||||
|
||||
Returns 1-3 query strings depending on depth.
|
||||
"""
|
||||
core = _extract_core_subject(topic)
|
||||
queries = [core]
|
||||
|
||||
# Include cleaned original topic as variant if different from core
|
||||
original_clean = topic.strip().rstrip('?!.')
|
||||
if core.lower() != original_clean.lower() and len(original_clean.split()) <= 8:
|
||||
queries.append(original_clean)
|
||||
|
||||
qtype = _infer_query_intent(topic)
|
||||
|
||||
# Intent-specific TikTok content-type variants
|
||||
if qtype in ("breaking_news", "opinion"):
|
||||
queries.append(f"{core} edit OR reaction OR trend")
|
||||
elif qtype == "product":
|
||||
queries.append(f"{core} review OR haul OR unboxing")
|
||||
elif qtype == "comparison":
|
||||
queries.append(f"{core} vs OR compared OR which is better")
|
||||
elif qtype == "how_to":
|
||||
queries.append(f"{core} tutorial OR hack OR tip")
|
||||
else:
|
||||
queries.append(f"{core} edit OR reaction OR trend")
|
||||
|
||||
# Deep depth: add viral content variant
|
||||
if depth == "deep":
|
||||
queries.append(f"{core} viral OR fyp OR trending")
|
||||
|
||||
# Cap by depth budget
|
||||
caps = {"quick": 1, "default": 2, "deep": 3}
|
||||
cap = caps.get(depth, 2)
|
||||
return queries[:cap]
|
||||
|
||||
|
||||
def _log(msg: str):
|
||||
"""Log to stderr (only in interactive terminals; spinner handles non-TTY)."""
|
||||
if sys.stderr.isatty():
|
||||
sys.stderr.write(f"[TikTok] {msg}\n")
|
||||
sys.stderr.flush()
|
||||
log.source_log("TikTok", msg)
|
||||
|
||||
|
||||
def _sc_headers(token: str) -> Dict[str, str]:
|
||||
@@ -65,18 +118,13 @@ def _sc_headers(token: str) -> Dict[str, str]:
|
||||
|
||||
|
||||
def _parse_date(item: Dict[str, Any]) -> Optional[str]:
|
||||
"""Parse date from ScrapeCreators TikTok item to YYYY-MM-DD.
|
||||
|
||||
Handles create_time (unix timestamp).
|
||||
"""
|
||||
"""Parse date from ScrapeCreators TikTok item to YYYY-MM-DD."""
|
||||
ts = item.get("create_time")
|
||||
if ts:
|
||||
try:
|
||||
dt = datetime.fromtimestamp(int(ts), tz=timezone.utc)
|
||||
return dt.strftime("%Y-%m-%d")
|
||||
except (ValueError, TypeError, OSError):
|
||||
return dates.timestamp_to_date(int(ts))
|
||||
except (ValueError, TypeError):
|
||||
pass
|
||||
|
||||
return None
|
||||
|
||||
|
||||
@@ -100,6 +148,157 @@ def _clean_webvtt(text: str) -> str:
|
||||
return ' '.join(cleaned)
|
||||
|
||||
|
||||
def _parse_items(raw_items: List[Dict[str, Any]], core_topic: str) -> List[Dict[str, Any]]:
|
||||
"""Parse raw TikTok items into normalized dicts."""
|
||||
items = []
|
||||
for raw in raw_items:
|
||||
video_id = str(raw.get("aweme_id", ""))
|
||||
text = raw.get("desc", "")
|
||||
|
||||
stats = raw.get("statistics") if isinstance(raw.get("statistics"), dict) else {}
|
||||
play_count = stats.get("play_count") if stats.get("play_count") is not None else 0
|
||||
digg_count = stats.get("digg_count") if stats.get("digg_count") is not None else 0
|
||||
comment_count = stats.get("comment_count") if stats.get("comment_count") is not None else 0
|
||||
share_count = stats.get("share_count") if stats.get("share_count") is not None else 0
|
||||
|
||||
author_raw = raw.get("author")
|
||||
if isinstance(author_raw, dict):
|
||||
author_name = author_raw.get("unique_id", "")
|
||||
elif isinstance(author_raw, str):
|
||||
author_name = author_raw
|
||||
else:
|
||||
author_name = ""
|
||||
|
||||
share_url = raw.get("share_url", "")
|
||||
text_extra = raw.get("text_extra") or []
|
||||
hashtag_names = [t.get("hashtag_name", "") for t in text_extra
|
||||
if isinstance(t, dict) and t.get("hashtag_name")]
|
||||
|
||||
video_raw = raw.get("video")
|
||||
duration = video_raw.get("duration") if isinstance(video_raw, dict) else None
|
||||
|
||||
date_str = _parse_date(raw)
|
||||
|
||||
# Compute relevance with hashtag boost
|
||||
relevance = _compute_relevance(core_topic, text, hashtag_names)
|
||||
|
||||
# Build URL: prefer share_url, fallback to constructed URL
|
||||
url = share_url.split("?")[0] if share_url else ""
|
||||
if not url and author_name and video_id:
|
||||
url = f"https://www.tiktok.com/@{author_name}/video/{video_id}"
|
||||
|
||||
items.append({
|
||||
"video_id": video_id,
|
||||
"text": text,
|
||||
"url": url,
|
||||
"author_name": author_name,
|
||||
"date": date_str,
|
||||
"engagement": {
|
||||
"views": play_count,
|
||||
"likes": digg_count,
|
||||
"comments": comment_count,
|
||||
"shares": share_count,
|
||||
},
|
||||
"hashtags": hashtag_names,
|
||||
"duration": duration,
|
||||
"relevance": relevance,
|
||||
"why_relevant": f"TikTok: {text[:60]}" if text else f"TikTok: {core_topic}",
|
||||
"caption_snippet": "", # populated by fetch_captions
|
||||
})
|
||||
return items
|
||||
|
||||
|
||||
def _hashtag_search(
|
||||
hashtag: str,
|
||||
token: str,
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""Search TikTok by hashtag via ScrapeCreators.
|
||||
|
||||
Args:
|
||||
hashtag: Hashtag name (without #)
|
||||
token: ScrapeCreators API key
|
||||
|
||||
Returns:
|
||||
List of raw TikTok item dicts (aweme_info format).
|
||||
"""
|
||||
_log(f"Hashtag search: #{hashtag}")
|
||||
if not _requests:
|
||||
try:
|
||||
from urllib.parse import urlencode
|
||||
params = urlencode({"hashtag": hashtag})
|
||||
url = f"{SCRAPECREATORS_BASE}/search/hashtag?{params}"
|
||||
headers = _sc_headers(token)
|
||||
headers["User-Agent"] = http.USER_AGENT
|
||||
data = http.get(url, headers=headers, timeout=30, retries=2)
|
||||
except Exception as e:
|
||||
_log(f"Hashtag search error (urllib) for #{hashtag}: {e}")
|
||||
return []
|
||||
else:
|
||||
try:
|
||||
resp = _requests.get(
|
||||
f"{SCRAPECREATORS_BASE}/search/hashtag",
|
||||
params={"hashtag": hashtag},
|
||||
headers=_sc_headers(token),
|
||||
timeout=30,
|
||||
)
|
||||
resp.raise_for_status()
|
||||
data = resp.json()
|
||||
except Exception as e:
|
||||
_log(f"Hashtag search error for #{hashtag}: {e}")
|
||||
return []
|
||||
|
||||
raw_items = data.get("aweme_list") or data.get("data") or []
|
||||
_log(f" -> {len(raw_items)} results for #{hashtag}")
|
||||
return raw_items
|
||||
|
||||
|
||||
def _profile_videos(
|
||||
handle: str,
|
||||
token: str,
|
||||
count: int = 10,
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""Fetch a TikTok creator's recent videos via ScrapeCreators.
|
||||
|
||||
Args:
|
||||
handle: TikTok username (without @)
|
||||
token: ScrapeCreators API key
|
||||
count: Max videos to return
|
||||
|
||||
Returns:
|
||||
List of raw TikTok item dicts (aweme_info format).
|
||||
"""
|
||||
_log(f"Profile videos: @{handle}")
|
||||
profile_url = "https://api.scrapecreators.com/v3/tiktok/profile/videos"
|
||||
if not _requests:
|
||||
try:
|
||||
from urllib.parse import urlencode
|
||||
params = urlencode({"handle": handle, "sort_by": "latest"})
|
||||
url = f"{profile_url}?{params}"
|
||||
headers = _sc_headers(token)
|
||||
headers["User-Agent"] = http.USER_AGENT
|
||||
data = http.get(url, headers=headers, timeout=30, retries=2)
|
||||
except Exception as e:
|
||||
_log(f"Profile videos error (urllib) for @{handle}: {e}")
|
||||
return []
|
||||
else:
|
||||
try:
|
||||
resp = _requests.get(
|
||||
profile_url,
|
||||
params={"handle": handle, "sort_by": "latest"},
|
||||
headers=_sc_headers(token),
|
||||
timeout=30,
|
||||
)
|
||||
resp.raise_for_status()
|
||||
data = resp.json()
|
||||
except Exception as e:
|
||||
_log(f"Profile videos error for @{handle}: {e}")
|
||||
return []
|
||||
|
||||
raw_items = data.get("aweme_list") or data.get("data") or []
|
||||
_log(f" -> {len(raw_items)} videos from @{handle}")
|
||||
return raw_items[:count]
|
||||
|
||||
|
||||
def search_tiktok(
|
||||
topic: str,
|
||||
from_date: str,
|
||||
@@ -165,51 +364,7 @@ def search_tiktok(
|
||||
raw_items = raw_items[:config["results_per_page"]]
|
||||
|
||||
# Parse items
|
||||
items = []
|
||||
for raw in raw_items:
|
||||
video_id = str(raw.get("aweme_id", ""))
|
||||
text = raw.get("desc", "")
|
||||
stats = raw.get("statistics") or {}
|
||||
play_count = stats.get("play_count") or 0
|
||||
digg_count = stats.get("digg_count") or 0
|
||||
comment_count = stats.get("comment_count") or 0
|
||||
share_count = stats.get("share_count") or 0
|
||||
author = raw.get("author") or {}
|
||||
author_name = author.get("unique_id", "")
|
||||
share_url = raw.get("share_url", "")
|
||||
text_extra = raw.get("text_extra") or []
|
||||
hashtag_names = [t.get("hashtag_name", "") for t in text_extra
|
||||
if isinstance(t, dict) and t.get("hashtag_name")]
|
||||
duration = (raw.get("video") or {}).get("duration")
|
||||
|
||||
date_str = _parse_date(raw)
|
||||
|
||||
# Compute relevance with hashtag boost
|
||||
relevance = _compute_relevance(core_topic, text, hashtag_names)
|
||||
|
||||
# Build URL: prefer share_url, fallback to constructed URL
|
||||
url = share_url.split("?")[0] if share_url else ""
|
||||
if not url and author_name and video_id:
|
||||
url = f"https://www.tiktok.com/@{author_name}/video/{video_id}"
|
||||
|
||||
items.append({
|
||||
"video_id": video_id,
|
||||
"text": text,
|
||||
"url": url,
|
||||
"author_name": author_name,
|
||||
"date": date_str,
|
||||
"engagement": {
|
||||
"views": play_count,
|
||||
"likes": digg_count,
|
||||
"comments": comment_count,
|
||||
"shares": share_count,
|
||||
},
|
||||
"hashtags": hashtag_names,
|
||||
"duration": duration,
|
||||
"relevance": relevance,
|
||||
"why_relevant": f"TikTok: {text[:60]}" if text else f"TikTok: {core_topic}",
|
||||
"caption_snippet": "", # populated by fetch_captions
|
||||
})
|
||||
items = _parse_items(raw_items, core_topic)
|
||||
|
||||
# Hard date filter
|
||||
in_range = [i for i in items if i["date"] and from_date <= i["date"] <= to_date]
|
||||
@@ -307,25 +462,70 @@ def search_and_enrich(
|
||||
to_date: str,
|
||||
depth: str = "default",
|
||||
token: str = None,
|
||||
hashtags: List[str] | None = None,
|
||||
creators: List[str] | None = None,
|
||||
) -> Dict[str, Any]:
|
||||
"""Full TikTok search: find videos, then fetch captions for top results.
|
||||
|
||||
Uses expand_tiktok_queries() to generate multiple search queries,
|
||||
runs ScrapeCreators for each, and merges/deduplicates results by video ID.
|
||||
|
||||
Args:
|
||||
topic: Search topic
|
||||
topic: Search topic (raw topic, not planner's narrowed query)
|
||||
from_date: Start date (YYYY-MM-DD)
|
||||
to_date: End date (YYYY-MM-DD)
|
||||
depth: 'quick', 'default', or 'deep'
|
||||
token: ScrapeCreators API key
|
||||
hashtags: Optional list of TikTok hashtags to search (without #)
|
||||
creators: Optional list of TikTok creator handles to fetch videos from
|
||||
|
||||
Returns:
|
||||
Dict with 'items' list. Each item has a 'caption_snippet' field.
|
||||
"""
|
||||
# Step 1: Search
|
||||
search_result = search_tiktok(topic, from_date, to_date, depth, token)
|
||||
items = search_result.get("items", [])
|
||||
core_topic = _extract_core_subject(topic)
|
||||
seen_ids: Set[str] = set()
|
||||
items: List[Dict[str, Any]] = []
|
||||
last_error = None
|
||||
|
||||
# Step 0a: Hashtag search (high-signal, runs first)
|
||||
if hashtags and token:
|
||||
for hashtag in hashtags:
|
||||
raw_items = _hashtag_search(hashtag, token)
|
||||
parsed = _parse_items(raw_items, core_topic)
|
||||
for item in parsed:
|
||||
vid = item.get("video_id", "")
|
||||
if vid and vid not in seen_ids:
|
||||
seen_ids.add(vid)
|
||||
items.append(item)
|
||||
|
||||
# Step 0b: Creator profile videos (high-signal)
|
||||
if creators and token:
|
||||
for creator in creators:
|
||||
raw_items = _profile_videos(creator, token)
|
||||
parsed = _parse_items(raw_items, core_topic)
|
||||
for item in parsed:
|
||||
vid = item.get("video_id", "")
|
||||
if vid and vid not in seen_ids:
|
||||
seen_ids.add(vid)
|
||||
items.append(item)
|
||||
|
||||
# Step 1: Multi-query keyword search — run ScrapeCreators for each expanded query
|
||||
queries = expand_tiktok_queries(topic, depth)
|
||||
for q in queries:
|
||||
search_result = search_tiktok(q, from_date, to_date, depth, token)
|
||||
if search_result.get("error"):
|
||||
last_error = search_result["error"]
|
||||
for item in search_result.get("items", []):
|
||||
vid = item.get("video_id", "")
|
||||
if vid and vid not in seen_ids:
|
||||
seen_ids.add(vid)
|
||||
items.append(item)
|
||||
|
||||
# Sort merged results by views descending
|
||||
items.sort(key=lambda x: x.get("engagement", {}).get("views", 0), reverse=True)
|
||||
|
||||
if not items:
|
||||
return search_result
|
||||
return {"items": [], "error": last_error}
|
||||
|
||||
# Step 2: Fetch captions for top N
|
||||
captions = fetch_captions(items, token, depth)
|
||||
@@ -337,7 +537,7 @@ def search_and_enrich(
|
||||
if caption:
|
||||
item["caption_snippet"] = caption
|
||||
|
||||
return {"items": items, "error": search_result.get("error")}
|
||||
return {"items": items, "error": last_error}
|
||||
|
||||
|
||||
def parse_tiktok_response(response: Dict[str, Any]) -> List[Dict[str, Any]]:
|
||||
|
||||
Reference in New Issue
Block a user