Matt Van Horn
7c5763d048
Pass logger=None to Apify .call() to prevent the SDK from streaming raw actor run logs (status messages, crawler stats, warnings) that drown out the clean spinner UI in Claude Code. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
84 lines
2.2 KiB
Python
84 lines
2.2 KiB
Python
"""Shared Apify client utilities for last30days sources.
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Provides a common wrapper around the apify-client SDK so that
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TikTok, Facebook, Instagram (future) all share the same client
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initialization, error handling, and cost-control patterns.
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One APIFY_API_TOKEN covers all Apify-backed sources.
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"""
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import sys
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from typing import Any, Dict, List, Optional
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try:
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from apify_client import ApifyClient
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except ImportError:
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ApifyClient = None
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def is_apify_available() -> bool:
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"""Check if the apify-client library is installed."""
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return ApifyClient is not None
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def get_apify_client(token: str) -> "ApifyClient":
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"""Initialize Apify client with token.
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Args:
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token: Apify API token (from https://console.apify.com)
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Returns:
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Initialized ApifyClient instance
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Raises:
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ImportError: If apify-client is not installed
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"""
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if ApifyClient is None:
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raise ImportError(
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"apify-client is not installed. Run: pip install apify-client"
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)
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return ApifyClient(token=token)
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def run_actor_sync(
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client: "ApifyClient",
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actor_id: str,
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run_input: Dict[str, Any],
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timeout_secs: int = 300,
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max_items: Optional[int] = None,
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) -> List[Dict[str, Any]]:
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"""Run an Apify actor synchronously and return dataset items.
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Args:
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client: Initialized ApifyClient
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actor_id: Actor identifier, e.g. "clockworks/tiktok-scraper"
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run_input: Actor-specific input dict
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timeout_secs: Max wait time (default 5 min)
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max_items: Cap on returned items (cost control)
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Returns:
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List of result dicts from the actor's default dataset
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"""
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_log(f"Running actor {actor_id} (timeout={timeout_secs}s)")
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run = client.actor(actor_id).call(
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run_input=run_input,
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timeout_secs=timeout_secs,
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logger=None, # Suppress verbose actor log streaming to stderr
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)
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dataset_id = run["defaultDatasetId"]
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items = list(client.dataset(dataset_id).iterate_items())
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if max_items and len(items) > max_items:
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items = items[:max_items]
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_log(f"Actor {actor_id} returned {len(items)} items")
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return items
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def _log(msg: str):
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"""Log to stderr."""
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sys.stderr.write(f"[Apify] {msg}\n")
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sys.stderr.flush()
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