Scweet Twitter/X Scraper

Scweet is a Twitter/X scraper for search results and profile timelines. Extract tweets into JSON, CSV, and XLSX with a simple input model.

Run Actor on Apify | Open-Source Scweet Library

Quick Navigation

• Pricing
• Quick Start
• Why Choose Scweet
• Inputs
• Output
• Responsible Usage
• Data and Privacy Note
• Support

💰 Pricing (Effective March 4, 2026)

You are billed for:

• Tweets collected
• A one-time run-start fee per run

Plan	Tweet Price	Run-start
Free (No discount)	$3.00 / 1,000 tweets	$0.006
Starter (Bronze)	$0.30 / 1,000 tweets	$0.0006
Scale (Silver)	$0.28 / 1,000 tweets	$0.0006
Business (Gold)	$0.25 / 1,000 tweets	$0.0006

Apify currently advertises monthly free platform credit (commonly $5/month, subject to change).

Why free pricing is higher:

• Free tier is for evaluation, not high-volume automation.
• Higher free pricing helps reduce abuse and repeated empty runs.
• It helps keep paid-tier pricing low for production users.

⚡ Quick Start

1. Open Scweet on Apify.
2. Paste one of the inputs below.
3. Run the Actor.
4. Export dataset results.

Input can be partial. Omitted fields use defaults.

🔎 Minimal Twitter Search Input

{
  "source_mode": "search",
  "search_query": "bitcoin lang:en from:elonmusk -filter:replies min_faves:100",
  "since": "2025-02-17",
  "until": "2026-02-19",
  "search_sort": "Latest",
  "max_items": 1000
}

👤 Minimal Twitter Profile Input

{
  "source_mode": "profiles",
  "profile_urls": [
    "https://x.com/elonmusk",
    "@apify"
  ],
  "max_items": 1000
}

🔀 Combined Search + Profiles Input

{
  "source_mode": "auto",
  "all_words": ["ai", "agent"],
  "since": "2025-02-17",
  "profile_urls": ["https://x.com/apify"],
  "search_sort": "Top",
  "max_items": 500
}

✅ Why Choose Scweet

• Actively maintained scraping logic for changing X/Twitter behavior.
• Reliability features: retries, account failover, task requeue, and deduplication.
• Flexible modes: search, profiles, or both in one run.
• Production-friendly export workflow in Apify datasets.

🧩 Inputs

Core fields

Field	Type	Description
source_mode	string	auto, search, or profiles (default: auto)
search_query	string	Optional raw advanced query string : Twitter advanced search operators
profile_urls	array[string]	Handles or profile URLs (@handle, x.com/<handle>, twitter.com/<handle>)
max_items	integer	Global run target (default 1000)
since, until	string	Date or UTC timestamp window
search_sort	string	Top or Latest (default: Latest)

Search builder fields (optional)

• Keywords: all_words, any_words, exact_phrases, exclude_words
• Hashtags/users: hashtags_any, hashtags_exclude, from_users, to_users, mentioning_users
• Filters: tweet_type, verified_only, blue_verified_only, has_images, has_videos, has_links, has_mentions, has_hashtags, min_likes, min_replies, min_retweets
• Location: place, geocode, near, within
• Advanced operator reference:

Important behavior

• Minimum requested run size is enforced: if max_items < 100, it is auto-adjusted to 100.
• max_items is global per run, not per profile.
• source_mode="search" ignores profile input.
• source_mode="profiles" ignores search input.
• If both since and until are missing, lookback defaults to:
  • Top: 4 years
  • Latest: 180 days
• Free plan guardrails (current): 1000 tweets/day, 10 runs/day, minimum 60s between runs.

📤 Output

Results are stored in the Apify dataset for the run.

• Dataset output is deduplicated by tweet ID.
• Export formats: JSON, CSV, XLSX.
• Output includes source labeling fields (source_root, source_value).

What each item contains

Field	Description
id	Tweet ID
text	Tweet text
handle	Author handle
tweet_url	Tweet URL
favorite_count, retweet_count, reply_count	Core engagement metrics
source_root	search or profile_url
source_value	Effective query or normalized profile URL
user	Nested author object
tweet	Nested tweet details object

Full example output (generated sample values, not real user data)

[
  {
    "id": "tweet-1234567890123456789",
    "sort_index": "1999999999999999999",
    "entry_type": "TimelineTimelineItem",
    "tweet_display_type": "Tweet",
    "collected_at_utc": "2026-02-08T05:08:42.531721+00:00",
    "source_root": "search",
    "source_value": "(sample OR query) (#tag1 OR #tag2) lang:en since:2025-01-01 until:2025-01-31",
    "user": {
      "id": "VXNlcjoxMjM0NTY3OA==",
      "rest_id": "12345678",
      "name": "Sample Account",
      "verified": false,
      "verified_type": "None",
      "is_blue_verified": true,
      "created_at": "Mon Jan 01 00:00:00 +0000 2020",
      "description": "Sample profile description.",
      "url": "https://t.co/example",
      "urls": [
        {
          "url": "https://t.co/example",
          "expanded_url": "https://example.com",
          "display_url": "example.com"
        }
      ],
      "favourites_count": 1200,
      "followers_count": 98000,
      "friends_count": 350,
      "listed_count": 45,
      "statuses_count": 15000,
      "location": "Sample City",
      "media_count": 420,
      "handle": "sample_handle",
      "profile_banner_url": "https://pbs.twimg.com/profile_banners/12345678/sample",
      "profile_image_url_https": "https://pbs.twimg.com/profile_images/sample_normal.jpg"
    },
    "tweet": {
      "rest_id": "1234567890123456789",
      "conversation_id": "1234567890123456789",
      "in_reply_to_status_id": null,
      "in_reply_to_user_id": null,
      "quoted_status_id": null,
      "source": "<a href=\"https://example.com\" rel=\"nofollow\">Example App</a>",
      "created_at": "Wed Jan 15 10:00:00 +0000 2025",
      "mentions": ["example_user"],
      "tweet_url": "https://x.com/sample_handle/status/1234567890123456789",
      "view_count": "150000",
      "text": "This is a sample tweet text for documentation.",
      "hashtags": ["tag1", "tag2"],
      "favorite_count": 1234,
      "quote_count": 56,
      "reply_count": 78,
      "retweet_count": 90,
      "bookmark_count": 12,
      "is_quote_status": false,
      "possibly_sensitive": false,
      "is_translatable": false,
      "edit_control": {
        "edit_tweet_ids": ["1234567890123456789"],
        "editable_until_msecs": "1762993800000",
        "is_edit_eligible": true,
        "edits_remaining": "5"
      },
      "entities": {
        "hashtags": ["tag1", "tag2"],
        "mentions": ["example_user"],
        "urls": [
          {
            "url": "https://t.co/example",
            "expanded_url": "https://example.com/page",
            "display_url": "example.com/page"
          }
        ],
        "symbols": [],
        "timestamps": []
      },
      "lang": "en",
      "media": [
        {
          "id_str": "5555555555555555555",
          "media_key": "3_5555555555555555555",
          "type": "photo",
          "media_url": "https://pbs.twimg.com/media/sample.jpg",
          "expanded_url": "https://x.com/sample_handle/status/1234567890123456789/photo/1",
          "display_url": "pic.x.com/sample",
          "width": 1200,
          "height": 800
        }
      ]
    }
  }
]

⚖️ Responsible Usage

Use this Actor lawfully and ethically, and comply with applicable platform terms and local regulations.

🔒 Data and Privacy Note

Run metadata (such as user ID, timestamps, input payload, and counters) may be stored for rate-limiting, support, and stability operations. This data is used internally and is not shared with third parties.

🤝 Support

For help with query tuning, limits, or workflow design, contact us on the Actor page or open an issue in the open-source repository.