Dataspryva

Use X Article Announcement Post Metadata Collector with Python

Turn an X (Twitter) Article's announcement post or article link into structured metadata: title, preview text, cover image, publish date, and the announcement post with its author.

1. Choose the data you need

Review the published README for supported collection modes, examples, and limits. The recipe below uses the current published input definition.

2. Prepare a source-based input

This JSON contains published prefills and required-field defaults. Review every value for your task before running it; it is not a promise of successful collection.

{
  "includeAnnouncementPost": true,
  "includeArticleBody": true,
  "includeAuthorProfile": true,
  "includeCoverImage": true,
  "includePreviewText": true,
  "maxItems": 3,
  "tweetUrls": [
    "https://x.com/vxunderground/status/1979885711579865307"
  ]
}

Download input.example.json and save your reviewed copy as input.json.

FieldTypeRequiredDescription
tweetUrlsarrayrequiredPaste the post that announces the article (the post whose card opens the article), or the article link itself. For example https://x.com/vxunderground/status/1979885711579865307.
includeArticleBodybooleanoptionalInclude the complete article text: bodyText, bodyMarkdown, the rich content blocks, inline media and links.
includeAnnouncementPostbooleanoptionalAttach the full announcement post (text, author, metrics, media) to every article row.
includeAuthorProfilebooleanoptionalEnrich the author with their public profile (follower count, bio, verification, join date) so engagementRate can be computed.
includeCoverImagebooleanoptionalInclude the article's cover image link.
includePreviewTextbooleanoptionalInclude the short preview text X shows for the article.
maxItemsintegeroptionalStop after this many article rows. Status rows are not counted.

3. Start an Actor run

Set APIFY_TOKEN in your environment. Python 3.10 or newer is sufficient; this recipe uses no third-party packages.

Execution may incur charges. Review current pricing on Apify. The request asks for a 120-second timeout and a charge limit; these settings are subject to Apify’s pricing and do not guarantee an all-inclusive spending cap.

import json
import os
import urllib.request

# Save the schema-derived example as input.json; review and edit it first.
with open("input.json", encoding="utf-8") as stream:
    actor_input = json.load(stream)

token = os.environ["APIFY_TOKEN"]
request = urllib.request.Request(
    "https://api.apify.com/v2/acts/o7cusCXLyJuONdRYF/runs?timeout=120&maxTotalChargeUsd=0.50",
    data=json.dumps(actor_input).encode("utf-8"),
    headers={"Authorization": "Bearer " + token, "Content-Type": "application/json"},
    method="POST",
)
# This starts a potentially billable run. Do not automatically retry this POST.
with urllib.request.urlopen(request, timeout=40) as response:
    run = json.load(response)["data"]
print("Run ID:", run["id"])
print("Status:", run["status"])
# Inspect and download results in Apify Console once the run succeeds.

4. Inspect the actual results

Open the run in Apify Console and wait for a successful completion. Use the published output schema to locate results and the dataset schema to understand declared views. Missing or optional record fields must not be treated as guaranteed values.

Questions before you run

Which inputs are required?

The published required fields are tweetUrls

What does this guide verify?

The fields, prefills, and schema links are rendered from the published build. This is a usage recipe, not a paid live extraction test. Source availability and collection results can vary.

What if the run request times out?

Check Apify Console before retrying. The first request may already have created a run. Do not automatically repeat a run-creation POST.

Generated from source build KudCUoXaZ0RG342mm and its README and schemas. Source changes regenerate this guide; no third-party editorial claims are inferred.