Pricing

from $1.99 / 1,000 results

Substack Newsletter Scraper

Substack Newsletter scraper extracts publicly available newsletter posts, titles, authors, publication dates, subscriber-facing content, and metadata 📰📊 Perfect for content research, trend analysis, competitive intelligence, and newsletter monitoring.

Pricing

from $1.99 / 1,000 results

Rating

0.0

(0)

Developer

Scrapers Hub

Actor stats

Bookmarked

Total users

Monthly active users

2 days ago

Last modified

Input

Field	Type	Default	Description
`newsletterUrls`	array	–	List of newsletter URLs, e.g. `[{ "url": "https://www.lennysnewsletter.com" }]`. Custom domains and `*.substack.com` both work.
`postScrapingMode`	string	`information_and_content`	`information_only` (metadata only) or `information_and_content` (also fetch full post text).
`maxPostsPerNewsletter`	integer	`12`	Max posts scraped per newsletter.
`delayBetweenRequests`	integer	`3000`	Delay between HTTP requests, in milliseconds.
`maxRetries`	integer	`2`	Retries per request before giving up (falls back to curl_cffi).

{
  "newsletterUrls": [
    { "url": "https://www.lennysnewsletter.com" },
    { "url": "https://andrewsullivan.substack.com" }
  ],
  "postScrapingMode": "information_and_content",
  "maxPostsPerNewsletter": 12,
  "delayBetweenRequests": 3000,
  "maxRetries": 2
}

Output

One dataset item per newsletter: author fields (author_*), publication fields (publication_*), leaderboard ranking, all_publications, and a posts array where each post has url, title, subtitle, date, author, likes, comments_count, content_preview, content, and word_count.

How it works

Fetch the newsletter homepage and extract the embedded window._preloads JSON (regex + parsel) → publication object.
Fetch the author's public profile (substack.com/api/v1/user/{handle}/public_profile) → follower count, socials, leaderboard, all publications.
List posts via /api/v1/archive, and (in content mode) fetch each post's body_html via /api/v1/posts/{slug}, then strip it to plain text.

Run locally

pip install -r requirements.txt
# via the Apify CLI (recommended):
apify run
# or drive the scraper directly without the Apify SDK:
python _local_test.py

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