Pricing

Pay per event

Go to Apify Store

Snapchat Ads Library Scraper

Try for free

Download and filter public Snapchat political ads archive records from Snap's transparency ZIP files.

Pricing

Pay per event

Rating

0.0

(0)

Developer

Stas Persiianenko

Actor stats

Bookmarked

Total users

Monthly active users

5 days ago

Last modified

What does Snapchat Ads Library Scraper do?

Snapchat Ads Library Scraper automates the public Snap political ads archive workflow.

It can:

📦 Download selected yearly Snap political ads ZIP archives
🧾 Parse the PoliticalAds.csv archive files
💰 Extract spend, currency, and impression counts
🧑‍💼 Extract organization, paying advertiser, committee, and disclosure fields
🗓️ Normalize start and end dates
🎯 Preserve targeting fields such as country, regions, interests, OS, age, gender, language, postal codes, and metros
🎬 Return creative URLs and media type hints
🔎 Filter by year, advertiser, country, date range, and free-text search terms
🧰 Include raw archive columns when you need audit-grade exports

Who is it for?

This scraper is built for teams that monitor paid political communication on social platforms.

Typical users include:

🏛️ Political compliance teams tracking paid Snapchat election ads
📊 Ad-intelligence analysts comparing spend and impressions across advertisers
📰 Journalists and researchers investigating public political advertising archives
🧑‍⚖️ Public affairs and legal teams documenting disclosures
🏢 Agencies monitoring a candidate, issue group, nonprofit, or advertiser portfolio
🧪 Data teams that need structured CSV/JSON exports for dashboards

Why use this actor?

Snap publishes political ad transparency data as yearly downloadable archives. That is useful, but manual ZIP downloads are slow, repetitive, and hard to integrate.

This actor turns the archive into an Apify dataset with consistent field names and filters.

Use it when you need:

repeatable scheduled monitoring,
one API call instead of a manual download,
structured JSON, CSV, Excel, or API output,
consistent field names across archive years,
a small filtered extract instead of the whole archive,
or raw fields for compliance review.

What data can you extract?

Field	Description
`adId`	Snap archive ad identifier
`archiveYear`	Year inferred from the downloaded archive URL
`creativeUrl`	Snap-hosted creative asset URL when present
`mediaType`	Media type inferred from the creative URL
`currencyCode`	Spend currency code
`spend`	Numeric spend value
`impressions`	Numeric impression count
`startDate`	Normalized ad start timestamp
`endDate`	Normalized ad end timestamp when present
`organizationName`	Organization from the Snap archive
`payingAdvertiserName`	Paying advertiser name
`committeeName`	Committee name
`disclosureNameOfCommittee`	Disclosure committee name
`countryCode`	Country/country-code field from the archive
`regionsIncluded`	Included region targeting
`regionsExcluded`	Excluded region targeting
`interests`	Interest targeting
`language`	Language targeting
`osType`	OS targeting
`ageBracket`	Age targeting
`gender`	Gender targeting
`creativeProperties`	Creative metadata field from the archive
`rawFields`	Optional original archive columns

How much does it cost to scrape Snapchat political ads?

The actor uses pay-per-event pricing.

Start event: a small one-time fee per run.
Item event: a tiered fee per ad record saved to the dataset.

The exact platform pricing is visible on the Apify Store page. Use maxItems and filters to keep test runs small.

Input options

`years`

Archive years to download. Snap archives are available as yearly ZIP files. The default input uses the latest public archive year.

Example:

{
  "years": ["2026"],
  "maxItems": 100
}

`archiveUrls`

Optional direct ZIP URLs. Use this only when Snap publishes a new archive URL before the schema is updated, or when you need to test a mirrored archive.

`maxItems`

Maximum matching ad records to save.

For first tests, keep this at 100 or less. For production monitoring, raise it based on the archive size and your export needs.

`advertiserNames`

Case-insensitive advertiser filters matched against organization, paying advertiser, committee, and disclosure names.

`countryCodes`

Filters the archive CountryCode field. Snap sometimes stores country names and sometimes code-like values, so use the exact form you see in your target archive when possible.

`searchTerms`

Free-text filters matched across advertiser, creative URL, targeting, language, OS, age, gender, regions, and creative metadata.

`startDate` and `endDate`

Date range filters for ads active in a window.

`includeRawFields`

Set to true to include the original Snap archive column names and values in each output row.

Example input: latest archive

{
  "years": ["2026"],
  "maxItems": 100,
  "includeRawFields": false
}

Example input: advertiser monitoring

{
  "years": ["2026"],
  "advertiserNames": ["Human Appeal"],
  "countryCodes": ["united arab emirates"],
  "maxItems": 50
}

Example input: multi-year targeting audit

{
  "years": ["2025", "2026"],
  "searchTerms": ["election"],
  "startDate": "2025-01-01",
  "maxItems": 250,
  "includeRawFields": true
}

Output example

{
  "adId": "f917ba828f9b6dcbd5b6dfff8e1210d04812f9fb40d916df84ddfaa7866f85ca",
  "archiveYear": 2026,
  "creativeUrl": "https://www.snap.com/political-ads/asset/...",
  "mediaType": "mp4",
  "currencyCode": "GBP",
  "spend": 10,
  "impressions": 2144,
  "startDate": "2026-05-07T19:14:44.000Z",
  "organizationName": "Human Appeal Arabic",
  "payingAdvertiserName": "HUMAN APPEAL",
  "countryCode": "united arab emirates",
  "language": "ar",
  "osType": "IOS"
}

How to run

Choose one or more archive years.
Add optional filters for advertiser, country, dates, or search terms.
Set maxItems.
Run the actor.
Export the dataset as JSON, CSV, Excel, XML, RSS, or HTML.

Tips for best results

Start with one year and maxItems: 100.
Add filters only after confirming the archive contains the fields you expect.
Use includeRawFields: true for compliance audits or when Snap changes columns.
Use scheduled runs for repeat monitoring.
Use multiple small targeted runs for advertiser watchlists.

Integrations

You can connect the dataset to:

Google Sheets for analyst review,
BigQuery or Snowflake for long-term ad intelligence,
Slack or email alerts for new advertiser matches,
compliance dashboards,
newsroom research notebooks,
or CRM/enrichment pipelines.

A common workflow is to schedule one run per archive year, filter by advertiser watchlist, and send new rows to a review queue.

API usage: Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('automation-lab/snapchat-ads-library-scraper').call({
  years: ['2026'],
  maxItems: 100,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.slice(0, 3));

API usage: Python

from apify_client import ApifyClient

client = ApifyClient('YOUR_APIFY_TOKEN')
run = client.actor('automation-lab/snapchat-ads-library-scraper').call(run_input={
    'years': ['2026'],
    'maxItems': 100,
})
items = client.dataset(run['defaultDatasetId']).list_items().items
print(items[:3])

API usage: cURL

curl -X POST 'https://api.apify.com/v2/acts/automation-lab~snapchat-ads-library-scraper/runs?token=YOUR_APIFY_TOKEN' \
  -H 'Content-Type: application/json' \
  -d '{"years":["2026"],"maxItems":100}'

MCP usage

Use the Apify MCP server with this actor when you want Claude Desktop or Claude Code to run archive checks from natural language.

MCP URL:

https://mcp.apify.com/?tools=automation-lab/snapchat-ads-library-scraper

Claude Code setup:

$claude mcp add apify-snapchat-ads --transport http "https://mcp.apify.com/?tools=automation-lab/snapchat-ads-library-scraper"

Claude Desktop JSON config:

{
  "mcpServers": {
    "apify-snapchat-ads": {
      "url": "https://mcp.apify.com/?tools=automation-lab/snapchat-ads-library-scraper"
    }
  }
}

Example prompts:

"Run the Snapchat Ads Library Scraper for 2026 and summarize the top advertisers by spend."
"Find Snap political ads mentioning election in 2025 and 2026."
"Export the latest Snapchat political ads archive records as CSV."

Scheduling

For monitoring workflows, schedule the actor weekly or monthly. Political ad archives may update over time, so scheduled pulls help maintain a historical local copy.

Data source

The actor uses Snap's public political ads transparency archives linked from https://www.snap.com/political-ads.

It does not require a Snapchat login, browser automation, cookies, or private APIs.

Limitations

The actor depends on the public archive files Snap makes available.
Column names may drift between years.
Some records may omit optional fields such as end date, targeting, committee, or creative metadata.
Creative asset availability is controlled by Snap.

Legality

This actor extracts public transparency archive data. You are responsible for using the data lawfully, respecting Snap's terms, and complying with privacy, election, and advertising regulations in your jurisdiction.

FAQ

Is this an official Snapchat API?

No. The actor downloads and parses public transparency archive ZIP files linked from Snap's political ads page.

Can I scrape all years?

Yes. Add multiple values to years, but start with one year while testing so runs stay fast and inexpensive.

Troubleshooting

Why did I get zero results?

Your filters may be too narrow. Try removing advertiserNames, countryCodes, searchTerms, and date filters, then run one archive year with a small maxItems.

Why is a country value not matching?

Snap's archive field may contain a country name rather than a two-letter code. Inspect a broad sample or enable includeRawFields to see the exact value.