# Snapchat Political Ads Library Scraper (`datapeak/snapchat-ads-library`) Actor
Scrape Snapchat's Political Ads Library at scale. Extract advertiser, ad creatives, spend, impressions, targeting, dates and country as JSON/CSV. Built for researchers, journalists and transparency teams. No login, pay per result ($1/1k), one-click run or Apify API.
- **URL**: https://apify.com/datapeak/snapchat-ads-library.md
- **Developed by:** [Gal Gilboa](https://apify.com/datapeak) (community)
- **Categories:** News, Social media, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $1.00 / 1,000 ad scrapeds
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
## Snapchat Political Ads Library Scraper
Download and search **Snapchat's Political & Advocacy Ads Library** — the full public archive of every political and advocacy ad run on Snapchat, by year. Get structured data on who paid, how much they spent, how many impressions the ad received, when it ran, the creative, and exactly who it was targeted to.
Snap publishes this data as one downloadable archive per year. This Actor fetches the years you ask for, parses them, applies your filters, and returns clean, ready-to-use records — one row per ad.
### What you get per ad
- **Advertiser** — paying advertiser, organization name, committee, billing address
- **Spend & reach** — amount spent, currency, impressions
- **Run dates** — start and end date
- **Creative** — direct URL to the ad's media (image/video) and creative properties
- **Ballot info** — candidate / ballot information where provided
- **Targeting** — country, regions, electoral districts, metros, postal codes, age bracket, gender, interests, segments, language, OS, connection type, carrier, radius targeting
- **`raw`** — the complete original CSV row, so nothing is ever lost
### Input
| Field | Description |
|---|---|
| **Years** | Which yearly archives to pull (`2018`–current). Add one 4-digit year per entry. Years Snap hasn't published yet are skipped automatically. |
| **Country filter** | Keep only ads targeted to a country. Accepts a name (`United States`) or a 2-letter code (`US`, `GB`) — codes are mapped automatically. |
| **Advertiser filter** | Keep only ads whose paying advertiser or organization contains this text. |
| **Keyword filter** | Free-text search across advertiser, organization, ballot info, address, creative URL, interests, segments and targeting keywords. |
| **Max ads** | Cap the number of matching ads returned across all selected years. |
All filters are optional and combined with AND. Leave them empty to export an entire year.
### Example uses
- Monitor a **candidate, PAC, or advocacy group's** Snapchat spend over time
- Pull **every political ad in a country** for a given election year
- Build a **competitive/again-issue intelligence** dataset for researchers, journalists or campaigns
- Feed the archive into your own **dashboard, database, or analysis** via the Apify API
### Notes
- The source is Snap's official, public Political Ads Library. Only **political and advocacy** ads are covered — Snap does not publish a library for commercial ads.
- Country and other targeting values follow Snap's own formatting (e.g. country names rather than ISO codes); the country filter handles both for you.
- No login and no browser required — the Actor reads Snap's published archives directly, so it's fast and reliable.
# Actor input Schema
## `years` (type: `array`):
Which yearly archives to pull. Snap publishes one CSV per year from 2018 to the current year. Add one 4-digit year per entry, e.g. 2026, 2025. Any year Snap hasn't published yet is skipped automatically.
## `country` (type: `string`):
Keep only ads targeted to a country. Accepts a country name (United States, Canada) or a 2-letter code (US, GB) — codes are mapped to Snap's names automatically. Leave empty for all countries.
## `advertiser` (type: `string`):
Keep only ads whose paying advertiser or organization name contains this text (case-insensitive). Leave empty for all advertisers.
## `keyword` (type: `string`):
Free-text search across advertiser, organization, ballot info, address, creative URL, interests, segments and targeting keywords (case-insensitive substring). Leave empty to skip.
## `maxItems` (type: `integer`):
Maximum number of matching ads to return across all selected years.
## `proxyConfiguration` (type: `object`):
Optional. The archive is public static storage, so a proxy is not required. Datacenter proxy is fine if you want one.
## Actor input object example
```json
{
"years": [
"2026",
"2025"
],
"maxItems": 1000
}
````
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"years": [
"2026",
"2025"
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("datapeak/snapchat-ads-library").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Apify API token
# Replace '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = { "years": [
"2026",
"2025",
] }
# Run the Actor and wait for it to finish
run = client.actor("datapeak/snapchat-ads-library").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"years": [
"2026",
"2025"
]
}' |
apify call datapeak/snapchat-ads-library --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=datapeak/snapchat-ads-library",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Snapchat Political Ads Library Scraper",
"description": "Scrape Snapchat's Political Ads Library at scale. Extract advertiser, ad creatives, spend, impressions, targeting, dates and country as JSON/CSV. Built for researchers, journalists and transparency teams. No login, pay per result ($1/1k), one-click run or Apify API.",
"version": "0.1",
"x-build-id": "LcPZIqoSW5G5rcBOo"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/datapeak~snapchat-ads-library/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-datapeak-snapchat-ads-library",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/datapeak~snapchat-ads-library/runs": {
"post": {
"operationId": "runs-sync-datapeak-snapchat-ads-library",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/datapeak~snapchat-ads-library/run-sync": {
"post": {
"operationId": "run-sync-datapeak-snapchat-ads-library",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"years": {
"title": "Years",
"type": "array",
"description": "Which yearly archives to pull. Snap publishes one CSV per year from 2018 to the current year. Add one 4-digit year per entry, e.g. 2026, 2025. Any year Snap hasn't published yet is skipped automatically.",
"items": {
"type": "string"
}
},
"country": {
"title": "Country filter",
"type": "string",
"description": "Keep only ads targeted to a country. Accepts a country name (United States, Canada) or a 2-letter code (US, GB) — codes are mapped to Snap's names automatically. Leave empty for all countries."
},
"advertiser": {
"title": "Advertiser filter",
"type": "string",
"description": "Keep only ads whose paying advertiser or organization name contains this text (case-insensitive). Leave empty for all advertisers."
},
"keyword": {
"title": "Keyword filter",
"type": "string",
"description": "Free-text search across advertiser, organization, ballot info, address, creative URL, interests, segments and targeting keywords (case-insensitive substring). Leave empty to skip."
},
"maxItems": {
"title": "Max ads",
"minimum": 1,
"maximum": 200000,
"type": "integer",
"description": "Maximum number of matching ads to return across all selected years.",
"default": 1000
},
"proxyConfiguration": {
"title": "Proxy configuration",
"type": "object",
"description": "Optional. The archive is public static storage, so a proxy is not required. Datacenter proxy is fine if you want one."
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```