# Wikipedia Pageviews Tracker (`gochujang/wikipedia-pageviews-tracker`) Actor

Track Wikipedia pageview trends via Wikimedia REST API — no key needed. Monitor daily views for specific articles or get top-viewed pages per day. Supports all language editions. Ideal for tracking public interest in people, companies, and events.

- **URL**: https://apify.com/gochujang/wikipedia-pageviews-tracker.md
- **Developed by:** [Hojun Lee](https://apify.com/gochujang) (community)
- **Categories:** Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 pageview fetcheds

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Wikipedia Pageviews Tracker

**Wikipedia Pageviews Tracker** retrieves **daily or monthly pageview counts** for any Wikipedia article or surfaces the **top-viewed pages** for any date range — using the Wikimedia REST API. Monitor public interest trends for people, companies, events, products, and technologies across all 60+ Wikipedia language editions. No API key required.

Wikipedia pageviews are a high-quality proxy for real-world public interest. Unlike social media metrics, they're unaffected by bots, advertising, or algorithmic amplification — they reflect genuine information-seeking behavior.

***

### Why use Wikipedia Pageviews Tracker?

1. **Real-world interest measurement** — Track how public interest in a company, person, or topic changes over time. A CEO's Wikipedia page spiking often precedes news coverage, not follows it.
2. **Event impact measurement** — Compare pageviews before, during, and after a product launch, earnings release, or PR crisis to quantify attention impact.
3. **Trend discovery** — Pull the top-100 most-viewed pages for any day to discover what the world is paying attention to — without social media noise.
4. **Brand monitoring** — Track pageviews for your company, competitors, and key executives. A sudden spike often signals news coverage before it appears in media databases.
5. **Research and journalism** — Measure public awareness of scientific topics, diseases, political figures, or historical events with reliable, unbiased data.

***

### How to use

1. Open the actor on Apify Store and click **Try for free**.
2. Choose `mode`: `article` for specific article pageviews, or `top` for daily top-viewed pages.
3. In `article` mode, paste article titles (exact Wikipedia page title format, underscores for spaces).
4. Set `startDate` and `endDate` for your date range.
5. Click **Start**. Returns daily pageview records per article or daily top-article lists.

***

### Input

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `mode` | string | `"article"` | `article` (specific articles) or `top` (top-viewed pages per day) |
| `articles` | string\[] | `["Python_(programming_language)","ChatGPT"]` | Article titles to track (use Wikipedia URL format with underscores) |
| `project` | string | `"en.wikipedia"` | Wikipedia language edition (`"en.wikipedia"`, `"de.wikipedia"`, `"ja.wikipedia"`) |
| `startDate` | string | `"2026-08-01"` | Start date in YYYY-MM-DD format |
| `endDate` | string | `"2026-08-31"` | End date in YYYY-MM-DD format |
| `topCount` | integer | `50` | Number of top articles per day in `top` mode (max 1000) |

***

### Output

**Article mode:**

```json
{
  "article": "ChatGPT",
  "project": "en.wikipedia",
  "date": "2026-08-15",
  "views": 187420
}
```

**Top mode:**

```json
{
  "rank": 1,
  "article": "Main_Page",
  "project": "en.wikipedia",
  "date": "2026-08-15",
  "views": 18234012
}
```

```json
{
  "rank": 7,
  "article": "Kamala_Harris",
  "project": "en.wikipedia",
  "date": "2026-08-15",
  "views": 892341
}
```

#### Output fields

| Field | Type | Description |
|-------|------|-------------|
| `article` | string | Wikipedia article title (underscored) |
| `project` | string | Wikipedia language edition |
| `date` | string | Date of pageview count (YYYY-MM-DD) |
| `views` | integer | Number of pageviews on that date |
| `rank` | integer | Daily rank (top mode only) |

***

### Cost estimation

**Pay-Per-Event: $0.005 per actor start + $0.001 per pageview record returned.**

| Use case | Records | Estimated cost |
|----------|---------|----------------|
| 5 articles × 30 days | 150 | ~$0.15/run |
| Daily top-100 for 7 days | 700 | ~$0.70/run |
| 10 articles × 365 days | 3650 | ~$3.65/run |
| Daily top-50 monitoring | 50/day | ~$0.05/day |

***

### FAQ

**How do I find the correct article title format?**
Use the Wikipedia URL slug: `en.wikipedia.org/wiki/OpenAI` → article title is `OpenAI`. For titles with spaces, use underscores: `en.wikipedia.org/wiki/Artificial_intelligence` → `Artificial_intelligence`. Special characters in the URL are URL-encoded; the actor handles decoding automatically.

**Does it support non-English Wikipedia?**
Yes — set `project` to any Wikimedia project: `"de.wikipedia"` (German), `"ja.wikipedia"` (Japanese), `"fr.wikipedia"` (French), `"zh.wikipedia"` (Chinese), etc. The same article may have different views in different language editions.

**How far back does the data go?**
The Wikimedia Pageviews API has data from July 1, 2015 onward. Daily granularity is available for the entire period.

**Are bots included in the view count?**
The actor uses the `user` access type by default, which excludes known bot traffic. Total views including all traffic can be significantly higher.

***

### Related actors

- [Wikidata SPARQL Query](https://apify.com/gochujang/wikidata-sparql-query) — Structured metadata for the same entities (people, companies, events) you're tracking pageviews for
- [Reddit Subreddit Tracker](https://apify.com/gochujang/reddit-subreddit-tracker) — Community discussion volume for the same topics
- [Crypto News Sentiment](https://apify.com/gochujang/crypto-news-sentiment) — News volume and sentiment alongside Wikipedia interest for crypto entities

### Feedback

If this actor is useful, a quick review helps other researchers find it: [Leave a review on Apify Store](https://apify.com/gochujang/wikipedia-pageviews-tracker#reviews)

***

**Keywords:** Wikipedia pageviews tracker, Wikimedia REST API, Wikipedia traffic data, article popularity tracker, Wikipedia trending topics, public interest measurement, Wikipedia view count, top viewed Wikipedia pages, Wikipedia analytics, multilingual Wikipedia stats, page traffic monitoring, Wikipedia engagement metrics, topic popularity tracker, no API key required

# Actor input Schema

## `mode` (type: `string`):

"article" — fetch daily pageviews for specified articles. "top" — fetch the most-viewed articles for each day in the date range.

## `articles` (type: `array`):

List of Wikipedia article titles (URL-encoded underscores, e.g. "Python\_(programming_language)"). Used only in article mode.

## `project` (type: `string`):

Language edition to query (e.g. "en.wikipedia", "ko.wikipedia", "de.wikipedia").

## `startDate` (type: `string`):

Start date in YYYY-MM-DD format (inclusive).

## `endDate` (type: `string`):

End date in YYYY-MM-DD format (inclusive).

## `topCount` (type: `integer`):

Number of top articles to return per day (used only in top mode). Max 1000.

## Actor input object example

```json
{
  "mode": "article",
  "articles": [
    "Python_(programming_language)",
    "ChatGPT"
  ],
  "project": "en.wikipedia",
  "startDate": "2026-08-01",
  "endDate": "2026-08-31",
  "topCount": 50
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("gochujang/wikipedia-pageviews-tracker").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("gochujang/wikipedia-pageviews-tracker").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call gochujang/wikipedia-pageviews-tracker --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,gochujang/wikipedia-pageviews-tracker"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/kPktAFkFPG7kILqdf/builds/H4Tk5MlhPbf0BOdhu/openapi.json