# See what a website looked like in a past year

**Use case:** 

Returns the archived captures of a page inside a date window, oldest first, so you can read how it changed across that period. Set the year range and get the capture dates, status codes and links back as rows.

## Input

```json
{
  "urls": [
    "example.com"
  ],
  "matchType": "exact",
  "from": "2024",
  "to": "2025",
  "collapseDuplicates": false,
  "maxSnapshotsPerUrl": 1000,
  "maxItems": 50000
}
```

## Output

```json
{
  "capturedAt": {
    "label": "Captured At",
    "format": "string"
  },
  "statusCode": {
    "label": "Status Code",
    "format": "integer"
  },
  "mimeType": {
    "label": "Mime Type",
    "format": "string"
  },
  "length": {
    "label": "Length (bytes)",
    "format": "integer"
  },
  "digest": {
    "label": "Content Digest",
    "format": "string"
  },
  "original": {
    "label": "Original",
    "format": "string"
  },
  "snapshotUrl": {
    "label": "Snapshot Url",
    "format": "string"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Wayback Machine Scraper — Website History & Snapshots Actor is ready to run with the inputs already set for "See what a website looked like in a past year". [Sign up or log in](https://console.apify.com/create-task-from-example/2fVRqVNJekyF1BjsJ) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "See what a website looked like in a past year" task

The Wayback Machine Scraper — Website History & Snapshots Actor will start running based on the input automatically. You can also change all the input fields, like URLs, match type, and more, to match your specific use case.

### 3. Receive the "See what a website looked like in a past year" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as captured at, status code, mime type, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "See what a website looked like in a past year" task via API](https://apify.com/alaudinburki/wayback-machine-snapshots.md).

## About this Actor

This example demonstrates how to use [Wayback Machine Scraper — Website History & Snapshots](https://apify.com/alaudinburki/wayback-machine-snapshots.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/alaudinburki/wayback-machine-snapshots.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/alaudinburki/wayback-machine-snapshots.md

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`).