# Paris Fashion Week Calendar (`runtime/paris-fashion-week-calendar`) Actor

Extract Paris Fashion Week calendar entries with brands, dates, show types, locations, and source links.

- **URL**: https://apify.com/runtime/paris-fashion-week-calendar.md
- **Developed by:** [scraping automation](https://apify.com/runtime) (community)
- **Categories:** News, Automation, AI
- **Stats:** 4 total users, 1 monthly users, 100.0% runs succeeded, 3 bookmarks
- **User rating**: No ratings yet

## Pricing

$29.00/month + usage

To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## Paris Fashion Week Calendar

Extract Paris Fashion Week calendar entries with brands, dates, show types, locations, and source links.

### Who this is for

- Fashion teams
- PR teams
- Event researchers
- Brand intelligence workflows

### What it helps you do

- Monitor Fashion Week schedules
- Collect brand show and presentation entries
- Prepare calendar datasets for planning

### Inputs you can use

- Calendar URLs or season settings
- Maximum events

### Data you get

- brand
- event type
- date
- time
- venue
- city
- calendar URL
- source

### How to get better results

- Start with a narrow, specific query or a small list of source URLs.
- Use realistic limits for the first run, then increase the volume once the output looks right.
- Keep source URLs, dates, and location context when you need repeatable market monitoring.
- Review a few sample records before connecting the dataset to a larger workflow.

### Notes

- Results depend on what the public source exposes at run time.
- Some pages may hide, delay, rename, or remove fields, so individual records can have partial data.
- Use the built-in output table to inspect results before exporting to spreadsheets, dashboards, or automation tools.

### Support

If a run returns unexpected data, open an issue from the Actor page with the input used, the run ID, and the result you expected.

# Actor input Schema

## `url` (type: `string`):

Full URL of the Paris Fashion Week calendar page to start from. Keep the default unless the calendar path or locale changes.

## `maxRetries` (type: `integer`):

Maximum retry attempts per request when navigation or network errors occur. Increase for flaky connections; decrease to fail fast.

## `timeoutSecs` (type: `integer`):

Navigation and request timeout in seconds. Increase on slow networks or heavy pages.

## `paginationLimit` (type: `integer`):

Maximum number of paginated calendar pages to follow. Use 1 to scrape only the first page.

## `failOnNoResults` (type: `boolean`):

Fail the run when no fashion week records are extracted. Keep enabled for production tasks so empty runs do not look successful.

## Actor input object example

```json
{
  "url": "https://www.fhcm.paris/fr/paris-fashion-week/calendar",
  "maxRetries": 3,
  "timeoutSecs": 60,
  "paginationLimit": 1,
  "failOnNoResults": true
}
```

# Actor output Schema

## `overview` (type: `string`):

Brand-level results with each brand's raw entries array.

## `schedule` (type: `string`):

Flattened schedule entries with dates, times, and formats.

# 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("runtime/paris-fashion-week-calendar").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("runtime/paris-fashion-week-calendar").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 '{}' |
apify call runtime/paris-fashion-week-calendar --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=runtime/paris-fashion-week-calendar",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/E8gCIKb1eGJyD7i5x/builds/FLjOxlHVQw3rPcGTK/openapi.json