Algolia Website Indexer avatar

Algolia Website Indexer

Try for free

No credit card required

View all Actors
Algolia Website Indexer

Algolia Website Indexer

apify/algolia-website-indexer
Try for free

No credit card required

The Indexer crawls recursively a website using the Puppeteer browser (headless Chrome) and indexes the selected pages to the Algolia index.

Do you want to learn more about this Actor?

Get a demo

You can access the Algolia Website Indexer programmatically from your own Python applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = {
9    "startUrls": [{ "url": "http://example.com" }],
10    "selectors": [{
11            "key": "h1",
12            "value": "body",
13        }],
14    "requiredAttributes": [],
15    "additionalPageAttrs": {},
16}
17
18# Run the Actor and wait for it to finish
19run = client.actor("apify/algolia-website-indexer").call(run_input=run_input)
20
21# Fetch and print Actor results from the run's dataset (if there are any)
22print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
23for item in client.dataset(run["defaultDatasetId"]).iterate_items():
24    print(item)
25
26# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Algolia Website Indexer API in Python

The Apify API client for Python is the official library that allows you to use Algolia Website Indexer API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

pip install apify-client

Other API clients include:

Developer
Maintained by Apify
Actor metrics
  • 2 monthly users
  • 2 stars
  • 100.0% runs succeeded
  • Created in Jul 2019
  • Modified 5 months ago