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Failed Runs Monitor

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Failed Runs Monitor

Failed Runs Monitor

jannovotny/failed-runs-monitor
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This actor will let you know about failed or time outed runs of your actors and tasks via Slack or email. It can also notice you about successful runs with empty dataset, check JSON schema of dataset items, or about runs that are running for too long.

You can access the Failed Runs Monitor 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 = { "config": [{
9            "actorId": "apify/web-scraper",
10            "minDatasetItems": 0,
11            "maxRunTimeSecs": 3600,
12        }] }
13
14# Run the Actor and wait for it to finish
15run = client.actor("jannovotny/failed-runs-monitor").call(run_input=run_input)
16
17# Fetch and print Actor results from the run's dataset (if there are any)
18print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
19for item in client.dataset(run["defaultDatasetId"]).iterate_items():
20    print(item)
21
22# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Failed Runs Monitor API in Python

The Apify API client for Python is the official library that allows you to use Failed Runs Monitor 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 Community
Actor metrics
  • 3 monthly users
  • 3 stars
  • 100.0% runs succeeded
  • Created in Mar 2019
  • Modified about 2 years ago
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