Dataset Freshness & SLA Compliance Monitor
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from $2.45 / 1,000 results
Measure dataset recency against a timestamp field and enforce freshness, minimum-volume, and recent-item SLA thresholds for scheduled pipelines.
Pricing
from $2.45 / 1,000 results
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Rafael Barreto Haddad
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12 hours ago
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You can access the Dataset Freshness & SLA Compliance Monitor programmatically from your own 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 API & Integrations in Apify Console.
1from apify_client import ApifyClient2
3# Initialize the ApifyClient with your Apify API token4# Replace '<YOUR_API_TOKEN>' with your token.5client = ApifyClient("<YOUR_API_TOKEN>")6
7# Prepare the Actor input8run_input = {}9
10# Run the Actor and wait for it to finish11run = client.actor("quanmatrix/dataset-freshness-sla-monitor").call(run_input=run_input)12
13# Fetch and print Actor results from the run's dataset (if there are any)14print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")15for item in client.dataset(run.default_dataset_id).iterate_items():16 print(item)17
18# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-startThe Apify API client for Python is the official library that allows you to use Dataset Freshness & SLA Compliance Monitor API in Python, providing convenience functions and automatic retries on errors.
Install the apify-client
$pip install apify-clientOther API clients include: