Get SEER monitoring up and running in under 5 minutes. No complex configuration required.
df_)pip install seerpy
Requirements: Python 3.7 or higher
from seerpy import Seer
import os
# api_key= is the preferred parameter (apiKey= kept for backwards compat)
seer = Seer(api_key=os.getenv("SEER_API_KEY"))
# Your existing function — job_name must match a pipeline in your dashboard
def process_data():
data = load_data()
transformed = transform(data)
save_results(transformed)
# Wrap it with monitoring
with seer.monitor("data_pipeline"):
process_data()Done! SEER now tracks execution time, success/failure, and sends alerts if something goes wrong.
Start time, end time, duration, and success/failure status tracked automatically
Get notified via Slack or email when your scripts fail
Full stack traces and error messages captured automatically
View past runs, execution trends, and success rates in the dashboard
Prefer not to modify your code? Wrap any command with the Seer CLI — works with any language.
# Install curl -fsSL https://raw.githubusercontent.com/seer-monitoring/seer-cli/main/cli/install.sh | sh export SEER_API_KEY=your_key # Monitor any command (job_name must exist in your Seer dashboard) seer run daily_etl --tags=etl,prod -- python etl.py