Skills Data Science Exporting Clari Forecasts and Pipeline Snapshots

Exporting Clari Forecasts and Pipeline Snapshots

v20260423
clari-hello-world
This guide provides a comprehensive walkthrough for interacting with the Clari API to export critical business data. It covers listing available forecasts, initiating the export of forecast and quota snapshots, monitoring the job status, and ultimately downloading and parsing the structured data. This skill is ideal for testing API connectivity and integrating Clari's revenue intelligence into external data pipelines.
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Overview

Clari Hello World

Overview

First API calls against Clari: list available forecasts, export a forecast snapshot, and check export job status. The Clari Export API is the primary integration point for getting forecast, quota, and CRM data out of Clari.

Prerequisites

  • Completed clari-install-auth setup
  • CLARI_API_KEY environment variable set
  • At least one forecast configured in Clari

Instructions

Step 1: List Available Forecasts

curl -s -H "apikey: ${CLARI_API_KEY}" \
  https://api.clari.com/v4/export/forecast/list \
  | jq '.forecasts[] | {forecastName, forecastId, timePeriods}'

Step 2: Export a Forecast

import requests
import json
import os
import time

api_key = os.environ["CLARI_API_KEY"]
headers = {"apikey": api_key, "Content-Type": "text/plain"}

# Replace with your forecast name from Step 1
forecast_name = "company_forecast"

payload = json.dumps({
    "timePeriod": "2026_Q1",
    "typesToExport": [
        "forecast",
        "quota",
        "forecast_updated",
        "adjustment",
        "crm_total",
        "crm_closed"
    ],
    "currency": "USD",
    "schedule": "NONE",
    "includeHistorical": False,
    "exportFormat": "JSON"
})

response = requests.post(
    f"https://api.clari.com/v4/export/forecast/{forecast_name}",
    headers=headers,
    data=payload,
)
response.raise_for_status()

job = response.json()
print(f"Export job started: {job['jobId']}")
print(f"Status: {job['status']}")

Step 3: Check Export Job Status

# Poll for job completion
job_id = job["jobId"]

while True:
    status_resp = requests.get(
        f"https://api.clari.com/v4/export/jobs/{job_id}",
        headers={"apikey": api_key},
    )
    status = status_resp.json()

    if status["status"] == "COMPLETED":
        print(f"Export ready: {status['downloadUrl']}")
        break
    elif status["status"] == "FAILED":
        print(f"Export failed: {status.get('error', 'Unknown')}")
        break

    print(f"Status: {status['status']}... waiting 5s")
    time.sleep(5)

Step 4: Download and Parse Results

if status["status"] == "COMPLETED":
    download = requests.get(status["downloadUrl"])
    forecast_data = download.json()

    # Print summary
    for entry in forecast_data.get("entries", [])[:5]:
        print(f"  Rep: {entry.get('ownerName')}")
        print(f"  Forecast: ${entry.get('forecastAmount', 0):,.0f}")
        print(f"  Quota: ${entry.get('quotaAmount', 0):,.0f}")
        print()

Output

  • List of forecasts with IDs and time periods
  • Exported forecast data with rep-level calls
  • Quota, adjustments, and CRM totals

Error Handling

Error Cause Solution
401 Unauthorized Bad API key Regenerate token in Clari settings
No forecasts listed Wrong org or no forecasts configured Contact Clari admin
Job stays PENDING Large export Wait longer, check job status endpoint
404 on forecast name Name mismatch Use exact name from list endpoint

Resources

Next Steps

Proceed to clari-local-dev-loop for development workflow setup.

Info
Category Data Science
Name clari-hello-world
Version v20260423
Size 3.81KB
Updated At 2026-04-28
Language