clari-sdk-patterns
Production-ready Clari API client patterns in Python and TypeScript. Use when building reusable Clari clients, implementing export pipelines, or wrapping the Clari v4 API for team use. Trigger with phrases like "clari API patterns", "clari client wrapper", "clari Python client", "clari TypeScript client".
What this skill does
# Clari SDK Patterns
## Overview
Clari has no official SDK -- build typed wrappers around the v4 REST API. These patterns cover the Export API for forecasts, job polling, and data transformation pipelines.
## Prerequisites
- Completed `clari-install-auth` setup
- Python 3.10+ (primary) or TypeScript 5+
## Instructions
### Step 1: Python Client
```python
# clari_client.py
import os
import time
import requests
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class ClariConfig:
api_key: str
base_url: str = "https://api.clari.com/v4"
poll_interval: int = 5
max_poll_attempts: int = 60
class ClariClient:
def __init__(self, config: Optional[ClariConfig] = None):
self.config = config or ClariConfig(
api_key=os.environ["CLARI_API_KEY"]
)
self.session = requests.Session()
self.session.headers.update({
"apikey": self.config.api_key,
"Content-Type": "text/plain",
})
def list_forecasts(self) -> list[dict]:
resp = self.session.get(f"{self.config.base_url}/export/forecast/list")
resp.raise_for_status()
return resp.json()["forecasts"]
def export_forecast(
self,
forecast_name: str,
time_period: str,
types: list[str] = None,
currency: str = "USD",
export_format: str = "JSON",
) -> dict:
payload = {
"timePeriod": time_period,
"typesToExport": types or [
"forecast", "quota", "forecast_updated",
"adjustment", "crm_total", "crm_closed"
],
"currency": currency,
"schedule": "NONE",
"includeHistorical": False,
"exportFormat": export_format,
}
resp = self.session.post(
f"{self.config.base_url}/export/forecast/{forecast_name}",
json=payload,
)
resp.raise_for_status()
return resp.json()
def wait_for_job(self, job_id: str) -> dict:
for attempt in range(self.config.max_poll_attempts):
resp = self.session.get(
f"{self.config.base_url}/export/jobs/{job_id}",
)
resp.raise_for_status()
status = resp.json()
if status["status"] == "COMPLETED":
return status
if status["status"] == "FAILED":
raise ClariExportError(f"Job {job_id} failed: {status}")
time.sleep(self.config.poll_interval)
raise ClariExportError(f"Job {job_id} timed out after {self.config.max_poll_attempts} attempts")
def download_export(self, download_url: str) -> dict:
resp = requests.get(download_url)
resp.raise_for_status()
return resp.json()
def export_and_download(
self, forecast_name: str, time_period: str
) -> dict:
job = self.export_forecast(forecast_name, time_period)
completed = self.wait_for_job(job["jobId"])
return self.download_export(completed["downloadUrl"])
class ClariExportError(Exception):
pass
```
### Step 2: TypeScript Client
```typescript
// clari-client.ts
interface ClariConfig {
apiKey: string;
baseUrl?: string;
pollIntervalMs?: number;
maxPollAttempts?: number;
}
interface ForecastExport {
entries: ForecastEntry[];
}
interface ForecastEntry {
ownerName: string;
ownerEmail: string;
forecastAmount: number;
quotaAmount: number;
crmTotal: number;
crmClosed: number;
adjustmentAmount: number;
timePeriod: string;
}
class ClariClient {
private apiKey: string;
private baseUrl: string;
private pollIntervalMs: number;
private maxPollAttempts: number;
constructor(config: ClariConfig) {
this.apiKey = config.apiKey;
this.baseUrl = config.baseUrl ?? "https://api.clari.com/v4";
this.pollIntervalMs = config.pollIntervalMs ?? 5000;
this.maxPollAttempts = config.maxPollAttempts ?? 60;
}
private async request<T>(path: string, options?: RequestInit): Promise<T> {
const response = await fetch(`${this.baseUrl}${path}`, {
...options,
headers: {
apikey: this.apiKey,
"Content-Type": "text/plain",
...options?.headers,
},
});
if (!response.ok) {
throw new Error(`Clari API ${response.status}: ${await response.text()}`);
}
return response.json();
}
async listForecasts(): Promise<{ forecasts: any[] }> {
return this.request("/export/forecast/list");
}
async exportForecast(forecastName: string, timePeriod: string): Promise<any> {
return this.request(`/export/forecast/${forecastName}`, {
method: "POST",
body: JSON.stringify({
timePeriod,
typesToExport: ["forecast", "quota", "crm_total", "crm_closed"],
currency: "USD",
schedule: "NONE",
includeHistorical: false,
exportFormat: "JSON",
}),
});
}
async exportAndDownload(
forecastName: string,
timePeriod: string
): Promise<ForecastExport> {
const job = await this.exportForecast(forecastName, timePeriod);
const completed = await this.waitForJob(job.jobId);
const resp = await fetch(completed.downloadUrl);
return resp.json();
}
private async waitForJob(jobId: string): Promise<any> {
for (let i = 0; i < this.maxPollAttempts; i++) {
const status = await this.request(`/export/jobs/${jobId}`);
if (status.status === "COMPLETED") return status;
if (status.status === "FAILED") throw new Error(`Job failed: ${jobId}`);
await new Promise((r) => setTimeout(r, this.pollIntervalMs));
}
throw new Error(`Job ${jobId} timed out`);
}
}
```
## Error Handling
| Status | Meaning | Action |
|--------|---------|--------|
| 401 | Invalid API key | Regenerate token |
| 403 | Insufficient permissions | Admin must grant API access |
| 404 | Wrong forecast name | List forecasts first |
| 429 | Rate limited | Back off and retry |
## Resources
- [Clari API Reference](https://developer.clari.com/documentation/external_spec)
- [Clari Community API Guide](https://community.clari.com/product-q-a-6/clari-api-all-you-need-to-know-556)
## Next Steps
Apply patterns in `clari-core-workflow-a` for forecast export pipelines.
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.