qdash-client 0.1.0

Python client for the QDash API

qdash.client README

qdash.client is a Python client for calling the QDash API.

• services: domain logic such as authentication, retries, and response normalization
• rest: low-level HTTP communication

This package follows the same approach as oqtopus-client, separating the transport layer from the service layer. For user-facing examples, see docs/user-guide/qdash-client.md.

Installation

Install the lightweight client package when only programmatic API access is needed.

pip install qdash-client

For development against this repository:

pip install ./src/qdash/client

The distribution name is qdash-client, but the Python import path is qdash.client.

Publishing

qdash-client is published from this repository with PyPI Trusted Publishing. Configure the qdash-client project on PyPI to trust this GitHub repository and the .github/workflows/publish-qdash-client.yml workflow.

Release tags use the qdash-client-v<version> format and must match the version in pyproject.toml.

git tag qdash-client-v0.1.0
git push origin qdash-client-v0.1.0

Minimal Quick Start

This is a minimal example using /chips, /metrics/config, and /task-results/timeseries.

from qdash.client import QDashClient

client = QDashClient()
try:
    chips = client.list_chips()
    print(chips.total)
    print([chip.chip_id for chip in chips.chips])

    metrics_config = client.get_metrics_config()
    print(metrics_config.keys())

    series = client.get_task_results_timeseries(
        chip_id="chip-001",
        parameter="t1",
        start_at="2026-06-01T00:00:00Z",
        end_at="2026-06-02T00:00:00Z",
    )
    print(series.data)
finally:
    client.close()

1. Public API

In most cases, you will use the following:

• QDashClient
• QDashConfig
• Exception classes such as QDashApiError

from qdash.client import QDashClient, QDashConfig

2. Configuration

2.1 From Environment Variables

from qdash.client import QDashConfig, QDashClient

config = QDashConfig.from_env()
client = QDashClient(config)

Main environment variables:

• QDASH_BASE_URL
• QDASH_API_TOKEN
• QDASH_PROJECT_ID
• QDASH_CF_ACCESS_CLIENT_ID
• QDASH_CF_ACCESS_CLIENT_SECRET
• QDASH_TIMEOUT_SECONDS
• QDASH_RETRY_MAX_ATTEMPTS
• QDASH_RETRY_BACKOFF_SECONDS
• QDASH_RETRY_MAX_BACKOFF_SECONDS
• QDASH_VERIFY_TLS
• QDASH_PROXY
• QDASH_USER_AGENT

For legacy username/password authentication, set:

• QDASH_USERNAME
• QDASH_PASSWORD_ENV
• the environment variable named by QDASH_PASSWORD_ENV (defaults to QDASH_PASSWORD)

2.2 From a Configuration File

from qdash.client import QDashConfig, QDashClient

config = QDashConfig.from_file(section="default")
client = QDashClient(config)

If path is omitted:

1. If XDG_CONFIG_HOME is set: $XDG_CONFIG_HOME/qdash/config.ini
2. Otherwise: ~/.config/qdash/config.ini

Example configuration:

[default]
base_url = https://example.qdash/api
api_token = your-token
project_id = your-project-id
cf_access_client_id = your-cf-client-id
cf_access_client_secret = your-cf-client-secret
timeout_seconds = 30
retry_max_attempts = 3
retry_backoff_seconds = 0.2
retry_max_backoff_seconds = 5.0

For legacy username/password authentication from a config file, use username and password_env instead of api_token.

2.3 Automatic Loading

from qdash.client import QDashClient

# Loads config.ini by default
client = QDashClient()

3. Usage (Synchronous API)

3.1 List Chips

from qdash.client import QDashClient

client = QDashClient()
try:
    chips = client.list_chips()
    print([chip.chip_id for chip in chips.chips])
finally:
    client.close()

3.2 Time-Series Metrics

from qdash.client import QDashClient

client = QDashClient()
try:
    series = client.get_task_results_timeseries(
        chip_id="chip-001",
        parameter="t1",
        tag="calibration",
        start_at="2026-06-01T00:00:00Z",
        end_at="2026-06-08T00:00:00Z",
        qid="Q00",
    )
    print(series.data)
finally:
    client.close()

3.3 Metrics Configuration

from qdash.client import QDashClient

client = QDashClient()
try:
    config = client.get_metrics_config()
    print(config.get("qubit_metrics", {}).keys())
    print(config.get("coupling_metrics", {}).keys())
finally:
    client.close()

4. Usage (Asynchronous API)

import asyncio
from qdash.client import QDashClient

async def main() -> None:
    client = QDashClient()
    try:
        chips = await client.list_chips_async()
        print([chip.chip_id for chip in chips.chips])

        metrics_config = await client.get_metrics_config_async()
        print(metrics_config.get("qubit_metrics", {}).keys())

        series = await client.get_task_results_timeseries_async(
            chip_id="chip-001",
            parameter="t1",
            start_at="2026-06-01T00:00:00Z",
            end_at="2026-06-02T00:00:00Z",
        )
        print(series.data)
    finally:
        client.close()

asyncio.run(main())

5. Error Handling

Main exceptions:

• QDashApiError (base class)
• QDashAuthError (missing or invalid authentication)
• QDashNotFoundError (404)
• QDashValidationError (422)
• QDashTransportError (transport errors, timeouts, or other HTTP statuses)

from qdash.client import QDashClient, QDashApiError

client = QDashClient()
try:
    print(client.list_chips().chips)
except QDashApiError as exc:
    print(exc.status_code, exc)
finally:
    client.close()

6. Exporter Helper Functionality

QDashClient provides helper methods for exporters.

• normalize_chip_metrics(chip_id, payload)

This method converts a QDash API response into a list of NormalizedMetricRecord objects that are easier for exporters to consume.

7. Using the Low-Level REST Client Directly

In most cases, using QDashClient is recommended.

If you need direct access to the low-level API, you can use qdash.client.rest.

from qdash.client.rest import ApiClient, Configuration

cfg = Configuration(host="https://example.qdash/api")
rest_client = ApiClient(cfg)

try:
    resp = rest_client.request("GET", "/chips")
    print(resp.status_code, resp.data)
finally:
    rest_client.close()