runapy 1.221.0

Python client for Run:ai REST API

Runapy

Python client for the Run:ai REST API.

• A single class interface to perform all Run:ai REST API actions
• Automatic API token refresh, useful for long-running tasks
• Built-in retry mechanism for handling transient network errors
• Runtime data validation and serialization using Pydantic models

from runai.configuration import Configuration
from runai.api_client import ApiClient
from runai.runai_client import RunaiClient

config = Configuration(
    client_id="your-client-id",
    client_secret="your-client-secret",
    runai_base_url="https://your-org.run.ai",
)

client = RunaiClient(ApiClient(config))

# Start making API calls
projects = client.organizations.projects.get_projects()

Jump to our examples section for more detailed examples.

Table of Contents

1. Requirements
2. Installation
3. Getting Started
4. API Structure
5. Client Configuration Options
6. Authentication Methods
7. Examples
8. Versioning
9. About
10. License

Requirements

• Run:ai control-plane version >= 2.18: The client requires Run:ai control-plane version 2.18 or higher
• Python version >= 3.8: Required for compatibility with core dependencies
• Run:ai Client Application: Required to generate the client_id and client_secret credentials. Create a client application

Note on Token Permissions

Ensure your application token has the required role and scope permissions for your intended API operations.
API calls will fail with a 403 error if the token lacks sufficient role or scope.

Installation

For SaaS environments or latest Run:ai control-plane:

pip3 install runapy

For self-hosted environments, specify the minor version matching your control-plane version.
For example, with Run:ai 2.19 control-plane:

pip3 install runapy~=1.219.0

To understand the versioning scheme, refer to the Versioning section.

Getting Started

The client provides three client types to suit different use cases:

1. ApiClient: Standard synchronous client for sequential operations
2. ThreadedApiClient: Thread-safe client for parallel operations in multithreaded environments
3. AsyncApiClient: Asynchronous client for async/await support

Here's a basic example using the standard client:

from runai.configuration import Configuration
from runai.api_client import ApiClient
from runai.runai_client import RunaiClient

config = Configuration(
    client_id="your-client-id",
    client_secret="your-client-secret",
    runai_base_url="https://your-org.run.ai",
)

client = RunaiClient(ApiClient(config))

# Start making API calls
projects = client.organizations.projects.get_projects()

See all client configuration options in the Client configuration options

See Examples for quickstart guides

Multithreaded Operations

For parallel operations in a multithreaded environment, use ThreadedApiClient:

from runai.api_client import ThreadedApiClient

with RunaiClient(ThreadedApiClient(config)) as client:
    # These operations can run concurrently
    projects = client.organizations.projects.get_projects()

Asynchronous Operations

For async/await support, use AsyncApiClient:

import asyncio
from runai.api_client import AsyncApiClient

async def main():
    async with RunaiClient(AsyncApiClient(config)) as client:
        projects = await client.organizations.projects.get_projects()

asyncio.run(main())

API Structure

The client matches the Run:ai REST API documentation structure with three levels of groups:

1. API Categories: Top-level groupings (e.g., organizations, authentication_and_authorization)
2. API Groups: Resource-specific groups within categories (e.g., projects, departments under organizations)
3. API Methods: Individual operations on resources (e.g., get_projects, create_project)

Example of navigating the API structure:

# List available API groups in the organizations category
client.organizations.options()
# ['projects', 'departments', 'clusters', 'nodes', ...]

# List available methods in the projects group
client.organizations.projects.options()
# ['get_projects', 'create_project', 'delete_project', ...]

Deprecated Methods

Deprecated methods are hidden by default.
To view both supported and deprecated methods, use the include_deprecated flag:

client.organizations.projects.options(include_deprecated=True)

Client Configuration Options

Parameter	Type	Description
client_id	string	Required: The Run:ai application client ID, usually representing the application name
client_secret	string	Required: The client secret associated with the Run:ai application
runai_base_url	string	Required: The base URL for the Run:ai instance your organization uses (e.g., https://myorg.run.ai)
bearer_token	string	Optional: Bearer token for CLIv2 compatibility. Cannot be used together with client credentials
verify_ssl	bool	Optional: Whether to verify SSL certificates. Default is True
ssl_ca_cert	string	Optional: Path to CA certificate file
cert_file	string	Optional: Path to client certificate file
key_file	string	Optional: Path to client key file
pool_maxsize	int	Optional: Maximum number of connections to keep in pool. Default is 4
pool_size	int	Optional: Initial number of connections in pool. Defaults to pool_maxsize
retry_enabled	bool	Optional: Whether to enable request retries. Default is True
retry_max_retries	int	Optional: Maximum number of retry attempts. Default is 3
retry_backoff_factor	float	Optional: Exponential backoff factor between retries. Default is 0.5
proxy_url	string	Optional: URL for proxy server
proxy_headers	dict	Optional: Additional headers for proxy
proxy_server_name	string	Optional: SNI hostname for TLS connections
auto_refresh_token	bool	Optional: Whether to auto refresh token before expiry. Default is True
token_refresh_margin	int	Optional: Seconds before expiry to refresh token. Default is 60
debug	bool	Optional: Enable debug logging. Default is False

Authentication Methods

The client supports three authentication methods:

1. Client Credentials

Use client ID and secret from your Run:ai application:

config = Configuration(
    client_id="your-client-id",
    client_secret="your-client-secret",
    runai_base_url="https://your-org.run.ai"
)

2. Bearer Token

Direct authentication using a bearer token:

config = Configuration(
    bearer_token="your-bearer-token",
    runai_base_url="https://your-org.run.ai"
)

3. CLIv2 Token (Bearer token)

The CLIv2 token method is useful for:

• Local development and testing
• Scripts running on machines with existing CLI authentication
• Maintaining consistent authentication with CLI sessions
• End user operations

Requirements:

• Run:ai CLI v2 installed
• Successful runai login completed
• Valid authentication token in CLI config

from runai.cliv2_config_loader import CLIv2Config

# Default config path is ~/.runai
config = CLIv2Config()
# Or specify a custom path
config = CLIv2Config(cliv2_config_path="/path/to/.runai")

token = config.token
runai_base_url = config.control_plane_url
cluster_id = config.cluster_uuid

client = RunaiClient(
    cluster_id=cluster_id,
    bearer_token=token,
    runai_base_url=runai_base_url
)

Examples

The repo provides Hand-crafted examples showing common use cases.
See here.

The API client include APIs for all Run:ai UI functionalities.
We encourage you to explore the client relevant categories if you attempt to run a task that is not shown in the examples.

Note: There are also auto-generated examples under /examples/generated (may require syntax adjustments to run properly)

Versioning

The Run:ai API is an integral part of the control-plane microservices.
As the control-plane evolves, APIs may be added, modified, or deprecated.
This version binding ensures that API changes in the client match the control-plane capabilities.

The client follows semantic versioning (X.Y.Z) with a special alignment to Run:ai's control-plane versions:

• X (Major): Major changes in the client
• Y (Minor): Run:ai control-plane version (e.g., 219 for control-plane 2.19)
• Z (Patch): Small bug fixes and non-breaking changes

For example:

1.218.0  # Initial release for control-plane 2.18
1.218.1  # Patch release for control-plane 2.18
1.219.0  # Initial release for control-plane 2.19

This versioning convention ensures that:

1. Each control-plane version has a matching client version
2. Client versions clearly indicate their compatible control-plane version
3. Client breaking changes are managed in major version bumps

About

This package is an open-source project maintained by the Run:ai Professional Services team.
If you experience any issues or have feature requests, please submit them via the repository’s issue tracker.

License

This project is licensed under the Apache-2 License.
See the LICENSE file for details.