Globus Python SDK: Creating Mapped Collections
If you're working with Globus Compute (GCP) and need to create a new collection for use with GCP without the necessity of having GCP already running, you might find yourself looking for a Python equivalent to the globus gcp create mapped command. This is a common scenario for setting up new environments or integrating Globus Compute into automated workflows. As of globus_sdk==4.1.0, directly achieving this specific functionality through the SDK might not be immediately obvious, leading users to seek guidance.
Understanding the globus gcp create mapped Command
The globus gcp create mapped command is a powerful tool within the Globus CLI. It allows users to establish a new Globus Compute collection that is mapped. What this essentially means is that it creates a new endpoint resource that can be used for Globus Compute tasks, but critically, it doesn't require an already operational GCP instance to be present. This is a significant advantage when you're provisioning resources or setting up a distributed computing environment from scratch. It streamlines the process by enabling the creation of the compute collection in advance, ready to be configured and launched when needed. This is particularly useful in cloud-agnostic setups or when integrating with infrastructure-as-code practices where the creation of resources is handled declaratively.
The ability to create a mapped collection is key here. Unlike some other types of endpoint creation that might link to an existing, running service, a mapped collection is a definition of a future compute resource. This allows for a more flexible and decoupled approach to managing Globus Compute environments. For instance, you could use this command in a script that deploys virtual machines or containers, and as part of that deployment, you'd also create the corresponding Globus Compute collection that will eventually run on those deployed resources. The command abstracts away the underlying API calls and handles the necessary parameters to register this new mapped collection with the Globus service. This makes it a go-to for administrators and developers who need to automate the setup and management of Globus Compute resources across various platforms.
Exploring the Globus SDK for Similar Functionality
When diving into the globus_sdk for Python, you might initially look for methods that directly mirror the CLI commands. One function that could catch your eye is TransferClient.create_shared_endpoint. While this method is indeed for creating endpoints, it's designed for a different purpose. The create_shared_endpoint function typically requires a host_endpoint parameter. This indicates that it's intended for scenarios where you're creating a shared endpoint that is hosted by an existing Globus Transfer endpoint. This is fundamentally different from creating a new, standalone Globus Compute collection that doesn't rely on a pre-existing, running transfer service.
The distinction is important: create_shared_endpoint is about sharing data transfer capabilities, often in a read-only or restricted write manner, from an established location. On the other hand, globus gcp create mapped is about defining a compute resource that can execute tasks. The goal is not data transfer, but computation. Therefore, while both involve creating endpoints, their underlying mechanisms and use cases diverge significantly. The host_endpoint requirement in create_shared_endpoint means it's not suitable for the goal of creating a GCP collection that can be set up independently of an existing transfer endpoint. This leads to the realization that a direct one-to-one mapping for this specific GCP creation functionality isn't readily available through the standard shared endpoint creation methods in the SDK.
The Challenge of Direct API Interaction
Given the apparent lack of a direct SDK method, the next logical step for many developers is to attempt interacting with the Globus API directly. This involves bypassing the SDK's higher-level abstractions and making raw HTTP requests to the relevant API endpoints. You might try to POST to the /v0.10/endpoint resource, providing necessary data such as a display_name. However, as encountered by some users, this approach can lead to errors like `{
