📄️ Introduction and Setup
LOC CLI is the dedicated command line tool for developers to create data processes/other assets and deploy/manage them remotely in LOC. Combined with TypeScript support, local runtime and powerful IDEs like Visual Studio Code, CLI makes coding and debug much easier than doing so in LOC Studio.
📄️ Create and Deploy Data Process
CLI allows you to create data process projects locally and deploy them with console commands.
📄️ Single Data Process Execution
If a data process is deployed, it can be run without using triggers (or rather, a simulated API route). This is exactly the same as using the Execution function in Studio.
📄️ Deploy API Route
API routes is one of the trigger features that can be deployed and managed from CLI, which make data processes RESTful-like.
📄️ Deploy MQ Client, Pub and Sub
Message queue clients, publishers and subscribers together are one of the trigger featuures that can be deployed and managed from CLI.
📄️ Deploy Scheduler
Scheduler - schedules and scheduled jobs - together are one of the triggers that can be deployed and managed from CLI.
📄️ Deploy Agent Configuration
Agent Configuration is for creating and managing secrets for the following agents in SDK:
📄️ Using Local Simple Runtime
Local Simple Runtime is a Docker-based LOC local developing environment. It offers the following benefits:
📄️ Add Extra Local Data Services
It is possible to add extra local data storage services in the Local Simple Runtime. A containerized test environment is great for testing and can be deleted at any time. These services can also be accessed directly via 127.0.0.1 instead of host.docker.internal.
📄️ Source Control with Git
Although CLI does not offer version control, you can use Git to upload data processes to a Gitbub repository and shared with other team members.
🗃️ CLI Command Reference
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