@ancient-wolf-19325 How do i structure my codes in flyte using flyte structure

A typical Flyte project is structured as a directory containing your workflow and task code, a requirements.txt for Python dependencies, and configuration files. The recommended layout is:

my_project/
├── LICENSE
├── README.md
├── requirements.txt
└── workflows/
    ├── __init__.py
    └── example.py  # Contains @task and @workflow definitions

You can initialize this structure using pyflyte init, and place your Flyte tasks and workflows in the workflows directory. Use requirements.txt to list dependencies, and optionally use ImageSpec in your workflow code to define container images. For more details, see the Flyte project components documentation. Would you like a step-by-step example or more detail on organizing larger projects? Sources: - Flyte project components documentation - Creating a Flyte project 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@ancient-wolf-19325 what does workflow and tasks mean and do?

In Flyte, a task is the core unit of computation—a Python function decorated with @task that runs in its own isolated environment (like a Kubernetes pod) and performs a specific operation. A workflow is a higher-level construct that organizes and connects multiple tasks, defining the order and data flow between them as a directed acyclic graph (DAG) to accomplish a larger goal or pipeline. Tasks are strongly typed, reusable, and can be executed independently, while workflows specify dependencies and orchestrate the execution of tasks to produce desired outputs. For more, see the Flyte tasks and workflows guide. Would you like a code example or a deeper explanation? Sources: - Flyte tasks and workflows guide 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@ancient-wolf-19325 Does flyte do rollout deployments?

There is no mention in the provided data sources that Flyte natively supports rollout deployments (such as blue/green or canary deployments) for workflows or tasks. Flyte focuses on versioning tasks and workflows for reproducibility and rollback, but automated rollout deployment strategies are not described. Would you like more detail on Flyte's versioning and rollback capabilities? Sources: - https://flyte.org/blog/orchestrating-data-pipelines-at-lyft-comparing-flyte-and-airflow#starCount 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@ancient-wolf-19325 since flyte doesn't do rollout deployments what can we do next?

It seems likely that, since Flyte does not natively support rollout deployments, you would need to manage rollout strategies (like blue/green or canary) externally—using your CI/CD system, Kubernetes deployment tools, or by manually controlling which workflow or task versions are activated and scheduled. Flyte's versioning allows you to register multiple versions of workflows and tasks, so you can control which version is used in production by updating launch plans or schedules accordingly, but the actual rollout logic (traffic shifting, gradual promotion, etc.) must be handled outside of Flyte. Would you like more detail on integrating Flyte with CI/CD or Kubernetes rollout tools? Sources: - https://github.com/flyteorg/flyte/issues/6762 - https://github.com/flyteorg/flyte/issues/6446 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

@ancient-wolf-19325 does this work: flyte_project/ │ ├── pyproject.toml ├── requirements.txt ├── README.md ├── flyte.config.yaml │ ├── src/ │ └── my_project/ │ ├── init.py │ │ ├── tasks/ │ │ ├── init.py │ │ ├── extract.py │ │ ├── transform.py │ │ ├── load.py │ │ └── validate.py │ │ │ ├── workflows/ │ │ ├── init.py │ │ └── main_workflow.py │ │ │ ├── launchplans/ │ │ ├── init.py │ │ └── scheduled.py │ │ │ ├── domain/ │ │ ├── init.py │ │ └── logic.py │ │ │ ├── config/ │ │ └── settings.yaml │ │ │ └── utils/ │ └── helpers.py │ ├── tests/ │ ├── test_tasks.py │ └── test_workflows.py │ └── Dockerfile Is it the standard form it should be?

Yes, this structure is compatible with Flyte and follows best practices for Python projects, especially with a src/ layout. Your tasks, workflows, and launch plans are organized into submodules, and you have configuration, tests, and a Dockerfile included. To ensure Flyte discovers your modules, set the root directory (e.g., with flyte.init_from_config(root_dir=pathlib.Path(file).parent.parent)) and adjust your Dockerfile’s WORKDIR and PYTHONPATH accordingly. See Flyte project components and code bundling best practices. Would you like a sample Dockerfile or more detail on import paths and registration? Sources: - Flyte project components - Code bundling and root_dir best practices 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.