Hi @ancient-wolf-19325 what is flyte directory How to use it?

A FlyteDirectory is a Flyte type representing a directory (folder) in remote or local storage, allowing tasks to work with collections of files as a single input or output. It supports efficient batch upload/download and streaming via the fsspec library, and can be annotated with batch size for chunked processing according to FlyteDirectory documentation and Flyte 1.10 release notes. To use FlyteDirectory, import it from flytekit, define it as a task input/output, and return or accept directories in your task logic. You can also use batch size annotations for large directories. Example:

from flytekit import task, workflow
from flytekit.types.directory import FlyteDirectory
from typing_extensions import Annotated

@task
def generate_files() -> Annotated[FlyteDirectory, BatchSize(100)]:
    # create files in a directory and return as FlyteDirectory
    ...

@task
def process_files(d: Annotated[FlyteDirectory, BatchSize(100)]):
    # process files in the directory
    ...

@workflow
def my_wf():
    d = generate_files()
    process_files(d=d)

Would you like more detail or examples? Sources: - FlyteDirectory documentation - Flyte 1.10 release notes 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

suppose I have a data present in gcs bucket of size 100gb I want to use in my workflows will copy 100gb to flyte directory and utilise? @ancient-wolf-19325

Yes, you can use a FlyteDirectory to reference a directory in a GCS bucket without copying all 100GB locally up front. FlyteDirectory supports remote URIs (e.g., gs://...), and files are only downloaded as needed by tasks, enabling efficient processing of large datasets without unnecessary data transfer. Batch download and streaming are also supported for large directories according to the FlyteDirectory documentation. To use it, pass the GCS path as a FlyteDirectory input to your task. Flyte will handle downloading files on demand:

from flytekit import task
from flytekit.types.directory import FlyteDirectory

@task
def process_gcs_dir(data: FlyteDirectory):
    # data.path will be a local path after download
    ...

Would you like more detail or a full workflow example? Sources: - FlyteDirectory documentation 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

yes, I want to know that I am running command that it will process the some log file inorder convert into some other format will it reference from uri or it will download into pod that log file will do the operation? @ancient-wolf-19325

When you use FlyteDirectory with a remote URI (like a GCS path), Flyte will not process the file directly from the URI. Instead, it downloads the required files from the remote location (e.g., GCS) into the pod's local filesystem before your task code accesses them. Your task then operates on the local copy of the file, not directly on the remote URI. This ensures compatibility with standard file operations in Python and other tools, as described in the FlyteDirectory documentation. Would you like a step-by-step example of how this works in a Flyte task? Sources: - FlyteDirectory documentation 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

to pod means it utilises local memory of pod /node right? @ancient-wolf-19325

Yes, when Flyte downloads files from a remote URI (like GCS) into a pod, the files are stored in the pod's local filesystem, which uses the pod's allocated memory and disk resources. This means large files will consume local storage on the pod/node during processing, as confirmed in the FlyteDirectory documentation. Would you like more detail on resource management or best practices for handling large files? Sources: - https://www.union.ai/docs/v2/flyte/user-guide/task-programming/files-and-directories/ - https://github.com/flyteorg/flyte/blob/master/docs/user_guide/data_types_and_io/flytefile.md 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.