Files

List directories, upload files, and download content. File metadata travels in X-Datahub-* headers, which the SDK percent-encodes for you.

List

Java

DataWrapper<IndexNode> root = client.files().list();
DataWrapper<IndexNode> reports = client.files().list("/reports/2026");

Python

roots = client.files.list_root_directory()
listing = client.files.list_directory_by_path("/reports/2026")

Rust

let roots = api.files.list_root_directory().await?;
let listing = api.files.list_directory_by_path("/reports/2026").await?;

Upload

The Java client uploads raw content bytes to a destination path; the Python and Rust clients upload a local file and a destination_path.

Java

byte[] content = Files.readAllBytes(Path.of("report.csv"));

DataWrapper<IndexNode> uploaded = client.files().upload(
        FileUploadRequest.builder()
                .path("reports/2026/q2.csv")
                .content(content)
                .contentType("text/csv")        // default: application/octet-stream
                .externalId("report_2026_q2")   // optional
                .dataSetId(42L)                 // optional
                .description("Q2 production")   // optional
                .build());

Python

import intellistream_datahub_sdk

upload = intellistream_datahub_sdk.FileUpload(
    path="report.csv",                 # local file
    destination_path="/reports/2026/",
    external_id="report_2026_q2",
    name="q2.csv",
    data_set_id=42,
    description="Q2 production")

uploaded = client.files.upload_file(upload)   # -> list[INode]

Rust

use intellistream_datahub_sdk::files::FileUpload;

// mime type is inferred from the file content
let mut upload = FileUpload::new_with_destination_path("report.csv", "/reports/2026/");
upload.set_external_id("report_2026_q2".into());
upload.set_file_name("q2.csv".into());
upload.set_data_set_id(42);
upload.set_description("Q2 production".into());
let uploaded = api.files.upload_file(upload).await?;

Download

All three clients download a file's raw bytes by id. Python and Rust add a streaming variant that writes straight to a path, so a large file never has to sit in memory whole.

Java

byte[] bytes = client.files().download("99");
Files.write(Path.of("q2.csv"), bytes);

Python

download = client.files.download(99)
print(download.file_name, download.mime_type, len(download))
Path("q2.csv").write_bytes(download.content)

# or stream it to disk, which returns the byte count
written = client.files.download_to_path(99, "q2.csv")

Rust

let download = api.files.download(99).await?;
std::fs::write("q2.csv", &download.bytes)?;

// or stream it to disk, which returns the byte count
let written = api.files.download_to_path(99, "q2.csv").await?;

Delete

Java

client.files().delete(List.of(IdCollection.createFromExternalId("report_2026_q2")));

Python

client.files.delete(["report_2026_q2"])

Rust

use intellistream_datahub_sdk::generic::{DataWrapper, IdAndExtId};

api.files.delete(&DataWrapper::from(vec![IdAndExtId::from_external_id("report_2026_q2")])).await?;

What each client covers

Operation	Java	Python	Rust
List root	files().list()	files.list_root_directory	files.list_root_directory
List a path	files().list(path)	files.list_directory_by_path	files.list_directory_by_path
Upload	files().upload	files.upload_file	files.upload_file
Download	files().download	files.download / files.download_to_path	files.download / files.download_to_path
Delete	files().delete	files.delete	files.delete

Python and Rust add download_to_path, which streams to disk instead of holding the whole file in memory — see Download.