current-data-py

Management

ManagementClient connects over TLS. Pass address= to configure the service, or supply your own gRPC channel.

The examples below read deployment-specific values from environment variables. Set MANAGEMENT_ADDRESS to your service address and UPLOAD_DATA_TYPE to a valid integer enum value supplied by your deployment administrator. Set the bucket and object-key variables to resources you are authorized to access. These variables are read explicitly by the examples; they are not automatic SDK configuration.

import os

from current_data_py.management import ManagementClient, Metadata, MetadataFilter

with ManagementClient(address=os.environ["MANAGEMENT_ADDRESS"]) as client:
    upload = client.get_upload_credentials(data_type=int(os.environ["UPLOAD_DATA_TYPE"]))
    read = client.get_read_credentials(bucket=os.environ["READ_BUCKET"])

    # Register an already uploaded file; replace the example file details.
    record = client.register_data(Metadata(
        name="recording",
        data_type=int(os.environ["UPLOAD_DATA_TYPE"]),
        storages=[{"bucket": os.environ["UPLOADED_BUCKET"], "object_key": os.environ["UPLOADED_OBJECT_KEY"]}],
        file_info={"size_bytes": 1234, "checksum": "sha256:<file-hash>"},
    ))
    for item in client.stream_data_references(MetadataFilter(name_prefix="recording")):
        print(item.id, item.storages)

Metadata, MetadataFilter, and responses are Protobuf objects exported by the SDK. Registration only saves metadata; it does not upload files. Credential calls return fresh credentials without caching. Calls accept timeout= and metadata= for gRPC headers.

Remote TD reads

DataClient.open_td() accepts an optional bucket argument. Without it, reads use the management service's OSS_READ_BUCKET and OSS_READ_PREFIX defaults. With it, the SDK requests whole-bucket read credentials, limited by the server's RAM role, and selects the first matching storage in the reference. An explicit bucket does not inherit the default prefix. Default and per-bucket credentials are cached separately and refreshed automatically.

import os

from current_data_py.remote import DataClient

with DataClient(address=os.environ["MANAGEMENT_ADDRESS"]) as client:
    for reference in client.iter_data():
        # Use the service's default bucket and prefix.
        with client.open_td(reference) as reader:
            print(reader.summary())

        # Request read access to the selected bucket.
        with client.open_td(reference, bucket=os.environ["READ_BUCKET"]) as reader:
            print(reader.summary())

The explicit bucket must contain a storage listed in the reference. This uses the existing bucket-aware management API; no protocol changes are required.

OSS

import os

from current_data_py.management import ManagementClient
from current_data_py.oss import OSSClient

with ManagementClient(address=os.environ["MANAGEMENT_ADDRESS"]) as management:
    with OSSClient(management, permission="read", bucket=os.environ["READ_BUCKET"]) as source:
        source.download_file(os.environ["SOURCE_OBJECT_KEY"], "/tmp/input.h5")

    # Convert the input into /tmp/output.td before uploading.
    with OSSClient(management, permission="upload", data_type=int(os.environ["UPLOAD_DATA_TYPE"])) as destination:
        key = destination.object_prefix + "recording/output.td"
        destination.upload_file(key, "/tmp/output.td")
        print(destination.bucket, key)  # Use these values when registering metadata.

• Read access covers the requested bucket, subject to server permissions. The server chooses the upload bucket and prefix based on the requested data type.
• Credentials refresh automatically. Expired tokens trigger one refresh and retry.
• Uploads reject overwrites by default; set forbid_overwrite=False to replace. Downloads replace the local file only on success; its parent directory must exist.
• Uploads use a single PutObject request (maximum 5 GiB); multipart upload is not supported.
• Supply region= for custom upload endpoints. Deploy the current management credential API before using the new bucket and data-type arguments.

打包

cd current_data_py  # 从仓库根目录执行
# 发布新版本前，更新 pyproject.toml 中的 version
python -m pip install build twine
rm -rf build dist
python -m build

测试

python -m twine check dist/*
python tests/check_distribution.py
python -m pip install --force-reinstall dist/*.whl
python -I tests/check_package.py
python -I tests/check_management.py
python -I tests/check_remote.py
python -I tests/check_oss.py

推送

# TestPyPI
python -m twine upload --repository testpypi dist/*

# PyPI
python -m twine upload dist/*