sickn33/antigravity-awesome-skills/azure-storage-file-datalake-py

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Azure Data Lake Storage Gen2 SDK for Python. Use for hierarchical file systems, big data analytics, and file/directory operations.

Install

npx vskill@latest install sickn33/antigravity-awesome-skills/azure-storage-file-datalake-py

SKILL.md

Azure Data Lake Storage Gen2 SDK for Python

Hierarchical file system for big data analytics workloads.

Installation

bash
pip install azure-storage-file-datalake azure-identity

Environment Variables

bash
AZURE_STORAGE_ACCOUNT_URL=https://<account>.dfs.core.windows.net

Authentication

python
from azure.identity import DefaultAzureCredential
from azure.storage.filedatalake import DataLakeServiceClient
credential = DefaultAzureCredential()
account_url = "https://<account>.dfs.core.windows.net"
service_client = DataLakeServiceClient(account_url=account_url, credential=credential)

Client Hierarchy

ClientPurpose
DataLakeServiceClientAccount-level operations
FileSystemClientContainer (file system) operations
DataLakeDirectoryClientDirectory operations
DataLakeFileClientFile operations

These are independent fragments, not a run-all script. Confirm account/filesystem/path and protect existing data before writes, renames, recursive ACL changes or deletes. Never use production placeholders as cleanup targets. Bound recursive listings/download bytes and use non-overwriting local outputs. Recursive ACL updates can partially fail: inspect counters/failure details and resume only with exact scope. Close async credentials as well as clients in failure paths; upload success does not establish business correctness.

File System Operations

python
# Create file system (container)
file_system_client = service_client.create_file_system("myfilesystem")
# Get existing
file_system_client = service_client.get_file_system_client("myfilesystem")
# Delete
service_client.delete_file_system("myfilesystem")
# List file systems
for fs in service_client.list_file_systems():
print(fs.name)

Directory Operations

python
file_system_client = service_client.get_file_system_client("myfilesystem")
# Create directory
directory_client = file_system_client.create_directory("mydir")
# Create nested directories
directory_client = file_system_client.create_directory("path/to/nested/dir")
# Get directory client
directory_client = file_system_client.get_directory_client("mydir")
# Delete directory
directory_client.delete_directory()
# Rename/move directory
directory_client.rename_directory(new_name="myfilesystem/newname")

File Operations

Upload File
python
# Get file client
file_client = file_system_client.get_file_client("path/to/file.txt")
# Upload from local file
with open("local-file.txt", "rb") as data:
file_client.upload_data(data, overwrite=False)
# Upload bytes
file_client.upload_data(b"Hello, Data Lake!", overwrite=False)
# Separate append example: create an explicitly new empty file first.
file_client = file_system_client.create_file("disposable-append-example.txt")
file_client.append_data(data=b"chunk1", offset=0, length=6)
file_client.append_data(data=b"chunk2", offset=6, length=6)
file_client.flush_data(12) # Commit the data
Download File
python
file_client = file_system_client.get_file_client("path/to/file.txt")
# Download all content
download = file_client.download_file()
content = download.readall()
# Download to file
with open("downloaded.txt", "wb") as f:
download = file_client.download_file()
download.readinto(f)
# Download range
download = file_client.download_file(offset=0, length=100)
Delete File
python
file_client.delete_file()

List Contents

python
# List paths (files and directories)
for path in file_system_client.get_paths():
print(f"{'DIR' if path.is_directory else 'FILE'}: {path.name}")
# List paths in directory
for path in file_system_client.get_paths(path="mydir"):
print(path.name)
# Recursive listing
for path in file_system_client.get_paths(path="mydir", recursive=True):
print(path.name)

File/Directory Properties

python
# Get properties
properties = file_client.get_file_properties()
print(f"Size: {properties.size}")
print(f"Last modified: {properties.last_modified}")
# Set metadata
file_client.set_metadata(metadata={"processed": "true"})

Access Control (ACL)

python
# Get ACL
acl = directory_client.get_access_control()
print(f"Owner: {acl['owner']}")
print(f"Permissions: {acl['permissions']}")
# Set ACL
directory_client.set_access_control(
owner="user-id",
permissions="rwxr-x---"
)
# Update ACL entries
from azure.storage.filedatalake import AccessControlChangeResult
directory_client.update_access_control_recursive(
acl="user:user-id:rwx"
)

Async Client

python
from azure.storage.filedatalake.aio import DataLakeServiceClient
from azure.identity.aio import DefaultAzureCredential
async def datalake_operations():
credential = DefaultAzureCredential()
async with DataLakeServiceClient(
account_url="https://<account>.dfs.core.windows.net",
credential=credential
) as service_client:
file_system_client = service_client.get_file_system_client("myfilesystem")
file_client = file_system_client.get_file_client("test.txt")
await file_client.upload_data(b"async content", overwrite=False)
download = await file_client.download_file()
content = await download.readall()
import asyncio
asyncio.run(datalake_operations())

Best Practices

  1. Use hierarchical namespace for file system semantics
  2. Use `append_data` + `flush_data` for large file uploads
  3. Review ACL scope: default ACLs affect new descendants; existing descendants require a separately authorized recursive operation
  4. Use async client for high-throughput scenarios
  5. Use `get_paths` with `recursive=True` for full directory listing
  6. Set metadata for custom file attributes
  7. Consider Blob API for simple object storage use cases

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

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Source

Popularity

Repository stars
23,662
Repository forks
4,072
Repository npm downloads, 7 days
11,772
7-day trend score
72

Stars and forks are for the whole GitHub repository, not this skill alone. Downloads are for the repository's npm package. Refreshed 17 Mar 2026, 7 months ago.

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