| Azure Data Lake Storage Gen2 SDK for Python. Use for hierarchical file systems, big data analytics, and file/directory operations.
npx skills add https://github.com/microsoft/skills --skill azure-storage-file-datalake-py
Hierarchical file system for big data analytics workloads.
pip install azure-storage-file-datalake azure-identity
AZURE_STORAGE_ACCOUNT_URL=https://<account>.dfs.core.windows.net # Required for all auth methods
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production
> 🔑 Two rules apply to every code sample below:
>
> 1. Prefer DefaultAzureCredential. It works locally (Azure CLI / VS Code / Developer CLI) and in Azure (managed identity, workload identity) with no code change. Avoid connection strings, account/API keys — they bypass Entra audit and rotation.
> - Local dev: DefaultAzureCredential works as-is.
> - Production: set AZURE_TOKEN_CREDENTIALS=prod (or AZURE_TOKEN_CREDENTIALS=<specific_credential>) to constrain the credential chain to production-safe credentials.
> 2. Wrap every client in a context manager so HTTP transports, sockets, and token caches are released deterministically:
> - Sync: with <Client>(...) as client:
> - Async: async with <Client>(...) as client: and async with DefaultAzureCredential() as credential: (from azure.identity.aio)
>
> Snippets may abbreviate this setup, but production code should always follow both rules.
from azure.identity import DefaultAzureCredential, ManagedIdentityCredential
from azure.storage.filedatalake import DataLakeServiceClient
# Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
credential = DefaultAzureCredential(require_envvar=True)
# Or use a specific credential directly in production:
# See https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#credential-classes
# credential = ManagedIdentityCredential()
account_url = "https://<account>.dfs.core.windows.net"
with DataLakeServiceClient(account_url=account_url, credential=credential) as service_client:
# Use service_client here (see following sections for operations)
...
| Client | Purpose |
|--------|---------|
| DataLakeServiceClient | Account-level operations |
| FileSystemClient | Container (file system) operations |
| DataLakeDirectoryClient | Directory operations |
| DataLakeFileClient | File operations |
# 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)
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")
# 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=True)
# Upload bytes
file_client.upload_data(b"Hello, Data Lake!", overwrite=True)
# Append data (for large files)
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
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)
file_client.delete_file()
# 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)
# 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"})
# 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"
)
from azure.storage.filedatalake.aio import DataLakeServiceClient
from azure.identity.aio import DefaultAzureCredential
async def datalake_operations():
async with DefaultAzureCredential() as credential:
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=True)
download = await file_client.download_file()
content = await download.readall()
import asyncio
asyncio.run(datalake_operations())
azure.storage.filedatalake sync clients with azure.storage.filedatalake.aio async clients in the same call path. Choose one mode per module.with DataLakeServiceClient(...) as client: (sync) or async with DataLakeServiceClient(...) as client: (async). For async DefaultAzureCredential from azure.identity.aio, also use async with credential: so tokens and transports are cleaned up.DefaultAzureCredential for portable auth across local dev and Azure (avoid connection strings / API keys when possible).append_data + flush_data for large file uploadsget_paths with recursive=True for full directory listing10. Consider Blob API for simple object storage use cases
| File | Contents |
|------|----------|
| references/capabilities.md | Additional non-hero capabilities, operation-group coverage, and production checklists. |
| references/non-hero-scenarios.md | Dedicated non-hero examples for secondary/advanced scenarios. |
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