Token导航 LogoToken导航TokenDH.com
研究检索敏感数据clawhub未标认证来源可访问clear审计通过

azure-storage-blob-pyAzure storage blob PY 搜索

Agent Skill

用于辅助云资源、部署、容器、基础设施和运维自动化任务。它适合让 Agent 检查配置、整理部署步骤、分析资源状态、生成排障思路或辅助云服务接入。使用时需要明确目标环境、账号权限、区域和资源组,区分本地测试与生产操作;涉及删除资源、重启服务、修改网络或权限配置时,应先确认影响范围。

总安装

63,333

周安装

2,562

GitHub Stars

1

下载量

19,881
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:azure-storage-blob-py(Azure storage blob PY 搜索)
来源仓库:https://github.com/thegovind/azure-storage-blob-py
安装命令:
openclaw skills install azure-storage-blob-py
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install azure-storage-blob-py

简介

适用于 Python 的 Azure Blob 存储 SDK。用于上传、下载、列出 blob、管理容器和 blob 生命周期。

  • 触发器:“blob 存储”、“BlobServiceClient”、“ContainerClient”、“BlobClient”、“上传 blob”、“下载 blob”。

SKILL.md

name
azure-storage-blob-py
description
|
Triggers
blob storage", "BlobServiceClient", "ContainerClient", "BlobClient", "upload blob", "download blob".
package
azure-storage-blob

Azure Blob Storage SDK for Python

Client library for Azure Blob Storage — object storage for unstructured data.

Installation

pip install azure-storage-blob azure-identity

Environment Variables

AZURE_STORAGE_ACCOUNT_NAME=<your-storage-account>
# Or use full URL
AZURE_STORAGE_ACCOUNT_URL=https://<account>.blob.core.windows.net

Authentication

from azure.identity import DefaultAzureCredential
from azure.storage.blob import BlobServiceClient

credential = DefaultAzureCredential()
account_url = "https://<account>.blob.core.windows.net"

blob_service_client = BlobServiceClient(account_url, credential=credential)

Client Hierarchy

ClientPurposeGet From
BlobServiceClientAccount-level operationsDirect instantiation
ContainerClientContainer operationsblob_service_client.get_container_client()
BlobClientSingle blob operationscontainer_client.get_blob_client()

Core Workflow

Create Container

container_client = blob_service_client.get_container_client("mycontainer")
container_client.create_container()

Upload Blob

# From file path
blob_client = blob_service_client.get_blob_client(
    container="mycontainer",
    blob="sample.txt"
)

with open("./local-file.txt", "rb") as data:
    blob_client.upload_blob(data, overwrite=True)

# From bytes/string
blob_client.upload_blob(b"Hello, World!", overwrite=True)

# From stream
import io
stream = io.BytesIO(b"Stream content")
blob_client.upload_blob(stream, overwrite=True)

Download Blob

blob_client = blob_service_client.get_blob_client(
    container="mycontainer",
    blob="sample.txt"
)

# To file
with open("./downloaded.txt", "wb") as file:
    download_stream = blob_client.download_blob()
    file.write(download_stream.readall())

# To memory
download_stream = blob_client.download_blob()
content = download_stream.readall()  # bytes

# Read into existing buffer
stream = io.BytesIO()
num_bytes = blob_client.download_blob().readinto(stream)

List Blobs

container_client = blob_service_client.get_container_client("mycontainer")

# List all blobs
for blob in container_client.list_blobs():
    print(f"{blob.name} - {blob.size} bytes")

# List with prefix (folder-like)
for blob in container_client.list_blobs(name_starts_with="logs/"):
    print(blob.name)

# Walk blob hierarchy (virtual directories)
for item in container_client.walk_blobs(delimiter="/"):
    if item.get("prefix"):
        print(f"Directory: {item['prefix']}")
    else:
        print(f"Blob: {item.name}")

Delete Blob

blob_client.delete_blob()

# Delete with snapshots
blob_client.delete_blob(delete_snapshots="include")

Performance Tuning

# Configure chunk sizes for large uploads/downloads
blob_client = BlobClient(
    account_url=account_url,
    container_name="mycontainer",
    blob_name="large-file.zip",
    credential=credential,
    max_block_size=4 * 1024 * 1024,  # 4 MiB blocks
    max_single_put_size=64 * 1024 * 1024  # 64 MiB single upload limit
)

# Parallel upload
blob_client.upload_blob(data, max_concurrency=4)

# Parallel download
download_stream = blob_client.download_blob(max_concurrency=4)

SAS Tokens

from datetime import datetime, timedelta, timezone
from azure.storage.blob import generate_blob_sas, BlobSasPermissions

sas_token = generate_blob_sas(
    account_name="<account>",
    container_name="mycontainer",
    blob_name="sample.txt",
    account_key="<account-key>",  # Or use user delegation key
    permission=BlobSasPermissions(read=True),
    expiry=datetime.now(timezone.utc) + timedelta(hours=1)
)

# Use SAS token
blob_url = f"https://<account>.blob.core.windows.net/mycontainer/sample.txt?{sas_token}"

Blob Properties and Metadata

# Get properties
properties = blob_client.get_blob_properties()
print(f"Size: {properties.size}")
print(f"Content-Type: {properties.content_settings.content_type}")
print(f"Last modified: {properties.last_modified}")

# Set metadata
blob_client.set_blob_metadata(metadata={"category": "logs", "year": "2024"})

# Set content type
from azure.storage.blob import ContentSettings
blob_client.set_http_headers(
    content_settings=ContentSettings(content_type="application/json")
)

Async Client

from azure.identity.aio import DefaultAzureCredential
from azure.storage.blob.aio import BlobServiceClient

async def upload_async():
    credential = DefaultAzureCredential()
    
    async with BlobServiceClient(account_url, credential=credential) as client:
        blob_client = client.get_blob_client("mycontainer", "sample.txt")
        
        with open("./file.txt", "rb") as data:
            await blob_client.upload_blob(data, overwrite=True)

# Download async
async def download_async():
    async with BlobServiceClient(account_url, credential=credential) as client:
        blob_client = client.get_blob_client("mycontainer", "sample.txt")
        
        stream = await blob_client.download_blob()
        data = await stream.readall()

Best Practices

  1. Use DefaultAzureCredential instead of connection strings
  2. Use context managers for async clients
  3. Set overwrite=True explicitly when re-uploading
  4. Use max_concurrency for large file transfers
  5. Prefer readinto() over readall() for memory efficiency
  6. Use walk_blobs() for hierarchical listing
  7. Set appropriate content types for web-served blobs

适合场景

01

研究助手

02

事实核查

03

知识库问答

04

带来源的搜索总结

能力概览

能力 1

组合搜索和大模型调用

能力 2

支持多来源检索和总结

能力 3

强调引用来源和事实核查

能力 4

适合研究型 Agent 流程

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

80.76%
按下载量换算16,056

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills