[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71BH8YNVMNDZWSHQF3PJSJV":3,"skill-same:01M71BH8YNVMNDZWSHQF3PJSJV":81},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":54,"commitSha":55,"skillDirectory":56,"forksCount":57,"repositoryHtmlUrl":58,"repositoryHomepageUrl":6,"ownerHtmlUrl":59,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":60,"install":61,"resources":74},"01M71BH8YNVMNDZWSHQF3PJSJV","azure-storage-file-datalake-py",null,"Azure Data Lake Storage Gen2 SDK for Python. Use for hierarchical file systems, big data analytics, and file\u002Fdirectory operations.\nTriggers: \"data lake\", \"DataLakeServiceClient\", \"FileSystemClient\", \"ADLS Gen2\", \"hierarchical namespace\".","strmt7\u002Fai_skills_collection_benchmarked","strmt7","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F28989754?v=4","01M71929P914SWKQ7QJV24NBBY","Stratos","01M71929Q9VGKQ7PWYR95VSQQQ",1,"MIT","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fcloud-azure-microsoft-sdks\u002Fofficial-vendor-reference\u002Fazure-storage-file-datalake-py\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"azure storage file datalake py","file","storage","azure storage","datalake","azure","file systems","analytics","data","systems","directory","microsoft","sdk","operations","data analytics","use","big data","triggers","python","for","2026-11-10 10:12:30",false,"---\nname: azure-storage-file-datalake-py\ndescription: |\n  Azure Data Lake Storage Gen2 SDK for Python. Use for hierarchical file systems, big data analytics, and file\u002Fdirectory operations.\n  Triggers: \"data lake\", \"DataLakeServiceClient\", \"FileSystemClient\", \"ADLS Gen2\", \"hierarchical namespace\".\nlicense: MIT\nmetadata:\n  author: Microsoft\n  version: \"1.0.0\"\n  package: azure-storage-file-datalake\n---\n\n# Azure Data Lake Storage Gen2 SDK for Python\n\nHierarchical file system for big data analytics workloads.\n\n## Installation\n\n```bash\npip install azure-storage-file-datalake azure-identity\n```\n\n## Environment Variables\n\n```bash\nAZURE_STORAGE_ACCOUNT_URL=https:\u002F\u002F\u003Caccount>.dfs.core.windows.net\n```\n\n## Authentication\n\n```python\nfrom azure.identity import DefaultAzureCredential\nfrom azure.storage.filedatalake import DataLakeServiceClient\n\ncredential = DefaultAzureCredential()\naccount_url = \"https:\u002F\u002F\u003Caccount>.dfs.core.windows.net\"\n\nservice_client = DataLakeServiceClient(account_url=account_url, credential=credential)\n```\n\n## Client Hierarchy\n\n| Client | Purpose |\n|--------|---------|\n| `DataLakeServiceClient` | Account-level operations |\n| `FileSystemClient` | Container (file system) operations |\n| `DataLakeDirectoryClient` | Directory operations |\n| `DataLakeFileClient` | File operations |\n\n## File System Operations\n\n```python\n# Create file system (container)\nfile_system_client = service_client.create_file_system(\"myfilesystem\")\n\n# Get existing\nfile_system_client = service_client.get_file_system_client(\"myfilesystem\")\n\n# Delete\nservice_client.delete_file_system(\"myfilesystem\")\n\n# List file systems\nfor fs in service_client.list_file_systems():\n    print(fs.name)\n```\n\n## Directory Operations\n\n```python\nfile_system_client = service_client.get_file_system_client(\"myfilesystem\")\n\n# Create directory\ndirectory_client = file_system_client.create_directory(\"mydir\")\n\n# Create nested directories\ndirectory_client = file_system_client.create_directory(\"path\u002Fto\u002Fnested\u002Fdir\")\n\n# Get directory client\ndirectory_client = file_system_client.get_directory_client(\"mydir\")\n\n# Delete directory\ndirectory_client.delete_directory()\n\n# Rename\u002Fmove directory\ndirectory_client.rename_directory(new_name=\"myfilesystem\u002Fnewname\")\n```\n\n## File Operations\n\n### Upload File\n\n```python\n# Get file client\nfile_client = file_system_client.get_file_client(\"path\u002Fto\u002Ffile.txt\")\n\n# Upload from local file\nwith open(\"local-file.txt\", \"rb\") as data:\n    file_client.upload_data(data, overwrite=True)\n\n# Upload bytes\nfile_client.upload_data(b\"Hello, Data Lake!\", overwrite=True)\n\n# Append data (for large files)\nfile_client.append_data(data=b\"chunk1\", offset=0, length=6)\nfile_client.append_data(data=b\"chunk2\", offset=6, length=6)\nfile_client.flush_data(12)  # Commit the data\n```\n\n### Download File\n\n```python\nfile_client = file_system_client.get_file_client(\"path\u002Fto\u002Ffile.txt\")\n\n# Download all content\ndownload = file_client.download_file()\ncontent = download.readall()\n\n# Download to file\nwith open(\"downloaded.txt\", \"wb\") as f:\n    download = file_client.download_file()\n    download.readinto(f)\n\n# Download range\ndownload = file_client.download_file(offset=0, length=100)\n```\n\n### Delete File\n\n```python\nfile_client.delete_file()\n```\n\n## List Contents\n\n```python\n# List paths (files and directories)\nfor path in file_system_client.get_paths():\n    print(f\"{'DIR' if path.is_directory else 'FILE'}: {path.name}\")\n\n# List paths in directory\nfor path in file_system_client.get_paths(path=\"mydir\"):\n    print(path.name)\n\n# Recursive listing\nfor path in file_system_client.get_paths(path=\"mydir\", recursive=True):\n    print(path.name)\n```\n\n## File\u002FDirectory Properties\n\n```python\n# Get properties\nproperties = file_client.get_file_properties()\nprint(f\"Size: {properties.size}\")\nprint(f\"Last modified: {properties.last_modified}\")\n\n# Set metadata\nfile_client.set_metadata(metadata={\"processed\": \"true\"})\n```\n\n## Access Control (ACL)\n\n```python\n# Get ACL\nacl = directory_client.get_access_control()\nprint(f\"Owner: {acl['owner']}\")\nprint(f\"Permissions: {acl['permissions']}\")\n\n# Set ACL\ndirectory_client.set_access_control(\n    owner=\"user-id\",\n    permissions=\"rwxr-x---\"\n)\n\n# Update ACL entries\nfrom azure.storage.filedatalake import AccessControlChangeResult\ndirectory_client.update_access_control_recursive(\n    acl=\"user:user-id:rwx\"\n)\n```\n\n## Async Client\n\n```python\nfrom azure.storage.filedatalake.aio import DataLakeServiceClient\nfrom azure.identity.aio import DefaultAzureCredential\n\nasync def datalake_operations():\n    credential = DefaultAzureCredential()\n\n    async with DataLakeServiceClient(\n        account_url=\"https:\u002F\u002F\u003Caccount>.dfs.core.windows.net\",\n        credential=credential\n    ) as service_client:\n        file_system_client = service_client.get_file_system_client(\"myfilesystem\")\n        file_client = file_system_client.get_file_client(\"test.txt\")\n\n        await file_client.upload_data(b\"async content\", overwrite=True)\n\n        download = await file_client.download_file()\n        content = await download.readall()\n\nimport asyncio\nasyncio.run(datalake_operations())\n```\n\n## Best Practices\n\n1. **Use hierarchical namespace** for file system semantics\n2. **Use `append_data` + `flush_data`** for large file uploads\n3. **Set ACLs at directory level** and inherit to children\n4. **Use async client** for high-throughput scenarios\n5. **Use `get_paths` with `recursive=True`** for full directory listing\n6. **Set metadata** for custom file attributes\n7. **Consider Blob API** for simple object storage use cases\n","# Azure Data Lake Storage Gen2 SDK for Python\n\nHierarchical file system for big data analytics workloads.\n\n## Installation\n\n```bash\npip install azure-storage-file-datalake azure-identity\n```\n\n## Environment Variables\n\n```bash\nAZURE_STORAGE_ACCOUNT_URL=https:\u002F\u002F\u003Caccount>.dfs.core.windows.net\n```\n\n## Authentication\n\n```python\nfrom azure.identity import DefaultAzureCredential\nfrom azure.storage.filedatalake import DataLakeServiceClient\n\ncredential = DefaultAzureCredential()\naccount_url = \"https:\u002F\u002F\u003Caccount>.dfs.core.windows.net\"\n\nservice_client = DataLakeServiceClient(account_url=account_url, credential=credential)\n```\n\n## Client Hierarchy\n\n| Client | Purpose |\n|--------|---------|\n| `DataLakeServiceClient` | Account-level operations |\n| `FileSystemClient` | Container (file system) operations |\n| `DataLakeDirectoryClient` | Directory operations |\n| `DataLakeFileClient` | File operations |\n\n## File System Operations\n\n```python\n# Create file system (container)\nfile_system_client = service_client.create_file_system(\"myfilesystem\")\n\n# Get existing\nfile_system_client = service_client.get_file_system_client(\"myfilesystem\")\n\n# Delete\nservice_client.delete_file_system(\"myfilesystem\")\n\n# List file systems\nfor fs in service_client.list_file_systems():\n    print(fs.name)\n```\n\n## Directory Operations\n\n```python\nfile_system_client = service_client.get_file_system_client(\"myfilesystem\")\n\n# Create directory\ndirectory_client = file_system_client.create_directory(\"mydir\")\n\n# Create nested directories\ndirectory_client = file_system_client.create_directory(\"path\u002Fto\u002Fnested\u002Fdir\")\n\n# Get directory client\ndirectory_client = file_system_client.get_directory_client(\"mydir\")\n\n# Delete directory\ndirectory_client.delete_directory()\n\n# Rename\u002Fmove directory\ndirectory_client.rename_directory(new_name=\"myfilesystem\u002Fnewname\")\n```\n\n## File Operations\n\n### Upload File\n\n```python\n# Get file client\nfile_client = file_system_client.get_file_client(\"path\u002Fto\u002Ffile.txt\")\n\n# Upload from local file\nwith open(\"local-file.txt\", \"rb\") as data:\n    file_client.upload_data(data, overwrite=True)\n\n# Upload bytes\nfile_client.upload_data(b\"Hello, Data Lake!\", overwrite=True)\n\n# Append data (for large files)\nfile_client.append_data(data=b\"chunk1\", offset=0, length=6)\nfile_client.append_data(data=b\"chunk2\", offset=6, length=6)\nfile_client.flush_data(12)  # Commit the data\n```\n\n### Download File\n\n```python\nfile_client = file_system_client.get_file_client(\"path\u002Fto\u002Ffile.txt\")\n\n# Download all content\ndownload = file_client.download_file()\ncontent = download.readall()\n\n# Download to file\nwith open(\"downloaded.txt\", \"wb\") as f:\n    download = file_client.download_file()\n    download.readinto(f)\n\n# Download range\ndownload = file_client.download_file(offset=0, length=100)\n```\n\n### Delete File\n\n```python\nfile_client.delete_file()\n```\n\n## List Contents\n\n```python\n# List paths (files and directories)\nfor path in file_system_client.get_paths():\n    print(f\"{'DIR' if path.is_directory else 'FILE'}: {path.name}\")\n\n# List paths in directory\nfor path in file_system_client.get_paths(path=\"mydir\"):\n    print(path.name)\n\n# Recursive listing\nfor path in file_system_client.get_paths(path=\"mydir\", recursive=True):\n    print(path.name)\n```\n\n## File\u002FDirectory Properties\n\n```python\n# Get properties\nproperties = file_client.get_file_properties()\nprint(f\"Size: {properties.size}\")\nprint(f\"Last modified: {properties.last_modified}\")\n\n# Set metadata\nfile_client.set_metadata(metadata={\"processed\": \"true\"})\n```\n\n## Access Control (ACL)\n\n```python\n# Get ACL\nacl = directory_client.get_access_control()\nprint(f\"Owner: {acl['owner']}\")\nprint(f\"Permissions: {acl['permissions']}\")\n\n# Set ACL\ndirectory_client.set_access_control(\n    owner=\"user-id\",\n    permissions=\"rwxr-x---\"\n)\n\n# Update ACL entries\nfrom azure.storage.filedatalake import AccessControlChangeResult\ndirectory_client.update_access_control_recursive(\n    acl=\"user:user-id:rwx\"\n)\n```\n\n## Async Client\n\n```python\nfrom azure.storage.filedatalake.aio import DataLakeServiceClient\nfrom azure.identity.aio import DefaultAzureCredential\n\nasync def datalake_operations():\n    credential = DefaultAzureCredential()\n\n    async with DataLakeServiceClient(\n        account_url=\"https:\u002F\u002F\u003Caccount>.dfs.core.windows.net\",\n        credential=credential\n    ) as service_client:\n        file_system_client = service_client.get_file_system_client(\"myfilesystem\")\n        file_client = file_system_client.get_file_client(\"test.txt\")\n\n        await file_client.upload_data(b\"async content\", overwrite=True)\n\n        download = await file_client.download_file()\n        content = await download.readall()\n\nimport asyncio\nasyncio.run(datalake_operations())\n```\n\n## Best Practices\n\n1. **Use hierarchical namespace** for file system semantics\n2. **Use `append_data` + `flush_data`** for large file uploads\n3. **Set ACLs at directory level** and inherit to children\n4. **Use async client** for high-throughput scenarios\n5. **Use `get_paths` with `recursive=True`** for full directory listing\n6. **Set metadata** for custom file attributes\n7. **Consider Blob API** for simple object storage use cases\n",{"name":5,"license":15,"metadata":49,"description":53},{"author":50,"package":51,"version":52},"Microsoft","azure-storage-file-datalake","1.0.0","Azure Data Lake Storage Gen2 SDK for Python. 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Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML\u002FCSS layouts, or when styling\u002Fbeautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fsearch-retrieval-web-automation\u002Fofficial-reference\u002Ffrontend-design\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fsearch-retrieval-web-automation\u002Fofficial-reference\u002Ffrontend-design\u002FSKILL.md",[201,202,205],{"categoryNo":96,"categoryName":97,"taxonomyType":93,"taxonomyTypeDesc":94},{"categoryNo":203,"categoryName":204,"taxonomyType":93,"taxonomyTypeDesc":94},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":206,"categoryName":207,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000032","设计师",[104,209,210,184,211,212,213,102,214,215,39,132,181,216,188,217,189,218,219,109],"design","frontend design","ui design","generic","aesthetics","landing","pages","code","web ui","react components","examples",{"skillNo":221,"name":222,"nameZh":6,"description":223,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":224,"categories":225,"keywords":226,"publishedAt":44},"01M71CVZ54WFBTVA7R16PFY1ZE","zarr-python","Chunked N-D arrays for cloud storage. Compressed arrays, parallel I\u002FO, S3\u002FGCS integration, NumPy\u002FDask\u002FXarray compatible, for large-scale scientific computing pipelines.","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fscience-research-data-analysis\u002Flatest-release-community\u002Fzarr-python\u002FSKILL.md",[],[227,42,228,229,230,231,26,232,233,43,234,235,236,237,238,239,240,241],"zarr python","zarr","arrays","Cloud Storage","scientific","parallel","dask","numpy","gcs","s3","integration","scientific computing","cloud","scale","pipelines"]