feat: Add Official Microsoft & Gemini Skills (845+ Total)
🚀 Impact Significantly expands the capabilities of **Antigravity Awesome Skills** by integrating official skill collections from **Microsoft** and **Google Gemini**. This update increases the total skill count to **845+**, making the library even more comprehensive for AI coding assistants. ✨ Key Changes 1. New Official Skills - **Microsoft Skills**: Added a massive collection of official skills from [microsoft/skills](https://github.com/microsoft/skills). - Includes Azure, .NET, Python, TypeScript, and Semantic Kernel skills. - Preserves the original directory structure under `skills/official/microsoft/`. - Includes plugin skills from the `.github/plugins` directory. - **Gemini Skills**: Added official Gemini API development skills under `skills/gemini-api-dev/`. 2. New Scripts & Tooling - **`scripts/sync_microsoft_skills.py`**: A robust synchronization script that: - Clones the official Microsoft repository. - Preserves the original directory heirarchy. - Handles symlinks and plugin locations. - Generates attribution metadata. - **`scripts/tests/inspect_microsoft_repo.py`**: Debug tool to inspect the remote repository structure. - **`scripts/tests/test_comprehensive_coverage.py`**: Verification script to ensure 100% of skills are captured during sync. 3. Core Improvements - **`scripts/generate_index.py`**: Enhanced frontmatter parsing to safely handle unquoted values containing `@` symbols and commas (fixing issues with some Microsoft skill descriptions). - **`package.json`**: Added `sync:microsoft` and `sync:all-official` scripts for easy maintenance. 4. Documentation - Updated `README.md` to reflect the new skill counts (845+) and added Microsoft/Gemini to the provider list. - Updated `CATALOG.md` and `skills_index.json` with the new skills. 🧪 Verification - Ran `scripts/tests/test_comprehensive_coverage.py` to verify all Microsoft skills are detected. - Validated `generate_index.py` fixes by successfully indexing the new skills.
This commit is contained in:
Ahmed Rehan
219
skills/official/microsoft/python/data/blob/SKILL.md
Normal file
219
skills/official/microsoft/python/data/blob/SKILL.md
Normal file
@@ -0,0 +1,219 @@
|
||||
---
|
||||
name: azure-storage-blob-py
|
||||
description: |
|
||||
Azure Blob Storage SDK for Python. Use for uploading, downloading, listing blobs, managing containers, and blob lifecycle.
|
||||
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
|
||||
|
||||
```bash
|
||||
pip install azure-storage-blob azure-identity
|
||||
```
|
||||
|
||||
## Environment Variables
|
||||
|
||||
```bash
|
||||
AZURE_STORAGE_ACCOUNT_NAME=<your-storage-account>
|
||||
# Or use full URL
|
||||
AZURE_STORAGE_ACCOUNT_URL=https://<account>.blob.core.windows.net
|
||||
```
|
||||
|
||||
## Authentication
|
||||
|
||||
```python
|
||||
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
|
||||
|
||||
| Client | Purpose | Get From |
|
||||
|--------|---------|----------|
|
||||
| `BlobServiceClient` | Account-level operations | Direct instantiation |
|
||||
| `ContainerClient` | Container operations | `blob_service_client.get_container_client()` |
|
||||
| `BlobClient` | Single blob operations | `container_client.get_blob_client()` |
|
||||
|
||||
## Core Workflow
|
||||
|
||||
### Create Container
|
||||
|
||||
```python
|
||||
container_client = blob_service_client.get_container_client("mycontainer")
|
||||
container_client.create_container()
|
||||
```
|
||||
|
||||
### Upload Blob
|
||||
|
||||
```python
|
||||
# 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
|
||||
|
||||
```python
|
||||
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
|
||||
|
||||
```python
|
||||
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
|
||||
|
||||
```python
|
||||
blob_client.delete_blob()
|
||||
|
||||
# Delete with snapshots
|
||||
blob_client.delete_blob(delete_snapshots="include")
|
||||
```
|
||||
|
||||
## Performance Tuning
|
||||
|
||||
```python
|
||||
# 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
|
||||
|
||||
```python
|
||||
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
|
||||
|
||||
```python
|
||||
# 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
|
||||
|
||||
```python
|
||||
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
|
||||
Reference in New Issue
Block a user