feat: add marketplace metrics, privacy features, and service registry endpoints

- Add Prometheus metrics for marketplace API throughput and error rates with new dashboard panels
- Implement confidential transaction models with encryption support and access control
- Add key management system with registration, rotation, and audit logging
- Create services and registry routers for service discovery and management
- Integrate ZK proof generation for privacy-preserving receipts
- Add metrics instru
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---
title: Python SDK
description: Python SDK for AITBC platform integration
---
# Python SDK
The AITBC Python SDK provides a convenient way to interact with the AITBC platform from Python applications. It includes support for job management, marketplace operations, wallet management, and more.
## Installation
```bash
# Install from PyPI
pip install aitbc
# Or install from source
git clone https://github.com/aitbc/python-sdk.git
cd python-sdk
pip install -e .
```
## Quick Start
```python
from aitbc import AITBCClient
# Initialize the client
client = AITBCClient(
api_key="your_api_key_here",
base_url="https://api.aitbc.io" # or http://localhost:8011 for dev
)
# Create a job
job = client.jobs.create({
"name": "image-classification",
"type": "ai-inference",
"model": {
"type": "python",
"entrypoint": "model.py"
}
})
# Wait for completion
result = client.jobs.wait_for_completion(job["job_id"])
print(f"Result: {result}")
```
## Configuration
### Environment Variables
```bash
export AITBC_API_KEY="your_api_key"
export AITBC_BASE_URL="https://api.aitbc.io"
export AITBC_NETWORK="mainnet" # or testnet
```
### Code Configuration
```python
from aitbc import AITBCClient, Config
# Using Config object
config = Config(
api_key="your_api_key",
base_url="https://api.aitbc.io",
timeout=30,
retries=3
)
client = AITBCClient(config=config)
```
## Jobs API
### Create a Job
```python
# Basic job creation
job = client.jobs.create({
"name": "my-ai-job",
"type": "ai-inference",
"model": {
"type": "python",
"entrypoint": "model.py",
"requirements": ["numpy", "torch"]
},
"input": {
"type": "image",
"format": "jpeg"
},
"output": {
"type": "json"
},
"resources": {
"cpu": "1000m",
"memory": "2Gi"
},
"pricing": {
"max_cost": "0.10"
}
})
print(f"Job created: {job['job_id']}")
```
### Upload Job Data
```python
# Upload input files
with open("input.jpg", "rb") as f:
client.jobs.upload_input(job["job_id"], f, "image.jpg")
# Or upload multiple files
files = [
("image1.jpg", open("image1.jpg", "rb")),
("image2.jpg", open("image2.jpg", "rb"))
]
client.jobs.upload_inputs(job["job_id"], files)
```
### Monitor Job Progress
```python
# Get job status
status = client.jobs.get_status(job["job_id"])
print(f"Status: {status['status']}")
# Stream updates
for update in client.jobs.stream_updates(job["job_id"]):
print(f"Update: {update}")
# Wait for completion with timeout
result = client.jobs.wait_for_completion(
job["job_id"],
timeout=300, # 5 minutes
poll_interval=5
)
```
### Get Results
```python
# Get job results
results = client.jobs.get_results(job["job_id"])
print(f"Results: {results}")
# Download output files
client.jobs.download_output(job["job_id"], "output/")
client.jobs.download_outputs(job["job_id"], "outputs/") # All files
```
## Marketplace API
### List Available Offers
```python
# List all offers
offers = client.marketplace.list_offers()
# Filter by job type
offers = client.marketplace.list_offers(
job_type="image-classification",
max_price="0.01"
)
for offer in offers:
print(f"Offer: {offer['offer_id']}, Price: {offer['price']}")
```
### Create and Manage Offers
```python
# Create an offer (as a miner)
offer = client.marketplace.create_offer({
"job_type": "image-classification",
"price": "0.001",
"max_jobs": 10,
"requirements": {
"min_gpu_memory": "4Gi"
}
})
# Update offer
client.marketplace.update_offer(
offer["offer_id"],
price="0.002"
)
# Cancel offer
client.marketplace.cancel_offer(offer["offer_id"])
```
### Accept Offers
```python
# Accept an offer for your job
transaction = client.marketplace.accept_offer(
offer_id="offer_123",
job_id="job_456",
bid_price="0.001"
)
print(f"Transaction: {transaction['transaction_id']}")
```
## Wallet API
### Wallet Management
```python
# Create a new wallet
wallet = client.wallet.create()
print(f"Address: {wallet['address']}")
# Import existing wallet
wallet = client.wallet.import_private_key("your_private_key")
# Get wallet info
balance = client.wallet.get_balance()
address = client.wallet.get_address()
```
### Transactions
```python
# Send tokens
tx = client.wallet.send(
to="0x123...",
amount="1.0",
token="AITBC"
)
# Stake tokens
client.wallet.stake(amount="100.0")
# Unstake tokens
client.wallet.unstake(amount="50.0")
# Get transaction history
history = client.wallet.get_transactions(limit=50)
```
## Receipts API
### Verify Receipts
```python
# Get a receipt
receipt = client.receipts.get(job_id="job_123")
# Verify a receipt
verification = client.receipts.verify(receipt)
print(f"Valid: {verification['valid']}")
# Verify with local verification
from aitbc.crypto import verify_receipt
is_valid = verify_receipt(receipt)
```
### Stream Receipts
```python
# Stream new receipts
for receipt in client.receipts.stream():
print(f"New receipt: {receipt['receipt_id']}")
```
## WebSocket API
### Real-time Updates
```python
# Connect to WebSocket
ws = client.websocket.connect()
# Subscribe to job updates
ws.subscribe("jobs", job_id="job_123")
# Subscribe to marketplace updates
ws.subscribe("marketplace")
# Handle messages
@ws.on_message
def handle_message(message):
print(f"Received: {message}")
# Start listening
ws.listen()
```
### Advanced WebSocket Usage
```python
# Custom event handlers
ws = client.websocket.connect()
@ws.on_job_update
def on_job_update(job_id, status):
print(f"Job {job_id} status: {status}")
@ws.on_marketplace_update
def on_marketplace_update(update_type, data):
print(f"Marketplace {update_type}: {data}")
# Run with context manager
with client.websocket.connect() as ws:
ws.subscribe("jobs")
ws.listen(timeout=60)
```
## Error Handling
```python
from aitbc.exceptions import (
AITBCError,
APIError,
AuthenticationError,
NotFoundError,
RateLimitError
)
try:
job = client.jobs.create({...})
except AuthenticationError:
print("Invalid API key")
except RateLimitError as e:
print(f"Rate limited. Retry in {e.retry_after} seconds")
except APIError as e:
print(f"API error: {e.message}")
except AITBCError as e:
print(f"AITBC error: {e}")
```
## Advanced Usage
### Custom HTTP Client
```python
import requests
from aitbc import AITBCClient
# Use custom session
session = requests.Session()
session.headers.update({"User-Agent": "MyApp/1.0"})
client = AITBCClient(
api_key="your_key",
session=session
)
```
### Async Support
```python
import asyncio
from aitbc import AsyncAITBCClient
async def main():
client = AsyncAITBCClient(api_key="your_key")
# Create job
job = await client.jobs.create({...})
# Wait for completion
result = await client.jobs.wait_for_completion(job["job_id"])
print(f"Result: {result}")
asyncio.run(main())
```
### Batch Operations
```python
# Create multiple jobs
jobs = [
{"name": f"job-{i}", "type": "ai-inference"}
for i in range(10)
]
created_jobs = client.jobs.create_batch(jobs)
# Get status of multiple jobs
statuses = client.jobs.get_status_batch([
job["job_id"] for job in created_jobs
])
```
## Testing
### Mock Client for Testing
```python
from aitbc.testing import MockAITBCClient
# Use mock client for tests
client = MockAITBCClient()
# Configure responses
client.jobs.set_response("create", {"job_id": "test_job"})
# Test your code
job = client.jobs.create({...})
assert job["job_id"] == "test_job"
```
### Integration Tests
```python
import pytest
from aitbc import AITBCClient
@pytest.fixture
def client():
return AITBCClient(
api_key="test_key",
base_url="http://localhost:8011"
)
def test_job_creation(client):
job = client.jobs.create({
"name": "test-job",
"type": "ai-inference"
})
assert "job_id" in job
```
## Best Practices
### 1. Configuration Management
```python
# Use environment variables
import os
from aitbc import AITBCClient
client = AITBCClient(
api_key=os.getenv("AITBC_API_KEY"),
base_url=os.getenv("AITBC_BASE_URL", "https://api.aitbc.io")
)
```
### 2. Error Handling
```python
# Always handle potential errors
try:
result = client.jobs.get_results(job_id)
except NotFoundError:
print("Job not found")
except APIError as e:
print(f"API error: {e}")
```
### 3. Resource Management
```python
# Use context managers for resources
with client.jobs.upload_context(job_id) as ctx:
ctx.upload_file("model.py")
ctx.upload_file("requirements.txt")
```
### 4. Performance
```python
# Use async for concurrent operations
async def process_jobs(job_ids):
client = AsyncAITBCClient(api_key="your_key")
tasks = [
client.jobs.get_results(job_id)
for job_id in job_ids
]
results = await asyncio.gather(*tasks)
return results
```
## Examples
Check out the [examples directory](https://github.com/aitbc/python-sdk/tree/main/examples) for complete working examples:
- [Basic Job Submission](https://github.com/aitbc/python-sdk/blob/main/examples/basic_job.py)
- [Marketplace Bot](https://github.com/aitbc/python-sdk/blob/main/examples/marketplace_bot.py)
- [Mining Operation](https://github.com/aitbc/python-sdk/blob/main/examples/mining.py)
- [WebSocket Streaming](https://github.com/aitbc/python-sdk/blob/main/examples/websocket_streaming.py)
## Support
- 📖 [Documentation](../../)
- 🐛 [Issue Tracker](https://github.com/aitbc/python-sdk/issues)
- 💬 [Discord](https://discord.gg/aitbc)
- 📧 [python-sdk@aitbc.io](mailto:python-sdk@aitbc.io)
## Changelog
See [CHANGELOG.md](https://github.com/aitbc/python-sdk/blob/main/CHANGELOG.md) for version history and updates.