Design a set of services for processing bond deal streams.

To process a stream of bond transactions, you can design a set of microservices, each responsible for a specific stage of processing:

1. Transaction reception service — receives incoming transaction data (e.g., via REST API or message queue).
2. Validation service — checks the correctness of transaction data (format, mandatory fields, business rules).
3. Data enrichment service — adds additional information, such as current rates, issuer ratings.
4. Risk and metric calculation service — computes key indicators for each transaction.
5. Storage service — saves transactions and processing results in a database.
6. Notification and reporting service — sends notifications to interested systems or generates reports.

For implementation, you can use Python with frameworks like FastAPI for API, Celery for asynchronous processing, and databases like PostgreSQL or NoSQL, depending on data structure requirements.

Example of a simple transaction reception service using FastAPI:

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class Deal(BaseModel):
    bond_id: str
    quantity: int
    price: float
    trade_date: str

@app.post("/deals")
async def receive_deal(deal: Deal):
    # Here you can send the deal to a queue for further processing
    return {"status": "received", "deal": deal}

This approach ensures scalability, separation of responsibilities, and ease of maintenance.