1from fastapi import APIRouter, Query, Depends, Response, status
2from pydantic import BaseModel, Field
3from typing import Optional
4from sqlalchemy.orm import Session
5from app.models import ServiceCatalogEntry, ServiceType, ServiceTier
6from app.deps import get_db, encode_cursor, decode_cursor
7import hashlib
8import json
9
10router = APIRouter(prefix="/api/catalog", tags=["catalog"])
11
12class ListServicesQuery(BaseModel):
13    service_type: Optional[ServiceType] = None
14    tier: Optional[ServiceTier] = None
15    owner_team: Optional[str] = Field(default=None, max_length=64)
16    name_contains: Optional[str] = Field(default=None, max_length=64)
17    include_deprecated: bool = False
18    cursor: Optional[str] = None
19    page_size: int = Field(default=25, ge=1, le=100)
20
21class ServiceListResponse(BaseModel):
22    items: list[ServiceCatalogEntry]
23    next_cursor: Optional[str]
24    total_estimate: int
25
26@router.get("/services", response_model=ServiceListResponse)
27def list_services(
28    response: Response,
29    q: ListServicesQuery = Depends(),
30    db: Session = Depends(get_db),
31) -> ServiceListResponse:
32    stmt = db.query(ServiceCatalogEntry)
33    if q.service_type:
34        stmt = stmt.filter(ServiceCatalogEntry.service_type == q.service_type)
35    if q.tier:
36        stmt = stmt.filter(ServiceCatalogEntry.tier == q.tier)
37    if q.owner_team:
38        stmt = stmt.filter(ServiceCatalogEntry.owner_team == q.owner_team)
39    if q.name_contains:
40        stmt = stmt.filter(ServiceCatalogEntry.name.ilike(f"%{q.name_contains}%"))
41    if not q.include_deprecated:
42        stmt = stmt.filter(ServiceCatalogEntry.deprecated == False)  # noqa: E712
43
44    if q.cursor:
45        last_id = decode_cursor(q.cursor)
46        stmt = stmt.filter(ServiceCatalogEntry.service_id > last_id)
47
48    stmt = stmt.order_by(ServiceCatalogEntry.service_id)
49    rows = stmt.limit(q.page_size + 1).all()
50
51    next_cursor = None
52    if len(rows) > q.page_size:
53        next_cursor = encode_cursor(rows[q.page_size - 1].service_id)
54        rows = rows[: q.page_size]
55
56    body = ServiceListResponse(
57        items=rows, next_cursor=next_cursor, total_estimate=len(rows),
58    )
59    etag = hashlib.sha256(
60        json.dumps([r.service_id for r in rows], sort_keys=True).encode()
61    ).hexdigest()[:16]
62    response.headers["ETag"] = f'W/"{etag}"'
63    return body

• Lines 1–10: Import the FastAPI primitives, the Pydantic catalog models defined alongside this section's lab, and helper functions for cursor encoding. hashlib and json are used to compute a weak ETag over the result set.
• Lines 13–22: ListServicesQuery binds query parameters into a typed object. Every filter is optional, validated for length, and page_size is bounded between 1 and 100 to protect the server from a client requesting tens of thousands of rows in one call.
• Lines 25–28: ServiceListResponse wraps the page in a stable shape: an items array, an opaque cursor token, and a total_estimate field that downstream UIs can use to render approximate result counts without forcing the database to compute exact counts on every page.
• Lines 31–37: The list_services endpoint declares its query model as a FastAPI dependency, which automatically translates query string parameters into a validated ListServicesQuery instance.
• Lines 38–46: Each filter is conditionally applied to the SQLAlchemy query. The ilike pattern for name_contains is case-insensitive but should be backed by a trigram index in PostgreSQL for any catalog larger than a few hundred entries—without the index, every list request scans the full table.
• Lines 48–53: Cursor pagination uses the service_id as the key. Because service_id is unique and we order by it, the cursor cleanly resumes from where the previous page ended. Concurrent inserts of new services with service_id lexicographically before the cursor do not affect the in-progress pagination, which is the failure mode that offset pagination cannot survive.
• Lines 56–62: The query fetches page_size + 1 rows. If we received an extra row, there is at least one more page; we encode the last in-page row's service_id as the next cursor and trim the extra row off the response.
• Lines 64–72: The weak ETag header summarizes the page contents. A weak ETag (prefixed with W/) signals to caches that semantically equivalent representations may share the tag, which is appropriate when the server is allowed to choose its own ordering for ties.

1from fastapi import HTTPException, Header
2
3@router.get("/services/{service_id}", response_model=ServiceCatalogEntry)
4def get_service(
5    service_id: str,
6    response: Response,
7    if_none_match: Optional[str] = Header(default=None),
8    db: Session = Depends(get_db),
9) -> ServiceCatalogEntry:
10    entry = db.query(ServiceCatalogEntry).filter_by(service_id=service_id).first()
11    if entry is None:
12        raise HTTPException(status_code=404, detail=f"service '{service_id}' not found")
13
14    etag = f'W/"{entry.version}-{int(entry.updated_at.timestamp())}"'
15    if if_none_match and if_none_match == etag:
16        response.status_code = status.HTTP_304_NOT_MODIFIED
17        return None
18    response.headers["ETag"] = etag
19    return entry

• Lines 3–9: The endpoint accepts If-None-Match as an HTTP header. FastAPI's Header dependency normalizes the header name (if-none-match ↔ If-None-Match) and exposes it as a regular Python parameter.
• Lines 10–12: A missing entry raises HTTPException(404). The detail string includes the requested service_id so client logs are immediately actionable.
• Lines 14–18: The ETag is composed of the entry's semantic version and the unix timestamp of the last update. Any change to either field produces a different tag. When the client sends a matching If-None-Match, the server returns 304 Not Modified with no body, which is the cheapest possible response.

1class CatalogSearchResult(BaseModel):
2    services: list[ServiceCatalogEntry]
3    golden_paths: list[GoldenPathDefinition]
4
5@router.get("/search", response_model=CatalogSearchResult)
6def search_catalog(
7    text: str = Query(min_length=2, max_length=64),
8    owner_team: Optional[str] = None,
9    db: Session = Depends(get_db),
10) -> CatalogSearchResult:
11    services_q = db.query(ServiceCatalogEntry).filter(
12        ServiceCatalogEntry.name.ilike(f"%{text}%")
13        | ServiceCatalogEntry.description.ilike(f"%{text}%")
14    )
15    if owner_team:
16        services_q = services_q.filter(ServiceCatalogEntry.owner_team == owner_team)
17    services = services_q.limit(20).all()
18
19    paths_q = db.query(GoldenPathDefinition).filter(
20        GoldenPathDefinition.name.ilike(f"%{text}%")
21        | GoldenPathDefinition.description.ilike(f"%{text}%")
22    )
23    paths = paths_q.limit(20).all()
24
25    return CatalogSearchResult(services=services, golden_paths=paths)

• Lines 1–3: CatalogSearchResult packages both result types in a single response. Keeping them in distinct arrays preserves the type information that the UI uses to render different cards for services versus golden paths.
• Lines 6–11: The search_catalog endpoint requires a minimum query length of 2 characters to avoid expensive full-table scans on empty queries, and caps the maximum length at 64 to keep query plans bounded.
• Lines 12–18: Service search performs an ILIKE against both name and description with a single OR-combined predicate. PostgreSQL's GIN trigram indexes (pg_trgm) make this efficient even on large catalogs; without trigram indexing, switch the predicate to a tsvector full-text search.
• Lines 20–26: Golden path search uses the same shape against the path registry. The hard cap at 20 results per kind keeps the response small enough that the developer portal can render it inline without virtualization.