API design & gRPC
REST best practices, protobuf, API versioning, and backward-compatible service contracts.
Build a Bulk Array POST Mock Server in Python
Creates an HTTP mock server that accepts POST requests with a JSON array and returns incremental IDs for each item.
import json
from http.server import BaseHTTPRequestHandler, HTTPServer
from urllib.parse import urlparse
class MockHandler(BaseHTTPRequestHandler):
def do_POST(self):
if urlparse(self.path).path != "/bulk":
self.send_response(404)
self.end_headers()
return
cont…
How to Build a Batch Operations Multi-Status 207 Mock Server in Python
Build a mock HTTP server that accepts a batch of operations and returns HTTP 207 Multi-Status with per-operation status codes in JSON.
from http.server import BaseHTTPRequestHandler, HTTPServer
import json
class BatchHandler(BaseHTTPRequestHandler):
def do_POST(self):
if self.path != "/batch":
self.send_response(404)
self.end_headers()
return
content_length = int(self.headers.get("Content-Leng…
How to Build a Hypermedia Collection Resource in Python
Creates a paginated hypermedia collection resource with HATEOAS links and embedded items.
import json
import math
class HypermediaCollection:
"""A mock hypermedia collection resource."""
def __init__(self, items, base_url="/api/items"):
self.items = items
self.base_url = base_url
def to_dict(self, page=1, per_page=3):
total = len(self.items)
pages = math.ceil…
How to Build a Mock REST GET Endpoint Handler in Python
Create a lightweight mock REST GET server in Python using the standard library, with a dict-based route registry that maps paths to handler functions and returns JSON responses with proper HTTP status codes.
from http.server import BaseHTTPRequestHandler, HTTPServer
import json
# Mock API handler registry
def handle_users():
return {"status": "ok", "data": [{"id": 1, "name": "Alice"}, {"id": 2, "name": "Bob"}]}
def handle_products():
return {"status": "ok", "data": [{"id": 101, "name": "Laptop", "price": 999.99}…
How to Implement Content Negotiation with JSON and XML in Python
Build an HTTP server that returns JSON or XML responses based on the client's Accept header, with a 406 response for unsupported formats.
import json
import xml.etree.ElementTree as ET
from http.server import BaseHTTPRequestHandler, HTTPServer
class RequestHandler(BaseHTTPRequestHandler):
def do_GET(self):
data = {"message": "Hello, world!"}
accept_header = self.headers.get("Accept", "")
if "application/json" in accept_hea…
How to Validate Request Body JSON Against a Schema in Python
Build a lightweight schema validator to check required fields, types, string lengths, allowed values, and nested objects in a JSON request body.
import json
def validate_against_schema(data, schema, path=""):
errors = []
if not isinstance(data, dict):
errors.append(f"{path}: expected object, got {type(data).__name__}")
return errors
for field, rules in schema.items():
field_path = f"{path}.{field}" if path else field
…
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