API design & gRPC
REST best practices, protobuf, API versioning, and backward-compatible service contracts.
Create a Data Helper in Python for gRPC-style APIs
This code builds a simple DataHelper class that mimics gRPC request/response handling with in-memory storage, JSON serialization, and basic CRUD operations for beginners.
import json
from dataclasses import dataclass, asdict
from typing import Dict, Any
@dataclass
class User:
user_id: int
name: str
email: str
class DataHelper:
"""Simple helper to demonstrate gRPC-like data handling for beginners."""
def __init__(self) -> None:
self._users: Dict[int, Use…Format data in Python using dataclasses like gRPC messages
Convert Python dataclasses to and from dicts and format them gRPC-style for clean data handling.
from dataclasses import dataclass
from typing import Any, Dict, List, Optional
@dataclass
class ProductInfo:
"""Data class representing a gRPC-style product message."""
name: str
price: float
tags: List[str]
description: Optional[str] = None
def to_dict(self) -> Dict[str, Any]:
"""C…How to Add HATEOAS Links to a Python API Response
Build a Python API resource class that adds self and next HATEOAS links to JSON responses, with a mock example for pagination.
import json
class Resource:
def __init__(self, name, data, next_page=None):
self.links = {"self": f"/api/resources/{name}"}
if next_page is not None:
self.links["next"] = f"/api/resources?page={next_page}"
self.data = data
def to_dict(self):
return {"links": self.…How to Build a Data Helper Class in Python for Beginners
Create a beginner-friendly DataHelper class that stores, retrieves, filters, and summarizes records in a list of dictionaries.
from __future__ import annotations
import json
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional
@dataclass
class DataHelper:
"""A beginner-friendly helper for common data tasks."""
data: List[Dict[str, Any]] = field(default_factory=list)
def add_record(self, record…How to Build a Simple Data Helper in Python for API Design
Create a beginner-friendly DataHelper class that demonstrates basic CRUD operations (add, get, list, remove) using an in-memory dictionary, ideal for learning API design concepts.
class DataHelper:
"""Simple data helper for beginners learning API design concepts."""
def __init__(self):
self._data = {}
def add_record(self, key, value):
"""Add a record to the store."""
self._data[key] = value
return f"Added: {key} -> {value}"
def get_…How to Build a Simple Filter Helper in Python for API Design
Create a reusable data filter service with dataclasses that mimics gRPC request/response patterns for filtering dataset records.
from dataclasses import dataclass, field
from typing import List, Optional, Dict, Any
@dataclass
class FilterRequest:
"""A simple filter request mirroring a gRPC message structure."""
field_name: str
operator: str # eq, ne, gt, lt, contains
value: Any
page_size: int = 10
page_token: Optional…How to Build a Simple gRPC-Style Data Service in Python
Create a beginner-friendly gRPC-style service with dataclasses to simulate GetUser and CreateUser RPCs.
from dataclasses import dataclass
from typing import Optional
@dataclass
class User:
id: int
name: str
email: str
class UserService:
"""Simple gRPC-style service contract for beginner learners."""
def get_user(self, user_id: int) -> Optional[User]:
"""Simulated gRPC GetUser RPC."""
…How to Expand Related Resources with a Mock Embed in Python
Simulate API response embedding by attaching mock embedded data to each related resource in a list using a simple Python class.
import json
class EmbedMock:
def __init__(self, resources):
self.resources = resources
def expand(self):
for resource in self.resources:
resource["embedded"] = self._generate_embed()
def _generate_embed(self):
return {
"id": 1,
"type": "mock",
…How to Implement Sparse Fieldsets in Python
A function that filters API responses by resource type, returning only requested fields plus IDs, as a sparse fieldset mock.
from dataclasses import dataclass, field
from typing import Dict, List, Optional
@dataclass
class MockResponse:
data: Dict[str, object] = field(default_factory=dict)
included: List[Dict[str, object]] = field(default_factory=list)
def select_fields(
data: Dict[str, object],
sparse_fields: Optional[D…How to Serialize a Dataclass to JSON in Python
Serialize a Python dataclass instance to JSON using asdict and json.dumps for API responses or mocks.
from dataclasses import dataclass, asdict
import json
@dataclass
class UserResponse:
id: int
name: str
email: str
active: bool = True
if __name__ == "__main__":
response = UserResponse(id=42, name="Ada Lovelace", email="ada@example.com")
print(json.dumps(asdict(response), indent=2))How to Validate Data in Python for Beginners
A beginner-friendly Python class for validating required fields, types, ranges, and allowed choices in dict payloads.
import json
from typing import Any, Dict, List, Optional, Union
class Validator:
"""A simple validate data helper designed for beginners."""
def __init__(self, data: Union[Dict[str, Any], List[Any]]):
self.data = data
self.errors: Dict[str, str] = {}
def validate_required(self, field: s…Scope-based authorization in Python
A simple Python class that checks user scopes against required permissions for a resource, returning an authorization decision.
class ScopeAuthorization:
def __init__(self):
self.scopes = {
"read": ["resource:read"],
"write": ["resource:read", "resource:write"],
"admin": ["resource:read", "resource:write", "resource:delete"]
}
def authorize(self, user_scopes, required_scope, resource…Sort Python list by query param order_by
Sort a list of dataclass objects dynamically by a field name passed as a query param, with asc/desc direction support.
from dataclasses import dataclass
@dataclass
class Item:
name: str
price: int
def sort_items(items, order_by, direction="asc"):
if order_by not in ("name", "price"):
raise ValueError(f"Unsupported sort field: {order_by}")
reverse = direction.lower() == "desc"
return sorted(items, key=l…Browse by section
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API design & gRPC — Python code examples
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