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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…Generate an OpenAPI Spec from Mock Routes in Python
This Python script generates an OpenAPI 3.0 specification from a simple mock routes dictionary, mapping each HTTP method to response examples.
import json
from pathlib import Path
def generate_openapi_spec(routes: dict, title: str = "Mock API", version: str = "1.0.0") -> dict:
paths = {}
for route, methods in routes.items():
path_item = {}
for method, response_data in methods.items():
method = method.lower()
…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 Parse gRPC Request Data in Python
Build a beginner-friendly gRPC service handler that parses incoming protobuf messages into Python dictionaries and starts a simple gRPC server.
from google.protobuf import json_format
import grpc
from concurrent import futures
import time
class DataParsingService:
def parse(self, request):
return {
"received_json": json_format.MessageToJson(request),
"parsed_fields": {
"name": request.name,
…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…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…Build a Streaming Messaging Helper in Python
Create a simple message stream class that stores recent messages, sends user messages, and retrieves history or latest messages with timestamps.
from collections import deque
from dataclasses import dataclass
from datetime import datetime
import time
@dataclass
class Message:
user: str
text: str
timestamp: str = ""
def __post_init__(self):
if not self.timestamp:
self.timestamp = datetime.now().strftime("%H:%M:%S")
class…Event Envelope with Schema Version Field in Python
Build a typed event envelope dataclass with an explicit schema version field for mock streaming scenarios.
from dataclasses import dataclass, field
from datetime import datetime
import uuid
@dataclass
class Event:
event_id: str = field(default_factory=lambda: str(uuid.uuid4()))
event_type: str = "user.created"
version: str = "1.0.0"
created_at: str = field(default_factory=lambda: datetime.utcnow().isoform…How to Build a Materialized View Updater Consumer Mock in Python
A mock consumer that queues change events and triggers refresh callbacks to simulate materialized view updates.
import time
from collections import deque
from dataclasses import dataclass, field
from typing import Callable, Deque, Optional
@dataclass
class MaterializedViewUpdater:
"""Mock updater that consumes change events and refreshes a view."""
refresh: Optional[Callable[[str], None]] = None
queue: Deque[tuple…How to Build a Message Stream Queue in Python
A beginner-friendly MessageStream class built on deque that sends messages one at a time, tracks unread counts, and records sent items.
from collections import deque
import time
class MessageStream:
def __init__(self, messages):
self._queue = deque(messages)
self._sent = []
def send_next(self):
if not self._queue:
return None
message = self._queue.popleft()
self._sent.append(message)
…How to Build a Mock Change Data Capture Event Stream in Python
Generate a deterministic list of mock CDC events with event IDs, stream positions, payloads, and timestamps for testing streaming pipelines.
from itertools import count
from random import choice, randint, seed
from datetime import datetime, timedelta
seed(42) # Make output deterministic
event_types = ["INSERT", "UPDATE", "DELETE"]
table_names = ["users", "orders", "products", "payments"]
counter = count(1)
def mock_cdc_event(stream_index: int) -> dict:
…How to Implement a Priority Queue for Messages in Python
Build a message priority queue with heapq and dataclasses that pops messages by priority, using sequence numbers to keep insertion order.
import heapq
from dataclasses import dataclass, field
from typing import Any
@dataclass(order=True)
class Message:
priority: int
sequence: int = field(compare=False)
content: str = field(compare=False)
class PriorityQueue:
def __init__(self):
self._heap = []
def push(self, priority: int,…How to Simulate a Micro-Batch Interval Trigger in Python
A dataclass-based mock that emits batch numbers at fixed intervals, mimicking a micro-batch streaming scheduler for testing and development.
import time
from dataclasses import dataclass, field
from typing import List, Callable
@dataclass
class MicroBatchTriggerMock:
batch_interval_seconds: float = 0.5
max_batches: int = 5
_batches_emitted: int = 0
_next_emit_time: float = field(init=False, default=0)
def start(self, on_batch: Callab…How to Wrap Message Attributes in a CloudEvent with Python
Create a minimal CloudEvent dataclass that wraps arbitrary message attributes into a JSON envelope, matching CloudEvents 1.0 spec.
import json
from dataclasses import dataclass, field, asdict
from typing import Any, Dict
from datetime import datetime, timezone
@dataclass
class CloudEvent:
message_attributes: Dict[str, Any] = field(default_factory=dict)
def wrap(self, event_id: str, source: str, event_type: str, data: Any):
self…Cache Asides in Python with a Read-Through Loader
Implements a cache-aside pattern with a read-through loader that fetches missing keys from a backing data store and caches them.
class DataStore:
"""Mock database with a few records."""
def __init__(self):
self.data = {1: "Alice", 2: "Bob", 3: "Charlie"}
def get(self, key):
print(f"Loading key {key} from database")
return self.data.get(key)
class CacheAsideLoader:
"""Cache-aside pattern with a read-thr…Cache Data in Redis with Python
A beginner-friendly Redis cache helper that stores JSON strings with a TTL and retrieves them with the redis-py client.
import redis
class DataCache:
def __init__(self, host="localhost", port=6379, db=0):
self.client = redis.Redis(host=host, port=port, db=db, decode_responses=True)
def cache_data(self, key, value, ttl=60):
self.client.setex(key, ttl, value)
def get_cached_data(self, key):
return …How to Use Redis HSET and HGET in Python
This code demonstrates how to store and retrieve hash data in Redis using Python's redis library with HSET, HGET, HGETALL, and HDEL commands.
import redis
# Connect to Redis (adjust host/port as needed)
r = redis.Redis(host='localhost', port=6379, db=0, decode_responses=True)
# Clear any existing data for demonstration
r.delete('user:1')
# HSET - Store a hash
r.hset('user:1', mapping={'name': 'Alice', 'age': 30, 'city': 'New York'})
# HGET - Retrieve a …How to cache filtered data in Redis with Python
This code caches filtered list results in Redis using an MD5 hash key, returning cached results when available.
import redis
import json
import hashlib
import time
cache = redis.Redis(host='localhost', port=6379, db=0, decode_responses=True)
def filter_data(data, predicate_key, predicate_value):
"""Filter a list of dicts by key-value pair, with Redis caching."""
cache_key = hashlib.md5(
f"{predicate_key}:{pred…Browse by section
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