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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
How to Cache Function Results with Redis in Python
A RedisCache helper class caches function results using a decorator, with JSON serialization and TTL-based expiry.
import redis
import json
from functools import wraps
class RedisCache:
def __init__(self, host='localhost', port=6379, db=0, ttl=60):
self.client = redis.Redis(host=host, port=port, db=db, decode_responses=True)
self.ttl = ttl
def cached(self, key_prefix):
def decorator(func):
…How to Serialize Cache Values with JSON and Pickle in Python
Serialize cache values using JSON for simple types or pickle for arbitrary objects, with robust error handling for unsupported types like mocks.
import json
import pickle
from unittest.mock import Mock
def serialize(value, method="json"):
"""Serialize a cache value using JSON or pickle with type checking."""
if method == "json":
try:
return json.dumps(value).encode("utf-8")
except TypeError as e:
raise ValueErro…Simple Redis Cache Helper in Python
Build a minimal Redis-backed cache with TTL, JSON serialization, and automated fetching to speed up repeated expensive lookups.
import time
import redis
import json
class SimpleCache:
def __init__(self, host="localhost", port=6379, db=0, default_ttl=60):
self.client = redis.Redis(host=host, port=port, db=db, decode_responses=True)
self.default_ttl = default_ttl
def get(self, key):
value = self.client.get(key)…How to Implement a Data Helper for Microservices in Python
Create a reusable helper class to serialize, deserialize, and wrap data for microservice communication using dataclasses and JSON.
import json
from dataclasses import dataclass, asdict
from typing import Any, Dict, List
@dataclass
class ServiceResponse:
status: str
data: Any
message: str = ""
class DataHelper:
"""Simple helper for microservice data handling."""
@staticmethod
def serialize(data: Dict[str, Any]) -> str:…How to Mock a Schema Registry Avro Record in Python
Encode a Python dict into Avro binary using an inline schema, mimicking a schema registry record for tests or mocks.
import io
from avro.schema import parse
from avro.io import DatumWriter, BinaryEncoder
schema_json = """
{
"type": "record",
"name": "User",
"fields": [
{"name": "name", "type": "string"},
{"name": "age", "type": "int"},
{"name": "email", "type": ["null", "string"], "default": null}
]
}
"""
schem…How to Create a Mock Kafka Producer in Python
Build a Kafka producer that generates mock streaming records with JSON serialization and error handling for local testing.
import json
import time
from kafka import KafkaProducer
from kafka.errors import KafkaError
def create_mock_producer(bootstrap_servers="localhost:9092", topic="input-topic"):
"""Create a Kafka producer that generates mock streaming data."""
producer = KafkaProducer(
bootstrap_servers=bootstrap_servers…How to Create a Mock ONNX Model in Python
Build and export a minimal mock ONNX model with a Reshape and Gemm layer using the onnx helper API.
import onnx
import numpy as np
from onnx import helper, TensorProto
def create_mock_model():
# Define input and output tensors
input_tensor = helper.make_tensor_value_info('input', TensorProto.FLOAT, [1, 3, 224, 224])
output_tensor = helper.make_tensor_value_info('output', TensorProto.FLOAT, [1, 10])
…How to Save and Load a Mock Model with Pickle and joblib in Python
Serialize a custom machine learning model to a .joblib file with joblib.dump, reload it, and run a prediction with joblib.load.
import joblib
from pathlib import Path
class MockModel:
def __init__(self, weights):
self.weights = weights
def predict(self, features):
return sum(w * f for w, f in zip(self.weights, features))
def save_model_pickle(model, filepath):
with open(filepath, "wb") as f:
joblib.dump(…Browse by section
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