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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 Implement MapReduce Word Count in Python Using a Dict
Simulate a MapReduce word count pipeline in Python with a mock dict, splitting text into words, shuffling, and reducing to frequency counts.
def map_reduce_word_count(text: str) -> dict:
"""Simulate a MapReduce pipeline to count word frequencies."""
# MAP phase: split into words and emit (word, 1) pairs
mapped = []
for word in text.lower().split():
# Clean word of punctuation
clean_word = ''.join(char for char in word if cha…
How to Pivot and Group Aggregate in Python
Group records by a key, collect values, and apply an aggregate function (like sum) to build a pivot-style summary dictionary.
from collections import defaultdict
def pivot_group_aggregate(records, group_key, value_key, agg_func):
groups = defaultdict(list)
for record in records:
groups[record[group_key]].append(record[value_key])
return {key: agg_func(values) for key, values in groups.items()}
if __name__ == "__main__":…
Hudi Upsert Mock Copy on Write in Python
Simulates Apache Hudi's Copy-on-Write upsert behavior by merging update records into a deep copy of base records, replacing matches or appending new ones.
import copy
from typing import Dict, List, Any
def upsert_copy_on_write(base_records: List[Dict[str, Any]], updates: List[Dict[str, Any]], key_field: str = "id") -> List[Dict[str, Any]]:
"""Simulate Hudi Copy-on-Write upsert: merge updates into a copy of base records."""
result = copy.deepcopy(base_records)
…
StandardScaler mock in Python
A pure-Python StandarScaler class that standardizes features to zero mean and unit variance without sklearn.
import math
class StandardScaler:
def __init__(self):
self.mean_ = None
self.std_ = None
def fit(self, X):
n = len(X)
self.mean_ = [sum(col) / n for col in zip(*X)]
self.std_ = []
for col in zip(*X):
variance = sum((x - self.mean_[i]) ** 2 for i, x …
Generate a Mock Multi-Armed Bandit Report in Python
Simulate a multi-armed bandit experiment with random pulls and rewards, then output a JSON report with per-arm statistics.
import random
import json
def generate_mock_bandit_report(num_arms=5, num_rounds=100, seed=42):
random.seed(seed)
arms = ["A", "B", "C", "D", "E"][:num_arms]
true_means = {arm: random.uniform(0.3, 0.7) for arm in arms}
pulls = {arm: 0 for arm in arms}
rewards = {arm: 0 for arm in arms}
for _ …
How to Build a Guardrail Metrics Monitor in Python
This code implements a mock monitor that records metric values, checks them against thresholds, and summarizes pass/alert statistics.
import random
import time
from collections import defaultdict
class GuardrailMetricsMonitor:
def __init__(self):
self.metrics = defaultdict(list)
self.thresholds = {
"prompt_toxicity": 0.8,
"response_length": 500,
"latency_ms": 1000,
}
def record(s…
Geo shard by region in Python
Maps users to database shards based on geographic region with a deterministic hash fallback.
import json
from collections import defaultdict
REGION_SHARD_MAP = {
"na": ["shard-01", "shard-02"],
"eu": ["shard-03", "shard-04", "shard-05"],
"ap": ["shard-06"],
"sa": ["shard-07", "shard-08"],
}
# user_id -> region (mock lookup)
USER_REGIONS = {
"u_1001": "na",
"u_1002": "eu",
"u_1003…
How to Batch Load JSON Data in Python for Database Optimization
This code parses JSON data into records and loads them in batches to simulate efficient database insertion, reducing load and improving performance.
import json
import time
def parse_and_load(data, batch_size=100):
"""
Parse JSON data and batch-load into a list of dicts.
Demonstrates batching for database efficiency.
"""
records = json.loads(data)
batches = []
for i in range(0, len(records), batch_size):
batch = records[i:i + …
How to Build a Shard Map Mock Dict in Python
Implement a dictionary-like class that distributes keys across multiple shards using Python's hash() for realistic data partitioning.
class ShardMap:
def __init__(self, shard_count):
self.shards = {i: {} for i in range(shard_count)}
self.shard_count = shard_count
def _shard_for(self, key):
return hash(key) % self.shard_count
def __getitem__(self, key):
return self.shards[self._shard_for(key)][key]
d…
How to Mock Date Sharding by Range in Python
Split a date interval into fixed-size contiguous shards, returning each window as an ISO date string pair.
from datetime import date, timedelta
def shard_ranges(start_date, end_date, shard_days=7):
if start_date > end_date:
raise ValueError("start_date cannot be after end_date")
shards = []
current = start_date
while current <= end_date:
shard_end = min(current + timedelta(days=shard_days …
How to Mock a Cross-Shard Saga in Python
Simulate a distributed saga with compensating transactions across multiple database shards using a lightweight Python class that tracks executed steps and rolls them back in reverse on failure.
import json
class SagaState:
def __init__(self, saga_id):
self.saga_id = saga_id
self.executed_steps = []
self.compensations = []
def execute_step(self, shard, step_name, operation):
self.executed_steps.append((shard, step_name))
print(f"[Saga {self.saga_id}] Executin…
How to Mock a Hot Shard Split in Python
Simulate a database hot shard splitting into two shards by key ranges when it exceeds a threshold, with a mock class for testing.
import random
from collections import defaultdict
class HotShardMock:
"""Mock implementation of a hot shard split in a distributed database."""
def __init__(self, shard_id="shard_1", max_entries=5):
self.shard_id = shard_id
self.max_entries = max_entries
self.entries = {}
def ad…
How to Replicate Data Across All Shards in Python
Mocks a global table that replicates a key-value pair to every shard, ensuring reads return the same value from any shard.
from dataclasses import dataclass
from typing import Dict, List
@dataclass
class Shard:
id: str
data: Dict[str, int]
class GlobalTable:
def __init__(self, shards: List[Shard]):
self._shards = {s.id: s for s in shards}
def set_value(self, key: str, value: int) -> None:
"""Replicate …
How to Simulate Colocated Shard Joins in Python
Groups shards by their node and merges co-located shards into a single logical unit, checking capacity constraints.
import random
from collections import defaultdict
def simulate_colocated_shards_join(nodes: list[dict], shards: list[dict]) -> dict:
"""
Simulates the join of co-located shards (on the same node) into a single
logical shard. Returns the resulting node-to-shard mapping.
Each node: {'id': str, 'capaci…
How to Simulate a Stable Sort Cursor in Python
Build a MongoDB-style cursor mock that stably sorts records by a key while preserving original order for ties, with next() and rewind() methods.
```python
import random
class CursorStableSortMock:
"""Simulates stable sorting with a cursor-like pointer for MongoDB-style queries."""
def __init__(self, data, sort_key, reverse=False):
self.data = list(data)
self.sort_key = sort_key
self.reverse = reverse
self._index = …
How to mock directory-based sharding in Python
Simulates distributing files into logical shards using a deterministic hash of each filename, mocking how a database might shard rows across nodes.
import os
import hashlib
from collections import defaultdict
from pathlib import Path
def get_shard_for_key(key: str, num_shards: int) -> int:
"""Return a deterministic shard index (0..num_shards-1) for a key."""
digest = hashlib.md5(key.encode('utf-8')).hexdigest()
return int(digest, 16) % num_shards
…
Offset vs Keyset Pagination in Python
Demonstrate offset-based pagination and keyset (cursor) pagination with a simple in-memory dataset, showing how each returns pages of records.
"""Demonstrate pagination using offset vs keyset (cursor) approach."""
ITEMS = [
{"id": 1, "name": "Alice"},
{"id": 2, "name": "Bob"},
{"id": 3, "name": "Carol"},
{"id": 4, "name": "David"},
{"id": 5, "name": "Eve"},
]
def offset_paginate(items, page, page_size):
"""Return a page using offset…
Route SELECT Queries to Read Replicas in Python
A mock round-robin router that forwards SELECT queries to read replicas and sends writes to the primary.
import random
class ReadReplicaRouter:
"""Round-robin router that sends SELECT queries to read replicas."""
def __init__(self, replicas):
self.replicas = replicas
self.counter = 0
def route(self, sql):
if sql.strip().upper().startswith("SELECT"):
replica = sel…
Two Phase Commit Cross Shard Mock in Python
Simulates a two-phase commit across shards with failure handling to demonstrate distributed transaction coordination in Python.
"""Mock cross-shard two-phase commit with caution handling."""
class Shard:
def __init__(self, name):
self.name = name
self.prepared = False
self.committed = False
self.aborted = False
def prepare(self):
# Simulate potential failure (1 in 3 chance on third shard)
…
How to Hash Passwords Securely in Python
Hash passwords with PBKDF2, random salts, and constant pepper, plus generate secure API keys using Python's stdlib.
import hashlib
import secrets
import time
import hmac
def hash_password(password: str, salt: str = None, pepper: str = "static-pepper") -> dict:
"""Hash a password with a random salt and constant pepper."""
if salt is None:
salt = secrets.token_hex(16)
salted = f"{pepper}{salt}{password}"
dig…
How to Hash Passwords and Authenticate Users in Python
A beginner-friendly dataclass-based design that hashes passwords with PBKDF2 and verifies them securely using constant-time comparisons.
import hashlib
import hmac
import secrets
from dataclasses import dataclass
from typing import Optional
@dataclass
class User:
id: int
username: str
password_hash: str
salt: str
def hash_password(password: str) -> tuple[str, str]:
salt = secrets.token_hex(16)
password_hash = hashlib.pbkdf2_…
How to Hash Passwords with bcrypt in Python
Hash a plaintext password with bcrypt using a randomly generated salt, then verify a plaintext attempt against the stored hash.
import bcrypt
def hash_password(password: str) -> str:
"""Hash a password using bcrypt with a generated salt."""
salt = bcrypt.gensalt()
return bcrypt.hashpw(password.encode("utf-8"), salt).decode("utf-8")
def check_password(password: str, hashed: str) -> bool:
"""Verify a plaintext password against …
How to Hash and Verify Passwords in Python
Hash passwords securely with PBKDF2-SHA256 and verify them using a constant-time comparison.
import hashlib
import hmac
import secrets
from typing import Tuple
def hash_password(password: str, salt: str = None) -> Tuple[str, str]:
"""Hash a password with a random salt using PBKDF2-SHA256."""
salt = salt or secrets.token_hex(16)
hashed = hashlib.pbkdf2_hmac(
"sha256", password.encode("utf…
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