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Event Sourcing Store in Python: Append-Only Log Mock
Mock an append-only event store in Python — record events, list them, and fetch by ID using a simple list-backed class.
class EventStore:
def __init__(self):
self._events = []
def append(self, event):
event_id = len(self._events) + 1
stored_event = {"id": event_id, "data": event}
self._events.append(stored_event)
return stored_event
def get_events(self):
return list(self._ev…How to Build a Health Check Service Registry in Python
Build a minimal Python service registry that handles registration, deregistration, health checks, and service listing in one simple class.
import random
import time
class ServiceRegistry:
def __init__(self):
self.services = {}
def register(self, name, address):
self.services[name] = {
"address": address,
"status": "healthy",
"registered_at": time.time(),
"checks": 0
}
…How to Build an In-Memory Service Registry Mock in Python
A simple in-memory ServiceRegistry class to register, retrieve, list, and unregister microservice endpoints or configs using a dict, with KeyError guards.
class ServiceRegistry:
def __init__(self):
self._services = {}
def register(self, name, service):
self._services[name] = service
def unregister(self, name):
if name not in self._services:
raise KeyError(f"Service '{name}' not found")
del self._services[name]
…How to Mock a Service Registry in Python with an In-Memory Dict
A lightweight ServiceRegistry class backed by a dict, exposing register, unregister, lookup, list, and health-check methods.
class ServiceRegistry:
def __init__(self):
self._services = {}
def register(self, name, endpoint, version="1.0"):
self._services[name] = {
"endpoint": endpoint,
"version": version,
"status": "healthy"
}
def unregister(self, name):
return…How to implement round-robin load balancing in Python
Implement a client-side round-robin load balancer that distributes requests sequentially across a list of mock servers using itertools.cycle.
import itertools
import random
class MockServer:
def __init__(self, name):
self.name = name
def handle_request(self, request_id):
return f"Server {self.name} handled request #{request_id}"
class RoundRobinLoadBalancer:
def __init__(self, servers):
self.servers = servers
…Approximate Distinct Count in Python with HyperLogLog
Mock a large data stream and estimate the number of distinct items with a HyperLogLog-style probabilistic counter to save memory.
import random
import string
from collections import Counter
import math
class ApproxCountDistinct:
def __init__(self, num_buckets=16):
self.num_buckets = num_buckets
self.max_zeros = [0] * num_buckets
def _hash(self, item):
# Simple string hash to a 32-bit integer
h = …How to Implement collect_list in Python
Group rows by a key and collect all corresponding values into a list — a pure-Python mock of Spark's collect_list aggregation.
from collections import defaultdict
def collect_list(rows, key_field, value_field):
grouped = defaultdict(list)
for row in rows:
grouped[row[key_field]].append(row[value_field])
return dict(grouped)
if __name__ == "__main__":
data = [
{"dept": "sales", "emp": "alice"},
{"dept"…How to Truncate Lineage Back to a Checkpoint in Python
Walks a linked list of lineage nodes upward to find the nearest checkpoint and returns that node, truncating the lineage.
class LineageNode:
def __init__(self, name, parent=None, checkpoint=None):
self.name = name
self.parent = parent
self.checkpoint = checkpoint
def truncate_at_checkpoint(self):
"""Truncate lineage back to the last checkpoint."""
current = self
while current.check…HyperLogLog Cardinality Estimation in Python
A small HyperLogLog implementation using MD5 hashing and 256 registers to estimate the number of unique items in a large stream with fixed memory.
import hashlib
import math
class HyperLogLog:
def __init__(self, b=8):
self.b = b
self.m = 1 << b
self.registers = [0] * self.m
self.alpha = 0.7213 / (1 + 1.079 / self.m)
def add(self, item):
h = int(hashlib.md5(str(item).encode()).hexdigest(), 16)
idx = h & (s…How to Compute a Confusion Matrix in Python
Compute a multi-class confusion matrix from true and predicted labels using pure Python dictionaries and nested lists, then format it for readable output.
from collections import defaultdict
def compute_confusion_matrix(y_true, y_pred, labels):
"""Compute confusion matrix using Python dicts and nested lists."""
label_index = {label: i for i, label in enumerate(labels)}
matrix = [[0] * len(labels) for _ in range(len(labels))]
for true, pred in zip(y…How to Impute Missing Values with Mean in Python
Replace None values in a list with the mean of the existing values using Python's statistics module.
import statistics
from statistics import mean
def impute_mean(values):
"""Replace None with the mean of the non-None values."""
# Filter out None to compute the mean of existing values
valid = [v for v in values if v is not None]
if not valid:
return values # nothing to impute if all are Non…How to Run Batch Predictions with a Mock Model in Python
Build a lightweight mock model class and run predictions across a batch of samples, returning results as a plain Python list.
import numpy as np
class MockModel:
def __init__(self, weights):
self.weights = np.array(weights)
def predict(self, X):
return X @ self.weights
def predict_batch(model, batch):
"""Run predictions for a batch of samples and return results as a list."""
return model.predict(np.array(ba…Load CSV Training Data Without Pandas in Python
This code loads a CSV file into a list of dictionaries using only the standard library, ideal for small ML training data without heavy dependencies.
import csv
from pathlib import Path
def load_csv(path):
"""Load CSV file into list of dicts without pandas."""
rows = []
with open(path, newline='', encoding='utf-8') as f:
reader = csv.DictReader(f)
for row in reader:
rows.append(dict(row))
return rows
if __name__ == "__m…Model registry version mock in Python
A simple in-memory model registry that stores model versions with metadata and supports version listing and latest retrieval.
class ModelRegistry:
def __init__(self):
self.models = {}
def register(self, name, version, model_type, metrics=None):
if name not in self.models:
self.models[name] = []
entry = {
"version": version,
"model_type": model_type,
"metrics": m…One Hot Encode Categories in Python
Convert a list of categorical strings into one-hot encoded numeric vectors using pure Python and NumPy.
import numpy as np
categories = ["red", "green", "blue", "red", "blue", "green", "red"]
unique = sorted(set(categories))
lookup = {cat: i for i, cat in enumerate(unique)}
one_hot = []
for cat in categories:
row = [0] * len(unique)
row[lookup[cat]] = 1
one_hot.append(row)
print("Categories:", categories…Bonferroni Correction in Python
Applies the Bonferroni correction to a list of p-values to control the family-wise error rate when performing multiple comparisons.
import numpy as np
def bonferroni_correction(p_values, alpha=0.05):
"""Apply Bonferroni correction to a list of p-values."""
n = len(p_values)
corrected_alpha = alpha / n
significant = [p < corrected_alpha for p in p_values]
return corrected_alpha, significant
if __name__ == "__main__":
# Moc…How to Mock an Exposure Event Log Record in Python
Generate a realistic exposure event record with UUID, UTC timestamp, and risk level for testing or experimentation.
import uuid
from datetime import datetime, timezone
def mock_exposure_event(person_id: str, location: str, duration_minutes: int) -> dict:
return {
"event_id": str(uuid.uuid4()),
"person_id": person_id,
"location": location,
"duration_minutes": duration_minutes,
"timestamp…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 Convert Data with Scaling for Database Optimization in Python
A beginner-friendly helper that normalizes and scales numeric fields in a list of dicts, reducing storage footprint for database efficiency.
import json
from datetime import datetime
def convert_data(data: list[dict], scale_factor: int = 1) -> list[dict]:
"""Convert a list of dicts to a scaled, normalized format for database efficiency."""
converted = []
for row in data:
normalized = {}
for key, value in row.items():
…How to Count Star vs Estimate Matches in Python
Count how many times 'star' and 'estimate' annotations match their actual labels in a list of mock comparison results.
def count_star_vs_estimate(mock_scores):
"""
Count the number of times 'star' wins and 'estimate' wins
from a list of mock comparison results.
Args:
mock_scores: list of tuples, each (annotation, actual)
where annotation is 'star' or 'estimate'
Returns:
dict w…How to Limit a Result Set to Top N Rows in Python
Sort a list of dictionaries by a numeric key and return only the top N results, formatted as a readable ranked list.
import random
def top_n_mock(limit: int = 5):
"""Return a formatted top-N result set as a mock example."""
# Simulated data source
scores = [
{"name": "Alice", "score": 87},
{"name": "Bob", "score": 92},
{"name": "Charlie", "score": 78},
{"name": "Diana", "score": 95},
…How to Mock Replica Lag Monitoring in Python
Simulates database replica lag with a mock monitor class that generates realistic lag metrics and health statuses.
import time
import random
from datetime import datetime, timedelta
class MockReplicaLagMonitor:
def __init__(self, replicas=3, base_lag=0.5, jitter=0.2):
self.replicas = [f"replica-{i}" for i in range(replicas)]
self.base_lag = base_lag
self.jitter = jitter
self.last_write = dateti…How to Implement an HSTS Preload List Mock in Python
Implements a mock HSTS preload list in Python that supports adding, removing, checking domains with subdomain inheritance, and listing domains.
import json
class HSTSPreloadList:
def __init__(self):
self.domains = {}
def add_domain(self, domain, include_subdomains=False, max_age=31536000):
self.domains[domain] = {
"include_subdomains": include_subdomains,
"max_age": max_age
}
def remove_domain(sel…How to Mock a CORS Allow Origin Whitelist in Python
A decorator-based mock of a CORS middleware that whitelists allowed origins and injects proper Access-Control-Allow-Origin headers while rejecting others.
from functools import wraps
class MockCORSConfig:
def __init__(self, allowed_origins):
self.allowed_origins = allowed_origins
def is_origin_allowed(self, origin):
return origin in self.allowed_origins
def cors_middleware(config):
def decorator(handler):
@wraps(handler)
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