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Session window gap mock in Python
Group sorted timestamps into sessions where any gap between consecutive events exceeds a threshold starts a new session.
from datetime import datetime, timedelta
def session_windows(timestamps, gap_seconds=300):
"""Group timestamps into sessions where gaps > gap_seconds start new sessions."""
if not timestamps:
return []
# Sort timestamps chronologically to ensure correct windowing
timestamps = sorted(timestam…
Sliding Window Streaming Mock in Python
A simple Python class that maintains a sliding window of recent streaming values and computes the running average.
import time
import random
class StreamingMock:
"""Produces a stream of numbers using a sliding window."""
def __init__(self, window_size=5):
self.window = []
self.window_size = window_size
def push(self, value):
"""Add a value, sliding the window forward."""
s…
How to Build a Simple ML Pipeline with ZenML in Python
Build a mock machine learning pipeline with ZenML steps for data loading, training, and evaluation, and run it to print the final accuracy.
from zenml import pipeline, step
@step
def load_data() -> dict:
"""Simulate loading data from a source."""
return {"accuracy": 0.0, "loss": 1.0}
@step
def train_model(data: dict) -> dict:
"""Simulate training a model."""
data["accuracy"] = 0.95
data["loss"] = 0.1
return data
@step
def eva…
How to Save and Load PyTorch Model State Dict in Python
This code demonstrates how to save a PyTorch model's state dict to a file and load it back into a new model instance, verifying weights match.
import torch
import torch.nn as nn
class SimpleNet(nn.Module):
def __init__(self):
super().__init__()
self.fc1 = nn.Linear(4, 8)
self.fc2 = nn.Linear(8, 2)
def forward(self, x):
x = torch.relu(self.fc1(x))
return self.fc2(x)
if __name__ == "__main__":
model = Simp…
How to ordinal encode categorical data in Python with sklearn
Convert job title categories into ordinal numeric labels using sklearn's OrdinalEncoder with explicit ordering.
from sklearn.preprocessing import OrdinalEncoder
import numpy as np
# Mock data: small job title categories with known ordering
data = np.array([
["intern"],
["junior"],
["mid"],
["senior"],
["lead"]
])
# Define the ordinal order (lowest to highest)
categories = [["intern", "junior", "mid", "seni…
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…
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…
How to Mock a Confidence Interval for a Proportion in Python
Simulate a Bernoulli sample and compute a 95% confidence interval for a proportion using the normal approximation in Python.
import random
import math
def mock_ci(n=100, p_true=0.5, z=1.96, seed=42):
"""Simulate a sample proportion and compute its 95% confidence interval."""
random.seed(seed)
successes = sum(1 for _ in range(n) if random.random() < p_true)
p_hat = successes / n
se = math.sqrt(p_hat * (1 - p_hat) / n)
…
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 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 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 Validate Data Before Scaling in Python
A reusable Python helper that validates required fields and constraint checks on data rows before entering a database pipeline, improving data quality and throughput.
def validate_data(data, required_fields, constraints=None):
"""
Basic validation helper demonstrating data-quality workflows
before scaling (catches bad rows early, improves throughput).
"""
constraints = constraints or {}
errors = []
for field in required_fields:
if field not in d…
How to enforce a unique index constraint in Python
Mock a database unique index in Python that rejects duplicate rows based on one or more columns.
class MockIndex:
def __init__(self, columns):
self.columns = columns
self._values = set()
def insert(self, row):
key = tuple(row[col] for col in self.columns)
if key in self._values:
raise ValueError(f"Duplicate key {key} for columns {self.columns}")
self._v…
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
…
Build a Mock OIDC Userinfo Endpoint in Python with Flask
Create a local mock OIDC userinfo endpoint in Flask that returns a standard JSON user payload, ideal for testing auth flows without a real identity provider.
from flask import Flask, jsonify
app = Flask(__name__)
@app.route("/userinfo")
def userinfo():
mock_user = {
"sub": "1234567890",
"name": "John Doe",
"email": "john@example.com",
"email_verified": True,
"groups": ["admin", "dev"]
}
return jsonify(mock_user)
if __n…
How to Check Negotiated Cipher Suite in Python
Connect to a TLS server with Python's ssl module and print the negotiated protocol version and cipher suite details.
import ssl
import socket
def get_cipher_suites(hostname, port=443):
context = ssl.create_default_context()
context.set_ciphers("DEFAULT:@SECLEVEL=2")
with socket.create_connection((hostname, port), timeout=5) as sock:
with context.wrap_socket(sock, server_hostname=hostname) as ssock:
…
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 …
Docker healthcheck CMD mock in Python
Runs a subprocess to curl a health endpoint and returns exit code 0 when healthy, 1 when unhealthy, mimicking a Docker HEALTHCHECK command.
import subprocess
import sys
def run_healthcheck() -> int:
result = subprocess.run(["curl", "-fsS", "http://localhost:8080/health"], capture_output=True, text=True)
if result.returncode == 0:
print("healthy")
return 0
print("unhealthy", file=sys.stderr)
return 1
if __name__ == "__ma…
How to Create a Liveness Probe HTTP Mock in Python
Build a lightweight HTTP server in Python that mimics a Kubernetes-style liveness endpoint, returning JSON health status for local testing.
import http.server
import threading
import time
class LivenessHandler(http.server.BaseHTTPRequestHandler):
def do_GET(self):
if self.path == "/healthz":
self.send_response(200)
self.send_header("Content-Type", "application/json")
self.end_headers()
self.wfi…
How to Mock Multi-Stage Docker Builds in Python
Simulate a multi-stage Docker build in pure Python using classes and temp directories to understand how build stages copy artifacts into a final image.
# Simulate multi-stage Docker build with pure Python
from pathlib import Path
import tempfile
import shutil
class BuildContext:
"""Mimics a Docker build context with stages."""
def __init__(self, name):
self.name = name
self.files = {}
def add_file(self, dest, content):
s…
How to Mock a SIGTERM Handler in Python
Create a graceful shutdown handler for SIGTERM and SIGINT signals, then test it by simulating a signal delivery without terminating the process.
import signal
import time
class Service:
def __init__(self):
self.running = True
def shutdown(self, signum, frame):
print(f"Received signal {signum}, shutting down gracefully...")
self.running = False
def run(self):
signal.signal(signal.SIGTERM, self.shutdown)
sig…
How to Simulate a Packer AMI Build in Python
A simple Python class that mimics a Packer AMI build lifecycle — creates a build object, transitions its state to completed, and prints a JSON snapshot.
import json
class PackerBuildMock:
def __init__(self, name, ami_id, region="us-east-1", state="pending"):
self.name = name
self.ami_id = ami_id
self.region = region
self.state = state
def build(self):
if self.state == "pending":
self.state = "completed"
…
How to build a maintenance mode page in Python
Mock a service maintenance status page that computes remaining downtime and lists affected features from a simple class.
from datetime import datetime
class MaintenanceMode:
"""Mock a maintenance mode status page for a service."""
def __init__(self, service_name: str, scheduled_end: str):
self.service_name = service_name
self.scheduled_end = datetime.fromisoformat(scheduled_end)
self.affected_featur…
How to simulate a database migration init container mock in Python
A mock init container that runs environment checks and a staged database migration job before the main application starts, printing progress to stdout.
```python
class MigrationJob:
def __init__(self, name, steps):
self.name = name
self.steps = steps
self.current_step = 0
self.status = "pending"
def run(self):
print(f"Initializing migration job: {self.name}")
for step in self.steps:
self.current_ste…
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