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Python Code Samples

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385 matches
Big data & Spark easy

Session window gap mock in Python

Group sorted timestamps into sessions where any gap between consecutive events exceeds a threshold starts a new session.

timestamps sessions windowing
Python
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…
15 0 Open
Big data & Spark easy

Sliding Window Streaming Mock in Python

A simple Python class that maintains a sliding window of recent streaming values and computes the running average.

streaming sliding-window averages
Python
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…
13 0 Open
ML engineering pipelines easy

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.

zenml ml pipeline
Python
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…
13 0 Open
ML engineering pipelines easy

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.

pytorch state-dict model
Python
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…
14 0 Open
ML engineering pipelines easy

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.

ordinal-encoding sklearn categorical-data
Python
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…
17 0 Open
ML engineering pipelines easy

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.

csv data-loading standard-library
Python
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…
16 0 Open
ML engineering pipelines easy

One Hot Encode Categories in Python

Convert a list of categorical strings into one-hot encoded numeric vectors using pure Python and NumPy.

one-hot encoding categorical numpy
Python
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…
14 0 Open
A/B testing & experimentation easy

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.

confidence-interval simulation statistics
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)
  …
17 0 Open
Database scaling & optimization easy

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.

json batching database
Python
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 + …
13 0 Open
Database scaling & optimization easy

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.

data conversion database scaling
Python
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():
          …
15 0 Open
Database scaling & optimization easy

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.

date datetime sharding
Python
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 …
15 0 Open
Database scaling & optimization easy

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.

validation data-quality scaling
Python
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…
16 0 Open
Database scaling & optimization easy

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.

database unique index constraint
Python
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…
15 0 Open
Database scaling & optimization easy

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.

sharding hash partitioning
Python
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


…
15 0 Open
Auth & security at scale easy

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.

flask oidc userinfo
Python
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…
16 0 Open
Auth & security at scale easy

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.

tls ssl security
Python
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:
        …
18 0 Open
Auth & security at scale easy

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.

bcrypt password security
Python
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 …
14 0 Open
Production deployment patterns easy

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.

docker healthcheck subprocess
Python
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…
21 0 Open
Production deployment patterns easy

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.

http healthcheck mock-server
Python
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…
16 0 Open
Production deployment patterns easy

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.

docker multi-stage simulation
Python
# 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…
16 0 Open
Production deployment patterns easy

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.

signals graceful-shutdown sigterm
Python
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…
15 0 Open
Production deployment patterns easy

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.

packer ami mock
Python
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"
  …
14 0 Open
Production deployment patterns easy

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.

maintenance status datetime
Python
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…
14 0 Open
Production deployment patterns easy

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.

init-container migration simulation
Python
```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…
16 0 Open

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