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Python Code Samples

Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.

69 matches
Automation & scripting easy

How to generate an htpasswd bcrypt entry in Python

Create a mock htpasswd file entry with a bcrypt-hashed password for a given username using a simple Python script.

bcrypt htpasswd password
Python
import bcrypt

def mock_htpasswd_entry(username, password):
    salt = bcrypt.gensalt(rounds=12)
    hashed = bcrypt.hashpw(password.encode(), salt).decode()
    return f"{username}:{hashed}"

if __name__ == "__main__":
    entry = mock_htpasswd_entry("demo_user", "s3cretP@ss")
    print(entry)
15 0 Open
Automation & scripting medium

Track File Changes with Version History in Python

A Python utility that monitors a file for changes, creating versioned backups with SHA-256 hashing to detect modifications and store a local JSON history.

file-monitoring versioning automation
Python
import hashlib, json, os, shutil, time
from pathlib import Path

class FileTracker:
    def __init__(self, history_file="file_history.json"):
        self.history_file = Path(history_file)
        self.history = self._load_history()

    def _load_history(self):
        if self.history_file.exists():
            retur…
37 0 Open
Data pipelines & processing easy

Generate a Deterministic Hash for Deduplication in Python

Create a stable SHA-256 fingerprint from nested data and file contents to deduplicate records in a data pipeline.

hashing deduplication sha256
Python
import hashlib
import json
from pathlib import Path

def natural_key_hash(data, salt=""):
    """
    Generate a deterministic fingerprint from raw data (dict/list/str).
    Uses JSON canonical-ish serialization with sorted keys and SHA-256.
    """
    canonical = json.dumps(data, sort_keys=True, separators=(",", ":"…
14 0 Open
Data pipelines & processing easy

How to Hash Email Addresses in a PII Masking Pipeline in Python

Replaces every email address in a text string with its SHA-256 hash to protect personally identifiable information (PII).

pii hashing sha256
Python
import hashlib
import re

def hash_email(email: str) -> str:
    """Mask an email address by hashing it with SHA-256."""
    normalized = email.strip().lower()
    return hashlib.sha256(normalized.encode("utf-8")).hexdigest()

def mask_pii_emails(text: str) -> str:
    """Replace all email addresses in text with their…
14 0 Open
Data pipelines & processing easy

How to shard output by primary key hash mod N in Python

This code computes a consistent shard index for any primary key string using an MD5 hash mod the number of shards, enabling stable key-based data distribution.

hashing sharding hashlib
Python
import hashlib

def shard_id(primary_key: str, num_shards: int) -> int:
    """Return the shard index for a primary key using MD5 hash mod N."""
    digest = hashlib.md5(primary_key.encode("utf-8")).hexdigest()
    hash_int = int(digest, 16)
    return hash_int % num_shards

if __name__ == "__main__":
    keys = ["use…
11 0 Open
System design patterns medium

How to Build an Immutable Money Value Object in Python

Implement an immutable Money class with rounded decimal amounts, currency, safe equality, and hashing for use as a value object.

value-object immutability money
Python
class Money:
    def __init__(self, amount: float, currency: str):
        object.__setattr__(self, "_amount", round(amount, 2))
        object.__setattr__(self, "_currency", currency)

    def __setattr__(self, name, value):
        raise AttributeError(f"Money is immutable: cannot set '{name}'")

    def __delattr__…
13 0 Open
System design patterns medium

Implement a Consistent Hash Ring in Python

Build a minimal consistent hash ring with virtual nodes to map keys to servers stably as nodes are added or removed.

consistent-hashing hashing distributed-systems
Python
import hashlib
import bisect


class ConsistentHashRing:
    def __init__(self, nodes=None, replicas=3):
        self.replicas = replicas
        self.ring = {}
        self.sorted_keys = []
        if nodes:
            for node in nodes:
                self.add_node(node)

    def _hash(self, key):
        return i…
15 0 Open
System design patterns medium

Inbox pattern consumer dedupe mock in Python

Implements a mock inbox consumer that deduplicates incoming messages by ID, with automatic eviction of old seen IDs to prevent unbounded memory growth.

deduplication inbox-pattern dataclasses
Python
import json
from collections import deque
from dataclasses import dataclass, field
from hashlib import sha256
from typing import Any


@dataclass
class InboxConsumer:
    max_seen: int = 1000
    seen_ids: set = field(default_factory=set)
    seen_history: deque = field(default_factory=deque)

    def _mark_seen(self,…
13 0 Open
API design & gRPC medium

How to Build an Idempotency-Key POST Handler in Python

Python HTTP server mock that accepts POST requests and deduplicates them using an Idempotency-Key header, returning the same response for repeated calls.

http-server idempotency api-mock
Python
import hashlib
import json
from http.server import BaseHTTPRequestHandler, HTTPServer
from urllib.parse import urlparse


class MockAPI(BaseHTTPRequestHandler):
    responses = {}

    def do_POST(self):
        length = int(self.headers.get("Content-Length", 0))
        body = self.rfile.read(length).decode("utf-8")
…
14 0 Open
API design & gRPC medium

How to Implement ETag Optimistic Concurrency in Python

Build a lightweight in-memory resource store that uses MD5 hash ETags to prevent lost updates via optimistic concurrency control.

etag concurrency hashing
Python
import hashlib
import json

class ResourceStore:
    def __init__(self):
        self.data = {}
        self.etags = {}

    def get(self, resource_id):
        if resource_id not in self.data:
            return None, None
        return self.data[resource_id], self.etags[resource_id]

    def put(self, resource_id, …
13 0 Open
API design & gRPC medium

Verify Webhook HMAC Signatures in Python

Create and verify HMAC-SHA256 signatures for webhook payloads using Python's hmac module, protecting against tampering.

webhooks hmac security
Python
import hashlib
import hmac
import json

SECRET = b"super-secret-webhook-key"

def create_signature(payload: bytes) -> str:
    return hmac.new(SECRET, payload, hashlib.sha256).hexdigest()

def verify_signature(payload: bytes, signature: str) -> bool:
    expected = create_signature(payload)
    return hmac.compare_dig…
12 0 Open
Streaming & messaging easy

How to Partition and Order Kafka-Style Messages by Key in Python

Group messages with the same key into ordered buckets using hashing and a defaultdict, mimicking Kafka partition ordering.

streaming partitioning kafka-pattern
Python
from dataclasses import dataclass
from collections import defaultdict

@dataclass
class Message:
    key: str
    content: str

def partition_and_order(messages, num_partitions=3):
    partitions = defaultdict(list)
    for msg in messages:
        partition_id = hash(msg.key) % num_partitions
        partitions[parti…
14 0 Open
Caching & Redis medium

Consistent Hashing Cache Shard in Python

A minimal consistent hashing ring with virtual nodes that distributes cache keys across shards and minimizes re-mapping when a node is removed.

caching sharding consistent-hashing
Python
import hashlib
import bisect


class ConsistentHashRing:
    def __init__(self, nodes=None, replicas=3):
        self.replicas = replicas
        self.ring = {}
        self.sorted_keys = []
        if nodes:
            for node in nodes:
                self.add_node(node)

    def _hash(self, key):
        return i…
16 0 Open
Caching & Redis medium

How to Build a Bloom Filter to Reduce Cache Misses in Python

Implement a probabilistic Bloom filter in Python that lets a cache quickly determine which keys are definitely not present, reducing expensive source lookups on cache misses.

bloom-filter caching probabilistic
Python
import hashlib
import random

class BloomFilter:
    def __init__(self, size=100, num_hashes=3):
        self.size = size
        self.num_hashes = num_hashes
        self.bit_array = [0] * size

    def _hashes(self, item):
        result = []
        for i in range(self.num_hashes):
            hash_value = int(hash…
14 0 Open
Caching & Redis easy

How to Use Redis HSET and HGET in Python

This code demonstrates how to store and retrieve hash data in Redis using Python's redis library with HSET, HGET, HGETALL, and HDEL commands.

redis hset hget
Python
import redis

# Connect to Redis (adjust host/port as needed)
r = redis.Redis(host='localhost', port=6379, db=0, decode_responses=True)

# Clear any existing data for demonstration
r.delete('user:1')

# HSET - Store a hash
r.hset('user:1', mapping={'name': 'Alice', 'age': 30, 'city': 'New York'})

# HGET - Retrieve a …
12 0 Open
Caching & Redis easy

How to cache filtered data in Redis with Python

This code caches filtered list results in Redis using an MD5 hash key, returning cached results when available.

redis caching filtering
Python
import redis
import json
import hashlib
import time

cache = redis.Redis(host='localhost', port=6379, db=0, decode_responses=True)

def filter_data(data, predicate_key, predicate_value):
    """Filter a list of dicts by key-value pair, with Redis caching."""
    cache_key = hashlib.md5(
        f"{predicate_key}:{pred…
13 0 Open
Caching & Redis easy

How to create a stable cache key from function arguments in Python

Generate a stable SHA-256 cache key from normalized function arguments, with keyword order normalized and tests using mocks.

caching hash key-normalization
Python
import hashlib
import json
from unittest.mock import Mock


def make_cache_key(*args, **kwargs):
    """Normalize args/kwargs into a stable hash key for caching."""
    normalized = {
        "args": [repr(arg) for arg in args],
        "kwargs": {key: repr(value) for key, value in sorted(kwargs.items())}
    }
    pa…
13 0 Open
Microservices patterns easy

How to Deduplicate Events in Python with SHA256 Hashing

Build an event deduplicator that identifies duplicate inbox messages using SHA256 hashes and tracks duplicate counts per event type.

deduplication event-processing hashing
Python
```python
import hashlib
import json
from collections import defaultdict


class EventDeduplicator:
    def __init__(self):
        self.seen_hashes = set()
        self.duplicate_counts = defaultdict(int)

    def process_event(self, event):
        event_key = f"{event['event_id']}:{event['timestamp']}"
        even…
12 0 Open
Big data & Spark medium

Bloom Filter Join Mock in Python

A mock hash join that uses a Bloom filter to pre-filter one table before performing an exact match, reducing the number of comparisons in large dataset joins.

bloom filter join hashing
Python
import hashlib
import random
import string


class BloomFilter:
    def __init__(self, size: int = 200, num_hashes: int = 3):
        self.bits = [False] * size
        self.size = size
        self.num_hashes = num_hashes

    def _hashes(self, item: str):
        result = []
        for seed in range(self.num_hashes…
13 0 Open
Big data & Spark easy

How to Mock a Hash Join on Large and Small Tables in Python

This code efficiently joins a large dataset (1000 rows) with a small lookup table (20 rows) by building a dictionary hash lookup, mimicking a hash join strategy used in big data systems.

hash-join dictionaries data-join
Python
import random
from pprint import pprint

# Large table: 1000 rows (id, group_id, value)
large = [{"id": i, "group_id": random.randint(1, 20), "value": random.random() * 100} for i in range(1000)]

# Small table: 20 rows (group_id, label)
small = [{"group_id": g, "label": f"Group-{g}"} for g in range(1, 21)]

# Mock a …
13 0 Open
Big data & Spark medium

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.

hyperloglog cardinality estimation
Python
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…
14 0 Open
Big data & Spark easy

Partition Data by Hash Key Mod N in Python

Returns a partition index for a string key by hashing it with MD5 and taking modulo N, then groups sample keys into partitions.

hashing partitioning hashlib
Python
import hashlib


def partition_key(key: str, num_partitions: int) -> int:
    """Return partition index for key using MD5 hash mod N."""
    digest = hashlib.md5(key.encode()).hexdigest()
    return int(digest, 16) % num_partitions


if __name__ == "__main__":
    keys = ["alice", "bob", "carol", "dave", "eve"]
    nu…
12 0 Open
A/B testing & experimentation easy

How to Hash a User ID to an Experiment Bucket in Python

Deterministically map a user ID to one of N experiment buckets using MD5 hashing and modulo arithmetic.

hashing ab-testing bucketing
Python
import hashlib

def hash_to_bucket(user_id: str, num_buckets: int = 10) -> int:
    """Deterministically map a user_id to a bucket (0 to num_buckets-1)."""
    digest = hashlib.md5(user_id.encode("utf-8")).hexdigest()
    return int(digest[:8], 16) % num_buckets

if __name__ == "__main__":
    # Mock experiment: split…
14 0 Open
A/B testing & experimentation easy

How to hash user IDs to experiment buckets in Python

Deterministically map a user ID to an experiment bucket using MD5 hashing, ensuring stable and consistent assignment for A/B testing.

hashing ab-testing experiments
Python
import hashlib


def hash_user_to_bucket(user_id: str, num_buckets: int = 10) -> int:
    """Deterministically map a user ID to an experiment bucket (0..num_buckets-1)."""
    digest = hashlib.md5(user_id.encode("utf-8")).hexdigest()
    return int(digest, 16) % num_buckets


if __name__ == "__main__":
    mock_users …
12 0 Open

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Guide: free Python code samples library

Copy-ready Python snippets for learners and developers

PythonSkillset code samples are short, focused examples organised by topic and difficulty. Every snippet is server-rendered HTML — readable by search engines and easy to copy. Open any sample, read the notes, copy the code, then press Try in editor to run it in the browser with Pyodide.

How to use this library

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  2. Open a sample, read How it works, and copy the code block
  3. Run it in the IDE, tweak values, then take a related quiz or tutorial lesson

Samples vs tutorials and challenges

Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.