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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
Build a Secure Local Password Vault with Encrypted Storage in Python
A Python class that stores and retrieves passwords in an encrypted JSON file using Fernet symmetric encryption from the cryptography library.
import json
import os
import base64
import hashlib
from cryptography.fernet import Fernet
from getpass import getpass
class PasswordVault:
def __init__(self, vault_file="vault.json", key_file="vault.key"):
self.vault_file = vault_file
self.key_file = key_file
self.key = self._load_or_creat…Create a Personal Knowledge Base That Searches Notes Instantly in Python
Build a lightweight personal knowledge base with JSON storage and instant case-insensitive full-text search across note titles and content.
import json
import re
import sys
class PersonalKnowledgeBase:
def __init__(self, file_path="kb_notes.json"):
self.file_path = file_path
self.notes = self._load_notes()
def _load_notes(self):
try:
with open(self.file_path, "r") as f:
return json.load(f)
…How to Load and Save JSON Files in Python
Load and save JSON files with pretty formatting using Python's standard library json module and pathlib.
import json
from pathlib import Path
def load_json(filepath: str) -> dict:
"""Load JSON data from a file."""
path = Path(filepath)
with path.open("r", encoding="utf-8") as f:
return json.load(f)
def save_json(filepath: str, data: dict) -> None:
"""Save data to a JSON file with pretty format…Implement Exactly-Once Transaction Log in Python
A mock transaction log that deduplicates transaction IDs so each is recorded only once, with a dataclass for records and simple in-memory storage.
from dataclasses import dataclass
from typing import Dict, Optional
@dataclass
class TxnRecord:
txn_id: str
status: str
class ExactlyOnceTxnLog:
def __init__(self) -> None:
self._log: Dict[str, TxnRecord] = {}
self._processed_ids: set = set()
def record(self, txn_id: str, status: s…Create a Cloud Storage Helper Class in Python
Build a simple local file-based helper class that mimics cloud storage operations like save, load, and list JSON objects.
import datetime
import json
from pathlib import Path
class CloudDataHelper:
"""Simple helper for reading/writing JSON files in a cloud-style folder."""
def __init__(self, base_dir: str = "cloud_storage"):
self.base_dir = Path(base_dir)
self.base_dir.mkdir(exist_ok=True)
def save_json(se…Mock Azure Blob Upload and Download in Python
Simulate Azure Blob Storage upload and download operations with a lightweight in-memory mock class for testing.
import io
import json
from datetime import datetime, timezone
class MockBlob:
def __init__(self, name):
self.name = name
self.content = b""
self.properties = {
"last_modified": datetime.now(timezone.utc).isoformat(),
"size": 0,
}
def upload(self, data, …Mock GCP storage bucket blob upload in Python
Simulate uploading a blob to a GCP Storage bucket for testing without hitting the cloud.
import io
from datetime import datetime
from unittest.mock import MagicMock, patch
class MockBlob:
"""Simulates a GCP storage blob for unit testing."""
def __init__(self, name):
self.name = name
self.uploaded_at = None
self.content = b""
def upload_from_file(self, file_obj):
…Mock S3, GCS, and Azure storage with a Python abstract interface
Define an abstract Storage interface and implement a local, filesystem-backed mock so S3, GCS, and Azure code can be tested without cloud dependencies.
from abc import ABC, abstractmethod
from pathlib import Path
class Storage(ABC):
@abstractmethod
def put(self, name: str, data: bytes) -> None:
pass
@abstractmethod
def get(self, name: str) -> bytes:
pass
class LocalStorage(Storage):
def __init__(self, base_dir: str = "mock_sto…How to Use Array Typecodes for Compact Numeric Storage in Python
This code demonstrates how to use the `array` module with typecodes to store integers, floats, and bytes in a memory-efficient way compared to standard Python lists.
from array import array
def demonstrate_array_types():
# Compact integer arrays
small_ints = array('i', [1, 2, 3, 4, 5])
unsigned_ints = array('I', [10, 20, 30])
# Floating point arrays
floats = array('f', [1.5, 2.5, 3.5])
doubles = array('d', [1.123456789, 2.987654321])
# Charac…Using a Python Generator Instead of a List to Save Memory
Compare a list approach with a generator to stream values lazily, avoiding memory-heavy storage of large sequences.
def fibonacci_generator(limit):
a, b = 0, 1
count = 0
while count < limit:
yield a
a, b = b, a + b
count += 1
def sum_first_n(generator, n):
total = 0
for i, value in enumerate(generator):
if i >= n:
break
total += value
return total
if __…Create a Data Helper in Python for gRPC-style APIs
This code builds a simple DataHelper class that mimics gRPC request/response handling with in-memory storage, JSON serialization, and basic CRUD operations for beginners.
import json
from dataclasses import dataclass, asdict
from typing import Dict, Any
@dataclass
class User:
user_id: int
name: str
email: str
class DataHelper:
"""Simple helper to demonstrate gRPC-like data handling for beginners."""
def __init__(self) -> None:
self._users: Dict[int, Use…How to implement a write-behind cache with async queue in Python
Build an async write-behind cache that queues writes in memory and flushes them in batches to persistent storage.
import asyncio
from collections import deque
from dataclasses import dataclass
@dataclass
class CacheEntry:
key: str
value: str
class WriteBehindCache:
def __init__(self, flush_interval=1.0):
self.cache = {}
self.queue = deque()
self.flush_interval = flush_interval
self._f…Mock Predicate Pushdown in Python for Big Data Queries
Simulate predicate pushdown by applying filters at the storage layer before materializing rows, showing how big data engines optimize queries.
class Query:
def __init__(self, table, rows):
self.table = table
self.rows = rows
def filter(self, predicate):
return Query(
self.table,
[row for row in self.rows if all(predicate(row) for predicate in predicate)]
)
def filter_pushdown(self, predica…Modeling a Hive Metastore Table Schema in Python
A dataclass that mimics a Hive metastore table schema—columns, partition keys, storage format, and location—with helper methods for description and mutation.
from dataclasses import dataclass, field
from typing import Dict, List, Optional
@dataclass
class HiveTable:
"""Simple mock of a Hive metastore table schema."""
name: str
database: str = "default"
columns: List[Dict[str, str]] = field(default_factory=list)
partition_keys: List[Dict[str, str]] = f…How to mock an artifact store with local paths in Python for ML pipelines
Create a temporary local artifact store with dummy files and metadata to test ML pipeline code without real storage.
import tempfile
from pathlib import Path
import json
def create_artifact_store_mock(base_path: Path = None):
"""Create a local artifact store mock directory structure."""
if base_path is None:
base_path = Path(tempfile.mkdtemp())
store_layout = {
"artifacts": [
{"name": "mode…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():
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