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Extract Schema.org Structured Data from Any Website in Python
A Python tool that fetches a webpage and extracts all JSON-LD structured data (Schema.org) embedded in <script> tags with type="application/ld+json".
import requests
from bs4 import BeautifulSoup
import json
def extract_schema_org(url):
"""Extract structured data (Schema.org) from a website."""
try:
response = requests.get(url, timeout=10)
response.raise_for_status()
except requests.exceptions.RequestException as e:
return {"err…How to Convert Data Types in a Python Data Pipeline
Demonstrates a simple Python data pipeline that converts string values to proper types (bool, int, float, datetime) and outputs structured JSON.
import json
from datetime import datetime
def convert_value(value):
"""Convert string values to appropriate Python types."""
if value.lower() == "true":
return True
if value.lower() == "false":
return False
if value.isdigit():
return int(value)
try:
return float(val…How to Count JSON Records in Python
Read a JSON file and count the number of top-level records, handling both list and dictionary structures.
import json
from pathlib import Path
def count_records(json_file):
"""Count top-level records in a JSON file."""
with open(json_file, "r") as f:
data = json.load(f)
# Handle both list of records and dict of records
if isinstance(data, list):
return len(data)
elif isinstance(da…Generate Release Notes Markdown from PR Titles in Python
Generate structured Markdown release notes from a list of pull request titles using conventional commit types.
import json
from datetime import datetime, timezone
PRS = [
{"title": "feat: add user login", "number": 12, "merged_at": "2025-01-10"},
{"title": "fix: resolve payment timeout", "number": 13, "merged_at": "2025-01-11"},
{"title": "chore: bump dependencies", "number": 14, "merged_at": "2025-01-12"},
{"…How to Build a Git Helper Class in Python
A beginner-friendly GitHelper class that wraps common git commands (status, log, branch) into reusable Python methods with structured output.
import subprocess
import json
from pathlib import Path
class GitHelper:
def __init__(self, repo_path="."):
self.repo = Path(repo_path)
def run(self, *args):
result = subprocess.run(
["git", *args],
cwd=self.repo,
capture_output=True,
text=True,…How to generate and parse an interactive rebase TODO list in Python
Generate a Git interactive rebase TODO list from commit data and parse it back into structured records.
import re
from collections import namedtuple
Commit = namedtuple("Commit", ["hash", "subject"])
def generate_rebase_todo(commits, action="pick"):
todo_lines = []
for i, commit in enumerate(commits):
if i == 0 and action == "reword":
todo_lines.append(f"reword {commit.hash} {commit.subject…Upload Assets to GitHub Release with Python Mock
Simulates uploading binary and text assets to a GitHub release using a mock server, returning structured metadata for each upload.
import json
import os
import tempfile
from datetime import datetime
class ReleaseUploader:
"""Simulates uploading assets to a release with a mock server."""
def __init__(self, owner: str, repo: str, tag: str):
self.owner = owner
self.repo = repo
self.tag = tag
self.uploade…How to Convert Python Dict to JSON and Back
Convert Python dictionaries to JSON text and back with a simple helper that serializes and deserializes data structures.
import json
from datetime import datetime, timezone
def convert_data(data, source_format=None, target_format="json"):
"""
Convert Python data structures to txt/json and back.
For beginners: shows how to serialize/deserialize.
"""
if source_format == "json" and target_format == "dict":
ret…How to Mock GCP Cloud Functions HTTP Events in Python
Simulate a GCP Cloud Functions HTTP event with a Python mock handler that constructs a realistic event payload and returns a JSON response.
import json
from datetime import datetime, timezone
def mock_http_event(data):
"""Simulate a GCP Cloud Function HTTP event."""
event = {
"event_id": "mock-event-12345",
"timestamp": datetime.now(timezone.utc).isoformat(),
"event_type": "google.cloud.functions.http",
"resource"…Mock Google Pub/Sub publish and pull in Python
A lightweight in-memory mock of Google Pub/Sub with publisher/subscriber classes to test topic-based fan-out and message pulling without real infrastructure.
import json
import time
from collections import deque
from dataclasses import dataclass, field
from typing import Any, Callable
@dataclass
class Message:
data: str
attributes: dict[str, str] = field(default_factory=dict)
message_id: str | None = None
ack_id: str | None = None
class MockPublisher:
…Mock Route53 change_resource_record_sets in Python
This code demonstrates how to mock AWS Route53 change_resource_record_sets API calls using the botocore Stubber, allowing you to test DNS update logic without touching real infrastructure.
import boto3
from botocore.exceptions import ClientError
def mock_change_resource_record_sets():
"""Demonstrates Route53 change_resource_record_sets with a mock client."""
# Create a mock Route53 client
route53 = boto3.client('route53', region_name='us-east-1',
aws_access_key_id…How to Bind and Mock structlog Context in Python
Shows how to bind persistent key-value context to a structlog logger, unbind keys, and mock the logger in tests to verify context is passed correctly.
import structlog
from unittest.mock import patch
logger = structlog.get_logger()
def demo():
logger = structlog.get_logger()
logger = logger.bind(user_id=42, request_id="abc123")
logger.info("user logged in", action="login")
# Unbind a key
logger = logger.unbind("user_id")
logger.info("r…How to Parse and Extract Nested Data in Python
Load JSON files with Path and recursively extract values by key from nested Python structures using modern typing and standard library.
import json
from pathlib import Path
from typing import Any, Dict, List, Union
def load_data(filepath: Union[str, Path]) -> Union[Dict[str, Any], List[Any]]:
"""Load JSON data from a file with modern Path handling."""
path = Path(filepath)
if not path.exists():
raise FileNotFoundError(f"File not f…How to build a tox multi-env matrix with mock config in Python
Simulate a tox multi-environment matrix by validating environment names and grouping extras into a readable matrix structure.
```python
import tox
def run_tox_matrix(mock_envs):
"""Simulate a tox multi-env configuration and verify mock choices."""
config = {
"tox": {
"envlist": mock_envs,
"config": {
"basepython": "python3.9",
"deps": ["pytest", "mock"],
},
…Mocking loguru for Structured Logging in Python
Simulate loguru's structured logging with a custom mock that captures JSON-formatted log entries with bound context.
import json
import sys
from io import StringIO
from unittest.mock import patch
def mock_loguru():
# Simulate a structured logger with context binding
class StructuredLogger:
def __init__(self):
self.context = {}
def bind(self, **kwargs):
logger = StructuredLogger()
…How to Parse Data with Type Hints in Python
A beginner-friendly helper that parses simple dictionary- or list-like strings into typed Python structures using modern typing annotations.
from typing import Any, Dict, List, Union
def parse_data(raw: str) -> Union[Dict[str, Any], List[Any], str]:
"""Parse a simple string into structured data using type hints."""
cleaned = raw.strip()
if not cleaned:
return {}
if cleaned.startswith("{") and cleaned.endswith("}"):
…How to Use TypedDict and Dataclasses in Python
Create typed data structures with TypedDict and dataclasses, then use them as helper functions for describing objects in a type-safe way.
from typing import TypedDict, NotRequired, Optional
from dataclasses import dataclass
class User(TypedDict):
name: str
age: NotRequired[int]
email: Optional[str]
@dataclass
class Product:
id: int
title: str
price: float = 0.0
def describe_user(user: User) -> str:
age = user.get("age",…How to Use TypedDict for Data Validation in Python
Define a TypedDict schema and validate raw dictionary input with type hints for safer, more readable data handling.
from typing import Any, Dict, List, Optional, Union, TypedDict, Literal
class Product(TypedDict):
product_id: int
name: str
price: Union[int, float]
in_stock: bool
tags: Optional[List[str]]
def validate_product(data: Dict[str, Any]) -> Product:
product_id: int = int(data["product_id"])
na…How to Use TypedDict for Structured Dict Typing in Python
Define and use TypedDict to add type hints to dictionaries, improving code clarity and enabling static type checking in your Python projects.
from typing import TypedDict
class User(TypedDict):
name: str
age: int
email: str
def greet(user: User) -> str:
return f"Hello {user['name']}, age {user['age']}, contact {user['email']}"
if __name__ == "__main__":
alice: User = {"name": "Alice", "age": 30, "email": "alice@example.com"}
pr…How to Use setUp and tearDown in Python unittest TestCase
Demonstrates how to structure unit tests with setUp and tearDown methods in Python's unittest framework for reusable test fixtures.
import unittest
class ExampleTest(unittest.TestCase):
def setUp(self):
self.data = [1, 2, 3]
def tearDown(self):
self.data = None
def test_length(self):
self.assertEqual(len(self.data), 3)
def test_contains(self):
self.assertIn(2, self.data)
if __name__ == "__main…Builder pattern for mocking complex objects in Python
Use a fluent Builder to construct realistic mock objects with defaults, enabling readable test data setup.
class User:
def __init__(self):
self.name = "default"
self.age = 0
self.email = "unknown@example.com"
self.address = "unknown"
def __repr__(self):
return f"User(name={self.name!r}, age={self.age}, email={self.email!r}, address={self.address!r})"
class UserBuilder:
…How to Aggregate Mock API Routes by Method in Python
Groups mock API routes by path and method, collecting response bodies and counts into a nested dictionary structure.
from collections import defaultdict
def aggregate_mock_routes(routes):
"""Aggregate mock API routes by method and aggregate their response bodies."""
aggregated = defaultdict(lambda: defaultdict(list))
for route in routes:
method = route["method"]
path = route["path"]
response = …How to Implement CQRS with Separate Read and Write Models in Python
Implements Command Query Responsibility Segregation (CQRS) by splitting data into separate write and read models with dedicated repositories, using dataclasses for structure.
from dataclasses import dataclass, field
from typing import List, Dict, Optional
@dataclass
class OrderWriteModel:
order_id: int
customer: str
items: List[str] = field(default_factory=list)
def add_item(self, item: str) -> None:
self.items.append(item)
@dataclass
class OrderReadModel:
…How to Implement the Flyweight Pattern in Python
Implements the Flyweight design pattern to share immutable intrinsic state (character + font) across many document objects, reducing memory usage.
class Character:
"""Flyweight - stores only intrinsic state (shared)."""
def __init__(self, char: str, font: str):
self.char = char
self.font = font
def render(self, size: int) -> str:
return f"{self.char}_{self.font}_{size}"
class CharacterFactory:
"""Flyweight factory - ma…Browse by section
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