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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 perform a star schema join in Python
Denormalize mock fact and dimension tables by building lookup dicts and enriching each sales fact with customer, product, and date attributes.
from datetime import date
# Mock dimension tables
customers = [
{"customer_id": 1, "name": "Alice", "city": "New York"},
{"customer_id": 2, "name": "Bob", "city": "Los Angeles"},
{"customer_id": 3, "name": "Carol", "city": "Chicago"},
]
products = [
{"product_id": 101, "name": "Laptop", "category": "…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 Validate Request Body JSON Against a Schema in Python
Build a lightweight schema validator to check required fields, types, string lengths, allowed values, and nested objects in a JSON request body.
import json
def validate_against_schema(data, schema, path=""):
errors = []
if not isinstance(data, dict):
errors.append(f"{path}: expected object, got {type(data).__name__}")
return errors
for field, rules in schema.items():
field_path = f"{path}.{field}" if path else field
…Backward Compatible Schema Evolution in Python
A mock schema validator that evolves JSON schemas while preserving backward compatibility by keeping old fields and validating required ones.
import json
from copy import deepcopy
class SchemaValidator:
def __init__(self, schema):
self.schema = schema
def evolve(self, new_schema):
"""Evolve mock schema while keeping backward compatibility."""
for field in self.schema:
if field not in new_schema:
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Guide: free Python code samples library
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Samples vs tutorials and challenges
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