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Set Comprehension for Unique Word Lengths in Python
Use a set comprehension to extract unique word lengths from a string, then sort and print the result.
text = "hello world hello python programming"
word_lengths = {len(word) for word in text.split()}
print("Unique word lengths:", word_lengths)
print("Sorted:", sorted(word_lengths))How to Parse JSON from LLM Model Output Fence in Python
Extract and parse a JSON object from a language model's output that may be wrapped in triple-backtick fences with an optional language tag.
import json
import re
def parse_json_from_fence(text):
"""
Extract JSON object from a model output that may be wrapped in
triple-backtick fences with optional language tag.
"""
# Match content insideJSON Mode Prompt Schema Output in Python
Extract a user object to JSON with explicit schema keys, ready for LLM JSON-mode prompts.
import json
from typing import Any, Dict
def extract_user_as_json(user: Dict[str, Any]) -> str:
"""Extract a user object and return it as JSON using explicit schema keys."""
schema_fields = ("id", "name", "email", "is_active")
user_subset = {key: user[key] for key in schema_fields if key in user}
ret…How to rename music files by ID3 tags in Python
Renames MP3 files in a folder using artist and title extracted from ID3 tags, with a mock fallback that parses filenames.
import os
import re
from pathlib import Path
def sanitize_filename(name: str) -> str:
return re.sub(r'[<>:"/\\|?*]', '_', name).strip()
def rename_mp3_from_id3(path: Path) -> None:
for f in path.glob("*.mp3"):
# Mock ID3 extraction: derive artist/title from filename
stem = f.stem
if "…Parse WHOIS Data with Python Regex
Extract domain registration fields from a mock WHOIS record using regex and compute days until expiration.
import re
from datetime import datetime
def parse_whois(whois_text: str) -> dict:
"""Extract key registration fields from a mock WHOIS record."""
patterns = {
"domain": r"Domain Name:\s*(.+)",
"registrar": r"Registrar:\s*(.+)",
"creation_date": r"Creation Date:\s*(.+)",
"expir…Parse nginx access log top IPs in Python
Reads an nginx access log line by line, extracts the client IP, and returns the most frequent IPs using a regex and Counter.
import re
from collections import Counter
def top_ips(log_file, n=10):
ip_pattern = re.compile(r'^(\S+)')
ip_counts = Counter()
with open(log_file, 'r') as f:
for line in f:
match = ip_pattern.match(line)
if match:
ip_counts[match.group(1)] += 1
return…Run pytest and email summary in Python
Runs pytest via subprocess, extracts the test summary line, and sends it in an email (mocked for demonstration).
import smtplib
import subprocess
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
def run_tests():
"""Run pytest and capture the summary output."""
result = subprocess.run(
["pytest", "-q"],
capture_output=True,
text=True
)
return result.stdo…ETL in Python: Extract CSV, Transform Dict, Load JSON
Build a simple ETL pipeline in Python that reads a CSV file, transforms each row (stripping whitespace and converting numeric fields), and writes the result to JSON.
import csv
import json
from pathlib import Path
def extract_csv(file_path):
"""Read CSV file and return list of row dictionaries."""
with Path(file_path).open('r', newline='', encoding='utf-8') as f:
reader = csv.DictReader(f)
return list(reader)
def transform_dicts(rows):
"""Transform ro…ETL in Python: Extract CSV, Transform Dicts, Load JSON
Build a simple ETL pipeline that reads a CSV, normalizes keys and converts price to float, then writes structured JSON.
import csv
import json
from pathlib import Path
def etl_csv_to_json(csv_path: str, json_path: str) -> None:
"""Extract CSV, transform rows to dicts, load to JSON."""
with open(csv_path, mode='r', newline='', encoding='utf-8') as f:
reader = csv.DictReader(f)
records = list(reader)
# Trans…How to Parse Data in Python: A Beginner's Helper
This helper parses a JSON payload, extracts user names, emails, and signup dates, then summarizes the results.
import json
from datetime import datetime
from typing import Dict, List
def parse_data(payload: str) -> Dict[str, List]:
"""Parse a JSON payload and extract useful fields."""
raw = json.loads(payload)
users = raw.get("users", [])
parsed = {
"names": [],
"emails": [],
"signup_…How to Partition Output Files by Date Key in Python
Group output files into a dictionary partitioned by a YYYYMMDD date key extracted from the filename prefix.
from pathlib import Path
from collections import defaultdict
def partition_files_by_date(directory: str) -> dict:
"""Partition output files by date key extracted from filename (YYYYMMDD prefix)."""
path = Path(directory)
partitions = defaultdict(list)
for file in path.iterdir():
if file.i…Parallel Extract Multiple Sources with Threads in Python
Extract data from multiple sources in parallel using ThreadPoolExecutor and verify results match sequential processing.
import threading
from concurrent.futures import ThreadPoolExecutor
def extract_from_source(source):
"""Simulate extracting data from a source."""
return f"Data from {source}"
def main():
sources = ["source_a", "source_b", "source_c", "source_d"]
# Sequential extraction for comparison
sequent…How to Check an SCP Deny List in Python
Load a JSON SCP policy file, extract the deny_list, and check if a target ARN is denied.
import json
from pathlib import Path
def evaluate_scp_deny_list(policy_path: Path, target_path: str) -> bool:
policy = json.loads(policy_path.read_text())
deny_list = policy.get("deny_list", [])
return target_path in deny_list
if __name__ == "__main__":
policy_file = Path("scp_policy.json")
pol…How to Parse an AWS API Gateway Proxy Event in Python
Extract and parse common fields from a mock API Gateway proxy event, turning the JSON body into a native Python dict.
import json
from typing import Any, Dict, Optional
def parse_proxy_event(event: Dict[str, Any]) -> Dict[str, Any]:
"""Extract and parse common fields from an API Gateway proxy event."""
body = event.get("body", "")
if isinstance(body, str):
body = json.loads(body) if body else {}
elif body is…How to Mock Poetry pyproject.toml Dependencies Sections in Python
Parse and extract dependency lists from Poetry-style pyproject.toml text using Python's standard library.
from pathlib import Path
import re
def parse_pyproject_dependencies(text):
"""Extract dependencies from a pyproject.toml style text."""
lines = text.splitlines()
sections = {
"dependencies": [],
"dev": [],
"optional": [],
}
current_section = None
patterns = {
…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 Read the Python Path from VS Code settings.json in Python
This code loads VS Code's settings.json file and extracts the python.defaultInterpreterPath value, with a mock demonstration for testing.
import json
from pathlib import Path
from unittest.mock import patch
def read_vscode_python_path(settings_path: Path) -> str:
"""Extract python.defaultInterpreterPath from VS Code settings.json."""
with open(settings_path, "r") as f:
settings = json.load(f)
return settings.get("python", {}).get("d…How to Mock Content-Disposition and Extract Filename in Python
Parse and mock Content-Disposition headers in Python to extract filenames, handling both plain and RFC 5987 encoded values.
import os
from pathlib import Path
import re
from unittest.mock import patch
def get_filename_from_content_disposition(header_value):
"""
Extract filename from a Content-Disposition header value.
Supports both filename and filename* parameters (RFC 5987).
"""
if not header_value:
return No…How to Parse Log Lines with Regex in Python
Extracts timestamp, log level, service name, and message from a log line using compiled regex named groups.
import re
LOG_PATTERN = re.compile(
r'^(?P<timestamp>\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}) '
r'\[(?P<level>\w+)\] '
r'\((?P<service>[^)]+)\) '
r'(?P<message>.*)$'
)
def parse_log_line(line: str) -> dict:
match = LOG_PATTERN.match(line)
if not match:
return {"error": "invalid log format…How to Implement a Data Helper Class in Python for Production Deployments
Build an environment-aware data helper in Python that loads config, extracts, transforms, and reports on JSON data using small, testable functions.
"""Production-style data helper for beginners.
Demonstrates:
- environment-aware config
- central data extraction
- small, testable functions
"""
import os
import json
from pathlib import Path
from typing import List, Dict, Any
def load_config(env: str = os.getenv("APP_ENV", "development")) -> Dict[str, Any]:
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