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How to Create a Simple Data Helper in Python for LLM Projects
Create a beginner-friendly Python class that stores, filters, and serializes data records for AI/LLM workflows.
import json
from typing import Any, Dict, List, Optional
class DataHelper:
"""Simple helper for beginners to manage data in AI/LLM projects."""
def __init__(self, data: Optional[List[Dict[str, Any]]] = None) -> None:
self.data: List[Dict[str, Any]] = data or []
def add_item(self, item: Dict[str…How to Filter Blocked Words in Python
Scans input text against a moderation blocklist, returning blocked terms and their counts.
MODERATION_BLOCKLIST = {"spam", "scam", "fraud", "phishing", "malware", "abuse"}
def scan_text(text: str) -> dict:
normalized = text.lower()
words = normalized.replace(".", " ").replace(",", " ").replace("!", " ").replace("?", " ").split()
found_terms = []
for word in words:
if word in MO…How to Filter Toxic Keywords in Python
Filter toxic keywords from text by replacing each occurrence with asterisks, useful as a basic guardrail for LLM inputs.
TOXIC_KEYWORDS = ["insult", "threat", "hate", "violence", "spam"]
def guardrails_filter(text: str, keywords: list[str] | None = None) -> str:
"""Filter out toxic keywords from the given text.
Args:
text: The input text to filter.
keywords: Optional keyword list. Defaults to TOXIC_KEYWORDS.
…Prepare LLM prompt data with a Python helper class
A beginner-friendly Python class that collects records, converts them to JSON, and produces a quick summary for building LLM prompt context.
import json
from typing import Any, Dict, List
class DataHelper:
"""Simple helper to prepare data for LLM prompts."""
def __init__(self):
self.data = []
def add(self, item: Dict[str, Any]) -> "DataHelper":
self.data.append(item)
return self
def to_json(self) -> s…Build a Command-Line Password Generator in Python
Generate cryptographically strong random passwords using Python's secrets module and print them for command-line use.
import secrets
import string
def generate_password(length=16):
"""Generate a cryptographically strong random password."""
alphabet = string.ascii_letters + string.digits + string.punctuation
password = ''.join(secrets.choice(alphabet) for _ in range(length))
return password
if __name__ == "__main__":…Extract Every Open Graph and Social Media Meta Tag from Web Pages in Python
A Python script that fetches a webpage and extracts all Open Graph, Twitter Card, Facebook, and Article meta tags using the standard library HTML parser.
from html.parser import HTMLParser
import re
from urllib.request import urlopen
from urllib.parse import urlparse
class MetaExtractor(HTMLParser):
def __init__(self):
super().__init__()
self.meta_tags = []
def handle_starttag(self, tag, attrs):
if tag == 'meta':
attrs_…Find Sensitive Information in Log Files with Python
Scan log files for emails, IP addresses, API keys, and passwords using regular expressions in Python.
import re
import os
from pathlib import Path
def find_sensitive_info(log_path):
"""Scans log files for patterns like emails, IPs, API keys, and passwords."""
patterns = {
'Email': r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}',
'IP Address': r'\b(?:\d{1,3}\.){3}\d{1,3}\b',
'API Key'…Generate Strong Random Passwords with Custom Rules in Python
Build a configurable password generator using Python's secrets module that lets you toggle lowercase, uppercase, digits, and punctuation.
import secrets
import string
def generate_password(length=16, use_lower=True, use_upper=True, use_digits=True, use_punct=True):
pool = ''
if use_lower:
pool += string.ascii_lowercase
if use_upper:
pool += string.ascii_uppercase
if use_digits:
pool += string.digits
if use_pu…How to Generate Project Statistics Including Lines of Code and Complexity in Python
Walk through a Python script that scans a project directory for Python files, counts lines of code excluding blanks and comments, and estimates cyclomatic complexity by counting decision keywords.
import os
from pathlib import Path
def count_lines_of_code(filepath):
"""Counts lines of code in a Python file, excluding blank lines and comments."""
try:
with open(filepath, 'r') as f:
lines = f.readlines()
code_lines = [line for line in lines if line.strip() and not line.strip()…How to Import Users from CSV into LDAP-like Dicts in Python
Reads a CSV of user records and converts each row into an LDAP-style dictionary with standard attributes using Python's csv module.
import csv
import io
from pathlib import Path
def mock_ldap_import(csv_path):
"""
Reads a CSV file with user data and returns a list of LDAP-like user dicts.
Adds standard LDAP attributes that would come from directory schema.
"""
with open(csv_path, newline="", encoding="utf-8") as csvfile:
…How to Perform a DNS Lookup for A Records in Python
Resolve a hostname to IPv4 A records using Python's built-in socket.getaddrinfo and return a sorted list of addresses.
import socket
def get_a_records(hostname):
"""Fetch A records (IPv4 addresses) for a given hostname."""
try:
# getaddrinfo with family AF_INET restricts to IPv4 (A records)
infos = socket.getaddrinfo(hostname, None, socket.AF_INET)
# Each info tuple: (family, type, proto, canonname, so…How to Sort Command-Line Arguments in Python
Build a beginner-friendly argparse CLI that sorts numbers or words passed as arguments, with an optional reverse flag.
import argparse
def main():
parser = argparse.ArgumentParser(description="Sort numbers or words from the command line.")
parser.add_argument("items", nargs="+", help="Items to sort (numbers or words)")
parser.add_argument("--reverse", "-r", action="store_true", help="Sort in descending order")
args =…Attach Source File Metadata to Records in Python
Add a source filename field to each record in a list by merging a new key into every dictionary using a dict unpacking comprehension.
from pathlib import Path
import json
def attach_source_metadata(records, source_file):
"""Attach source filename metadata to each record."""
return [
{**record, "source": Path(source_file).name}
for record in records
]
if __name__ == "__main__":
source = "/data/raw/customers.csv"
…Build a Python Utility That Detects Duplicate Records Across Multiple Excel Sheets
A Python utility that uses pandas to find overlapping records across different Excel sheets based on specified key columns.
import pandas as pd
from pathlib import Path
def find_duplicate_records_across_sheets(file_path: str, key_columns: list, sheet_names: list) -> dict:
"""
Detect duplicate records across multiple Excel sheets based on specified key columns.
Args:
file_path: Path to the Excel file
key_co…Count Records Processed per Category in Python
Use a Counter dictionary to track how many records of each type (ok, error, retry) were processed in a data pipeline.
from collections import Counter
import random
processed_counter = Counter()
def process_records(records):
for record in records:
processed_counter[record] += 1
return len(records)
if __name__ == "__main__":
sample_records = [random.choice(["ok", "error", "retry"]) for _ in range(10)]
print(f…Fan Out Records to Multiple Sinks in Python
Distribute the same records across multiple target sinks (database, API, queue, etc.) using a defaultdict-based fan-out pattern.
import json
from collections import defaultdict
SINKS = ["database", "api", "message_queue", "data_lake", "monitoring"]
def fan_out(records, *sinks):
dist = defaultdict(list)
for record in records:
for sink in sinks:
dist[sink].append(record)
return dict(dist)
if __name__ == "__main_…Filter Records by Required Fields in Python
Filter a list of dictionaries, keeping only records where every required field is present and not None.
def filter_records(records, required_fields):
"""Return only records that have all required fields non-null."""
return [
record for record in records
if all(record.get(field) is not None for field in required_fields)
]
if __name__ == "__main__":
sample_records = [
{"name": "Al…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.
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=(",", ":"…How to Build a Simple Data Pipeline in Python
A beginner-friendly data pipeline that loads JSON, filters records by a field value, and aggregates counts per category.
import json
from pathlib import Path
def load_json(filepath: str | Path) -> list[dict]:
"""Load a JSON file containing a list of records."""
with Path(filepath).open("r", encoding="utf-8") as f:
return json.load(f)
def filter_records(records: list[dict], field: str, value) -> list[dict]:
"""Kee…How to Clean and Format Data in Python
This code loads JSON data, cleans records by removing empty fields and normalizing text, then summarizes the results with counts and unique keys.
import json
from pathlib import Path
def load_data(filepath: str) -> dict:
"""Load JSON data from a file."""
with Path(filepath).open("r", encoding="utf-8") as f:
return json.load(f)
def clean_records(records: list[dict]) -> list[dict]:
"""Remove empty fields and normalize text to lowercase."""…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…How to Implement Slowly Changing Dimension Type 2 History in Python
Build a type-2 slowly changing dimension pipeline that closes old records and opens new ones when customer data changes.
from datetime import datetime, timedelta
def apply_scd_type2(records, current_date):
"""Returns active records after inserting new records with type-2 history."""
history = []
active = {}
for record in records:
key = record["customer_id"]
if key in active:
active[key]["end…How to List Failed Records in a Dead Letter Queue Mock in Python
A mock Dead Letter Queue stores failed processing records with error details and timestamps, lists them, and exports to JSON.
import json
from datetime import datetime, timedelta
import random
class DeadLetterQueue:
def __init__(self):
self.failed_records = []
def add_failed_record(self, record_id, payload, error_message):
self.failed_records.append({
"record_id": record_id,
"payload": paylo…How to Track Checkpoint Offset After Batch Commit in Python
A batch processor that tracks the last successfully committed offset after processing records in batches, advancing the checkpoint only when each batch commits successfully.
import json
from typing import Any
class BatchProcessor:
"""Tracks checkpoint offset after committing batches."""
def __init__(self, batch_size: int = 3):
self.batch_size = batch_size
self.offset = 0 # last successfully committed offset (exclusive)
self.total_committed = 0
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