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Merge Data with Comprehension and Generator in Python
Merge user and order data using a dictionary comprehension for lookups and a generator expression to filter and transform orders.
def merge_data(users, orders):
"""
Merge user and order data using a dictionary comprehension
and a generator expression for filtering.
"""
# Build a lookup: user_id -> user name
user_map = {user["id"]: user["name"] for user in users}
# Generator: yield orders with user names attached
…Python Generator to Filter Duplicates with a Seen Set
A lazily-evaluated generator function that yields only the first occurrence of each item, using a set to track seen values.
def unique_generator(items):
seen = set()
for item in items:
if item not in seen:
seen.add(item)
yield item
if __name__ == "__main__":
data = [1, 2, 2, 3, 3, 3, 4, 5, 5]
result = list(unique_generator(data))
print(result)Demonstrate Prompt Injection Bypass in Python
Simulate why naive system prompt filters fail against prompt injection with casing and spacing variations.
# Demonstrate why system prompts can be bypassed by simulated user input
# This demo shows a naive filter being ignored via prompt injection
def process_user_message(message, system_rules):
"""Simulate an AI that follows system rules but gets tricked."""
# Claim to check system rules
for rule in system_ru…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.
…Download Images from a Web Page Automatically in Python
Scrape all images from a webpage, filter by extension, and save them to a local folder using requests and BeautifulSoup.
import requests
from bs4 import BeautifulSoup
from urllib.parse import urljoin
import os
def download_images(url, output_folder="downloaded_images"):
"""Download all images from a given URL."""
os.makedirs(output_folder, exist_ok=True)
response = requests.get(url)
response.raise_for_status()
…Generate a Monthly Report CSV from Log Files in Python
Reads a CSV log file, filters events by a given month, aggregates daily event counts and revenue, and writes a summarized monthly report to a new CSV.
import csv
from collections import defaultdict
from datetime import datetime
def generate_monthly_report(log_file: str, month: str, output_file: str) -> None:
events_by_date = defaultdict(int)
revenue_by_date = defaultdict(float)
with open(log_file, 'r') as f:
for line in f:
date_…How to Build a Python Tool That Finds Trending Open Source Projects Daily
A Python script that queries the GitHub Search API to fetch the top 5 trending repositories created in the last day, sorted by stars, with optional language filtering.
import requests
import json
import datetime
def fetch_trending_projects(language: str = "", since: str = "daily"):
url = "https://api.github.com/search/repositories"
date_limit = (datetime.date.today() - datetime.timedelta(days=1)).isoformat()
query = f"created:>{date_limit} language:{language}" if langua…How to Build an argparse CLI That Filters File Lines by Keyword in Python
This Python script is a command-line tool built with argparse that reads a text file and prints only the lines that contain (or don't contain) a given keyword.
import argparse
import sys
def main():
parser = argparse.ArgumentParser(description="Filter lines from a file by keyword.")
parser.add_argument("input", type=str, help="File to read")
parser.add_argument("keyword", type=str, help="Keyword to filter lines")
parser.add_argument("--contains", action="sto…How to Filter Docker Containers for Pruning in Python
Simulate Docker's container prune by filtering a JSON list for exited containers older than a cutoff, returning pruned IDs and space freed.
import json
from datetime import datetime, timedelta
def parse_docker_ps(json_output: str, older_than_hours: int = 24) -> list:
containers = json.loads(json_output)
cutoff = datetime.now() - timedelta(hours=older_than_hours)
return [
c for c in containers
if datetime.fromisoformat(c["crea…How to Find Stale GitHub Issues in Python
Filter a list of GitHub issues to find those not updated within a configurable number of days using Python datetime arithmetic.
import os
from datetime import datetime, timezone, timedelta
import re
# Simulated GitHub issue data structure
SAMPLE_ISSUES = [
{"number": 101, "title": "Login button not working", "updated_at": "2025-06-01T12:00:00Z", "assignee": "alice"},
{"number": 102, "title": "Fix database migration error", "updated_at…Create Data Helper Functions in Python for Beginners
Build reusable Python helper functions to load, filter, sort, summarize, and save JSON data — a beginner-friendly starting point for small data pipelines.
import json
from pathlib import Path
from typing import Any, Dict, List
def load_json_file(filepath: str) -> Dict[str, Any]:
"""Load JSON data from a file."""
with Path(filepath).open("r", encoding="utf-8") as file:
return json.load(file)
def filter_by_key(
data: List[Dict[str, Any]], key: str,…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…How to Build Data Processing Functions in Python
Create reusable helper functions to load, filter, transform, and aggregate CSV data in Python.
import csv
from pathlib import Path
def load_data(filepath):
"""Load CSV data into a list of dicts."""
with open(filepath, "r", newline="", encoding="utf-8") as f:
return list(csv.DictReader(f))
def filter_rows(rows, column, value):
"""Keep rows where column equals value."""
return [row for…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 Filter Data in Python
Filter a list of dictionaries by exact key-value matches or numerical ranges using concise list comprehensions.
from typing import List, Dict, Any
def filter_data(
data: List[Dict[str, Any]], key: str, value: Any
) -> List[Dict[str, Any]]:
"""Return records where data[key] equals value."""
return [record for record in data if record.get(key) == value]
def filter_by_range(
data: List[Dict[str, Any]], key: str…How to Merge Multiple Data Sources in Python
A beginner-friendly helper that merges lists of dictionaries from multiple sources into one combined list using key filtering.
import json
def merge_pipeline_data(*data_sources, keys=()):
"""Merge multiple data sources (list of dicts) into a single list of merged dicts.
Args:
*data_sources: One or more lists of dictionaries.
keys: Tuple of keys to include from each source (empty means all keys).
Returns:
…How to Process CSV Data in Python with a Data Helper
Build a beginner-friendly data helper in Python that loads a CSV file, filters rows by a condition, and summarizes numeric fields.
import csv
from pathlib import Path
DATA = [
{"name": "Alice", "score": 88, "passed": True},
{"name": "Bob", "score": 42, "passed": False},
{"name": "Carol", "score": 95, "passed": True},
]
def load_csv(file_path: Path) -> list[dict]:
with file_path.open(newline="", encoding="utf-8") as f:
r…Idempotent Pipeline Dedupe by Record ID Set in Python
Filters records against a persistent set of seen IDs, returning only new ones and the updated set for idempotent pipeline processing.
def dedupe_records(records, seen_ids=None):
"""Return records whose id has not been seen before."""
if seen_ids is None:
seen_ids = set()
unique = []
for record in records:
record_id = record.get("id")
if record_id not in seen_ids:
seen_ids.add(record_id)
…How to Filter Git History to Remove Secret File Entries in Python
A pure-Python mock that filters a repository's history to drop any commit that touched a secret file, so you can plan a cleanup before rewriting Git history.
from pathlib import Path
import json
def filter_history(history, secret_path):
"""Remove entries that touch the secret file."""
return [entry for entry in history if secret_path not in entry["files"]]
if __name__ == "__main__":
repo_history = [
{"commit": "a1b2c3", "message": "Add app", "files": …How to Generate Git LFS Extension Patterns in Python
This script builds mock Git LFS file patterns for common geospatial extensions and filters them based on compression suffixes.
import itertools
import re
LFS_EXTENSIONS = {".csv", ".geojson", ".tif", ".shp", ".gpkg"}
def build_mock_lfs_pattern(base_name="data_usgs_lidar"):
patterns = []
for ext in sorted(LFS_EXTENSIONS):
for variant in (("", ".lz4"), (".compressed",), (".b", ".a"), ("_v1", ".zip")):
full_pattern …How to mock EC2 describe-instances tag filtering in Python
Simulate AWS EC2 describe-instances with tag-based filtering using a mock dataset and conditional list comprehension.
import json
from datetime import datetime, timezone
def mock_describe_instances(tag_key: str, tag_value: str) -> list[dict]:
"""Simulate EC2 describe-instances with tag filtering."""
all_instances = [
{"InstanceId": "i-0abc123", "State": "running", "Tags": [{"Key": "Name", "Value": "web-server"}, {"K…How to Build a Chainable Filter Helper in Python
A beginner-friendly dataclass helper that chains filters, uniqueness, and slicing on any sequence, returning a plain list at the end.
from dataclasses import dataclass
from typing import Callable, Iterator, Sequence, TypeVar
T = TypeVar("T")
@dataclass
class FilterAssistant:
"""Beginner-friendly helper to filter any collection."""
data: Sequence[T]
def where(self, predicate: Callable[[T], bool]) -> "FilterAssistant":
return …Browse by section
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