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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 Scan Files Against a Malware Hash List in Python
Compare a file's SHA-256 hash against a known malware hash set and report whether it's clean or infected.
import hashlib
from pathlib import Path
# Mock file content (in real usage, read from disk)
MOCK_FILE_CONTENT = b"print('hello world')"
KNOWN_MALWARE_HASHES = {
"8d969eef6ecad3c29a3a629280e686cf0c3f5d5a86aff3ca12020c923adc6c92",
"5e884898da28047151d0e56f8dc6292773603d0d6aabbdd62a11ef721d1542d8",
}
def sha25…How to Write an IP Block List to hosts.deny in Python
This Python script validates a list of IP addresses and CIDR ranges, then writes them to a hosts.deny file to block connections at the TCP wrapper level.
from ipaddress import ip_network
def write_hosts_deny(ip_list, output_file="hosts.deny"):
with open(output_file, "w") as f:
for ip in ip_list:
try:
ip_network(ip)
f.write(f"ALL: {ip}\n")
except ValueError:
continue
print(f"Written…Mock Certbot Renewal in Python for Testing
Simulates a Let's Encrypt certificate renewal by writing a mock certificate file and printing realistic certbot CLI output, without calling the actual certbot.
import subprocess
import sys
from datetime import datetime, timedelta
from pathlib import Path
def renew_cert(domain: str, output_dir: str = "certs") -> str:
"""Simulate a Let's Encrypt renewal with mock certbot output."""
out = Path(output_dir)
out.mkdir(parents=True, exist_ok=True)
cert_path = out…Stress CPU Threads with a Mock Compute in Python
Simulates CPU-intensive work across multiple threads to test how Python schedules parallel compute.
import threading
import time
def stress_cpu(iterations: int):
result = 0
for i in range(iterations):
result += i * i % 1000
return result
def run_mock_stress(thread_count: int, iterations: int):
threads = []
for tid in range(thread_count):
t = threading.Thread(target=lambda: str…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"
…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 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 Explode an Array Field into Multiple Rows in Python
This code flattens a list of dictionaries by exploding each array field value into its own row, duplicating the other fields as needed.
from collections import defaultdict
data = [
{"id": 1, "name": "Alice", "tags": ["python", "data", "ai"]},
{"id": 2, "name": "Bob", "tags": ["web", "devops"]},
{"id": 3, "name": "Carol", "tags": []},
]
def explode_array_field(records, array_field):
result = []
for record in records:
for v…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 Group Data by Key in Python
Group a list of dictionaries by a specified key using a defaultdict and compute per-group averages.
from collections import defaultdict
def group_by_key(data, key):
grouped = defaultdict(list)
for item in data:
grouped[item[key]].append(item)
return dict(grouped)
if __name__ == "__main__":
records = [
{"name": "Alice", "dept": "Engineering", "score": 85},
{"name": "Bob", "de…How to Group Rows by Key into Nested Arrays in Python
This code groups rows in a list of dictionaries by a specified key and returns a dictionary with each key mapped to a list of values from another key.
from collections import defaultdict
def implode_rows(rows, key, value_key):
grouped = defaultdict(list)
for row in rows:
grouped[row[key]].append(row[value_key])
return dict(grouped)
if __name__ == "__main__":
data = [
{"category": "fruit", "item": "apple"},
{"category": "fr…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 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 Reduce Aggregate Counts from Mapped Chunks in Python
Combine a list of mapped chunk dictionaries into a single aggregated count dictionary using functools.reduce.
from functools import reduce
from collections import defaultdict
def aggregate_chunks(mapped_chunks):
"""Combine mapped chunk counts into a single aggregate dict."""
return reduce(
lambda acc, chunk: {
**acc,
**{k: acc.get(k, 0) + v for k, v in chunk.items()}
},
…How to Sort a List of Dictionaries by Key in Python
A reusable helper function that sorts a list of dictionaries by a specified key, with optional descending order support.
from typing import List
def sort_records(records: List[dict], key: str, descending: bool = False) -> List[dict]:
"""Sort a list of dictionaries by a specified key."""
return sorted(records, key=lambda record: record[key], reverse=descending)
def demonstrate_sorting() -> None:
users = [
{"name": …How to Validate Data in a Python Pipeline
A helper module to validate common record types — email, positive integer, and non-empty string list — before processing data in a pipeline.
from typing import Any, Iterable
def is_valid_email(email: str) -> bool:
"""Basic email check: one '@', no spaces, dot after '@'."""
if "@" not in email or " " in email:
return False
local, _, domain = email.partition("@")
return bool(local) and "." in domain
def is_positive_int(value: Any)…How to detect anomalies in a column using z-score in Python
Detect outliers in a list of numbers using z-score statistics, flagging values that deviate significantly from the mean.
import random
def z_score_anomaly_detection(data, threshold=2.0):
"""
Detect anomalies in a list of numbers using z-score.
"""
mean = sum(data) / len(data)
variance = sum((x - mean) ** 2 for x in data) / len(data)
std_dev = variance ** 0.5
if std_dev == 0:
return []
a…How to route late-arriving data to a side output in Python
Separate late-arriving events from a streaming data batch into a dead-letter side output list using a timestamp threshold.
from collections import defaultdict
def late_arriving_side_output(events, late_threshold_ts):
"""
Mock a streaming pipeline that separates late-arriving data events
into a side output list (e.g., for dead-letter analysis).
events: list of (timestamp, data) tuples, timestamps as ints.
late_thresho…Bisect Good Bad Automation Script in Python
This Python script implements a binary search to find the first bad version in a list, simulating an automation script for git bisect.
import bisect
def find_first_bad(versions):
"""Given a list of version objects with .is_bad(), find first bad version."""
lo, hi = 0, len(versions)
while lo < hi:
mid = (lo + hi) // 2
if versions[mid].is_bad():
hi = mid
else:
lo = mid + 1
return lo
clas…Create a Mock GitHub Release API in Python for Testing gh CLI
Build an in-memory GitHub Releases API mock that mimics create_release and list_releases for unit testing gh CLI stubs without network calls.
import json
from unittest.mock import patch, Mock
class GitHubReleaseAPI:
"""Mock GitHub Releases API for testing gh CLI stub behavior."""
def __init__(self):
self.releases = {}
self.counter = 1
def create_release(self, repo, tag, name=None, notes=None):
release_id = self…How to List Changed Files in the Last Git Commit with Python
Runs `git diff --name-only HEAD~1 HEAD` via subprocess to list the names of files changed in the most recent commit.
import subprocess
def list_changed_files():
result = subprocess.run(
["git", "diff", "--name-only", "HEAD~1", "HEAD"],
capture_output=True,
text=True,
check=True
)
files = result.stdout.strip().splitlines()
return files
if __name__ == "__main__":
changed = list_cha…How to Parse git status --porcelain Output in Python
This code runs `git status --porcelain` and parses its output into a list of dictionaries with file paths and status descriptions.
import subprocess
def parse_git_status_porcelain():
try:
output = subprocess.check_output(
["git", "status", "--porcelain"],
text=True,
stderr=subprocess.DEVNULL
)
except (subprocess.CalledProcessError, FileNotFoundError):
return []
entries = …Create a Cloud Storage Helper Class in Python
Build a simple local file-based helper class that mimics cloud storage operations like save, load, and list JSON objects.
import datetime
import json
from pathlib import Path
class CloudDataHelper:
"""Simple helper for reading/writing JSON files in a cloud-style folder."""
def __init__(self, base_dir: str = "cloud_storage"):
self.base_dir = Path(base_dir)
self.base_dir.mkdir(exist_ok=True)
def save_json(se…Browse by section
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