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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.

csv ldap import

Python

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:
    …

14 0 Open

Automation & scripting easy

How to Parse Terraform Plan Output in Python

Parse mock Terraform plan output text into structured add, change, and destroy lists using Python.

terraform parsing automation

Python

import json
from typing import Dict, List

def parse_terraform_plan_output(plan_output_text: str) -> Dict[str, List[str]]:
    """
    Parses a mock Terraform plan output text into a structured dictionary.
    """
    parsed: Dict[str, List[str]] = {"add": [], "change": [], "destroy": []}

    for line in plan_output_…

11 0 Open

Automation & scripting easy

Parse WHOIS Data with Python Regex

Extract domain registration fields from a mock WHOIS record using regex and compute days until expiration.

whois regex parsing

Python

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…

12 0 Open

Automation & scripting easy

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.

nginx log parsing regex

Python

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…

14 0 Open

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