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combined_pattern = re.compile(r'''
    # Image reference
    ^\s*                    # Start of line, followed by optional whitespace
    \[image:\s+             # Literal '[image:', followed by at least one whitespace character
    ([^\]]+?)               # Capture group 1: Image name - one or more characters that are not ']', non-greedy
    \s*                     # Optional whitespace
    (?:                     # Start of non-capturing group for optional width
        (\d+)               # Capture group 2: One or more digits for width
        %                   # Literal '%' character
        \s*                 # Optional whitespace

judell

Claude

Concept	AWS	Azure	GCP
Hierarchical Grouping	AWS Organizations	Azure Management Groups	GCP Resource Hierarchy
Root Level	Root (Master Account)	Root Management Group	Organization
Tenant Concept	Not Applicable	Azure Active Directory (Azure AD) Tenant	Not Applicable
Grouping Levels	Organizational Units (OUs)	Management Groups	Folders
Lowest Level	AWS Accounts (Member Accounts)	Subscriptions	Projects
Policies	Service Control Policies (SCPs)	Azure Policies	Organization Policies

judell

Claude's initial classification of AWS/Azure/GCP storage types.

Storage Type	AWS	Azure	GCP
Object Storage	S3 (Simple Storage Service)	Blob Storage (part of Storage Account)	Cloud Storage
File Storage	EFS (Elastic File System)	File Storage (part of Storage Account)	Filestore
Block Storage	EBS (Elastic Block Store)	Managed Disks	Persistent Disk
Queue Storage	SQS (Simple Queue Service)	Queue Storage (part of Storage Account)	Cloud Pub/Sub

judell

example 1

with data as (
  select
    suppress_and_count_repeats (
      'pipes',
      'pipes_organization_member',
      'org_handle',
      'user_handle, user_id, status',

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CREATE OR REPLACE FUNCTION suppress_and_count_repeats(
    schema_name TEXT,                -- Schema name of the target table
    table_name TEXT,                 -- Name of the target table
    partition_by_column TEXT,        -- Column to partition by
    order_by_columns TEXT,           -- Columns to order by
    additional_column_names TEXT[]   -- Array of additional column names
) RETURNS SETOF JSON AS $$
DECLARE
    generated_query TEXT;            -- Variable to store the generated SQL query
    additional_selects TEXT;         -- Variable to store the dynamically constructed additional select statements

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WITH cte AS (
    SELECT
        org_handle,
        user_handle,
        status,
        ROW_NUMBER() OVER (PARTITION BY org_handle ORDER BY user_handle) AS rn,
        DENSE_RANK() OVER (ORDER BY org_handle) AS org_rank
    FROM
        pipes_organization_member
)

judell

import sys
import json
import base64
import os
from openai import OpenAI

# OpenAI API key
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")

client = OpenAI(api_key=OPENAI_API_KEY)

judell

import openai
import json
import os
from openai import OpenAI

client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))

# Mock function to simulate fetching weather data from an API
def get_weather(location):
    # In a real scenario, replace this with an actual API call

judell

func listDevices(ctx context.Context, d *plugin.QueryData, h *plugin.HydrateData) (interface{}, error) {
	var visitor ListPredicate = func(client *kolide.Client, cursor string, limit int32, searches ...kolide.Search) (interface{}, error) {
		return client.GetDevices(cursor, limit, searches...)
	}

	return listAnything(ctx, d, h, "kolide_device.listDevices", visitor, "Devices")
}


func listAdminUsers(ctx context.Context, d *plugin.QueryData, h *plugin.HydrateData) (interface{}, error) {

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func listAnything(ctx context.Context, d *plugin.QueryData, h *plugin.HydrateData, callee string, visitor ListPredicate, target string) (interface{}, error) {
	// Create a slice to hold search queries
	searches, err := query(ctx, d)
	if err != nil {
		plugin.Logger(ctx).Error(callee, "qualifier_operator_error", err)
		return nil, err
	}

	// Establish connection to Kolide client
	client, err := connect(ctx, d)