Intelrunner

[
  "accessapproval.googleapis.com",
  "aiplatform.googleapis.com",
  "alloydb.googleapis.com",
  "analyticshub.googleapis.com",
  "anthosedge.googleapis.com",
  "apigateway.googleapis.com",
  "apigee.googleapis.com",
  "apigeeconnect.googleapis.com",
  "apigeeregistry.googleapis.com",

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# Ensure these environment variables are set before running the script:
# export PROJECT_ID=<your-project-id>
# export USER_EMAIL=<user-email>
# export EXPIRATION_DATE=<expiration-date> # Format: YYYY-MM-DD

# Creates the custom role for BigQuery Reservations Viewer
gcloud iam roles create bigqueryReservationsViewer \
  --project="$PROJECT_ID" \
  --title="BigQuery Reservations Viewer" \
  --permissions="bigquery.reservations.list,bigquery.reservationAssignments.list,bigquery.capacityCommitments.list" \

Intelrunner

# This is not an original work, but crafted based on: https://gist.github.com/momota/ba302f0f0720ff5b2445fb81820c5b82
# I updated it to make a file closer to the size I needed consistantly. All praise goes to: @momota and @andrewFarley for
# The original gist.

import csv
import random

# 1000000 and 62 == roughly 1.3GB (will take a bit of time, go get a coffee)
rows = 1200000
columns = 62

Intelrunner

#!/bin/bash

# Create the crontab entry
(crontab -l 2>/dev/null; echo "*/5 * * * * source /var/user-scripts/backup_script.sh") | crontab -

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#!/bin/bash

# Check to see if the backup directory exists
# If not, create it
if [ ! -d "/var/mongobackup" ]; then
  sudo mkdir /var/mongobackup
fi
sudo chmod 777 /var/mongobackup

mongodb_pwd=$(curl "http://metadata.google.internal/computeMetadata/v1/instance/attributes/MONGODB_PWD" -H "Metadata-Flavor: Google")

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# Where and how to store data.
storage:
  dbPath: /var/lib/mongodb
#  engine:
#  wiredTiger:

# where to write logging data.
systemLog:
  destination: file
  logAppend: true

Intelrunner

from google.cloud import storage
import os
def update_soft_delete():
    """Lists all buckets in a project."""

    storage_client = storage.Client()
    buckets = storage_client.list_buckets()
      
    for bucket in buckets:
        print ("****************")

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"""
Instructions
- Download to folder
- > Run "pip3 freeze > requirements.txt"
- > Run pip3 "install -r requirements.txt"
- > run python3 -m main.py
- Enjoy
"""

from tabula import convert_into, read_pdf

Intelrunner

import subprocess

# Function to run shell commands
def run_command(command):
    try:
        output = subprocess.check_output(command, shell=True, text=True)
        return output.strip()  # Return output with whitespace stripped
    except subprocess.CalledProcessError as e:
        print(f"Command failed with error: {e}")
        return None

Intelrunner

#!/bin/bash

# The Organization ID (Replace with your organization's ID)
ORG_ID="your-organization-id"

# Gather all projects under the specified organization
PROJECT_IDS=$(gcloud projects list --organization=${ORG_ID} --format="value(projectId)")

# Loop through each project
for PROJECT_ID in ${PROJECT_IDS}; do