Intelrunner

SELECT
 TIMESTAMP_TRUNC(jobs.start_time, second) as sec,
 SUM(SAFE_DIVIDE(total_slot_ms, TIMESTAMP_DIFF(end_time, start_time, MILLISECOND))) AS Slot_Count, project_ID as project
FROM
 `region-us`.INFORMATION_SCHEMA.JOBS_BY_ORGANIZATION jobs
WHERE jobs.start_time BETWEEN TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 3 DAY) AND CURRENT_TIMESTAMP()
GROUP BY project_id, sec
ORDER BY sec DESC

Intelrunner

for VARIABLE in $(gsutil ls)
do
  echo $(gsutil du $VARIABLE | grep -v /$ | wc -l) $VARIABLE
done

Intelrunner

{
  "$schema": "https://raw.githubusercontent.com/jsonresume/resume-schema/v1.0.0/schema.json",
  "basics": {
    "name": "Yannick Caillaud",
    "label": "Data Scientist @Betclic-Group",
    "image": "",
    "email": "yannick.caillaud@hotmail.fr",
    "phone": "",
    "url": "",
    "summary": "Passionate about Machine Learning, Data Mining and Data Science in general.\nEnjoy create value based on not enough exploited data: from POC to MVP to Production, from quick-wins to R&D challenge.\n[Kaggle](https://www.kaggle.com/kinnay) competition contributor.",

Intelrunner

"""Script that parses pricing data from Google's API.

Intended to be run periodically for the terra-ui's estimated price UI. The
output is something you could copy and paste into a javascript file.
See https://cloud.google.com/billing/v1/how-tos/catalog-api for more detail
on Google Cloud pricing information.

Usage:
1) Follow the instructions at the above URL to create an API key
2) Run `python3 parse_pricing_api.py ${API_KEY}`

Intelrunner

from six.moves import urllib
import requests

def url_is_alive(url):
    """
    Checks that a given URL is reachable.
    :param url: A URL
    :rtype: bool
    """
    request = urllib.request.Request(url)

Intelrunner

#!/usr/bin/env bash

export PROJECT_ID=$(gcloud config get-value project)
export PROJECT_USER=$(gcloud config get-value core/account) # set current user
export PROJECT_NUMBER=$(gcloud projects describe $PROJECT_ID --format="value(projectNumber)")
export IDNS=${PROJECT_ID}.svc.id.goog # workload identity domain

export GCP_REGION="us-central1"
export GCP_ZONE="us-central1-a"

Intelrunner

#!/bin/sh
# more information: https://cloud.google.com/asset-inventory/docs/exporting-to-bigquery

# must have gcloud cli installed
gcloud asset export \      
# must provide a dataset 
 --bigquery-dataset $DATASET   \

# this is for a resource based output
 --content-type resource \

Intelrunner

FROM — specifies the base (parent) image.
LABEL —provides metadata. Good place to include maintainer info.
ENV — sets a persistent environment variable.
RUN —runs a command and creates an image layer. Used to install packages into containers.
COPY — copies files and directories to the container.
ADD — copies files and directories to the container. Can upack local .tar files.
CMD — provides a command and arguments for an executing container. Parameters can be overridden. There can be only one CMD.
WORKDIR — sets the working directory for the instructions that follow.
ARG — defines a variable to pass to Docker at build-time.
ENTRYPOINT — provides command and arguments for an executing container. Arguments persist.

Intelrunner

List only instances with no labels

gcloud compute instances list --filter=-labels:'*'

Intelrunner

""" Warning - this script automatically submits a request for GCP DLP job creation
to scan for every table, in every dataset available to a user. This will fail if the following APIs / Permissions
are not enabled. 

This script can, and may, cost you actual $$. Outcomes can be seen in the DLP console.

DLP - jobs.create, jobs.get, jobs.list

BQ - bigquery.user (role)