jonathanagustin

%matplotlib inline

def bootstrap():
    # @title Bootstrap Google Colab {display-mode:"form"}

    # CONFIGURE: Parameters
    GOOGLE_DRIVE_FOLDER = "my_folder" # @param {type:"string"}
    GitHub = True  # @param {type:"boolean"}
    OpenAI = True  # @param {type:"boolean"}
    HuggingFace = True  # @param {type:"boolean"}

jonathanagustin

Resource Extractor

This Go application parses the output of a helm template or kubectl kustomize command and extracts resource information, generating a CSV file with the extracted data.

Prerequisites

• Go (version 1.17 or later)
• Helm (version 3 or later) (if using Helm)
• kubectl (if using Kustomize)

jonathanagustin

%%capture
# ---------------------------------------------------------------------------- #
# @title Install autogluon on Google Colab { display-mode: "form" }
# ---------------------------------------------------------------------------- #
import contextlib
with open('/content/install-autogluon.log', 'w') as f:
    with contextlib.redirect_stdout(f):
        %pip install uv
        !git clone --recurse-submodules --depth=1 https://github.com/autogluon/autogluon.git
        !uv pip install --system -e /content/autogluon/common/

jonathanagustin

%%capture
# ---------------------------------------------------------------------------- #
# @title Install auto-sklearn on Google Colab { display-mode: "form" }
# ---------------------------------------------------------------------------- #
import contextlib
with open('/content/install-auto-sklearn.log', 'w') as f:
    with contextlib.redirect_stdout(f):
        %pip install uv
        !uv pip install --system Cython==0.29.36 pyparsing==2.4
        !uv pip install --system -r https://raw.githubusercontent.com/automl/auto-sklearn/master/requirements.txt

jonathanagustin

#!/usr/bin/env python3
import subprocess
from pathlib import Path

SKIP_LIST = [
    ".git",
    "build",
    "venv",
    ".venv",
    "node_modules",

jonathanagustin

print("Hello, World!")

jonathanagustin

# Colab2PDF v1.0.0 by Drengskapur (github.com/drengskapur/colab2pdf) (License: GPL-3.0-or-later)
# @title {display-mode:"form"}
# @markdown ⬇️ Download PDF
def colab2pdf():
    ENABLE=True # @param {type:"boolean"}
    if ENABLE:
        import os, datetime, json, pathlib, urllib, requests, werkzeug, nbformat, google, yaml, warnings
        NAME = pathlib.Path(werkzeug.utils.secure_filename(urllib.parse.unquote(requests.get(f"http://{os.environ['COLAB_JUPYTER_IP']}:{os.environ['KMP_TARGET_PORT']}/api/sessions").json()[0]["name"])))
        TEMP = pathlib.Path("/content/pdfs") / f"{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}_{NAME.stem}"; TEMP.mkdir(parents=True, exist_ok=True)
        NB = [cell for cell in nbformat.reads(json.dumps(google.colab._message.blocking_request("get_ipynb", timeout_sec=30)["ipynb"]), as_version=4).cells if "--Colab2PDF" not in cell.source]

jonathanagustin

# @title Convert Notebook to PDF. Save Notebook to: `/content/drive/MyDrive/Colab Notebooks'
NOTEBOOK_NAME = "notebooke.ipynb" # @param {type:"string"}
#------------------------------------------------------------------------------#
from google.colab import drive
drive.mount("/content/drive/", force_remount=True)
NOTEBOOKS = "/content/drive/MyDrive/Colab Notebooks"
NOTEBOOK_PATH = f"{NOTEBOOKS}/{NOTEBOOK_NAME}"
assert os.path.exists(NOTEBOOK_PATH), f"NOTEBOOK NOT FOUND: {NOTEBOOK_PATH}"
!apt install -y texlive-xetex texlive-fonts-recommended texlive-plain-generic
!jupyter nbconvert "$NOTEBOOK_PATH" --to pdf

jonathanagustin

{ 
  "project_name": "Index", 
  "author": "Anonymous"
}

jonathanagustin

Setup Ubuntu 16.04 to be used with Vagrant and Virtualbox

Prepare Vagrant box with Ubuntu 16.04

We will use official box "ubuntu/xenial64" and modify it to work with Vagrant.

• Vagrantfile