Andrei Berceanu berceanu

Connect via SSH to a Slurm compute job that runs as Enroot container

Being able to SSH directly into a compute job has the advantage of using all remote development tools such as using your IDE's debugger also for GPU jobs (VSCode, PyCharm, ...).

Slurm: Scheduling system that many HPC clusters use
Enroot: Container system like Docker for NVIDIA GPUs

General problem:

Obfuscating Python

Obfuscation isn't difficult in most programming languages. It's why we have "good practices" because it is so easy to hide what you mean in badly written code.

Obfuscation tends to be even easier in dynamic languages because of how forgiving they tend to be - and because they tend to give you direct access to the environment so that you can manipulate it.

Today, for fun, I'm going to obfuscate this code:

def _(n):

if n <= 0:

	;; nano-emacs.el --- NANO Emacs (minimal version) -- lexical-binding: t --

	;; Copyright (c) 2025 Nicolas P. Rougier
	;; Released under the GNU General Public License 3.0
	;; Author: Nicolas P. Rougier <[email protected]>
	;; URL: https://github.com/rougier/nano-emacs

	;; This is NANO Emacs in 256 lines, without any dependency
	;; Usage (command line): emacs -Q -l nano.el -[light\|dark]

	#!/bin/sh
	# Rasterize PDF files with Ghostscript and ImageMagick.

	set -e


	# parse options
	DENSITY='600'
	ADDEXT='.raster'

	def shimazaki_shinimoto_binning(x, min_bins, max_bins):
	"""The Shimazaki-Shinimoto histogram binning algorithm for choosing an
	optimal constant number of bins.

	Parameters
	----------

	x : array of int or float
	The data you want to bin

	"""
	===============
	Qt Fourier Demo
	===============
	"""

	import contextlib
	import sys

	from matplotlib.backends.backend_qt5agg import FigureCanvas

	# -- coding: utf-8 --
	"""
	Created on 2019-08-22 09:37:36

	@author: fmiorell
	"""

	# This script registers the "turbo" colormap to matplotlib, and the reversed version as "turbo_r"
	# Reference: https://ai.googleblog.com/2019/08/turbo-improved-rainbow-colormap-for.html

	# http://www.nvidia.com/download/driverResults.aspx/117079/en-us
	wget http://us.download.nvidia.com/tesla/375.51/nvidia-driver-local-repo-ubuntu1604_375.51-1_amd64.deb
	sudo dpkg -i nvidia-driver-local-repo-ubuntu1604_375.51-1_amd64.deb
	sudo apt-get update
	sudo apt-get -y install cuda-drivers

	echo "Reboot required."