dazzag24

I have an updated version of this on my blog here: https://chrisamico.com/blog/2023-01-14/python-setup/.

Python

This is my recommended Python setup, as of Fall 2022. The Python landscape can be a confusing mess of overlapping tools that sometimes don't work well together. This is an effort to standardize our approach and environments.

Tools and helpful links:

Python docs: https://docs.python.org/3/
Python Standard Library: - Start here when you're trying to solve a specific problem

1. choose a simple linux image

For example alpine, it's only about 5MB.

2. set timezone if necessary

RUN apk add --no-cache tzdata
ENV TZ America/New_York

documents

create key group

generate key pair

Cloud-Init Debugging

Cloud-init combined with terraform can be a powerful tool to provision instances on startup. Debugging scripts that are run by cloud-init however are not the easiest to debug.

Logs

Usually on an Ubuntu machine a lot of what is happening can be found in the syslog

cat /var/log/syslog

Currently, there is an explosion of tools that aim to manage secrets for automated, cloud native infrastructure management. Daniel Somerfield did some work classifying the various approaches, but (as far as I know) no one has made a recent effort to summarize the various tools.

This is an attempt to give a quick overview of what can be found out there. The list is alphabetical. There will be tools that are missing, and some of the facts might be wrong--I welcome your corrections. For the purpose, I can be reached via @maxvt on Twitter, or just leave me a comment here.

There is a companion feature matrix of various tools. Comments are welcome in the same manner.

	View: Pods(<namespace>)[number of pods listed]

	NAME pod name
	READY number of pods in ready state / number of pods to be in ready state
	RESTARTS number of times the pod has been restarted so far
	STATUS state of the pod life cycle, such as Running \| ... \| Completed
	CPU current CPU usage, unit is milli-vCPU
	MEM current main memory usage, unit is MiB
	%CPU/R current CPU usage as a percentage of what has been requested by the pod
	%MEM/R current main memory usage as a percentage of what has been requested by the pod

	use anyhow::*;
	use futures::io::{copy, AsyncReadExt, AsyncWriteExt};
	use futures::stream::StreamExt;
	use log::*;
	use smol::Async;

	use std::net;

	const PORT: u16 = 5000;

	# Derived from: https://github.com/pydicom/pydicom/blob/master/examples/input_output/plot_read_dicom_directory.py.

	import imageio
	import matplotlib.pyplot as plt
	import numpy as np
	import pydicom

	from os import mkdir
	from os.path import join
	from PIL import Image

	from flask import Flask
	from flask import render_template
	import csv
	import json

	app = Flask(__name__)

	@app.route('/')
	def my_runs():
	runs = []