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diff --git a/docs/.env b/docs/.env
index b24647eb..9f09d4cb 100644
--- a/docs/.env
+++ b/docs/.env
@@ -1 +1,2 @@
-PORT=8104
\ No newline at end of file
+PORT=8104
+FLASK_DEBUG=true
\ No newline at end of file

nottrobin

Yarn vs NPM speed test

Work in progress

I recently made a claim on Twitter that yarn is still significantly faster than npm for installing NodeJS dependencies.

My belief here was based on some light research I did near the end of 2017, not too long after NPM 5 was released claiming huge speed improvements. I found a blog post at the time claiming Yarn was still faster, and then did some light testing which confirmed this for me, by a large margin.

However, my assertion was challenged:

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# HELP wsgi_latency Multiprocess metric
# TYPE wsgi_latency histogram
wsgi_latency_sum{method="GET",status="200",view="flask.helpers.static"} 23.605999999999998
wsgi_latency_sum{method="GET",status="200",view="app.homepage"} 8083.161
wsgi_latency_sum{method="GET",status="304",view="flask.helpers.static"} 5.361
wsgi_latency_sum{method="GET",status="200",view="app.cloud_and_server"} 2901.036
wsgi_latency_bucket{le="4.0",method="GET",status="200",view="flask.helpers.static"} 4.0
wsgi_latency_bucket{le="8.0",method="GET",status="200",view="flask.helpers.static"} 7.0
wsgi_latency_bucket{le="16.0",method="GET",status="200",view="flask.helpers.static"} 7.0
wsgi_latency_bucket{le="32.0",method="GET",status="200",view="flask.helpers.static"} 7.0

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app=maas.io

deployment_failed_reason=$(kubectl get deployment --namespace staging --selector app=${app} -o=jsonpath='{.items[0].status.conditions[1].reason}')

if [ "${deployment_failed_reason}" == "ProgressDeadlineExceeded" ]; then
  non_ready_pod=$(kubectl get pod --namespace staging --selector app=${app} --output json | jq -r '(.items | map(select(.status.containerStatuses[0].ready==false)))[0].metadata.name')
  kubectl logs ${non_ready_pod} --namespace staging
fi

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#! /usr/bin/env python3

# Standard library
import re
from io import BytesIO
from glob import glob
from PIL import Image
from urllib.parse import urlparse, parse_qs
from urllib.request import urlopen
from xml.etree import ElementTree

nottrobin

# Get juju-docs and discoursifier
git clone -b devel https://github.com/juju/docs ~/git/juju-docs
git clone https://github.com/canonical-webteam/discoursifier ~/git/discoursifier

# Setup python venv for discoursifier
python3 -m venv ~/git/discoursifier/env3
source ~/git/discoursifier/env3/bin/activate
pip install -r ~/git/discoursifier/requirements.txt

# Enter the documentation directory

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# Get the codebase
git clone git+ssh://{username}@git.launchpad.net/crbs

# Start a new LXC container
lxc launch ubuntu:bionic crbs

# Share the local repository folder with the container (at ~/crbs)
setfacl -Rm user:lxd:rwx,default:user:lxd:rwx,user:165536:rwx,default:user:165536:rwx,user:166536:rwx,default:user:166536:rwx . # Add permissions for the LXD users
lxc config device add crbs crbs-repo disk source=`pwd` path=/home/ubuntu/crbs  # Share the folder as a LXD device

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First we need to find the user ID of the container's user.

LXD might be installed in one of two ways. You can tell which, by running:

$ which lxc
/usr/bin/lxc  # This means it's installed as a deb
# OR
/snap/bin/lxc  # This means it's installed as a snap

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[tool.poetry]
name = "django-project"
version = "0.1.0"
description = ""
authors = ["Your Name <you@example.com>"]

[tool.poetry.dependencies]
python = "^3.5"
django = "^2.1"

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[tool.poetry]
name = "django-project"
version = "0.1.0"
description = ""
authors = ["Your Name <you@example.com>"]

[tool.poetry.dependencies]
python = "^3.5"

[tool.poetry.dev-dependencies]