Pierdomenico Fiadino pierdom

This how-to has been tested using a Synology DS214play nas with DSM 6.X and Syncthing v1.1.4.

Default Synology certificate and private key (e.g., released by Let's Encrypt) at this path: /usr/syno/etc/certificate/system/default/{cert.pem|privkey.pem}.

After installing Syncthing using synocommunity.com repository, its self-signed certificate will be at this path: /volume1/@appstore/syncthing/var/. This directory contains the priv-pub key to identify the device (cert.pem and key.pem) and the certificate and private key for the web interface (https_cert.pem and https_key.pem). We need to replace these last two with the Synology's ones.

Backup Syncthing certificate:

Generate certificates using Easy-RSA

Istruzioni qui: https://firxworx.com/blog/it-devops/sysadmin/creating-certificates-and-keys-for-openvpn-server-with-easyrsa-on-macos/

Configurare server

https://www.sparklabs.com/support/kb/article/setting-up-an-openvpn-server-with-dd-wrt-and-viscosity/

	filetype on
	filetype plugin on
	filetype indent on
	syntax on
	set number
	set cursorline
	set showmode
	set showmatch
	set hlsearch
	set history=1000

	import matplotlib.pylab as plt
	import seaborn as sns
	import matplotlib

	sns.set_style('whitegrid')

	matplotlib.rcParams['figure.figsize'] = [9, 5]
	matplotlib.rcParams['figure.facecolor'] = "#f2ece3"
	matplotlib.rcParams['axes.facecolor'] = "#f2ece3"
	matplotlib.rcParams['legend.facecolor'] = "#f2ece3"

	# define a custom function that calculates the percentile using numpy
	def perc(n):
	def perc_(x):
	return np.percentile(x, n)
	perc_.__name__ = 'perc_%s' % n
	return perc_

	# apply this function (and other stuff) to Pandas Groupby
	df.groupby(['group_key_1', 'group_key_2']).agg({
	'col_a': np.sum,

	In [1]: from shapely.geometry import Point
	In [2]: import geopandas as gpd

	In [3]: shapely_polygon = Polygon([(0, 0), (0, 1), (1, 0)])

	In [4]: gpd.GeoSeries([shapely_polygon]).__geo_interface__
	Out[4]:
	{'bbox': (0.0, 0.0, 1.0, 1.0),
	'features': [{'bbox': (0.0, 0.0, 1.0, 1.0),
	'geometry': {'coordinates': (((0.0, 0.0),

	Host my_shortcut
	HostName my_hostname
	User my_username
	Compression yes
	ServerAliveInterval 60

	mybins = [0, 1, 2, 3, 4, 5]
	ax = sns.distplot(my_df.my_col, bins=mybins)
	_ = ax.xaxis.set(ticks=np.arange(0.5, len(mybins)), ticklabels=mybins)

	cnames = {
	'aliceblue': '#F0F8FF',
	'antiquewhite': '#FAEBD7',
	'aqua': '#00FFFF',
	'aquamarine': '#7FFFD4',
	'azure': '#F0FFFF',
	'beige': '#F5F5DC',
	'bisque': '#FFE4C4',
	'black': '#000000',
	'blanchedalmond': '#FFEBCD',