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services:
  hamclock:
    image: ghcr.io/chrisromp/hamclock-docker:latest
    container_name: hamclock
    ports:
      - "2080:8080/tcp"
      - "2081:8081/tcp"
    volumes:
      - "${DATA_PATH}/hamclock:/root/.hamclock"
    restart: unless-stopped

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

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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"

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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)

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ssh <user>@<server> "head -c 200M </dev/urandom" | dd of=/dev/null

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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:

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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/

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# 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,

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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),

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Host my_shortcut
	HostName my_hostname
	User my_username
	Compression yes
	ServerAliveInterval 60