yeiichi

#!/usr/bin/env zsh

# Constants
tgt='filename.txt'               # target file, as always.
dst='[email protected]:directory' # destination
pnr=####                         # port number
idf="/path/to/identity_file"     # identity file

display_help() {
  cat <<EOF

yeiichi

#!/usr/bin/env zsh

display_help() {
  cat <<EOF
Extract URL strings from webloc files in a directory.
EOF
}

extract_urls() {
  # Prepare an output filename

yeiichi

#!/usr/bin/env python3

from pathlib import Path
from pprint import pprint
from random import sample

from natsort import natsorted


def sampler(orig, dest, size, ptn='*'):

yeiichi

#!/usr/bin/env python3
import sqlite3

import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns

# https://hellomyworld.net/posts/matplotlib-how-to-resolve-missing-from-current-font-japanese/
plt.rcParams['font.family'] = 'Hiragino Maru Gothic Pro'

yeiichi

#!/usr/bin/env zsh
# Decode X.509 certificates and keys: PEM, CRT, etc.

decode_x509() { openssl x509 -in "$1" -text -noout }
display_help() { echo '\033[93musage: decode509 <pem file>\033[0m\n' }

main() {
  [[ -f "$1" ]] && decode_x509 "$1" && return 0
  display_help }

yeiichi

#!/usr/bin/env zsh
# Description: Download a remote eml file and extract an attached zip file.

src='user@server:path/to/source.eml'
port_num=<ssh port number>
id_file=</path/to/pubkey>

display_help(){
  cat <<EOF
check_remote_eml [get cline conv] 

yeiichi

#!/usr/bin/env python3
import numpy as np


def str2list(text_in: str, delimiter=';') -> list:
    """Convert a string to a list.
       c.f. ast.literal_eval()
    """
    crude_list = text_in.split(delimiter)  # 'foo; bar' -> ['foo', ' bar']
    return [i.strip() for i in crude_list]  # ['foo', ' bar'] -> ['foo', 'bar']

yeiichi

#!/usr/bin/env zsh

display_help() {
  cat <<EOF

SQL Runner
----------
Run a SQL script of choice for the designated DB.
Usage: run_sql <foobar.sql>
       Prerequisite: DB name: <qux.db>

yeiichi

#!/usr/bin/env python3
import re
from pathlib import Path

import pandas as pd
from sklearn.preprocessing import MultiLabelBinarizer


def add_multi_hot_to_df(df_in, target_col: str):
    """Multi-hot-encode the target column data

yeiichi

#!/usr/bin/env zsh
# References: https://stackoverflow.com/a/16596385/11042987

display_intro() {
  printf "\033[93m** Convert a reST file into an HTML5 file **\n"
  printf "** using rst2html5.py.                    **\033[0m\n"
  return 0
}

main() {