Cristian Cardellino crscardellino

## wines-data.csv

          
            Quality
            Split
            Alcohol
            Malic acid
            Ash
            Alcalinity of ash
            Magnesium
            Total phenols
            Flavanoids
            Nonflavanoid phenols
            Proanthocyanins
            Color intensity
            Hue
            OD280/OD315 of diluted wines
            Proline

            
              1
              train
              13.16
              2.36
              2.67
              18.6
              101
              2.8
              3.24
              0.3
              2.81
              5.68
              1.03
              3.17
              1185

            
              1
              train
              14.37
              1.95
              2.5
              16.8
              113
              3.85
              3.49
              0.24
              2.18
              7.8
              0.86
              3.45
              1480

            
              1
              train
              14.2
              1.76
              2.45
              15.2
              112
              3.27
              3.39
              0.34
              1.97
              6.75
              1.05
              2.85
              1450

            
              1
              train
              14.83
              1.64
              2.17
              14.0
              97
              2.8
              2.98
              0.29
              1.98
              5.2
              1.08
              2.85
              1045

            
              1
              train
              13.86
              1.35
              2.27
              16.0
              98
              2.98
              3.15
              0.22
              1.85
              7.22
              1.01
              3.55
              1045

            
              1
              train
              14.12
              1.48
              2.32
              16.8
              95
              2.2
              2.43
              0.26
              1.57
              5.0
              1.17
              2.82
              1280

            
              1
              train
              13.75
              1.73
              2.41
              16.0
              89
              2.6
              2.76
              0.29
              1.81
              5.6
              1.15
              2.9
              1320

            
              1
              train
              13.63
              1.81
              2.7
              17.2
              112
              2.85
              2.91
              0.3
              1.46
              7.3
              1.28
              2.88
              1310

            
              1
              train
              14.3
              1.92
              2.72
              20.0
              120
              2.8
              3.14
              0.33
              1.97
              6.2
              1.07
              2.65
              1280

## flatten_dict.py
from collections.abc import MutableMapping
from typing import Any, Dict


def _flatten_dict_gen(d: MutableMapping, parent_key: str, sep: str):
    for k, v in d.items():
        new_key = parent_key + sep + k if parent_key else k
        if isinstance(v, MutableMapping):
            yield from flatten_dict(v, new_key, sep).items()
        elif isinstance(v, list) or isinstance(v, list):

## get_1_to_n_combinations.py
def get_1_to_n_combinations(lst):
    return list(itertools.chain([
        c
        for r in range(1, len(lst) + 1)
        for c in itertools.combinations(sorted(lst), r)
    ]))

## nginx_access_logs_regex.py
import re

log_regex = re.compile(r"""(?P<remote_addr>[0-9a-f\.:]+)\s+-\s+""" +
                       r"""(?P<remote_user>\S+)\s+""" +
                       r"""\[(?P<date_day>\d{2})\/(?P<date_month>[a-zA-Z]{3})\/(?P<date_year>\d{4}):""" +
                       r"""(?P<time_hour>\d{2}):(?P<time_minutes>\d{2}):(?P<time_seconds>\d{2})\s+""" +
                       r"""(?P<time_offset>(?:\-|\+)\d{4})\]\s+""" +
                       r"""\"(?P<http_action>[a-zA-Z]+)\s+(?P<http_path>\S+)\s+(?P<http_protocol>\S+)\"\s+""" +
                       r"""(?P<status_code>\d+)\s+""" +
                       r"""(?P<bytes_sent>\d+)\s+""" +

## boot_ip_mailer.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-

from __future__ import absolute_import, print_function, unicode_literals

import datetime
import smtplib
import subprocess
import sys

## slurm.sh
#!/bin/bash
### Lines "#SBATCH" configure the job resources
### (even though they look like bash comments)

### Job queue to use (options: batch)
#SBATCH --partition=batch

### Amount of nodes to use
#SBATCH --nodes=1

## maxjobs.sh
#!/usr/bin/env bash
set -e

maxcores=${1:-6}
sleeptime=${2:-5}

function maxjobs {
  while [ $(jobs | wc -l) -ge $maxcores ]
  do
    sleep $sleeptime

## traverse_directory.py
# -*- coding: utf-8 -*-

from __future__ import absolute_import, print_function, unicode_literals

import fnmatch
import os

def traverse_directory(path, file_pattern='*'):
    for root, _, filenames in os.walk(path):
        for filename in fnmatch.filter(filenames, file_pattern):

## check_process.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-

from __future__ import absolute_import, print_function, unicode_literals

import argparse
import os
import smtplib
import subprocess
import sys
Quality	Split	Alcohol	Malic acid	Ash	Alcalinity of ash	Magnesium	Total phenols	Flavanoids	Nonflavanoid phenols	Proanthocyanins	Color intensity	Hue	OD280/OD315 of diluted wines	Proline
1	train	13.16	2.36	2.67	18.6	101	2.8	3.24	0.3	2.81	5.68	1.03	3.17	1185
1	train	14.37	1.95	2.5	16.8	113	3.85	3.49	0.24	2.18	7.8	0.86	3.45	1480
1	train	14.2	1.76	2.45	15.2	112	3.27	3.39	0.34	1.97	6.75	1.05	2.85	1450
1	train	14.83	1.64	2.17	14.0	97	2.8	2.98	0.29	1.98	5.2	1.08	2.85	1045
1	train	13.86	1.35	2.27	16.0	98	2.98	3.15	0.22	1.85	7.22	1.01	3.55	1045
1	train	14.12	1.48	2.32	16.8	95	2.2	2.43	0.26	1.57	5.0	1.17	2.82	1280
1	train	13.75	1.73	2.41	16.0	89	2.6	2.76	0.29	1.81	5.6	1.15	2.9	1320
1	train	13.63	1.81	2.7	17.2	112	2.85	2.91	0.3	1.46	7.3	1.28	2.88	1310
1	train	14.3	1.92	2.72	20.0	120	2.8	3.14	0.33	1.97	6.2	1.07	2.65	1280
	from collections.abc import MutableMapping
	from typing import Any, Dict


	def _flatten_dict_gen(d: MutableMapping, parent_key: str, sep: str):
	for k, v in d.items():
	new_key = parent_key + sep + k if parent_key else k
	if isinstance(v, MutableMapping):
	yield from flatten_dict(v, new_key, sep).items()
	elif isinstance(v, list) or isinstance(v, list):
	def get_1_to_n_combinations(lst):
	return list(itertools.chain([
	c
	for r in range(1, len(lst) + 1)
	for c in itertools.combinations(sorted(lst), r)
	]))
	import re

	log_regex = re.compile(r"""(?P<remote_addr>[0-9a-f\.:]+)\s+-\s+""" +
	r"""(?P<remote_user>\S+)\s+""" +
	r"""\[(?P<date_day>\d{2})\/(?P<date_month>[a-zA-Z]{3})\/(?P<date_year>\d{4}):""" +
	r"""(?P<time_hour>\d{2}):(?P<time_minutes>\d{2}):(?P<time_seconds>\d{2})\s+""" +
	r"""(?P<time_offset>(?:\-\|\+)\d{4})\]\s+""" +
	r"""\"(?P<http_action>[a-zA-Z]+)\s+(?P<http_path>\S+)\s+(?P<http_protocol>\S+)\"\s+""" +
	r"""(?P<status_code>\d+)\s+""" +
	r"""(?P<bytes_sent>\d+)\s+""" +
	#!/usr/bin/env python
	# -- coding: utf-8 --

	from __future__ import absolute_import, print_function, unicode_literals

	import datetime
	import smtplib
	import subprocess
	import sys
	#!/bin/bash
	### Lines "#SBATCH" configure the job resources
	### (even though they look like bash comments)

	### Job queue to use (options: batch)
	#SBATCH --partition=batch

	### Amount of nodes to use
	#SBATCH --nodes=1
	#!/usr/bin/env bash
	set -e

	maxcores=${1:-6}
	sleeptime=${2:-5}

	function maxjobs {
	while [ $(jobs \| wc -l) -ge $maxcores ]
	do
	sleep $sleeptime
	# -- coding: utf-8 --

	from __future__ import absolute_import, print_function, unicode_literals

	import fnmatch
	import os

	def traverse_directory(path, file_pattern='*'):
	for root, _, filenames in os.walk(path):
	for filename in fnmatch.filter(filenames, file_pattern):