Goodies of the Python Standard Library

The Python Standard Libary is part of your Python installation. It contains a wide range of packages which may be helpful while building your Python masterpieces. This notebook lists some of the commonly used packages and their main functionalities.

datetime for working with dates and times

In [1]:
import datetime as dt

local_now = dt.datetime.now()
print('local now: {}'.format(local_now))

utc_now = dt.datetime.utcnow()
print('utc now: {}'.format(utc_now))

# You can access any value separately:
print('{} {} {} {} {} {}'.format(local_now.year, local_now.month,
                                 local_now.day, local_now.hour,
                                 local_now.minute, local_now.second))

print('date: {}'.format(local_now.date()))
print('time: {}'.format(local_now.time()))
local now: 2018-04-29 09:37:51.098934
utc now: 2018-04-29 07:37:51.099132
2018 4 29 9 37 51
date: 2018-04-29
time: 09:37:51.098934

strftime()

For string formatting the datetime

In [2]:
formatted1 = local_now.strftime('%Y/%m/%d-%H:%M:%S')
print(formatted1)

formatted2 = local_now.strftime('date: %Y-%m-%d time:%H:%M:%S')
print(formatted2)
2018/04/29-09:37:51
date: 2018-04-29 time:09:37:51

strptime()

For converting a datetime string into a datetime object

In [3]:
my_dt = dt.datetime.strptime('2000-01-01 10:00:00', '%Y-%m-%d %H:%M:%S')
print('my_dt: {}'.format(my_dt))
my_dt: 2000-01-01 10:00:00

timedelta

For working with time difference.

In [4]:
tomorrow = local_now + dt.timedelta(days=1)
print('tomorrow this time: {}'.format(tomorrow))

delta = tomorrow - local_now
print('tomorrow - now = {}'.format(delta))
print('days: {}, seconds: {}'.format(delta.days, delta.seconds))
print('total seconds: {}'.format(delta.total_seconds()))
tomorrow this time: 2018-04-30 09:37:51.098934
tomorrow - now = 1 day, 0:00:00
days: 1, seconds: 0
total seconds: 86400.0
In [5]:
import logging

# Handy way for getting a dedicated logger for every module separately
logger = logging.getLogger(__name__)
logger.setLevel(logging.WARNING)

logger.debug('This is debug')
logger.info('This is info')
logger.warning('This is warning')
logger.error('This is error')
logger.critical('This is critical')
This is warning
This is error
This is critical

Formatting log entries

In [6]:
import logging

# This is only required for Jupyter notebook environment
from importlib import reload
reload(logging)

my_format = '%(asctime)s | %(name)-12s | %(levelname)-10s | %(message)s'
logging.basicConfig(format=my_format)

logger = logging.getLogger('MyLogger')

logger.warning('Something bad is going to happen')
logger.error('Uups, it already happened')
2018-04-29 09:37:51,152 | MyLogger     | WARNING    | Something bad is going to happen
2018-04-29 09:37:51,153 | MyLogger     | ERROR      | Uups, it already happened

random for random number generation

In [7]:
import random

rand_int = random.randint(1, 100)
print('random integer between 1-100: {}'.format(rand_int))

rand = random.random()
print('random float between 0-1: {}'.format(rand))
random integer between 1-100: 86
random float between 0-1: 0.1548320881860572

If you need pseudo random numbers, you can set the seed for random. This will reproduce the output (try running the cell multiple times):

In [8]:
import random

random.seed(5)  # Setting the seed

# Let's print 10 random numbers
for _ in range(10):
    print(random.random())
0.6229016948897019
0.7417869892607294
0.7951935655656966
0.9424502837770503
0.7398985747399307
0.922324996665417
0.029005228283614737
0.46562265437810535
0.9433567169983137
0.6489745531369242

re for regular expressions

Searching occurences

In [9]:
import re

secret_code = 'qwret 8sfg12f5 fd09f_df'
# "r" at the beginning means raw format, use it with regular expression patterns
search_pattern = r'(g12)' 

match = re.search(search_pattern, secret_code)
print('match: {}'.format(match))
print('match.group(): {}'.format(match.group()))

numbers_pattern = r'[0-9]'
numbers_match = re.findall(numbers_pattern, secret_code)
print('numbers: {}'.format(numbers_match))
match: <_sre.SRE_Match object; span=(9, 12), match='g12'>
match.group(): g12
numbers: ['8', '1', '2', '5', '0', '9']

Variable validation

In [10]:
import re

def validate_only_lower_case_letters(to_validate):
    pattern = r'^[a-z]+$'
    return bool(re.match(pattern, to_validate))

print(validate_only_lower_case_letters('thisshouldbeok'))
print(validate_only_lower_case_letters('thisshould notbeok'))
print(validate_only_lower_case_letters('Thisshouldnotbeok'))
print(validate_only_lower_case_letters('thisshouldnotbeok1'))
print(validate_only_lower_case_letters(''))
True
False
False
False
False