337 lines
9.0 KiB
Plaintext
337 lines
9.0 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Goodies of the [Python Standard Library](https://docs.python.org/3/library/#the-python-standard-library)\n",
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"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."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## [`datetime`](https://docs.python.org/3/library/datetime.html#module-datetime) for working with dates and times"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import datetime as dt\n",
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"\n",
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"local_now = dt.datetime.now()\n",
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"print('local now: {}'.format(local_now))\n",
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"\n",
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"utc_now = dt.datetime.utcnow()\n",
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"print('utc now: {}'.format(utc_now))\n",
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"\n",
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"# You can access any value separately:\n",
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"print('{} {} {} {} {} {}'.format(local_now.year, local_now.month,\n",
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" local_now.day, local_now.hour,\n",
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" local_now.minute, local_now.second))\n",
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"\n",
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"print('date: {}'.format(local_now.date()))\n",
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"print('time: {}'.format(local_now.time()))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### `strftime()`\n",
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"For string formatting the `datetime`"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"formatted1 = local_now.strftime('%Y/%m/%d-%H:%M:%S')\n",
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"print(formatted1)\n",
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"\n",
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"formatted2 = local_now.strftime('date: %Y-%m-%d time:%H:%M:%S')\n",
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"print(formatted2)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### `strptime()`\n",
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"For converting a datetime string into a `datetime` object "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"my_dt = dt.datetime.strptime('2000-01-01 10:00:00', '%Y-%m-%d %H:%M:%S')\n",
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"print('my_dt: {}'.format(my_dt))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### [`timedelta`](https://docs.python.org/3/library/datetime.html#timedelta-objects)\n",
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"For working with time difference."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"tomorrow = local_now + dt.timedelta(days=1)\n",
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"print('tomorrow this time: {}'.format(tomorrow))\n",
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"\n",
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"delta = tomorrow - local_now\n",
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"print('tomorrow - now = {}'.format(delta))\n",
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"print('days: {}, seconds: {}'.format(delta.days, delta.seconds))\n",
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"print('total seconds: {}'.format(delta.total_seconds()))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Working with timezones\n",
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"Let's first make sure [`pytz`](http://pytz.sourceforge.net/) is installed."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import sys\n",
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"!{sys.executable} -m pip install pytz"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import datetime as dt\n",
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"import pytz\n",
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"\n",
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"naive_utc_now = dt.datetime.utcnow()\n",
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"print('naive utc now: {}, tzinfo: {}'.format(naive_utc_now, naive_utc_now.tzinfo))\n",
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"\n",
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"# Localizing naive datetimes\n",
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"UTC_TZ = pytz.timezone('UTC')\n",
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"utc_now = UTC_TZ.localize(naive_utc_now)\n",
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"print('utc now: {}, tzinfo: {}'.format(utc_now, utc_now.tzinfo))\n",
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"\n",
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"# Converting localized datetimes to different timezone\n",
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"PARIS_TZ = pytz.timezone('Europe/Paris')\n",
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"paris_now = PARIS_TZ.normalize(utc_now)\n",
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"print('Paris: {}, tzinfo: {}'.format(paris_now, paris_now.tzinfo))\n",
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"\n",
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"NEW_YORK_TZ = pytz.timezone('America/New_York')\n",
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"ny_now = NEW_YORK_TZ.normalize(utc_now)\n",
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"print('New York: {}, tzinfo: {}'.format(ny_now, ny_now.tzinfo))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**NOTE**: If your project uses datetimes heavily, you may want to take a look at external libraries, such as [Pendulum](https://pendulum.eustace.io/docs/) and [Maya](https://github.com/kennethreitz/maya), which make working with datetimes easier for certain use cases."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## [`logging`](https://docs.python.org/3/library/logging.html#module-logging)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import logging\n",
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"\n",
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"# Handy way for getting a dedicated logger for every module separately\n",
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"logger = logging.getLogger(__name__)\n",
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"logger.setLevel(logging.WARNING)\n",
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"\n",
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"logger.debug('This is debug')\n",
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"logger.info('This is info')\n",
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"logger.warning('This is warning')\n",
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"logger.error('This is error')\n",
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"logger.critical('This is critical')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Formatting log entries"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import logging\n",
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"\n",
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"# This is only required for Jupyter notebook environment\n",
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"from importlib import reload\n",
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"reload(logging)\n",
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"\n",
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"my_format = '%(asctime)s | %(name)-12s | %(levelname)-10s | %(message)s'\n",
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"logging.basicConfig(format=my_format)\n",
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"\n",
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"logger = logging.getLogger('MyLogger')\n",
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"\n",
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"logger.warning('Something bad is going to happen')\n",
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"logger.error('Uups, it already happened')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## [`random`](https://docs.python.org/3/library/random.html) for random number generation"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import random\n",
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"\n",
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"rand_int = random.randint(1, 100)\n",
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"print('random integer between 1-100: {}'.format(rand_int))\n",
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"\n",
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"rand = random.random()\n",
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"print('random float between 0-1: {}'.format(rand))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"If you need pseudo random numbers, you can set the `seed` for random. This will reproduce the output (try running the cell multiple times):"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import random\n",
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"\n",
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"random.seed(5) # Setting the seed\n",
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"\n",
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"# Let's print 10 random numbers\n",
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"for _ in range(10):\n",
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" print(random.random())"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## [`re`](https://docs.python.org/3/library/re.html#module-re) for regular expressions"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Searching occurences"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import re\n",
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"\n",
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"secret_code = 'qwret 8sfg12f5 fd09f_df'\n",
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"# \"r\" at the beginning means raw format, use it with regular expression patterns\n",
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"search_pattern = r'(g12)' \n",
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"\n",
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"match = re.search(search_pattern, secret_code)\n",
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"print('match: {}'.format(match))\n",
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"print('match.group(): {}'.format(match.group()))\n",
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"\n",
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"numbers_pattern = r'[0-9]'\n",
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"numbers_match = re.findall(numbers_pattern, secret_code)\n",
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"print('numbers: {}'.format(numbers_match))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Variable validation"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import re\n",
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"\n",
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"def validate_only_lower_case_letters(to_validate):\n",
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" pattern = r'^[a-z]+$'\n",
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" return bool(re.match(pattern, to_validate))\n",
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"\n",
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"print(validate_only_lower_case_letters('thisshouldbeok'))\n",
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"print(validate_only_lower_case_letters('thisshould notbeok'))\n",
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"print(validate_only_lower_case_letters('Thisshouldnotbeok'))\n",
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"print(validate_only_lower_case_letters('thisshouldnotbeok1'))\n",
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"print(validate_only_lower_case_letters(''))"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.5.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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