vlad-bezden’s gists

vlad-bezden / group_by_sequence.py

Created May 3, 2020 16:23

Sometimes, we'll have raw data that is a flat list of values that we'd like to bunch up into subgroups.

	SIZE = 5


	def group_by_sequence_even(n, sequence):
	"""Groups sequence by n number of items
	It will only return number of rows divided evenly.
	Remaining items will not be generated
	"""
	data_iter = iter(sequence)
	return [tuple(next(data_iter) for _ in range(n)) for _ in range(len(sequence) // n)]

vlad-bezden / dynamic_func_invocation.py

Created April 16, 2020 12:09

Example of how dynamically invoke function in Python

	class Cleaner:
	@classmethod
	def clean(cls, type, args, *kwargs):
	getattr(cls, f"_clean_{type}")(args, *kwargs)

	@classmethod
	def _clean_email(cls, args, *kwargs):
	print("invoked _clean_email function")

	@classmethod

vlad-bezden / asynio_blocking_code_default_executor.py

Created March 18, 2020 21:20

Example of running blocking code in asyncio using default executor. There are four tasks each of them sleep from 1 to 4 seconds corresponding. If it were concurrent call then they would run for 1 + 2+ 3 + 4 = 10 seconds. However, running them in executor executes each task on separate thread and the total time to execute all of them took 4 secon…

	import asyncio
	from time import sleep
	import logging

	logging.basicConfig(
	level=logging.DEBUG, format="%(asctime)s %(thread)s %(funcName)s %(message)s"
	)


	def long_task(t):

vlad-bezden / db_connection.py

Created February 29, 2020 10:40

MODULE-SCOPED CODE TO CONFIGURE DEPLOYMENT ENVIRONMENTS.

	# db_connection.py
	from __main__ import TESTING

	class TestingDatabase:
	def __init__(self):
	print("Connecting to DEV database")

	class RealDatabase:
	def __init__(self):
	print("Connecting to PROD database")

vlad-bezden / filterfalse_remove_elements.py

Last active February 22, 2020 15:47

Remove more than one element from the iterable

	"""Remove more than one element from the iterable"""
	import random
	from itertools import filterfalse

	random.seed(42)

	data = [random.randrange(5) for _ in range(10)]
	clean = [*filterfalse(lambda i: i == 0, data)]
	print(f"Remove 0s\n{data=}\n{clean=}\n")

vlad-bezden / asynio_blocking_code.py

Last active March 3, 2020 15:08

Run blocking code on the separate executor. Use asyncio to execute blocking io operation without blocking execution thread using "run_in_executor" function

	import asyncio
	from concurrent.futures.thread import ThreadPoolExecutor
	from time import sleep
	import logging

	logging.basicConfig(
	level=logging.DEBUG, format="%(asctime)s %(thread)s %(funcName)s %(message)s"
	)

vlad-bezden / iterable_static_type_checking.py

Created January 20, 2020 20:02

Example on how to use Iterable type instead of List to make mypy happy :)

	"""Static type checking using Iterable

	show function receives List[Base]. However, if I specify type as List[Base]
	mypy will return following error:

	error: Argument 1 to "show" has incompatible type "List[Double]"; expected "List[Base]"

	To fix it use Iterable[Base] instead

	Output:

vlad-bezden / find_and_index_performance_test.py

Created January 18, 2020 20:06

Performance tests of 'find' and 'index' Python functions

	"""Performance tests of 'find' and 'index' functions.

	Results:
	using_index t = 0.0259 sec
	using_index t = 0.0290 sec
	using_index t = 0.6851 sec

	using_find t = 0.0301 sec
	using_find t = 0.0282 sec
	using_find t = 0.6875 sec

vlad-bezden / treadmill_speed_calculation.ipynb

Created January 16, 2020 09:33

Calculates how many seconds, or minutes to take to run one circle (1/4 of mile) on the treadmill, and difference in seconds between with increasing speed

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vlad-bezden / numpy_diff_and_formatting.py

Created November 28, 2019 10:20

Here is a powerful example of numpy diff function. In this example, I chunk of memory and I need to find start, end, and length of the memory. 1 means allocated and 0 means free. using numpy.diff I was able to find start and the end of the allocated memory. Another example thing I use here is dynamic size of the column col_size = 7 and the power…

	import numpy as np

	# Memory allocation:
	# '1' means allocated, '0' means free
	memory = np.array([0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0])
	# contiguous memory allocations
	diff = np.diff(memory)
	# starts indices
	starts = np.nonzero(diff == 1)[0] + 1
	# ends indices

Vlad Bezden vlad-bezden