normanlmfung

from collections import defaultdict

word_lists = defaultdict(list)

pairs = [('a', 1), ('b', 2), ('c', 3), ('a', 4), ('b', 5)]

for key, value in pairs:
  word_lists[key].append(value) # Append value to list

print(word_lists.get('d', []))

normanlmfung

# REST API guard: check api key (If incorrect API key, raise exception)
def check_api_key(api_key : str, request : Any, symmetric_key : str, kms_gizmo : Any):
			def decorator(method):
				headers = request.headers
				encrypted_api_key_from_header = headers.get("X-Api-Key")
				decrypted_api_key_from_header = encrypted_api_key_from_header
				if kms_gizmo:
					decrypted_api_key_from_header = kms_gizmo.decrypt(decrypted_api_key_from_header)
				if symmetric_key:
					decrypted_api_key_from_header = cipher_gizmo.decrypt(encrypted_text=decrypted_api_key_from_header, key=symmetric_key)

normanlmfung

# timer (Simply log the duration of time the wrapped method took). Can also be extended to filter/modify parameters.
def timer(method):
	def timed(*args, **kw):
		start = time.time()
		result = method(*args, **kw)
		elapsed = (time.time() - start) * 1000 

		logger.info(f'@timer {method.__qualname__} returned in {elapsed} ms. {args_}')

		return result

normanlmfung

# Taken DIRECTLY from William's article https://realpython.com/python-interface/
import abc

class FormalParserInterface(metaclass=abc.ABCMeta):
  @classmethod
  def __subclasshook__(cls, subclass):
    print("FormalParserInterface.__subclasshook__")
    return (hasattr(subclass, 'load_data_source') and 
        callable(subclass.load_data_source) and 
        hasattr(subclass, 'extract_text') and 

normanlmfung

# https://docs.python.org/3/library/contextlib.html
	
from contextlib import contextmanager 
class MessageWriter(object):
  def __init__(self, filename):
    self.file_name = filename

  @contextmanager
  def open_file(self):
    try:

normanlmfung

class MessageWriter(object):
		def __init__(self, file_name):
			self.file_name = file_name
		 
		def __enter__(self):
			self.file = open(self.file_name, 'w')
			return self.file
	 
		def __exit__(self, *args):
			self.file.close()

normanlmfung

def fibonacci():
    a, b = 0, 1
    while True:
        yield a
        a, b = b, a + b

# Generate Fibonacci numbers up to a certain limit
def fibonacci_up_to(limit):
    fib = fibonacci()
    while True:

normanlmfung

class square_all:
	def __init__(self, numbers):
		self.numbers = iter(numbers)
	def __next__(self):
		return next(self.numbers) ** 2
	def __iter__(self):
		return self

normanlmfung

import numpy as np
from keras.models import Sequential
from keras.layers import Dense

X_train = np.array([[0, 0], [0, 1], [1, 0], [1, 1]])
y_train = np.array([[0], [1], [1], [0]])

model = Sequential()
model.add(Dense(2, input_dim=2, activation='relu'))
model.add(Dense(1, activation='sigmoid'))

normanlmfung

import json
import pandas as pd
import numpy as np
import math
from datetime import datetime
from tabulate import tabulate

# Illustration 1. Array initialization: ones/zeros/arrange/linspace
np.arange(0, 10, 2) # array([0, 2, 4, 6, 8])
np.zeros(10)