Python Codes

Time complexity in above Picture Factorial of a number using Dynamic Programming: CODE: calculated = {} def fib(n): if n == 0: # base case 1 return 0 if n == 1: # base case 2 return 1 elif n in calculated: return calculated[n] else: # recursive step calculated[n] = fib(n-1) + fib(n-2) return calculated[n] Share and Support @Python_Codes

Time complexity in above Picture Factorial using Recursion CODE: def fib(n): if n <= 0: # base case 1 return 0 if n <= 1: # base case 2 return 1 else: # recursive step return fib(n-1) + fib(n-2) Share and Support @Python_Codes

Dynamic Programming: 👉 In simple words, the concept behind dynamic programming is to break the problems into sub-problems and save the result for the future so that we will not have to compute that same problem again. 👉 Dynamic programming is a problem-solving technique for resolving complex problems by recursively breaking them up into sub-problems, which are then each solved individually. Dynamic programming optimizes recursive programming and saves us the time of re-computing inputs later. Share and Support @Python_Codes

#numpy NumPy Smart use of ‘:’ to extract the right shape Sometimes you encounter a 3-dim array that is of shape (N, T, D), while your function requires a shape of (N, D). At a time like this, reshape() will do more harm than good, so you are left with one simple solution: Example: for t in xrange(T): x[:, t, :] = # ... Share and Support @Python_Codes

#numpy NumPy Broadcasting Broadcasting describes how NumPy automatically brings two arrays with different shapes to a compatible shape during arithmetic operations. Generally, the smaller array is “repeated” multiple times until both arrays have the same shape. Broadcasting is memory-efficient as it doesn’t actually copy the smaller array multiple times. Code:

import numpy as np

A = np.array([1, 2, 3])
res = A * 3 # scalar is broadcasted to [3 3 3]
print(res)

Output: # [3 6 9] Share and Support @Python_Codes

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#Basics Convert a value into a complex number

print(complex(10, 2)) 

Output: (10+2j) Share and Support @Python_Codes

#Basics Condition inside the print function def is_positive(number): print("Positive" if number > 0 else "Negative") is_positive(-3) Output: Negative Share and Support @Python_Codes

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#Basics Swap keys and values of a dictionary dictionary = {"a": 1, "b": 2, "c": 3} reversed_dictionary = {j: i for i, j in dictionary.items()} print(reversed) Output: {1: 'a', 2: 'b', 3: 'c'} Share and Support @Python_Codes

#Basics Checking if two words are anagrams Code:

from collections import Counter
def is_anagram(str1, str2):
     return Counter(str1) == Counter(str2)
  
# or without having to import anything 
def is_anagram(str1, str2): 
    return sorted(str1) == sorted(str2) 

print(is_anagram('code', 'doce')) print(is_anagram('python', 'yton')) Output: True False Share and Support @Python_Codes

#Basics Check The Memory Usage Of An Object. Code:

import sys
x = 1
print(sys.getsizeof(x))

Output: 28 Share and Support @Python_Codes

#Basics Find The Most Frequent Value In A List Code:

test = [1, 2, 3, 4, 2, 2, 3, 1, 4, 4, 4]
print(max(set(test), key = test.count))

Output: 4 Share and Support @Python_Codes

#Basics Return Multiple Values From Functions. Code:

def x():
    return 1, 2, 3, 4
a, b, c, d = x()

Input: print(a, b, c, d) Output: 1 2 3 4 Share and Support @Python_Codes

curry Curries a function. Use functools.partial() to return a new partial object which behaves like fn with the given arguments, args, partially applied. CODE: from functools import partial def curry(fn, *args): return partial(fn, *args) Examples: add = lambda x, y: x + y add10 = curry(add, 10) add10(20) # 30 Share and Support @Python_Codes