Answers for "convert python code to C code"

online c code to python code conversion

#include<stdio.h>
using namespace std;
void main()
{
  for (int i=1, i<=5, i++)
  {
    for(int j=1, j<=i,j++)
    {
      printf("%c",64+j)
    }
    printf("\n")
  }
}

convert python code to C code

"""
coronavirus
3
abcde
crnas
onarous

"""
# Iterative Python program to check if a
# string is a subsequence of another string

# Returns true if str1 is a subsequence of str2

def main(str1, str2):
    m = len(str1)
    n = len(str2)

    j = 0 # Index of str1
    i = 0 # Index of str2

    # Traverse both str1 and str2
    # Compare the current character of str2 with
    # first unmatched character of str1
    # If matched, then move ahead in str1

    while j < m and i < n:
        if str1[j] == str2[i]:
            j = j+1
        i = i + 1

    # If all characters of str1 matched,
    # then j is equal to m
    return j == m

# Driver Program
str2 = str(input())
N = int(input())

for i in range(N):
    str1 = str(input())
    if main(str1, str2):
        print("POSITIVE") 
    else:
        print( "NEGATIVE")

convert python code to C code

def ReadMatrix():
    matrix = []
    for i in range(int(input())):
        row = [int(j) for j in input().split()]
        matrix.append(row) 
    return matrix

def RotateMatrix(matrix, degrees):
    n = len(matrix[0])
    rotations = (degrees // 90) % 4
    for r in range(rotations):
        temp_matrix = []
        for i in range(n):
            column = [row[i] for row in matrix]
            column.reverse()
            temp_matrix.append(column)
        matrix = temp_matrix
    return matrix

matrix = ReadMatrix()
rotation = 0

while True:
    line = input().split()
    if line[0] == "-1":
        break;
    elif line[0] == "R":
        rotation += int(line[1])
        matrix = RotateMatrix(matrix, int(line[1]))
    elif line[0] == "U":
         matrix[int(line[1])][int(line[2])] = int(line[3])
         matrix = RotateMatrix(matrix, rotation)
    elif line[0] == "Q":
        print(matrix[int(line[1])][int(line[2])]) 
    else:
        print(line[0])
        exit(1)

convert python code to C code

# Importing
import sklearn
from sklearn.datasets import load_boston
import pandas as pd
import matplotlib.pyplot as plt
  
# Load the dataset
bos_hou = load_boston()
  
# Create the dataframe
column_name = bos_hou.feature_names
df_boston = pd.DataFrame(bos_hou.data)
df_boston.columns = column_name
df_boston.head()

python code to c code converter

class Buffer:

    def __init__(self,size_max):
        self.max = size_max
        self.data = []

    class __Full:

        def append(self, x):

            self.data[self.cur] = x
            self.cur = (self.cur+1) % self.max
        def get(self):

            return self.data[self.cur:]+self.data[:self.cur]

    def append(self,x):

        self.data.append(x)
        if len(self.data) == self.max:
            self.cur = 0

            self.__class__ = self.__Full

    def get(self):

        return self.data


if __name__=='__main__':
    n=input('Enter the occupide size of the buffer : ')
    x=Buffer(int(n))

    x.append(1); x.append(2); x.append(3); x.append(4)

    print (x.__class__, x.get(  ))
    l=len(x.data)
    print(f"The free buffer is :{l}")
    print(f"The left size buffer is :{int(n)-int(l)}")

    x.append(5)

    print (x.__class__, x.get(  ))
    x.append(6)
    print (x.data, x.get(  ))
    x.append(7); x.append(8); x.append(9); x.append(10)
    print (x.data, x.get(  ))

convert python code to c online

def main():
  # 4 x 4 csr matrix
  #    [1, 0, 0, 0],
  #    [2, 0, 3, 0],
  #    [0, 0, 0, 0],
  #    [0, 4, 0, 0],
  csr_values = [2, 3, 1, 4,5]
  col_idx    = [1, 2, 0, 1,1]
  row_ptr    = [0, 2, 4,5]
  csr_matrix = [
      csr_values,
      col_idx,
      row_ptr
      ]

  dense_matrix = [
      [0, 3, 0],
      [1, 4, 5],
      [2, 0, 0],
      ]

  res = [
      [0, 0, 0],
      [0, 0, 0],
      [0, 0, 0],
      ]

  # matrix order, assumes both matrices are square
  n = len(dense_matrix)

  # res = dense X csr
  csr_row = 0 # Current row in CSR matrix
  for i in range(n):
    start, end = row_ptr[i], row_ptr[i + 1]
    for j in range(start, end):
      col, csr_value = col_idx[j], csr_values[j]
      for k in range(n):
        dense_value = dense_matrix[k][csr_row]
        res[k][col] += csr_value * dense_value
    csr_row += 1

  print(res) 


if __name__ == '__main__':
  main()