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(  ))

                                    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()

                                    np.linspace(0,1,11)