A database is used to organize a large collection of data, hence the name database. It is literally a base that would contain a chunk of data that a person or an organization will need to pull out later when they need it. Databases are usually used by companies or organizations
Possibly rephrase or rewrite the heading or whatever else you decide to repeat. You should never say the exact thing twice.
Hope I helped :)
Answer:
c.Update DNS records dynamically for DHCP clients that don't request updates.
Explanation:
A DNS server is a computer server that contains a database of public IP addresses and their associated host names, and in most cases serves to resolve, or translate, those names to IP addresses as requested.
A DHCP Server is a network server that automatically provides and assigns IP addresses, default gateways and other network parameters to client devices.
Dynamic DNS is a method of automatically updating a name server in the Domain Name Server, often in real time.
Answer:
import sys
import turtle
import random
def n_pointed_star(total_points):
if total_points <= 4:
raise ValueError('Not enough total_points')
area = 150
for coprime in range(total_points//2, 1, -1):
if greatest_common_divisor(total_points, coprime) == 1:
start = turtle.position()
for _ in range(total_points):
turtle.forward(area)
turtle.left(360.0 / total_points * coprime)
turtle.setposition(start)
return
def greatest_common_divisor(a, b):
while b != 0:
a, b = b, a % b
return a
turtle.reset()
n_pointed_star(5)
Explanation:
- Inside the n_pointed_star function, check whether the total no. of points are less than or equal to 4 and then throw an exception.
- Loop through the total_points variable and check whether the result from greatest_common_divisor is equal to 1 or not and then set the starting position of turtle and move it.
- Create the greatest_common_divisor which takes two parameters a and b to find the GCD.
- Finally reset the turtle and call the n_pointed_star function.
Answer:
C)
Explanation:
One principle that can improve the efficiency of I/O would be to move processing primitives into hardware. Primitives are a semantic value representing something else such as words or numbers within the programming language. By moving them into hardware they system is able to read them at a much faster speed making the I/O more efficient.
