If it takes more than 15 minutes to solve the C problem, I will definitely solve the D problem! I feel like.

The following is a summary of what you should be careful about when solving problems A to D.

Problem A / Problem B

Most of the problems A and B can be solved if you know the basic grammar.

I don't think there was any particular problem of worrying about the amount of calculation, so let's simply solve it using a for statement or an if statement.

Also, let's be able to perform basic list processing.

test.py

l =[]
l.append(1)  #Add to list
a = l.pop()  #Take out the end of the list
l = [i for i in range(N)]  #Comprehension notation
max_l = max(l)  #Get the maximum value in the list
min_l = min(l)  #Get the minimum value of the list

And in the B problem, there is sometimes a problem such as "normal processing is performed when N> 1, but exception handling is performed when N = 0" (or rather, such a bug has occurred in the program I wrote. (Sometimes), so

test.py

import sys
if N == 0:
   #Special treatment
   sys.exit()
for i in range(N):
   #Normal processing

I sometimes write something like this.

C problem

C has some difficult problems, and the amount of calculation must be taken into consideration.

Point1: See the size of the input data (consider the amount of calculation)

Example 1: ABC133 C problem

In this problem, the input size is 2 * 10 ^ 9. This is a size that makes it TLE even in a single loop, so I have to think that a simple for statement cannot be used.

However, if you think about it positively, it is a hint because there is a way to surely reduce the amount of calculation.

Example 2: ARC061 C problem

In this problem, on the contrary, the input data is a character string of 10 characters or less. For problems with extremely small input data, ** full search ** is often used.

--If N <= 10, you can use bit full search and n! Street full search. --If 100 <N <200, you can use up to triple loop

I can expect something like that. It's just an expectation.

Point2: Write down useful libraries etc. in a memo

The C problem imports various Python libraries and modules.

Also, prepare frequently used functions in advance.

I will summarize the libraries, modules, and functions that I personally use for C problems.

--itertools (combination, permutation, full search of N! Streets) --math (least common multiple, greatest common divisor, etc.) --Enumeration of divisors (version obtained by O (√N)) --bit full search (valid only when N is small) --deque (list that can append and pop from the left and right edges) --heapq (priority queue) --collections (the one who counts the frequency of appearance) --bisect (binary search)

Please comment if there are others!

To put it the other way around, most problems can be solved without using difficult algorithms such as ** dynamic programming, Dijkstra's algorithm, DFS and BFS. ** **

D problem

Problem D is not stable because I can only solve it about 7 times if I have 10 contests, and sometimes I can solve it within 30 minutes and sometimes it is just 100 minutes.

Personally, I wondered if it would be stable if I could solve the problems listed in @ drken's this article without struggling. I will.

Therefore, the algorithm template written here is coded in advance, and it seems to be nice to add or modify the program depending on the problem.

E problem / F problem

If it's a green coder, you don't have to solve it. I have to study because I have to be able to solve the E problem to become light blue.

Finally

There are many personal opinions, but I hope it will be helpful.