I'm trying to round a number to the nearest ten (not tenth). e.g. 52 would go to 50, 29 would go to 30, 325 would go to 330, etc. How would I do this??
The simplest way is to use round(). Normally people think of this function as applying only to numbers past the decimal but using a negative number will accomplish what you're intending to do without recreating the wheel.
x = round(452.76543, -1)
>>> 450.0
If that decimal bothers you, prepend the round with an int statement int(round(452.76543, -1))
Now, I know you've already accepted the answer but consider what would happen if you had a decimal number (say 512.273). Using ThunderHorn's round_to_10 code you would get:
round_to_10(512.273)
>>> 509.273
Which doesn't work. It should be 510, which it is but only if you don't have a decimal value as in input.
But by using the built in function, you not only have less code, but robust and well-tested code that works in either case.
Explanation: there is no correct way to solve a problem
Newbie variant
we take the number i.e 123
step one get the last digit.
in python we can do this if we convert it into a string and then take [-1] of it ie
int(str(123)[-1]) #will return 3
and then we implement the logic if it is greater than 5 or lesser than 5
def round_to_10(i):
last_digit = int(str(i)[-1]) # it will give the last digit i.e 123 will return 3
if last_digit >= 5: # if 3 >= 5 sets round_up to True
return i + (10 - last_digit) # we add 10 to the number end subtract the extra
return i - last_digit # if the first condition never occurs we subtract the extra
Another approach
We can get the remaining value with % i.e we get if there is some values left if we take all 10ns out of the number. We can do it with the % operator
10%100 # returns 0 because there is no remaining value
10%123 # returns 3 and so on
This solution will work for negative numbers too.
def round_to_10(i):
last_digit = i%10
if last_digit >= 5:
return i + (10-last_digit)
return i-last_digit
In [7]: round_to_10(4)
Out[7]: 0
In [8]: round_to_10(5)
Out[8]: 10
In [9]: round_to_10(123)
Out[9]: 120
Try this:
What it does is that it gets the turns the number to a string and gets the last character (to find the last digit), then it checks if the lastDigit is less than 5. If it is less than 5, then it subtracts the lastDigit from the number, eg 24 -> 20. Else, it adds (10 - lastDigit) to make it equal to the nearest 10th, eg 25 -> 30
def roundToTenth(num):
num = round(num) # To get rid of small bugs
# To get the last digit, we turn it to a string and take the last character
lastDigit = int(str(num)[(len(str(num))-1)])
diff = 10 - lastDigit
if lastDigit < 5:
return num - lastDigit
else:
return num + (10-lastDigit)
Related
How to round numbers of different length size to the nearest zero or five?
Example:
1291 -> 1290
0.069 -> 0.07
1.08 -> 1.1
14 -> 15
6 -> 5
Tried to use round() and math.ceil() / math.floor() but since the numbers are different each time in length I canβt adapt it dynamically, numbers are returning from a function not an array.
Here you are, thanks for the other solutions:
import math
import decimal
def round_half_up(n):
if (str(n).find(".") > 0):
decimalsource = len(str(n).split(".")[1])
base = 10**decimalsource
number = n*base
rounded = 5 * round(number/5)
result = rounded / base
if (result == int(result)):
return int(result)
else:
return result
else:
return 5 * round(n/5)
print(round_half_up(1291))
print(round_half_up(0.069))
print(round_half_up(1.08))
print(round_half_up(14))
print(round_half_up(6))
print(round_half_up(12.121213))
print(round_half_up(12.3))
print(round_half_up(18.))
print(round_half_up(18))
I wrote a code and explained. It seems working. I didn't take into account negative numbers.
import numpy as np
convDict = {
"0":"0",
"1":"0",
"2":"0",
"3":"5",
"4":"5",
"5":"5",
"6":"5",
"7":"5",
"8":"0",
"9":"0"
}
def conv(f):
str_f = str(f)
# if input is like, 12. or 13.0,so actually int but float data type
# We will get rid of the .0 part
if str_f.endswith(".0"):
str_f = str(int(f))
# We need last character, and other body part
last_f = str_f[-1]
body_f = str_f[:-1]
# if last char is 8 or 9 we should increment body last value
if last_f in "89":
# Number of decimals
numsOfDec = body_f[::-1].find('.')
# numsOfDec = -1 means body is integer, we will add 1
if numsOfDec == -1:
body_f = str(int(body_f) + 1)
else:
# We will add 10 ** -numsOfDec , but it can lead some numerical differences like 0.69999, so i rounded
body_f = str(np.round(float(body_f) + 10 ** (-numsOfDec),numsOfDec))
# Finally we round last char
last_f = convDict[last_f]
return float(body_f + last_f)
And some examples,
print(conv(1291))
print(conv(0.069))
print(conv(1.08))
print(conv(14))
print(conv(6))
print(conv(12.121213))
print(conv(12.3))
print(conv(18.))
print(conv(18))
The kinda pythonic way to round dynamically to nearest five would be to use round() function and input number (divided by 5), the index in which you want the rounding to ocurr [-2: hundreds, -1: tens, 0: whole, 1:1/10ths, 2:1/100s] and multiply result by 5. You can calculate this index by finding how many decimal places there are using decimal module.
i = decimal.Decimal('0.069')
i.as_tuple().exponent
-3
Note that this function takes the number as a string and outputs the number
of decimal places in negative.
After getting this number, make it positive, and there you have the calculated index to put into the round function in the beginning.
round(0.069/5, 3) * 5
You need to also check before all this calculation if the number is a full number (meaning no decimal places--17, 290, 34.0) (in that case you shouldn't use above code at all), which you can easily do by using modulus, so the overall function would look like this:
if number % 1 == 0:
return round(int(number)/5)*5
else:
index = decimal.Decimal(str(number)).as_tuple().exponent
return round(number/5, -index)*5
Hope this helped !
I've been trying to implement the algorithm which does raising to a power every previous digit to current digit, which is also raised to. Then I find the last digit of this number. Here is the formula of this algorithm:
(x0 ** (x1 ** (x2 ** (x3 ** (...) **(Xn))))))
Then I find the last digit like that:
return find_last_digit % 10
If the list is empty, programm must return 1.
I have the Solution of this problem:
def last_digit(lst):
if len(lst) > 0:
temp = lst[-1]
for i in range(len(lst) - 2, -1, -1):
temp = lst[i] ** temp
return temp % 10
else:
return 1
But as you can see, this code takes a lot of time to be implemented if any value of the input list is large. Could you answer me, how can I make this code more effecient? Thx a lot
Here are some observations that can make the calculations more efficient:
As we need the last digit, and we are essentially doing multiplications, we can use the rules of modular arithmetic. If πβ
π = π, then π(mod π)β
π(mod π) = π(mod π). So a first idea could be to take π as 10, and perform the multiplications. But we don't want to split up exponentiation in individual mutliplications, so then see the next point:
For all unsigned integers π it holds that π2 = π6 modulo 20. You can verify this by doing this for all values of π in the range {0,...,19}. By consequence, ππ = ππ+4 for π > 1. We choose 20 as modulus as that is both a multiple of 10 and 4. A multiple of 10, because we need to maintain the last digit in the process, and 4 as we will reduce the exponent by a multiple of 4. Both are necessary conditions at the same time, so not to lose out on the final digit. In the end we have that π(mod 20)(mod 10) = π(mod 10)
With these simplification rules, you can keep the involved exponents limited to at most 5, the base to at most 21, and the resulting power to at most 215 = 4084101.
The code could become:
def last_digit(lst):
power = 1
for base in reversed(lst):
power = (base if base < 2 else (base - 2) % 20 + 2) ** (
power if power < 2 else (power - 2) % 4 + 2)
return power % 10
In practice you can skip the reduction of base to (base - 2) % 20 + 2 if these input numbers are not very large.
I am a beginner to Python coding. I have two numbers A and B from user.
My problem is to find the max(P AND Q) where A <= P < Q <= B
I have two solutions right now for this.
Solution 1 : # ANDing with all combinations, This solution works if combinations are less. For higher values, it throws memory exceeding error.
given = raw_input()
n= list(map(int,given.split()))
A = n[0]
B = n[1]
newlist = range(B+1)
# print newlist
# Finding all combinations
comb = list(itertools.combinations(newlist,2))
# print comb
# ANDing
l = []
for i in com:
x = i[0] & i[1]
l.append(x)
# print l
print max(l)
Solution 2: After observing many input-outputs, when B == Odd, max(value) = B-1 and for B == Even, max(value) = B-2.
given = raw_input()
n= list(map(int,given.split()))
A = n[0]
B = n[1]
if B % 2 == 0:
print (B - 2)
else:
print (B -1)
According to the problem statement I am not using any ANDing for Solution 2. Still I am getting correct output.
But I am looking for much easier and Pythonic logic. Is there any other way/logic to solve this?
Your second solution is the optimal solution. But why? First, consider that a logical AND is performed on the binary representation of a number, and it is only possible to produce a number less than or equal to the smallest operand of the AND operator. For instance, 9 is represented as 1001, and there is no number that 9 can be anded with that produces a number higher than 9. Indeed, the only possible outputs for anding another number with 9 would be 9, 8, 1 and 0. Or alternatively, the biggest result from anding 9 with a number smaller than 9, is 9 less its least significant bit (so 8). If you're not sure of the binary representation of a number you can always use the bin function. eg. bin(9) => '0b1001'.
Let's start with odd numbers (as they're the easiest). Odd numbers are easy because they always have a bit in the unit position. So the maximum possible number that we can get is B less that bit in the unit position (so B - 1 is the maximum). For instance, 9 is represented as 1001. Get rid of the unit bit and we have 1000 or 8. 9 and 8 == 8, so the maximum result is 8.
Now let's try something similar with evens. For instance, 14 is represented as 1110. The maximum number we can get from anding 14 with another number would be 1100 (or 12). Like with odds, we must always lose one bit, and the smallest possible bit that can be lost is the bit in 2s position. Here, we're fortunate as 14 already as a bit in the 2s position. But what about numbers that don't? Let's try 12 (represented as 1100). If we lost the smallest bit from 12, we would have 1000 or 8. However, this is not the maximum possible. And we can easily prove this, because the maximum for 11 is 10 (since we have shown the maximum for an odd number is the odd number less 1).
We have already shown that the biggest number that can be produced from anding two different numbers is the bigger number less its least significant bit. So if that bit has a value of 2 (in the case of 14), when we can just lose that bit. If that bit has a value higher than 2 (in the case of 12), then we know the maximum is the maximum of the biggest odd number less than B (which is 1 less than the odd number and 2 less than B).
So there we have it. The maximum for an odd number is the number less 1. And the maximum for an even number is the number less 2.
def and_max(A, B): # note that A is unused
if B & 1: # has a bit in the 1 position (odd)
P, Q = B - 1, B
else:
P, Q = B - 2, B - 1
# print("P = ", P, "Q = ", Q)
return P & Q # essentially, return P
Note that none of this covers negative numbers. This is because most representations of negative numbers are in two's complement. What this means is that all negative numbers are represented as constant negative number plus a positive number. For instance, using an 4-bit representation of integers the maximum possible number would be 0111 (or 7, 4 + 2 + 1). Negative numbers would be represented as -8 plus some positive number. This negative part is indicated by a leading bit. Thus -8 is 1000 (-8 + 0) and -1 is 1111 (-8 + 7). And that's the important part. As soon as you have -1, you have an all 1s bitmask which is guaranteed to lose the negative part when anded with a positive number. So the maximum for max(P and Q) where A <= P < Q <= B and A < 0 is always B. Where B < 0, we can no longer lose the negative bit and so must maximise the positive bits again.
I think this should work:
given = raw_input()
a, b = tuple(map(int,given.split()))
print(max([p & q for q in range(a,b+1) for p in range(a,q)]))
long a,b,c,ans;
for(int i=0;i<n;i++){
a=s.nextLong();
b=s.nextLong();
if(b%2==0)
ans=b-2;
else
ans=b-1;
if(ans>=a)
System.out.println(ans);
else
System.out.println(a&b);
}
I came across this problem Unlucky number 13! recently but could not think of efficient solution this.
Problem statement :
N is taken as input.
N can be very large 0<= N <= 1000000009
Find total number of such strings that are made of exactly N characters which don't include "13". The strings may contain any integer from 0-9, repeated any number of times.
# Example:
# N = 2 :
# output : 99 (0-99 without 13 number)
# N =1 :
# output : 10 (0-9 without 13 number)
My solution:
N = int(raw_input())
if N < 2:
print 10
else:
without_13 = 10
for i in range(10, int('9' * N)+1):
string = str(i)
if string.count("13") >= 1:
continue
without_13 += 1
print without_13
Output
The output file should contain answer to each query in a new line modulo 1000000009.
Any other efficient way to solve this ? My solution gives time limit exceeded on coding site.
I think this can be solved via recursion:
ans(n) = { ans([n/2])^2 - ans([n/2]-1)^2 }, if n is even
ans(n) = { ans([n/2]+1)*ans([n/2]) - ans([n/2])*ans([n/2]-1) }, if n is odd
Base Cases:
ans(0) = 1
ans(1) = 10
It's implementation is running quite fast even for larger inputs like 10^9 ( which is expected as its complexity is O(log[n]) instead of O(n) like the other answers ):
cache = {}
mod = 1000000009
def ans(n):
if cache.has_key(n):
return cache[n]
if n == 0:
cache[n] = 1
return cache[n]
if n == 1:
cache[n] = 10
return cache[n]
temp1 = ans(n/2)
temp2 = ans(n/2-1)
if (n & 1) == 0:
cache[n] = (temp1*temp1 - temp2*temp2) % mod
else:
temp3 = ans(n/2 + 1)
cache[n] = (temp1 * (temp3 - temp2)) % mod
return cache[n]
print ans(1000000000)
Online Demo
Explanation:
Let a string s have even number of digits 'n'.
Let ans(n) be the answer for the input n, i.e. the number of strings without the substring 13 in them.
Therefore, the answer for string s having length n can be written as the multiplication of the answer for the first half of the string (ans([n/2])) and the answer for the second half of the string (ans([n/2])), minus the number of cases where the string 13 appears in the middle of the number n, i.e. when the last digit of the first half is 1 and the first digit of the second half is 3.
This can expressed mathematically as:
ans(n) = ans([n/2])^2 - ans([n/2]-1)*2
Similarly for the cases where the input number n is odd, we can derive the following equation:
ans(n) = ans([n/2]+1)*ans([n/2]) - ans([n/2])*ans([n/2]-1)
I get the feeling that this question is designed with the expectation that you would initially instinctively do it the way you have. However, I believe there's a slightly different approach that would be faster.
You can produce all the numbers that contain the number 13 yourself, without having to loop through all the numbers in between. For example:
2 digits:
13
3 digits position 1:
113
213
313 etc.
3 digits position 2: 131
132
133 etc.
Therefore, you don't have to check all the number from 0 to n*9. You simply count all the numbers with 13 in them until the length is larger than N.
This may not be the fastest solution (in fact I'd be surprised if this couldn't be solved efficiently by using some mathematics trickery) but I believe it will be more efficient than the approach you have currently taken.
This a P&C problem. I'm going to assume 0 is valid string and so is 00, 000 and so on, each being treated distinct from the other.
The total number of strings not containing 13, of length N, is unsurprisingly given by:
(Total Number of strings of length N) - (Total number of strings of length N that have 13 in them)
Now, the Total number of strings of length N is easy, you have 10 digits and N slots to put them in: 10^N.
The number of strings of length N with 13 in them is a little trickier.
You'd think you can do something like this:
=> (N-1)C1 * 10^(N-2)
=> (N-1) * 10^(N-2)
But you'd be wrong, or more accurately, you'd be over counting certain strings. For example, you'd be over counting the set of string that have two or more 13s in them.
What you really need to do is apply the inclusion-exclusion principle to count the number of strings with 13 in them, so that they're all included once.
If you look at this problem as a set counting problem, you have quite a few sets:
S(0,N): Set of all strings of Length N.
S(1,N): Set of all strings of Length N, with at least one '13' in it.
S(2,N): Set of all strings of Length N, with at least two '13's in it.
...
S(N/2,N): Set of all strings of Length N, with at least floor(N/2) '13's in it.
You want the set of all strings with 13 in them, but counted at most once. You can use the inclusion-exclusion principle for computing that set.
Let f(n) be the number of sequences of length n that have no "13" in them, and g(n) be the number of sequences of length n that have "13" in them.
Then f(n) = 10^n - g(n) (in mathematical notation), because it's the number of possible sequences (10^n) minus the ones that contain "13".
Base cases:
f(0) = 1
g(0) = 0
f(1) = 10
g(1) = 0
When looking for the sequences with "13", a sequence can have a "13" at the beginning. That will account for 10^(n-2) possible sequences with "13" in them. It could also have a "13" in the second position, again accounting for 10^(n-2) possible sequences. But if it has a "13" in the third position, and we'd assume there would also be 10^(n-2) possible sequences, we could those twice that already had a "13" in the first position. So we have to substract them. Instead, we count 10^(n-4) times f(2) (because those are exactly the combinations in the first two positions that don't have "13" in them).
E.g. for g(5):
g(5) = 10^(n-2) + 10^(n-2) + f(2)*10^(n-4) + f(3)*10^(n-5)
We can rewrite that to look the same everywhere:
g(5) = f(0)*10^(n-2) + f(1)*10^(n-3) + f(2)*10^(n-4) + f(3)*10^(n-5)
Or simply the sum of f(i)*10^(n-(i+2)) with i ranging from 0 to n-2.
In Python:
from functools import lru_cache
#lru_cache(maxsize=1024)
def f(n):
return 10**n - g(n)
#lru_cache(maxsize=1024)
def g(n):
return sum(f(i)*10**(n-(i+2)) for i in range(n-1)) # range is exclusive
The lru_cache is optional, but often a good idea when working with recursion.
>>> [f(n) for n in range(10)]
[1, 10, 99, 980, 9701, 96030, 950599, 9409960, 93149001, 922080050]
The results are instant and it works for very large numbers.
In fact this question is more about math than about python.
For N figures there is 10^N possible unique strings. To get the answer to the problem we need to subtract the number of string containing "13".
If string starts from "13" we have 10^(N-2) possible unique strings. If we have 13 at the second possition (e.i. a string like x13...), we again have 10^(N-2) possibilities. But we can't continue this logic further as this will lead us to double calculation of string which have 13 at different possitions. For example for N=4 there will be a string "1313" which we will calculate twice. To avoid this we should calculate only those strings which we haven't calculated before. So for "13" on possition p (counting from 0) we should find the number of unique string which don't have "13" on the left side from p, that is for each p
number_of_strings_for_13_at_p = total_number_of_strings_without_13(N=p-1) * 10^(N-p-2)
So we recursevily define the total_number_of_strings_without_13 function.
Here is the idea in the code:
def number_of_strings_without_13(N):
sum_numbers_with_13 = 0
for p in range(N-1):
if p < 2:
sum_numbers_with_13 += 10**(N-2)
else:
sum_numbers_with_13 += number_of_strings_without_13(p) * 10**(N-p-2)
return 10**N - sum_numbers_with_13
I should say that 10**N means 10 in the power of N. All the other is described above. The functions also has a surprisingly pleasent ability to give correct answers for N=1 and N=2.
To test this works correct I've rewritten your code into function and refactored a little bit:
def number_of_strings_without_13_bruteforce(N):
without_13 = 0
for i in range(10**N):
if str(i).count("13"):
continue
without_13 += 1
return without_13
for N in range(1, 7):
print(number_of_strings_without_13(N),
number_of_strings_without_13_bruteforce(N))
They gave the same answers. With bigger N bruteforce is very slow. But for very large N recursive function also gets mush slower. There is a well known solution for that: as we use the value of number_of_strings_without_13 with parameters smaller than N multiple times, we should remember the answers and not recalculate them each time. It's quite simple to do like this:
def number_of_strings_without_13(N, answers=dict()):
if N in answers:
return answers[N]
sum_numbers_with_13 = 0
for p in range(N-1):
if p < 2:
sum_numbers_with_13 += 10**(N-2)
else:
sum_numbers_with_13 += number_of_strings_without_13(p) * 10**(N-p-2)
result = 10**N - sum_numbers_with_13
answers[N] = result
return result
Thanks to L3viathan's comment now it is clear. The logic is beautiful.
Let's assume a(n) is a number of strings of n digits without "13" in it. If we know all the good strings for n-1, we can add one more digit to the left of each string and calculate a(n). As we can combine previous digits with any of 10 new, we will get 10*a(n-1) different strings. But we must subtract the number of strings, which now starts with "13" which we wrongly summed like OK at the previous step. There is a(n-2) of such wrongly added strings. So a(n) = 10*a(n-1) - a(n-2). That is it. Such simple.
What is even more interesting is that this sequence can be calculated without iterations with a formula https://oeis.org/A004189 But practically that doesn't helps much, as the formula requires floating point calculations which will lead to rounding and would not work for big n (will give answer with some mistake).
Nevertheless the original sequence is quite easy to calculate and it doesn't need to store all the previous values, just the last two. So here is the code
def number_of_strings(n):
result = 0
result1 = 99
result2 = 10
if n == 1:
return result2
if n == 2:
return result1
for i in range(3, n+1):
result = 10*result1 - result2
result2 = result1
result1 = result
return result
This one is several orders faster than my previous suggestion. And memory consumption is now just O(n)
P.S. If you run this with Python2, you'd better change range to xrange
This python3 solution meets time and memory requirement of HackerEarth
from functools import lru_cache
mod = 1000000009
#lru_cache(1024)
def ans(n):
if n == 0:
return 1
if n == 1:
return 10
temp1 = ans(n//2)
temp2 = ans(n//2-1)
if (n & 1) == 0:
return (temp1*temp1 - temp2*temp2) % mod
else:
temp3 = ans(n//2 + 1)
return (temp1 * (temp3 - temp2)) % mod
for t in range(int(input())):
n = int(input())
print(ans(n))
I came across this problem on
https://www.hackerearth.com/problem/algorithm/the-unlucky-13-d7aea1ff/
I haven't been able to get the judge to accept my solution(s) in Python but (2) in ANSI C worked just fine.
Straightforward recursive counting of a(n) = 10*a(n-1) - a(n-2) is pretty slow when getting to large numbers but there are several options (one which is not mentioned here yet):
1.) using generating functions:
https://www.wolframalpha.com/input/?i=g%28n%2B1%29%3D10g%28n%29+-g%28n-1%29%2C+g%280%29%3D1%2C+g%281%29%3D10
the powers should be counted using squaring and modulo needs to be inserted cleverly into that and the numbers must be rounded but Python solution was slow for the judge anyway (it took 7s on my laptop and judge needs this to be counted under 1.5s)
2.) using matrices:
the idea is that we can get vector [a(n), a(n-1)] by multiplying vector [a(n-1), a(n-2)] by specific matrix constructed from equation a(n) = 10*a(n-1) - a(n-2)
| a(n) | = | 10 -1 | * | a(n-1) |
| a(n-1) | | 1 0 | | a(n-2) |
and by induction:
| a(n) | = | 10 -1 |^(n-1) * | a(1) |
| a(n-1) | | 1 0 | | a(0) |
the matrix multiplication in 2D should be done via squaring using modulo. It should be hardcoded rather counted via for cycles as it is much faster.
Again this was slow for Python (8s on my laptop) but fast for ANSI C (0.3s)
3.) the solution proposed by Anmol Singh Jaggi above which is the fastest in Python (3s) but the memory consumption for cache is big enough to break memory limits of the judge. Removing cache or limiting it makes the computation very slow.
You are given a string S of length N. The string S consists of digits from 1-9, Consider the string indexing to be 1-based.
You need to divide the string into blocks such that the i block contains the elements from the index((i 1) β’ X +1) to min(N, (i + X)) (both inclusive). A number is valid if it is formed by choosing exactly one digit from each block and placing the digits in the order of their block
number
Ive been give a task, it is as follows:
write a function called decToBin that takes in an integer and converts it to an 8-bit binary number represented as a string
As I am new to this im very lost! Having no introduction to my task as thrown me off a little and I really need some help!
I have tried the following code:
#function
def decTobin(integer)
return bin
#main program
decToBin(3)
decToBin(4)
decToBin(5)
However I had no sucess, could someone point me in the right direction, it would be much appreciated, thank you!
Please try to keep your questions tidy. Also, judging from your other questions, you should look at some basic python tutorials. Happy coding!
Try to learn about base conversions. Here is a great place to find a step by step walkthrough for doing it manually.
You will need to use the modulo (%) operator. The modulo operator is a binary operator, meaning it has two inputs. You use it like so:
a % b
It returns the remainder when a is divided by b:
10 % 7 = 3
The following code will do what you need:
def decToBin(x):
if x == 0:
return "00000000"
bits = []
while x:
bits.append(str(x % 2))
x >>= 1
return "".join(bits).zfill(8)
I will explain line by line.
def decToBin(x):
This declares the function.
if x == 0:
return "00000000"
This returns a string of eight zeros if the input is zero. We need this because the while loop only operates when x is not equal to zero.
bits = []
This initializes the array of bits. During the while loop, we will add to this with the append function.
while x:
This begins a while loop, which runs until x is false (or zero).
bits.append(str(x % 2))
This adds to the bits array the remainder when x is divided by 2. str() converts it to a string.
x >>= 1
>>= 1 Shifts the bits in x to the right one time like so:
Before: 1 1 0 1 0 1
After: 0 1 1 0 1 0
It is the same as dividing by 2, without keeping the remainder.
return "".join(bits).zfill(8)
Breakdown:
"abc".join(l)
Joins all the strings in list l, separating it with abc.
"2345".zfill(i)
adds zeros to the beginning of a string until there are i numbers. So
return "".join(bits).zfill(8)
returns the array of bits as one string, and pads the beginning until there are eight characters.