Calculate actual data size from Base64 encoded string length - base64

Given data encoded as a Base64-encoded string, can I somehow calculate the actual length of the raw data that has been encoded only by looking at the length of the Base64-encoded string?
I don't want to traverse the string if not necessary (this also includes string operations on the trailling characters of the encoded string to check for padding).

The exact length cannot be calculated unless you look at the padding. Without looking for padding, the best you can do is calculate an upper bound for the length by multiplying the encoded-string length with 3/4 (the encoded length is guaranteed to be exactly divisible by 4).
The upper bound calculated thus will be either N, N+1 or N+2, where N is the length of the raw data.

Related

Generate partial strings which have predefined minimum lengths (Matlab)

I have an initial string Init={ABCDEFGH}. How can I generate 100 partial strings (randomly) from Init string which have these conditions:
A pre-defined minimum lengths.
The order of elements in each partial string should be from 'A' to 'Z'.
No repeated characters in each partial strings
The expected output should be as follows: 100 partial strings, minimum length of each partial string is 5
Output = {'BCEGH';'ACEFG';'ABCDEF';'BCFGH';'BCDEG';....;'ABEFH';'ABCEGH'}
numel(Output) = 100
To do this, I started by generating random numbers for the length of each partial string. Then I generated random numbers corresponding to each letter in each string. Then I transferred those numbers into their corresponding letters. The comments should explain the rest.
n=100 %// how many samples to take
C='ABCDEFGH' %// take samples from these letters
maxL=numel(C) %// the longest string
minL=5 %// the shortest string
len=randi([minL maxL],[n 1]) %// generate length of each partial string
arrayfun(#(l) C(randsample(1:8,l)),len,'uni',0) %// randomly sample letters to give strings of correct length
and n=4 gives, for example
ans =
'CFHABEDG'
'CFHABE'
'FAHBE'
'DGHFABE'
I'm not sure this is truly random because it assumes that there are the same number of strings of each length, but I don't think this is true. I think len should be weighted with respect to the number of strings of each length. I think (but I'm not sure) that this should fix that:
for i=1:(maxL-minL+1)
w(i)=factorial(minL-1+i)*nchoosek(maxL,minL-1+i);
end
len=minL-1+randsample(1:(maxL-minL+1),n,true,w./sum(w))

Space-efficient way to encode numbers as sortable strings

Starting with a list of integers the task is to convert each integer into a string such that the resulting list of strings will be in numeric order when sorted lexicographically.
This is needed so that a particular system that is only capable of sorting strings will produce an output that is in numeric order.
Example:
Given the integers
1, 23, 3
we could convert the to strings like this:
"01", "23", "03"
so that when sorted they become:
"01", "03", "23"
which is correct. A wrong result would be:
"1", "23", "3"
because that list is sorted in "string order", not in numeric order.
I'm looking for something more efficient than the simple zero-padding scheme. In order to cover all possible 32 bit integers we'd need to pad to 10 digits which is inefficient.
For integers, prefix each number with the length. To make it more readable, use 'a' for length 1, and 'b' for length 2. Example:
non-encoded encoded
1 "a1"
3 "a3"
23 "b23"
This scheme is a bit simpler than prefixing each digit, but only works with numbers, not numbers mixed with text. It can be made to work for negative numbers as well, and even BigDecimal numbers, using some tricks. I wrote an implementation in Apache Jackrabbit 2.x, to make BigDecimal indexable (sortable) as text. For that, I used a format that only uses the characters '0' to '9' and consists of:
one character for: signum(value) + 2
one character for: signum(exponent) + 2
one character for: length(exponent) - 1
multiple characters for: exponent
multiple characters for: value (-1 if inverted)
Only the signum is encoded if the value is zero. The exponent is not encoded if zero. Negative values are "inverted" character by character (0 => 9, 1 => 8, and so on). The same applies to the exponent.
Examples:
non-encoded encoded
0 "2"
2 "322" (signum 1; exponent 0; value 2)
120 "330212" (signum 1; exponent signum 1, length 1, value 2; value 12)
-1 "179" (signum -1, rest inverted; exponent 0; value 1 (-1, inverted))
Values between BigDecimal(BigInteger.ONE, Integer.MIN_VALUE) and BigDecimal(BigInteger.ONE, Integer.MAX_VALUE) are supported.
TL;DR
Encode digits according to their order of magnitude (OM) and other characters so they sort as desired, relative to numbers: jj-a123 would be encoded zjzjz-zaC1B2A3
Longer explanation
This would depend somewhat upon the sorting algorithm that will finally be used to sort and how one would want any given punctuation characters to be sorted in relation to letters and numbers, but if it's "ascii-betical" or similar, you could encode each digit of a number to represent its order of magnitude (OM) in the number, while encoding other characters such that they would sort according to your desired sort order.
For simplicity, I would suggest beginning with encoding every non-numeric character with a "high" value (e.g. lower case z or even ~ if final value is ASCII), so that it sorts after encoded digits. Then cache each digit encountered until another non-numeric is encountered, then encode each cached digit with a value representing its OM. If the number 12945 was encountered in between non-numerics, you would output an E to encode an OM of 5, then the digit that is that order of magnitude, 1, followed by the next OM of 4 (D) and its associated digit, 2. Continue until all numeric digits have been flushed, then continue with non-numerics.
Non-numerics would be treated individually and ranked relative to the OM of digits. If it is desired for them to sort "above" numbers (perhaps the space character or certain others deemed special) they would be encoded by prepending a low-value character (like the space character, if final value will be treated and sorted as ASCII). When/if another numeric is encountered, begin caching and encode according to OM once all consecutive numerics are cached.
Alternately, processing the string in reverse order would preclude the need to cache numbers except for a single "is it a digit?" test and "is the last character a digit?" test. If the first is not true, then use (one of?) the "non-digit" OM character(s). If the first test is true then use the lowest-OM "digit" character (A in my examples). If both tests are true, then increment your OM character (A -> B or E -> F) before use.
Certain levels of additional filtering - or even translation - could be applied. If one wanted to allow accurate sorting based upon Roman numerals, one could encode them as decimal (or even hexadecimal) numbers with an appropriate OM.
Treating decimal points (either periods or commas, depending) as actual decimal separators, and distinct from other punctuation would probably be beyond the true utility of this encoding scheme, as alphanumeric fields seldom use a period or comma as a decimal separator. If it is desired to use them that way, the algorithm would simply detect a decimal separator (either period or comma as appropriate, in between digits) and not encode the numeric portion after that separator as anything but normal text. Fractional portions are actually sorted correctly during a normal ASCII based sort, because more digits represents greater precision - not greater magnitude.
Examples
non-encoded encoded
----------- -------
12345 E1D2C3B4A5
a100 zaC1B0A0
a20 zaB2A0
a2000 zaD2C0B0A0
x100.5 zxC1B0A0z.A5
x100.23 zxC1B0A0z.B2A3
1, 23, 3 A1z,z B2A1z,z A3
1, 2, 3 A1z,z A2z,z A3
1,2,3 A1z,A2z,A3
Potential advantages
Going somewhat beyond simple numeric sorting, some advantages to this encoding method would be several aspects of flexibility with final effective sort order - you are essentially encoding a category for each character - digits get a category based upon their position within the greater string of digits known as a number, while other characters are simply told to sort in their normal way (e.g. ASCII), but after numbers. Any exceptions that should sort before numbers or in other orders would be in one or more additional categories. ASCII can effectively be re-encoded to sort in a non-ASCII way:
You could encode lower case letters to sort before or along with upper case letters. To switch the lower and upper cases, you encode lower case letters with a y and upper case letters with a z. For a pseudo-case-insensitive sort, categorizing both A and a with the same encoding character would sort both of them before B and b, though A would nonetheless always sort before a
If you want Extended ASCII characters (e.g. with diacritics) to sort along with their ASCII cousins, you encode À, Á, Â, Ã, Ä, Å, and Æ along with A by using an a as the OM character, encode B, C, and Ç with a b, and E, È, É, Ê, and Ë with a c, etc. The same intra-category sort order caveat still applies, and some decisions need to be made on characters like capital Eth, and to a certain extent others like Thorn, and Sharp S (Ð, Þ, and ß respectively) as to whether they will sort based on similarities in appearance or pronunciation, or instead more properly perhaps, alphabetical order.
Small advantage of being basically human-readable, with effort
Caveats
Though this allows many 'categories' of characters to be defined, be sure to remember that each order of magnitude for digits is its own category - you need to know that the data will not contain numbers that are greater in OM than approximately 250, depending upon how many other categories you wish to define (ASCII 0 is reserved for storing strings, and there needs to be at least one other character to indicate "not a digit" - at least for alphanumeric data - making the maximum perhaps 254 orders of magnitude), but that should be plenty for any situation I can imagine. I'm not sure what other issues quantum computing will bring about, but there's probably a quantum solution to it, whatever it is.
Finally, if the hyphen is encoded as a non-numeric character, and all non-numerics are encoded with a higher OM than digits, negative numbers would be encoded as greater than any positive number. The hyphen should be encoded as a lower-than-digit-OM (perhaps only when preceding a digit) if negative numbers need to be sorted correctly according to magnitude.
Since the ASCII code of A is greater than 9, you could encode them as hexadecimal strings.
The integers
1, 23, 3
can be encoded as
00000001, 00000017, 00000003
and 32-bit integers can always be encoded as 8-character strings. (assume unsigned)

Why does the "Dopplr’s coloring algorithm" produce a color?

I stumbled over this blogpost by Brian Suda and quickly applied the "Dopplr’s coloring algorithm" to some examples, and that this works is not in question. What is, is why?
The process is as follows:
$hex_color = sub-string(md5($original_string), 0, 6)
Input some string (e.g. city names as with dopplr's original usage), make a md5-hash of this, and use the first 6 digits from the hash. Prepend this with a "#" and a string is transformed into a color fit for use in CSS-documents etc.
How is it that the six first digits of a md5-hash always matches a color in the hexadecimal representation?
MD5 always outputs hex. Colors can be represented as a 6-character hex string in css. So, the MD5 hash is just producing a semi-random hex string.
And any hex string (that is 6 characters long and begins with a #) is valid to define a color.

Problem parse integer within JSON response

I have following JSON response string
{"firstname":"a","lastname":"a","jobtitle":"software developer","companyname":"abc","mobileno":9461438988}
i cant get the string value for 'mobileno' field
This is how i read the 'mobileno' field
self.dispPhone = [NSString stringWithFormat:#"%# ",[parsedProfileData valueForKey:#"mobileno"]];
the string here becomes some garbage value '2147483647' when i NSLog it
First of all, a phone number is not an integer. Phone numbers may start with significant 0s or +. For example, in Germany 00.. is international, 0 national, and any other digit regional.
The returned value is the highest possible 31 bit number. Since your JSON encoder decodes to signed 32bit ints, this is the best value it can give you.
To solve this problem, format phone numbers as strings in the original.
The number 9,461,438,988 cannot be stored in a 32-bit value, so it's being truncated to fit.
You should store your phone numbers as the strings they are (just like ZIP codes).
In general, anything that you don't want to do arithmetic or numeric comparison on (< or >) is a string, not a number.

hashing string to an int between 0-19

I was wondering how I would hash a string value (ex: "myObjectName") to int values between 0-19
I'm guaranteed to have no more than 20 unique string values.
Thanks
Adding my comment as an answer as suggested:
I would suggest that hashing isn't the exact path you should follow here.
One method would be using a dictionary (like the built in data structure in Python) that has a key-value pair of your string and a number from 1-20 (or 0 - 19)
As you read or see each string, you could check to see if a dictionary entry exists, if so, do whatever needs to be done, if not, create a new dictionary entry with the next available number (generated by looking at the number of existing entries in the dictionary).
You could use any sort of hashing you like, but in this case, you could do with adding up the ASCII values (or unicode code point, if you like) of the characters, and apply modulo 20 to the result. It will give you a number from 0 to 19.
But this is nog guaranteed to result in a number that uniquely identifies your 20 strings. No hashing algorithm will guarantee that hashing a collection of 20 random strings will result in a unique code for each string..
Do md5 sum, convert to number and do modulo 20. E.g. in PHP:
hexdec(substr(md5("hello"), 1, 8)) % 20
The substr() is needed so that the number can be converted to integer.

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