## javascript – widens the range of compressed strings –

Let's say you have two strings: – exp-> aaccbb comp-> aa2bb
The example above will return true because there are 2 characters between aa and bb.
I wrote the code snippet. I was just wondering if there was a better way to solve this problem and I was missing a particular case.

Tracking -> each side can have compressions or both at the same time.

``````const isNumber = (ch)=>{
return Number(ch) == ch
}

const isExp = (exp, comp)=>{
let i=j=0;

while(i$$```$$``````

## command line – Where to get libcurl for Windows with the option –compressed enabled?

So, I copy curl commands from development tools to Firefox and they often include the –compressed flag and even if its removal often makes the command execution successful, my goal is to be able to execute commands with this indicator.

Right now, that's what I get using this flag:

``````curl: option --compressed: the installed libcurl version doesn't support this
``````

Is there a compiled version for Windows that supports this tag? I have tried several versions available but without success.

## Is there an algorithm to compress an array of strings represented as pointers into a long string of pointers with a compressed version of the long string?

In a program I write, I represent an array of long string strings, and pointers point to different substrings to present my array. For example.

``````str_array = struc string_array
long_str = "abcdefab"
pointer_array = ((start = 0, len = 3), (start = 3, len = 3), (start = 6, len=2))
end
``````

So `str_array = ("abc", "def", "ab")`, but notice that I can actually compress the long string by removing "ab" at the end. For example.

``````str_array2 = struc string_array
long_str = "abcdef"
pointer_array = ((start = 0, len = 3), (start = 3, len = 3), (start = 0, len=2))
end
``````

and note that `str_array2` is also `("abc", "def", "ab") === str_array`.

What is this type of compression called in computing? I suppose there is already literature on this type of algorithms?

## sony – How can I convert uncompressed raw files to compressed files?

I still shoot raw (Sony .arw) with my A7RII, but after a year, a lot of disk space is allocated.

One uncompressed file uses approx. 80 MB, so I decided to use the compressed format because there does not seem to be any big inconvenience.

Is there software that can perform batch conversions from uncompressed to compressed format?

## plugin – Unreal: Where should I put a DLL to be copied when it is compressed or compressed?

I am currently using the `FPaths::ProjectPluginsDir()` directory to store a custom DLL for Unreal. However, when I build or compress the project, I have to manually create a Plugins folder and copy the `DLL` in this file.

Is there another folder that would be a better directory to store my plugin in order to have my `DLL` copied automatically when it is compressed or compressed?

## usability – Propose a compressed file of about 1.2 GB to download, should we split it into smaller parts?

I think you should split the file into smaller parts, but not necessarily by file type but by the way the user consumes them.

Let's say your file contains documentation and multimedia files for Java. The PDF, video, images and code files all represent up to 1.2 GB. You may want to provide them as:

• Contents
• Java Core
• Java books
• Java tutorial series

## Javascript library or code to convert a bitcoin private key "uncompressed" into a compressed key

I created a very old brain wallet generator: https://dvdbng.github.io/memwallet/ – It is currently generating uncompressed bitcoin private keys. Is there a javascript library that can convert an uncompressed bitcoin private key into a compressed key? Or what are the fundamental knowledge required to know how to compress a Bitcoin private key?

## algorithms – Can the data be compressed using this hash function technique?

I would like to know if this data compression scheme would work or not, and why:

Suppose we have a file. If we treat the bits that make up the file as the binary representation of a number n, we have n (of course, if the first bit is zero, we return each bit so that n is unique). We now have the number n and a boolean that tells us whether to return all bits of the binary representation of n or not.

My idea was to approximate n down (for example, find a relatively large number high to a relatively large power, such as 17 ^ 6038), then start computing arbitrary hashes for all numbers from this approximation of n to real number, counting the number of collisions. When we finally get to n, we have "collision state" hashes, then we produce the compressed file, which basically contains information on how to get the approximation of n (by example 17 ^ 6038) and on "collision state". for n (note that this "collision state" must also occupy very few bits, so I'm not sure this is possible).

The decompression procedure would do a very similar process; it gets closer to n (for example, compute n as 17 ^ 6038) and then starts chopping (ie applying a function and checking the result) each number (we could also check every 5 digits or one another divisor of n – ~ n) until the "collision state" is the same as that specified in the compressed file. Once we match everything, we have n. Then, it would be enough to reverse or not each bit (as specified in the compressed file) and generate it in a file.

Could it work? The only problem I can think of is (besides the time required for treatment), the number of collisions is extremely important.

The whole process will only take a few moments.

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