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Note: Try to select your elements more specific to get all information in one process - Defining a list outside your loops will avoid from overwriting

Following steps will create a list of dicts, that for example could simply iterated or turned into a data frame.

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that are direct siblings of a

Okay, I think I found a solution, I can do this with MS Excel. I followed the guide found here, did a test, and it worked.

I'd still be very interested if there is another way, like doing it with NOTEPAD++ or a batch file.

Like this?

The confusion probably stems from the fact that there are two different things (albeit closely related) you could mean when you say "base 32".

The way a representation of a number is structured, defining how many different options of symbols a single "digit" has. We humans usually use base 10 to represent our numbers with 10 different symbols (0-9), but you can also have binary which is base 2 (using only symbols 0 and 1), octal which is base 8 (using symbols 0-7) and so on. See base/radix on Wikipedia. With bases higher than 10 you usually use letters, starting with A for the 11th symbol. For example, hexadecimal (base 16) uses symbols 0-9 and A-F.

Since we only have 26 distinct letters that can be used in addition to the 10 symbols 0-9, in most scenarios only representations up to base 36 are defined. If you try to run 12345..toString(40) you'll get a RangeError: toString() radix argument must be between 2 and 36 for this reason.

Now, representing the number 12345 in base 32 this way (using symbols 0-9 and A-V) will give you C1P since C has the value 13, 1 has the value 1 and P has the value 25, and 13 * 32^2 + 1 * 32^1 + 25 * 32^0 equals 12345. This is just a way to write a number using 32 distinct symbols instead of 10, I wouldn't call it an "encoding" as such.

If the base is larger than 10, this will result in a shorter¹ (or equally long) representation than regular base 10.

The term of a "baseN" encoding as in "base64" (the most well-known such encoding) means the encoding of an octet stream (a stream of bytes, of 8-bit binary² data) using an "alphabet" (a set of allowed symbols), where the N specifies how many symbols the alphabet has³. This is used to store or transmit any octet stream (regardless of its contents) on a medium that doesn't allow for the full range of possible values in a byte to be used (for instance, a medium such as an email which may only contain text, or an URL which doesn't allow for certain special characters such as / or ? because they have semantic meaning, etc. - or even a piece of paper because the symbols 0 and O as well as I and l and 1 can't be reliably used without danger for confusion between them when read back by a human).

Now comes the part that marks the relation to the first "thing": The way the conversion works can be imagined by turning the input bytes into a huge number, and changing its radix but using the alphabet the encoding defines, not necessarily digits followed by letters. A great visual explanation can be found here.

The "turning the input bytes into a huge number" part is where the charCodeAt comes into play that you mentioned: I can turn the string ABC into the number 4276803 for instance, which becomes more obvious when looking at the bytes in their hexadecimal representation because a byte can have 256 values this range fits neatly into the exact range of two hexadecimal "digits" (0x00-0xFF⁴). The three bytes⁵ in ABC have hexadecimal values of 0x65, 0x66 and 0x67 respectively, and if I put them next to each other I can look at them as a large number 0x656667 = 4276803.

An additional overlap with the first "thing" is that in cryptography, very large numbers come into play, and often those are also encoded using a mechanism like base32 or base58 or base64, but unless the programming language and/or processor have a data type/register that fits the large number, the number is at that point already represented as some sort of octet stream yet again (the inverse of what I just described, sometimes with the reverse byte order though).

Of course this is only conceptually how it's done, because otherwise the algorithm would have to cope with gigantic numbers once we are talking about encoding not 3 bytes but 3,000,000 bytes. In reality, clever ways involving bit shifting etc. are used to achieve the same result on any length of data sequentially.

Since a "string" as you are used to seeing (ignoring Unicode for a second) can be loosely compared to a byte's numerical number represented in sort of a base 256 (one symbol for each of the possible 256 values in a byte), this means that any such baseN encoding will make the output longer because the new "radix" is lower than 256. Note that putting 12345 into a base32 algorithm will mean the string 12345 which could be viewed as the number 211295614005 (or 0x3132333435) in my explanation above. Looking at it this way, 64t36d1n (what you got from base32) is definitely shorter than 211295614005 in base 10, so it all makes sense again.

Important note: This explanation isn't entirely correct if you have input data which can't be exactly mapped to its new representation without padding due to its length. For example, a 3-byte-long data chunk occupies 3*8=24 bits, and a base64 representation of it that uses 6 bits per symbol is easily possible because exactly four of these symbols would also occupy 4*6=24 bits. But a 4-byte-long data chunk occupies 4*8=32 bits and would therefore require 5.333... symbols in base64 (5.333...*6=32). To "fill up" the remaining data space, some sort of padding⁶ is used so we can round it up to 6 symbols. Normally, the padding is added to the end of the input data, and this is where reality differs from my "changing radix of huge number" concept above because in math you'd expect leading zeroes as padding.

To address your initial question:

Douglas Crockford's base32 algorithm is actually designed for numbers but with a modified alphabet, it doesn't take an octet stream as input as programmers are used to. So it's more like a middle ground of the two things described above. You are right that toString(32) goes half the way to what you need, but you'd have to map between the regular "alphabet" of radix 32 (0-9, A-V, case insensitive) and Crockford's (with 0-9 and A-Z but without I, O and U, case insensitive, mapping I to 1 and O to 0 when decoding).

Replacing those things back and forth is enough complexity that I guess it'd be cleaner (and more educational) to write the algorithm yourself from scratch instead of relying on toString.

(Also, Crockford proposes an additional "check symbol" at the end which goes beyond what was explained here anyway.)

_Footnotes:

_{1: This is assuming integers. If you have fractions, then things are very different, because you can get recurring decimals in the new radix for numbers that didn't have recurring decimals in the old radix, or the other way round. For instance, 0.1 in base 32 is 0.36CPJ6CPJ6CPJ6CPJ... which is an infinitely long number (in that particular representation).}

_{2: The term "binary" here doesn't refer to representation in radix 2 but to "any kind of data which can use the full range of values from 0-255 per byte, not restricted to values representing human-readable text in ASCII range 32-126".}

_{3: Note that from the N alone, you can't infer what the alphabet exactly is, only how long it is. Well-known encodings have universally accepted conventions about which alphabet is used, such as base64 and base58 (the latter often being used for cryptocurrency addresses, and its alphabet is not even in alphabetical order by the way). Note that even for base64 there are variations like base64url which change the alphabet slightly. Others such as base32 don't have a universally accepted alphabet yet which is why the website that you linked mentions "this is a base32 encoding and not the base32 encoding" - notably it's not the same as Crockford's alphabet.}

_{4: The prefix 0x is commonly used to denote that the following symbols are to be interpreted as a number in base 16 (hexadecimal) instead of base 10.}

_{5: I'm talking about bytes here, because this is what the baseN algorithms work with, but in fact strings are based on characters and not bytes, and they may also contain Unicode characters with numerical values beyond 255, therefore not fitting into a single byte anymore. Normally, strings are first encoded using a character encoding like UTF-8 to bytes and then the baseN encoding is performed on those bytes.}

_{6: base64 uses = as padding, and to retain the information how many padding characters were used, the same number of = characters is also appended to the output (= isn't in the alphabet of base64).}

Based on the documentation available here: https://docs.microsoft.com/en-us/azure/cosmos-db/serverless#using-serverless-resources, it is currently not possible to change a Cosmos DB server less account to provisioned throughput.

You need to await connection first inorder to use execute function:

The Flow pups is producing updated values as you can see in my logcat

Not exactly.

The Flow is emitting the same List of the same Puppy objects. I believe that Compose sees that the List is the same List object as before and assumes that there are no changes.

My suggested changes:

• Make Puppy be an immutable data class (i.e., no var properties)

• Get rid of changeFlow and have getPuppies() return a stable MutableStateFlow> (or make that just be a public property)

• In toggleAdoption(), create a fresh list of Puppy objects and use that to update the MutableStateFlow>:

Since misc is a python script and not a module in itself, you need to either import the function itself

Your approach is to always return 27 for the number of sections in your tableview, corresponding to digits and the letters A-Z. However, a UITableView cannot have a section with 0 rows. This means you have a problem when your data doesn't contain a last name starting with "b", for example; You return 0 for section 1, but this isn't allowed. The tableview still requests row 0 for the empty section and you get an array bounds exception.

For the purposes of an answer I have simplified your cell display code a little, since I didn't want to fully populate all of the data fields and set up a custom cell (You should really use an object to encapsulate your data model rather than a dictionary too).

Most of the work is done in the method splitClients - This creates the appropriate arrays for each section and the section titles. In this code I ensured that the data was created in sorted order, but you can sort the data as you do in your code.

By creating the right arrays you can see how much simpler numberOfSections and numberOfRowsInSection are - You want these functions, along with cellForRowAt to be efficient as they will be called numerous times as the table view scrolls.

The other method of note is sectionForSectionIndexTitle - Since not all of the index sections may be populated, this function is used to return the closest populated section, so if you select "b" and there are no "b"s, it will scroll to "c".