Is there a way to control the order in which files appear in a gist? They don't seem to be alphabetical or chronological. I'd like to have a README.md appear as the first file in a multi-file gist, but no amount of "deleting" a file and re-adding it seems to change anything.
Is there an order to these files that I'm not seeing, or does GitHub maintain an internal filetype priority list?
Since at least 2018, the order is alphabetical, with periods and numbers coming before letters.
That is, as mentioned in Andrew D.Bond's answer:
$
. (dot)
Numbers
Leading space (although the space doesn't appear after saving, the sort order is still updated)
(although bis, in Sept. 2020, IvanaGyro adds in the comments leading spaces will not affect the order any more)
_ (underscore)
Letters (case insensitive)
Around 2013-2014 a different order was used. See Andrew D. Bond's answer for more.
They are ordered automatically by name, following the ASCII table.
Unfortunatly, right now, it is not possible to order them by dragging, but there is a trick. You can control the order by adding one or more spaces before the name. The space will not be shown after editing, but the order will change.
E.g: lets say we have 3 files with the automatic order:
AFile.java
Readme.md
SomeFile.txt
We can invert the order by putting spaces like this:
(space)(space)SomeFile.txt
(space)Readme.md
AFile.txt
Updating my answer from an earlier year with additional testing I did just now:
Github automatically sorts files in a gist according to:
#
$
. (period)
Numbers
_ (underscore)
Letters (case insensitive)
Leading spaces are dropped.
If additional characters' sort order is discovered, feel free to edit this answer.
(Added this answer because even after I improved another answer to this question last year, I still couldn't find the sort order of special characters anywhere.)
As mentioned by #VonC in his answer, the order is asciibetical. Quick solution would be to prefix all files with numbers indicating the order in which you wish the files to appear, example 0_, 1_, 2_, ... 9_. Note, this solution will not work beyond 9 files as 10_ will appear before 2_. In that case, two digits need to be used 00_, 01_, 02_, ..., 09_, 10_, 11_, ... This can be generalized to any number of digits in the number of files. Although, it seems less likely, to me, that more more than 10 files to be shared in a gist.
Related
Disclaimer: I have no engineering background whatsoever - please don't hold it against me ;)
What I'm trying to do:
Scan a bunch of text strings and find the ones that
are more than one word
contain title case (at least one capitalized word after the first one)
but exclude specific proper nouns that don't get checked for title case
and disregard any parameters in curly brackets
Example: Today, a Man walked his dogs named {FIDO} and {Fifi} down the Street.
Expectation: Flag the string for title capitalization because of Man and Street, not because of Today, {FIDO} or {Fifi}
Example: Don't post that video on TikTok.
Expectation: No flag because TikTok is a proper noun
I have bits and pieces, none of them error-free from what https://www.regextester.com/ keeps telling me so I'm really hoping for help from this community.
What I've tried (in piece meal but not all together):
(?=([A-Z][a-z]+\s+[A-Z][a-z]+))
^(?!(WordA|WordB)$)
^((?!{*}))
I think your problem is not really solvable solely with regex...
My recommendation would be splitting the input via [\s\W]+ (e.g. with python's re.split, if you really need strings with more than one word, you can check the length of the result), filtering each resulting word if the first character is uppercase (e.g with python's string.isupper) and finally filtering against a dictionary.
[\s\W]+ matches all whitespace and non-word characters, yielding words...
The reasoning behind this different approach: compiling all "proper nouns" in a regex is kinda impossible, using "isupper" also works with non-latin letters (e.g. when your strings are unicode, [A-Z] won't be sufficient to detect uppercase). Filtering utilizing a dictionary is a way more forward approach and much easier to maintain (I would recommend using set or other data type suited for fast lookups.
Maybe if you can define your use case more clearer we can work out a pure regex solution...
I'm having an issue with specific entries in my wordforms file that are not being
interpreted as expected.
Here are a couple of examples:
1/48 > forty-eighth
1/96 > ninety-sixth
As you can see, these entries contain both slashes and hyphens, which may be related to
my issue.
For some reason, Sphinx doesn't correctly equate each fraction to the spelled out
version. Search results for "1/48" are not the same as for "forty-eighth", as they should
be. In other words, the mapping between these equivalent forms is not working.
In my Sphinx config, I have the forward slash (/) set as a blend character, so I assume
that the fraction is being recognized properly.
In support of that belief, the following wordforms entry does work correctly:
1/4 > fourth
Does anyone have any idea why my multi-term synonyms would not be working as expected?
I have tried replacing the hyphen with a space, but this doesn't change the result at
all. Would it help to change the order of the terms (i.e., on which side of the ">" they
should be placed)?
Thank you very much for any help.
When using characters in Sphinx it is always good to keep in mind the following:
By default, the Sphinx tokenizer handles unknown characters as whitespace
https://sphinxsearch.com/blog/2014/11/26/sphinx-text-processing-pipeline/
That has given me weird results too when using wordforms.
I would suggest you add the hyphen to charset_tables so ninety-sixth becomes one word. ignore_chars is also an option but then you will be looking for ninetysixth instead.
Much depends on the rest of your dataset and use cases ofcourse.
I have two versions of a large book in txt format and I'd like to compare them to find significant changes between the versions, ignoring small single character differences.
There are lots of diffing tools that can ignore whitespace differences, but I also want to ignore small typos and single or couple character differences. For example, one version of the book has a repeated misspelling of leige hundreds of times and this is corrected in the next version to liege. Some proper nouns have also changed their spelling. (I could make custom workarounds for each misspelling, but would like something more general purpose)
Since I only care about more significant multi-word differences want I really want is to set a filter that ignores changes for a line unless the Levenshtein edit distance is above some threshold.
Looking around all the diff/comparisons tools I find seem to have code in mind so they lack any feature around ignoring small text changes. Google's diff_match_patch library is great for diffing plaintext and ignoring whitespace changes (demo here) but doesn't seem to have an out of the box way to ignore single character non-whitespace differences.
tl;dr; Are there any diff tools that can compare text documents but filter out minor single character non-whitespace differences?
In Beyond compare you can define "replacements".
An example:
Differences are marked red:
Then you can go to Session->Session Settings and set a replacement:
Or even easier: Mark the text and define the replacement immediate:
Now the difference is unimportant and marked blue:
With one click you can ignore the unimportant differences (red arrow in the screenshot).
Technical remark: I use BC4 with the pro edition.
We just added Swiftlint to our project and we want to follow all the rules but I'm not sure what's meant by 'type_body_length' warning. I'm not a native english speaker so I find it a bit confusing.
There is a rule for file length aswell so how do they differ? What falls under this definition?
type_body_length violation means that the class has too many lines in it. I dont think it counts extensions, comments or whitespace
Type name should only contain alphanumeric characters, start with an uppercase character and span between 3 and 40 characters in length.
The rules documentation linked here and above also gives examples of what would and wouldn't be accepted (Triggering & Non Triggering). - Edit suggested by #GoodSp33d, thanks
I've prepared a macro in Notepad++ to transform a ldif file in a csv file with a few fields. Everything is OK but I have a final problem: I have to have 2 fields with a specific length and in this moment I cannot ensure that length because in the source file they are not coming so
For instance, I generate this line:
12345,namenamename,123456
And I have to ensure that the 2nd and 3rd fields have 30 (filling with spaces at right side) and 9 (filling with zeros at left) characters, so in this case I should generate:
12345,namenamename ,000123456
I haven't found how Notepad++ could match a pattern in order to add spaces/zeros, so I have though in to add 1 space/zero to the proper field and repeat this step so many times as needed to ensure the lengths (this is, 29 and 8, because they cannot come empty) and search with the length in the regex (for instance: \d{1,8} for the third field)
My question is: can I repeat only one step of the macro several times (and the rest of the macro only 1 repetition)?
I've read the wiki related to this point (http://sourceforge.net/apps/mediawiki/notepad-plus/index.php?title=Editing_Configuration_Files#.3CMacros.3E) and I don't found anything neither
If not possible, how could be a good solution? Create another 2 different macros and after execute the main one, execute this new 2 macros several times?
Thanks in advance!
A two pass solution with Notepad++ is possible. Find a pair of characters or two short sequence of characters that never occurs in your data file. I will use =#<= and =>#= here.
First pass, generate or convert the input text into the form 12345,=#<=namenamename______________________________,000000000123456=>#=. Ie add 30 spaces after the name and nine zeroes before the number (underscores used here just to make things clearer).
Second pass, do a regular expression search for =#<=(.{30})_*,0*(\d{9})=>#= and replace with \1,\2.
I have just suggested a similar solution in special timestamp format of csv