diff-match-patch VS zstd

I also came across this diff match algorithms: https://github.com/google/diff-match-patch

Outside of that, to get the diffs there is a library called diff-match-patch that has implementations in most languages. Your data model / state tracking sounds like it matches the internal constraints.

So I'll just leave you with this question - why, as a developer, would I ever advise using this, when fast diff is an industry standard tool that does exactly this, but better, using well tested methods that are being implemented in JS and further optimized by one of the largest global tech companies. Mind you, this is the same company which has developed its own proprietary monolithic VCS, managing versioning for 2billion+ lines of code.

Hello HN!

I was always annoyed by conflicts that can be solved automatically, but still need human intervention. E.g. two people changing the same line, but at different, non-conflicting positions. So I searched for a character based patching library and found this nice article https://neil.fraser.name/writing/patch/ and its corresponding library https://github.com/google/diff-match-patch.

Parsing git conflicts, applying patches and showing some useful diffs in the UI helps me to solve 80% of my conflicts automatically. I hope it can help you too.

Happy Hacking!

A bit late to the party but have you checked this? google/diff-match-patch

Found this, simple and seems interesting: https://github.com/google/diff-match-patch

If you need to know exactly what the diff is, you might want to use something like github.com/google/diff-match-patch. Otherwise, a simple Levenshtein distance would suffice. This library seems to have a whole bunch of string distances implemented. Hope this helps!

Photo by Markus Spiske on Diff.Match.Patch based on Google library.

This VFS will read a sqlite file after it has been compressed using [zstd seekable format](https://github.com/facebook/zstd/blob/dev/contrib/seekable_f...). Built to support read-only databases for full-text search. Benchmarks are provided in README.

Of course, you may get different results with another dataset.

gzip (zlib -6) [ratio=32%] [compr=35Mo/s] [dec=407Mo/s]

zstd (zstd -2) [ratio=32%] [compr=356Mo/s] [dec=1067Mo/s]

NB1: The default for zstd is -3, but the table only had -2. The difference is probably small. The range is 1-22 for zstd and 1-9 for gzip.

NB2: The default program for gzip (at least with Debian) is the executable from zlib. With my workflows, libdeflate-gzip iscompatible and noticably faster.

NB3: This benchmark is 2 years old. The latest releases of zstd are much better, see https://github.com/facebook/zstd/releases

For a high compression, according to this benchmark xz can do slightly better, if you're willing to pay a 10× penalty on decompression.

xz -9 [ratio=23%] [compr=2.6Mo/s] [dec=88Mo/s]

zstd -9 [ratio=23%] [compr=2.6Mo/s] [dec=88Mo/s]

Compression, synchronization and backup systems often use rolling hash to implement "content-defined chunking", an effective form of deduplication.

In optimized implementations, Rabin-Karp is likely to be the bottleneck. See for instance https://github.com/facebook/zstd/pull/2483 which replaces a Rabin-Karp variant by a >2x faster Gear-Hashing.

Get the data https://publicdistst.blob.core.windows.net/data/root.tar.zst magnet:?xt=urn:btih:84931cd80409ba6331f2fcfbe64ba64d4381aec5&dn=root.tar.zst How to extract https://github.com/facebook/zstd Linux (debian): `sudo apt install zstd` ``` tar -I 'zstd -d -T0' -xvf root.tar.zst ```

I've done that experiment with zstd before.

https://github.com/facebook/zstd/blob/dev/programs/zstd.1.md...

Not sure about brotli though.

If you want this functionality in zstd itself, check this out: https://github.com/facebook/zstd/pull/2349