ebook-reader-dict VS FlatBuffers

I just stumbled across Kobo dictionaries, but none in a format which could be imported into Calibre, for further upload to Kindle. Copying the actual files or directories obtained by extraction of one of the Kobo dictionaries, into the documents directories of Kindle (as I've done to Littré and Roberts, to make them avail in the dictionary settings of Kindle) leads nowhere, either, so I am pretty much stuck.

I just had a look at a .dict from ebook-reader-dict (where the content comes from Wiktionary too, and they seem to deal with inflections too); "unfortunately" they seem to use .syn file too to store the inflections, so the behavior with the default dictionary app is similar... About further coding, I'll play with their code1 this week to check how the converting/compiling is done (who knows, maybe I/we can help there? :) ). So their is hope for a relatively quick solution :)

One can also access the whole content of Wikipedia -and a looot more- offline, thank to among others the project "Kiwix" (Wiktionaries can be found here, other readings are available also to download trough the app, and finally, you can always "ZIM it", if you don't find what you want in the lists). Kiwix doesn't have to be used in a "stand-alone" fashion, as you can access it within the pop-up window in NeoReader as shown in the 3rd pic (working on firmware 3.3.1 too). At last but not least, another offline solution based on Wiki AND in the StarDict format is the "e-book-reader-dict" project (thank to cerank for sharing it! I have to admit I didn't find it by myself before starting this...)

I use a stardict version of Wiktionary I have found on Github (others languages are available like French, German, ...)

I have no experience with studying/reading German books on a Kobo, so I cannot comment on that. However, the Kobo dictionaries are generally not very good for languages with a lot of inflection such as Spanish, Russian, etc. It seems there is a good French dictionary for it (but I don't read French either, so I cannot confirm): https://github.com/BoboTiG/ebook-reader-dict. (They also have a German dictionary that should support conjugated forms - check it out!)

You could look at https://github.com/BoboTiG/ebook-reader-dict

Wiktionary

I am trying to install these dictionaries using this guide.

I have not heard of the .dic format. Just check this link: https://github.com/BoboTiG/ebook-reader-dict You just need to download a zip file and copy it where you already tried to copy your other file.

Here are other Spanish dictionaries: https://github.com/BoboTiG/ebook-reader-dict/releases/tag/es

I don't work at Cloudflare but follow their work and occasionally work on performance sensitive projects.

If I had to guess, they looked at the landscape a bit like I do and regarded Cap'n Proto, flatbuffers, SBE, etc. as being in one category apart from other data formats like Avro, protobuf, and the like.

So once you're committed to record'ish shaped (rather than columnar like Parquet) data that has an upfront parse time of zero (nominally, there could be marshalling if you transmogrify the field values on read), the list gets pretty short.

https://capnproto.org/news/2014-06-17-capnproto-flatbuffers-... goes into some of the trade-offs here.

Cap'n Proto was originally made for https://sandstorm.io/. That work (which Kenton has presumably done at Cloudflare since he's been employed there) eventually turned into Cloudflare workers.

Another consideration: https://github.com/google/flatbuffers/issues/2#issuecomment-...

Much more in the discussion of this particular issue onGitHub: flatbuffers:Reverse engineering #4258

Related but not Rust-specific: FlatBuffers, Cap'n Proto.

If json files are a concern because of space, you can always look into something like protobuffers or flatbuffers. But whatever you use, you should try to find a solution where you don't have to think about the actual serialization/deserialization of your objects, and can just concentrate on the data.

Or, as an alternative to protobuffers, there's also flatbuffers, which is lighter weight and needs less memory: https://google.github.io/flatbuffers/

As the title suggests, I am considering using Flatbuffers as a way to parse sensor data that has been stored in local datafiles. The project language is python.