feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
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import 'dart:convert';
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import 'dart:io';
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import 'package:args/args.dart';
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import 'package:halkyon_learn_curator/src/sources/jlpt.dart';
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import 'package:halkyon_learn_curator/src/sources/jmdict.dart';
|
2026-10-09 16:33:48 +02:00
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import 'package:halkyon_learn_curator/src/sources/jmdict_xml.dart';
|
feat(curator): KANJIDIC2 and the kana as a dictionary of characters; KanjiVG's strokes for the app
A dictionary file now says whether it holds words or characters (`kind`).
The kanjidic adapter turns KANJIDIC2 into one entry per kanji that has a
Japanese reading or an English meaning (12,633), with its readings,
meanings, school grade, strokes, frequency and JLPT level (Jonathan
Waller's, through kanji-data's kanji.json), labelled `jlpt:nX`,
`grade:N`/`grade:secondary`, followed by the 71 hiragana and katakana of
the kana table with their romaji. A kun reading is found whole; its kanji
part only as a loose key, so typing "ta" brings た before every kanji read
so.
`curate kanjivg` writes KanjiVG's strokes and components as the app's
stroke files, one gzipped JSON file per 256 code points, keyed by the code
point in each entry's id (KanjiVG's 橅 names itself 機).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 14:37:22 +02:00
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import 'package:halkyon_learn_curator/src/sources/kanjidic.dart';
|
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import 'package:halkyon_learn_curator/src/sources/kanjivg.dart';
|
feat(curator): curate update keeps a server's dictionaries current
EDRDG's licence asks of servers showing its dictionaries that they update
them at least monthly. `curate update --into <folder>` downloads EDRDG's
files of the day (JMdict with Tatoeba's sentences, KANJIDIC2), converts
them with the JLPT levels the curator now brings along (yomitan-jlpt-vocab's
lists, CC BY-SA 4.0, and the kanji levels of kanji-data's kanji.json: both
static, in data/ with their origin), and puts each file in place at once
(written beside it as .part, then renamed over it), so the server never
reads half a file; a failure leaves the files as they were. With --every 7
it keeps running and updates whenever the files are a week old, as their
dates say, so a restart doesn't download again; after a failure it tries
again in six hours. A real update takes some 50 seconds and 400 MB.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 16:40:19 +02:00
|
|
|
import 'package:halkyon_learn_curator/src/update.dart';
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
|
|
|
|
|
/// Turns a dictionary download into a dictionary file for the server's
|
feat(curator): KANJIDIC2 and the kana as a dictionary of characters; KanjiVG's strokes for the app
A dictionary file now says whether it holds words or characters (`kind`).
The kanjidic adapter turns KANJIDIC2 into one entry per kanji that has a
Japanese reading or an English meaning (12,633), with its readings,
meanings, school grade, strokes, frequency and JLPT level (Jonathan
Waller's, through kanji-data's kanji.json), labelled `jlpt:nX`,
`grade:N`/`grade:secondary`, followed by the 71 hiragana and katakana of
the kana table with their romaji. A kun reading is found whole; its kanji
part only as a loose key, so typing "ta" brings た before every kanji read
so.
`curate kanjivg` writes KanjiVG's strokes and components as the app's
stroke files, one gzipped JSON file per 256 code points, keyed by the code
point in each entry's id (KanjiVG's 橅 names itself 機).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 14:37:22 +02:00
|
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|
/// `dictionaries` folder, or KanjiVG into the app's stroke files
|
|
|
|
|
/// (README.md):
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
///
|
|
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/// dart run halkyon_learn_curator:curate jmdict \
|
2026-10-09 16:33:48 +02:00
|
|
|
/// --input JMdict_e_examp.gz --jlpt original_data \
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
/// --output jmdict-en.jsonl.gz
|
feat(curator): KANJIDIC2 and the kana as a dictionary of characters; KanjiVG's strokes for the app
A dictionary file now says whether it holds words or characters (`kind`).
The kanjidic adapter turns KANJIDIC2 into one entry per kanji that has a
Japanese reading or an English meaning (12,633), with its readings,
meanings, school grade, strokes, frequency and JLPT level (Jonathan
Waller's, through kanji-data's kanji.json), labelled `jlpt:nX`,
`grade:N`/`grade:secondary`, followed by the 71 hiragana and katakana of
the kana table with their romaji. A kun reading is found whole; its kanji
part only as a loose key, so typing "ta" brings た before every kanji read
so.
`curate kanjivg` writes KanjiVG's strokes and components as the app's
stroke files, one gzipped JSON file per 256 code points, keyed by the code
point in each entry's id (KanjiVG's 橅 names itself 機).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 14:37:22 +02:00
|
|
|
/// dart run halkyon_learn_curator:curate kanjidic \
|
|
|
|
|
/// --input kanjidic2.xml.gz --jlpt kanji.json \
|
|
|
|
|
/// --output kanjidic-en.jsonl.gz
|
|
|
|
|
/// dart run halkyon_learn_curator:curate kanjivg \
|
|
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|
|
/// --input kanjivg-20260714.xml.gz \
|
|
|
|
|
/// --output ../halkyon_learn_flutter/assets/kanjivg
|
feat(curator): curate update keeps a server's dictionaries current
EDRDG's licence asks of servers showing its dictionaries that they update
them at least monthly. `curate update --into <folder>` downloads EDRDG's
files of the day (JMdict with Tatoeba's sentences, KANJIDIC2), converts
them with the JLPT levels the curator now brings along (yomitan-jlpt-vocab's
lists, CC BY-SA 4.0, and the kanji levels of kanji-data's kanji.json: both
static, in data/ with their origin), and puts each file in place at once
(written beside it as .part, then renamed over it), so the server never
reads half a file; a failure leaves the files as they were. With --every 7
it keeps running and updates whenever the files are a week old, as their
dates say, so a restart doesn't download again; after a failure it tries
again in six hours. A real update takes some 50 seconds and 400 MB.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 16:40:19 +02:00
|
|
|
///
|
|
|
|
|
/// Or brings a server's dictionaries up to date from EDRDG's files of the
|
|
|
|
|
/// day, once or every so many days:
|
|
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|
|
///
|
|
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|
|
/// dart run halkyon_learn_curator:curate update \
|
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|
|
/// --into ../halkyon_learn_server/dictionaries [--every 7]
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
Future<void> main(List<String> args) async {
|
|
|
|
|
final parser = ArgParser()
|
feat(curator): KANJIDIC2 and the kana as a dictionary of characters; KanjiVG's strokes for the app
A dictionary file now says whether it holds words or characters (`kind`).
The kanjidic adapter turns KANJIDIC2 into one entry per kanji that has a
Japanese reading or an English meaning (12,633), with its readings,
meanings, school grade, strokes, frequency and JLPT level (Jonathan
Waller's, through kanji-data's kanji.json), labelled `jlpt:nX`,
`grade:N`/`grade:secondary`, followed by the 71 hiragana and katakana of
the kana table with their romaji. A kun reading is found whole; its kanji
part only as a loose key, so typing "ta" brings た before every kanji read
so.
`curate kanjivg` writes KanjiVG's strokes and components as the app's
stroke files, one gzipped JSON file per 256 code points, keyed by the code
point in each entry's id (KanjiVG's 橅 names itself 機).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 14:37:22 +02:00
|
|
|
..addOption(
|
|
|
|
|
'input',
|
|
|
|
|
abbr: 'i',
|
|
|
|
|
help: 'The source file, unpacked or gzipped (.gz).',
|
|
|
|
|
)
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
..addOption(
|
|
|
|
|
'jlpt',
|
feat(curator): KANJIDIC2 and the kana as a dictionary of characters; KanjiVG's strokes for the app
A dictionary file now says whether it holds words or characters (`kind`).
The kanjidic adapter turns KANJIDIC2 into one entry per kanji that has a
Japanese reading or an English meaning (12,633), with its readings,
meanings, school grade, strokes, frequency and JLPT level (Jonathan
Waller's, through kanji-data's kanji.json), labelled `jlpt:nX`,
`grade:N`/`grade:secondary`, followed by the 71 hiragana and katakana of
the kana table with their romaji. A kun reading is found whole; its kanji
part only as a loose key, so typing "ta" brings た before every kanji read
so.
`curate kanjivg` writes KanjiVG's strokes and components as the app's
stroke files, one gzipped JSON file per 256 code points, keyed by the code
point in each entry's id (KanjiVG's 橅 names itself 機).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 14:37:22 +02:00
|
|
|
help:
|
|
|
|
|
"jmdict: yomitan-jlpt-vocab's original_data folder (n1.csv … "
|
|
|
|
|
"n5.csv); kanjidic: kanji-data's kanji.json.",
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
)
|
2026-10-09 13:36:16 +02:00
|
|
|
..addFlag(
|
|
|
|
|
'examples',
|
|
|
|
|
help:
|
2026-10-09 16:33:48 +02:00
|
|
|
"The input is JMdict's examples edition (EDRDG's "
|
|
|
|
|
"JMdict_e_examp.gz, jmdict-simplified's jmdict-examples-eng-*.json): "
|
|
|
|
|
'credit Tatoeba for its sentences. On by default for a file named '
|
|
|
|
|
'so.',
|
2026-10-09 13:36:16 +02:00
|
|
|
defaultsTo: null,
|
|
|
|
|
)
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
..addOption(
|
|
|
|
|
'output',
|
|
|
|
|
abbr: 'o',
|
feat(curator): KANJIDIC2 and the kana as a dictionary of characters; KanjiVG's strokes for the app
A dictionary file now says whether it holds words or characters (`kind`).
The kanjidic adapter turns KANJIDIC2 into one entry per kanji that has a
Japanese reading or an English meaning (12,633), with its readings,
meanings, school grade, strokes, frequency and JLPT level (Jonathan
Waller's, through kanji-data's kanji.json), labelled `jlpt:nX`,
`grade:N`/`grade:secondary`, followed by the 71 hiragana and katakana of
the kana table with their romaji. A kun reading is found whole; its kanji
part only as a loose key, so typing "ta" brings た before every kanji read
so.
`curate kanjivg` writes KanjiVG's strokes and components as the app's
stroke files, one gzipped JSON file per 256 code points, keyed by the code
point in each entry's id (KanjiVG's 橅 names itself 機).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 14:37:22 +02:00
|
|
|
help:
|
|
|
|
|
'The dictionary file to write, gzipped when it ends in .gz; for '
|
|
|
|
|
'kanjivg the folder to write the stroke files into.',
|
feat(curator): curate update keeps a server's dictionaries current
EDRDG's licence asks of servers showing its dictionaries that they update
them at least monthly. `curate update --into <folder>` downloads EDRDG's
files of the day (JMdict with Tatoeba's sentences, KANJIDIC2), converts
them with the JLPT levels the curator now brings along (yomitan-jlpt-vocab's
lists, CC BY-SA 4.0, and the kanji levels of kanji-data's kanji.json: both
static, in data/ with their origin), and puts each file in place at once
(written beside it as .part, then renamed over it), so the server never
reads half a file; a failure leaves the files as they were. With --every 7
it keeps running and updates whenever the files are a week old, as their
dates say, so a restart doesn't download again; after a failure it tries
again in six hours. A real update takes some 50 seconds and 400 MB.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 16:40:19 +02:00
|
|
|
)
|
|
|
|
|
..addOption('into', help: 'update: the folder of the dictionary files.')
|
|
|
|
|
..addOption(
|
|
|
|
|
'data',
|
|
|
|
|
help: "update: the curator's data folder (the JLPT lists).",
|
|
|
|
|
defaultsTo: 'data',
|
|
|
|
|
)
|
|
|
|
|
..addOption(
|
|
|
|
|
'every',
|
|
|
|
|
help:
|
|
|
|
|
'update: keep running, and update once the files are this many '
|
|
|
|
|
'days old.',
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
);
|
|
|
|
|
final ArgResults options;
|
|
|
|
|
try {
|
|
|
|
|
options = parser.parse(args);
|
|
|
|
|
} on FormatException catch (error) {
|
|
|
|
|
_fail('${error.message}\n${parser.usage}');
|
|
|
|
|
}
|
|
|
|
|
final [source, ...] = options.rest.isEmpty ? [''] : options.rest;
|
feat(curator): curate update keeps a server's dictionaries current
EDRDG's licence asks of servers showing its dictionaries that they update
them at least monthly. `curate update --into <folder>` downloads EDRDG's
files of the day (JMdict with Tatoeba's sentences, KANJIDIC2), converts
them with the JLPT levels the curator now brings along (yomitan-jlpt-vocab's
lists, CC BY-SA 4.0, and the kanji levels of kanji-data's kanji.json: both
static, in data/ with their origin), and puts each file in place at once
(written beside it as .part, then renamed over it), so the server never
reads half a file; a failure leaves the files as they were. With --every 7
it keeps running and updates whenever the files are a week old, as their
dates say, so a restart doesn't download again; after a failure it tries
again in six hours. A real update takes some 50 seconds and 400 MB.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 16:40:19 +02:00
|
|
|
if (source == 'update') {
|
|
|
|
|
final into = options.option('into');
|
|
|
|
|
final every = options.option('every');
|
|
|
|
|
final days = every == null ? null : int.tryParse(every);
|
|
|
|
|
if (into == null || (every != null && (days == null || days < 1))) {
|
|
|
|
|
_fail(
|
|
|
|
|
'Usage: curate update --into <folder> [--data <folder>] '
|
|
|
|
|
'[--every <days>]\n${parser.usage}',
|
|
|
|
|
);
|
|
|
|
|
}
|
|
|
|
|
await _update(Directory(into), Directory(options.option('data')!), days);
|
|
|
|
|
return;
|
|
|
|
|
}
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
final input = options.option('input');
|
|
|
|
|
final output = options.option('output');
|
feat(curator): KANJIDIC2 and the kana as a dictionary of characters; KanjiVG's strokes for the app
A dictionary file now says whether it holds words or characters (`kind`).
The kanjidic adapter turns KANJIDIC2 into one entry per kanji that has a
Japanese reading or an English meaning (12,633), with its readings,
meanings, school grade, strokes, frequency and JLPT level (Jonathan
Waller's, through kanji-data's kanji.json), labelled `jlpt:nX`,
`grade:N`/`grade:secondary`, followed by the 71 hiragana and katakana of
the kana table with their romaji. A kun reading is found whole; its kanji
part only as a loose key, so typing "ta" brings た before every kanji read
so.
`curate kanjivg` writes KanjiVG's strokes and components as the app's
stroke files, one gzipped JSON file per 256 code points, keyed by the code
point in each entry's id (KanjiVG's 橅 names itself 機).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 14:37:22 +02:00
|
|
|
if (!['jmdict', 'kanjidic', 'kanjivg'].contains(source) ||
|
|
|
|
|
input == null ||
|
|
|
|
|
output == null) {
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
_fail(
|
feat(curator): KANJIDIC2 and the kana as a dictionary of characters; KanjiVG's strokes for the app
A dictionary file now says whether it holds words or characters (`kind`).
The kanjidic adapter turns KANJIDIC2 into one entry per kanji that has a
Japanese reading or an English meaning (12,633), with its readings,
meanings, school grade, strokes, frequency and JLPT level (Jonathan
Waller's, through kanji-data's kanji.json), labelled `jlpt:nX`,
`grade:N`/`grade:secondary`, followed by the 71 hiragana and katakana of
the kana table with their romaji. A kun reading is found whole; its kanji
part only as a loose key, so typing "ta" brings た before every kanji read
so.
`curate kanjivg` writes KanjiVG's strokes and components as the app's
stroke files, one gzipped JSON file per 256 code points, keyed by the code
point in each entry's id (KanjiVG's 橅 names itself 機).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 14:37:22 +02:00
|
|
|
'Usage: curate jmdict|kanjidic|kanjivg --input <file> [--jlpt <path>] '
|
|
|
|
|
'--output <path>\n${parser.usage}',
|
|
|
|
|
);
|
|
|
|
|
}
|
|
|
|
|
final read = File(input).openRead();
|
|
|
|
|
final text = (input.endsWith('.gz') ? read.transform(gzip.decoder) : read)
|
|
|
|
|
.transform(utf8.decoder);
|
|
|
|
|
final jlptPath = options.option('jlpt');
|
|
|
|
|
|
|
|
|
|
if (source == 'kanjivg') {
|
|
|
|
|
final strokes = kanjivgStrokes(await text.join());
|
|
|
|
|
final folder = await Directory(output).create(recursive: true);
|
|
|
|
|
final files = strokeFiles(strokes);
|
|
|
|
|
for (final MapEntry(key: name, value: characters) in files.entries) {
|
|
|
|
|
await File('${folder.path}/$name.json.gz')
|
|
|
|
|
.writeAsBytes(gzip.encode(utf8.encode(jsonEncode(characters))));
|
|
|
|
|
}
|
|
|
|
|
stdout.writeln(
|
|
|
|
|
'Wrote the strokes of ${strokes.length} characters to '
|
|
|
|
|
'${files.length} files in $output.',
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
);
|
feat(curator): KANJIDIC2 and the kana as a dictionary of characters; KanjiVG's strokes for the app
A dictionary file now says whether it holds words or characters (`kind`).
The kanjidic adapter turns KANJIDIC2 into one entry per kanji that has a
Japanese reading or an English meaning (12,633), with its readings,
meanings, school grade, strokes, frequency and JLPT level (Jonathan
Waller's, through kanji-data's kanji.json), labelled `jlpt:nX`,
`grade:N`/`grade:secondary`, followed by the 71 hiragana and katakana of
the kana table with their romaji. A kun reading is found whole; its kanji
part only as a loose key, so typing "ta" brings た before every kanji read
so.
`curate kanjivg` writes KanjiVG's strokes and components as the app's
stroke files, one gzipped JSON file per 256 code points, keyed by the code
point in each entry's id (KanjiVG's 橅 names itself 機).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 14:37:22 +02:00
|
|
|
return;
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
}
|
|
|
|
|
|
feat(curator): KANJIDIC2 and the kana as a dictionary of characters; KanjiVG's strokes for the app
A dictionary file now says whether it holds words or characters (`kind`).
The kanjidic adapter turns KANJIDIC2 into one entry per kanji that has a
Japanese reading or an English meaning (12,633), with its readings,
meanings, school grade, strokes, frequency and JLPT level (Jonathan
Waller's, through kanji-data's kanji.json), labelled `jlpt:nX`,
`grade:N`/`grade:secondary`, followed by the 71 hiragana and katakana of
the kana table with their romaji. A kun reading is found whole; its kanji
part only as a loose key, so typing "ta" brings た before every kanji read
so.
`curate kanjivg` writes KanjiVG's strokes and components as the app's
stroke files, one gzipped JSON file per 256 code points, keyed by the code
point in each entry's id (KanjiVG's 橅 names itself 機).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 14:37:22 +02:00
|
|
|
final Stream<String> lines;
|
|
|
|
|
final int withLevel;
|
|
|
|
|
if (source == 'kanjidic') {
|
|
|
|
|
final jlpt = jlptPath == null
|
|
|
|
|
? const <String, int>{}
|
|
|
|
|
: await readKanjiJlpt(File(jlptPath));
|
|
|
|
|
lines = Stream.fromIterable(
|
|
|
|
|
kanjidicDictionary(await text.join(), jlpt: jlpt),
|
|
|
|
|
);
|
|
|
|
|
withLevel = jlpt.length;
|
|
|
|
|
} else {
|
|
|
|
|
final jlpt = jlptPath == null
|
|
|
|
|
? const <String, JlptLevel>{}
|
|
|
|
|
: await readJlptLevels(Directory(jlptPath));
|
2026-10-09 16:33:48 +02:00
|
|
|
final name = File(input).uri.pathSegments.last;
|
|
|
|
|
final examples = options.wasParsed('examples')
|
|
|
|
|
? options.flag('examples')
|
|
|
|
|
: name.contains('examp');
|
|
|
|
|
// jmdict-simplified's JSON (`jmdict-eng-….json`), else EDRDG's XML.
|
|
|
|
|
lines = name.contains('.json')
|
|
|
|
|
? jmdictDictionary(text, jlpt: jlpt, examples: examples)
|
|
|
|
|
: jmdictXmlDictionary(text, jlpt: jlpt, examples: examples);
|
feat(curator): KANJIDIC2 and the kana as a dictionary of characters; KanjiVG's strokes for the app
A dictionary file now says whether it holds words or characters (`kind`).
The kanjidic adapter turns KANJIDIC2 into one entry per kanji that has a
Japanese reading or an English meaning (12,633), with its readings,
meanings, school grade, strokes, frequency and JLPT level (Jonathan
Waller's, through kanji-data's kanji.json), labelled `jlpt:nX`,
`grade:N`/`grade:secondary`, followed by the 71 hiragana and katakana of
the kana table with their romaji. A kun reading is found whole; its kanji
part only as a loose key, so typing "ta" brings た before every kanji read
so.
`curate kanjivg` writes KanjiVG's strokes and components as the app's
stroke files, one gzipped JSON file per 256 code points, keyed by the code
point in each entry's id (KanjiVG's 橅 names itself 機).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 14:37:22 +02:00
|
|
|
withLevel = jlpt.length;
|
|
|
|
|
}
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
var entries = -1;
|
feat(curator): KANJIDIC2 and the kana as a dictionary of characters; KanjiVG's strokes for the app
A dictionary file now says whether it holds words or characters (`kind`).
The kanjidic adapter turns KANJIDIC2 into one entry per kanji that has a
Japanese reading or an English meaning (12,633), with its readings,
meanings, school grade, strokes, frequency and JLPT level (Jonathan
Waller's, through kanji-data's kanji.json), labelled `jlpt:nX`,
`grade:N`/`grade:secondary`, followed by the 71 hiragana and katakana of
the kana table with their romaji. A kun reading is found whole; its kanji
part only as a loose key, so typing "ta" brings た before every kanji read
so.
`curate kanjivg` writes KanjiVG's strokes and components as the app's
stroke files, one gzipped JSON file per 256 code points, keyed by the code
point in each entry's id (KanjiVG's 橅 names itself 機).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 14:37:22 +02:00
|
|
|
final bytes = lines
|
|
|
|
|
.map((line) {
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
entries++;
|
|
|
|
|
return line;
|
feat(curator): KANJIDIC2 and the kana as a dictionary of characters; KanjiVG's strokes for the app
A dictionary file now says whether it holds words or characters (`kind`).
The kanjidic adapter turns KANJIDIC2 into one entry per kanji that has a
Japanese reading or an English meaning (12,633), with its readings,
meanings, school grade, strokes, frequency and JLPT level (Jonathan
Waller's, through kanji-data's kanji.json), labelled `jlpt:nX`,
`grade:N`/`grade:secondary`, followed by the 71 hiragana and katakana of
the kana table with their romaji. A kun reading is found whole; its kanji
part only as a loose key, so typing "ta" brings た before every kanji read
so.
`curate kanjivg` writes KanjiVG's strokes and components as the app's
stroke files, one gzipped JSON file per 256 code points, keyed by the code
point in each entry's id (KanjiVG's 橅 names itself 機).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 14:37:22 +02:00
|
|
|
})
|
|
|
|
|
.transform(utf8.encoder);
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
await (output.endsWith('.gz') ? bytes.transform(gzip.encoder) : bytes).pipe(
|
|
|
|
|
File(output).openWrite(),
|
|
|
|
|
);
|
|
|
|
|
stdout.writeln(
|
|
|
|
|
'Wrote $entries entries to $output'
|
feat(curator): KANJIDIC2 and the kana as a dictionary of characters; KanjiVG's strokes for the app
A dictionary file now says whether it holds words or characters (`kind`).
The kanjidic adapter turns KANJIDIC2 into one entry per kanji that has a
Japanese reading or an English meaning (12,633), with its readings,
meanings, school grade, strokes, frequency and JLPT level (Jonathan
Waller's, through kanji-data's kanji.json), labelled `jlpt:nX`,
`grade:N`/`grade:secondary`, followed by the 71 hiragana and katakana of
the kana table with their romaji. A kun reading is found whole; its kanji
part only as a loose key, so typing "ta" brings た before every kanji read
so.
`curate kanjivg` writes KanjiVG's strokes and components as the app's
stroke files, one gzipped JSON file per 256 code points, keyed by the code
point in each entry's id (KanjiVG's 橅 names itself 機).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 14:37:22 +02:00
|
|
|
'${withLevel == 0 ? '' : ' ($withLevel with a JLPT level)'}.',
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
);
|
|
|
|
|
}
|
|
|
|
|
|
feat(curator): curate update keeps a server's dictionaries current
EDRDG's licence asks of servers showing its dictionaries that they update
them at least monthly. `curate update --into <folder>` downloads EDRDG's
files of the day (JMdict with Tatoeba's sentences, KANJIDIC2), converts
them with the JLPT levels the curator now brings along (yomitan-jlpt-vocab's
lists, CC BY-SA 4.0, and the kanji levels of kanji-data's kanji.json: both
static, in data/ with their origin), and puts each file in place at once
(written beside it as .part, then renamed over it), so the server never
reads half a file; a failure leaves the files as they were. With --every 7
it keeps running and updates whenever the files are a week old, as their
dates say, so a restart doesn't download again; after a failure it tries
again in six hours. A real update takes some 50 seconds and 400 MB.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 16:40:19 +02:00
|
|
|
/// Updates the dictionaries in [into]; with [every], keeps running and
|
|
|
|
|
/// updates them whenever they are that many days old (as the files' dates
|
|
|
|
|
/// say, so a restart doesn't download them again), trying again after six
|
|
|
|
|
/// hours when an update fails.
|
|
|
|
|
Future<void> _update(Directory into, Directory data, int? every) async {
|
|
|
|
|
void say(String message) =>
|
|
|
|
|
stdout.writeln('${DateTime.now().toUtc().toIso8601String()} $message');
|
|
|
|
|
Future<bool> once() async {
|
|
|
|
|
try {
|
|
|
|
|
final written = await updateDictionaries(into: into, data: data);
|
|
|
|
|
say(
|
|
|
|
|
'Updated ${[for (final file in written) file.uri.pathSegments.last].join(', ')}.',
|
|
|
|
|
);
|
|
|
|
|
return true;
|
|
|
|
|
} on Object catch (error) {
|
|
|
|
|
say('Updating the dictionaries failed: $error');
|
|
|
|
|
return false;
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
if (every == null) {
|
|
|
|
|
if (!await once()) {
|
|
|
|
|
exit(1);
|
|
|
|
|
}
|
|
|
|
|
return;
|
|
|
|
|
}
|
|
|
|
|
for (;;) {
|
|
|
|
|
final due = lastUpdated(into)?.add(Duration(days: every));
|
|
|
|
|
final now = DateTime.now();
|
|
|
|
|
if (due == null || !now.isBefore(due)) {
|
|
|
|
|
if (!await once()) {
|
|
|
|
|
await Future<void>.delayed(const Duration(hours: 6));
|
|
|
|
|
}
|
|
|
|
|
continue;
|
|
|
|
|
}
|
|
|
|
|
say('Up to date; the next update ${due.toUtc().toIso8601String()}.');
|
|
|
|
|
await Future<void>.delayed(due.difference(now));
|
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
feat(curator): turn JMdict and the JLPT lists into dictionary files
A package of its own in the workspace, without Serverpod (AGPL, like the
tooling): an adapter per source writes one format for all, documented in
its README, which the server will load. The format is JSON Lines: a
header (source, version, languages, licence, credits), then entries with
a headword and reading, labels (`common`, `jlpt:n5`), a rank, the keys a
search matches, and the entry as cards take it. Everything specific to a
language happens in its adapter (Japanese: forms, readings in kana and
Hepburn romaji, long vowels typed once, meanings without "to" and
articles), so the server's search knows no language.
JMdict comes as jmdict-simplified's JSON, read one entry at a time: all
218,863 entries in some 20 seconds and 300 MB, 16.8 MB gzipped. The JLPT
lists (yomitan-jlpt-vocab, CC BY-SA 4.0, from Waller's CC BY lists) add
levels by JMdict entry, the easiest when a word is on several, and give
the headword its common spelling. Words rank N5 to N1, then the other
common words, then the rest.
The server's image leaves the package out, as it does the client's.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MMm7usAo6q9ZZRoPkWjoxi
Signed-off-by: Tizian 「ティツィアーン」 <raisondetredev@pm.me>
2026-10-09 00:25:16 +02:00
|
|
|
Never _fail(String message) {
|
|
|
|
|
stderr.writeln(message);
|
|
|
|
|
exit(64);
|
|
|
|
|
}
|