diff --git a/add-readings.py b/add-readings.py
index 0cf77ad..5f987fa 100644
--- a/add-readings.py
+++ b/add-readings.py
@@ -1,138 +1,17 @@
-import json
-import MeCab
-import re
-
-import requests
-
-request_url = "http://127.0.0.1:19633"
-request_timeout = 10
-
-# Generate Hiragana and Katakana characters
-hiragana = tuple(chr(i) for i in range(12353, 12436)) # \u3041 - \u3094
-katakana = tuple(chr(i) for i in range(12450, 12532)) # \u30A2 - \u30F4
-punctuation = tuple(chr(i) for i in range(65281, 65382))
-
-# Combine both into one tuple
-all_kana = hiragana + katakana + punctuation + (' ', 'ー', '・')
-
-KANJI_RE = re.compile(r"[\u4E00-\u9FFF]")
-
-def katakana_to_hiragana(text: str) -> str:
- return "".join(
- chr(ord(ch) - 0x60) if 0x30A1 <= ord(ch) <= 0x30F6 else ch
- for ch in text
- )
-
-# def get_node_reading(node) -> str:
-# features = node.feature.split(",")
-# print()
-# if len(features) >= 8 and features[7] != "*":
-# return katakana_to_hiragana(features[7])
-# return node.surface
-
-def has_kanji(text: str) -> bool:
- return bool(KANJI_RE.search(text))
-
-def get_node_reading(node) -> str:
- features = node.feature.split(",")
- ## These depend on what dictionary is being used.
- if len(features) > 6 and features[6] != "*":
- return katakana_to_hiragana(features[6])
- return node.surface
-
-def annotate_phrase(text: str) -> str:
- tagger = MeCab.Tagger()
- node = tagger.parseToNode(text)
- vocab = ()
- parts = []
- # 漢字
- furi = []
- while node:
- surface = node.surface
- if surface:
- vocab += (surface,)
- if has_kanji(surface):
- reading = get_node_reading(node)
- parts.append(f"{surface}({reading})")
- furi.append(f"{surface}")
- else:
- parts.append(surface)
- furi.append(surface)
- node = node.next
-
- return {'reading':("".join(parts)),'vocab':vocab,"furigana":("".join(furi))}
-
-def elide(text: str) -> str:
- elide_max_length = 100
- if len(text) > elide_max_length:
- return text[:100] + "..."
- return text
-
-def anki_fields_term(term : str) -> dict:
- params = {
- "text": term,
- "type": "term",
- "markers": ["audio", "cloze-body-kana", "conjugation", "expression", "furigana", "furigana-plain", "glossary", "glossary-brief", "glossary-no-dictionary", "glossary-first", "glossary-first-brief", "glossary-first-no-dictionary", "part-of-speech", "phonetic-transcriptions", "pitch-accents", "pitch-accent-graphs", "pitch-accent-graphs-jj", "pitch-accent-positions", "pitch-accent-categories", "reading", "tags", "clipboard-image", "clipboard-text", "cloze-body", "cloze-prefix", "cloze-suffix", "dictionary", "dictionary-alias", "document-title", "frequencies", "frequency-harmonic-rank", "frequency-harmonic-occurrence", "frequency-average-rank", "frequency-average-occurrence", "screenshot", "search-query", "popup-selection-text", "sentence", "sentence-furigana", "sentence-furigana-plain", "url"],
- "maxEntries": 1,
- "includeMedia": False,
- }
- response = requests.post(request_url + "/ankiFields", json = params, timeout = request_timeout)
- return json.loads(response.text)
-
-def term_entries(term :str) -> dict:
- #print("Requesting termEntries:")
- params = {
- "term": term,
- "maxEntries": 1,
- "includeMedia": False,
- }
- response = requests.post(request_url + "/termEntries", json = params, timeout = request_timeout)
- return json.loads(response.text)
-
-# perhaps set up a filter parameter.
-def flatten_string(node):
- if isinstance(node,str):
- yield node
- elif isinstance(node, list):
- for item in node:
- yield from flatten_string(item)
- elif isinstance(node,dict):
- if isinstance(node.get("content"), str):
- yield node["content"]
- else:
- for v in node.values():
- yield from flatten_string(v)
-
-def extract_text_by_type(node, target_type):
- if isinstance(node,dict):
- data = node.get("data")
- if isinstance(data,dict) and data.get("content") == target_type:
- yield from flatten_string(node.get("content"))
- #yield from ",".join(node.get("content"))
- for value in node.values():
- yield from extract_text_by_type(value, target_type)
- elif isinstance(node,list):
- for item in node:
- yield from extract_text_by_type(item,target_type)
-
-def get_glossary(word :str) -> list:
- glossary = list()
- dict_items = term_entries(word)
-
- entry = next(iter(dict_items.get("dictionaryEntries",[])),None)
- if entry:
- definition = next(iter(entry.get("definitions",[])),None)
- if definition:
- def_entry = next(iter(definition.get("entries", [])),None)
- if def_entry:
- glossary.extend( list(extract_text_by_type(def_entry, "glossary")) )
- return glossary[:2]
+from parser import *
#print(annotate_phrase("私は学校へ行きます"))
with open("dump2.json", "r", encoding="utf-16") as f:
dump = json.load(f)
+# foo = anki_fields_term(surface)
+# for entry in foo.get("fields"):
+# entry['expression']
+# entry['glossary-first-brief']
+ # entry['glossary-plain-no-dictionary']
+ # entry['frequency-average-rank']
+
vocab_dict = {}
## A micab phrase based word parser
for cd in dump:
@@ -196,8 +75,8 @@ for cd in dump:
vocab_dict = sorted(vocab_dict.items(), key= lambda x: x[1]['count'], reverse=True)
-with open("dump-withFuri.json", "w", encoding="utf-16") as outfile:
- json.dump(dump, outfile, ensure_ascii=False, indent=2)
+#with open("dump-withFuri.json", "w", encoding="utf-16") as outfile:
+# json.dump(dump, outfile, ensure_ascii=False, indent=2)
#with open("dump-vocab.json", "w", encoding="utf-16") as outfile:
# json.dump(vocab_dict, outfile, ensure_ascii=False, indent=2)
diff --git a/create-notes.py b/create-notes.py
index 255647f..377b446 100644
--- a/create-notes.py
+++ b/create-notes.py
@@ -1,79 +1,13 @@
-import json
-import MeCab
-import re
-
-import requests
+from parser import *
import os
from pathlib import Path
import shutil
-
-request_url = "http://127.0.0.1:19633"
-request_timeout = 10
+import hashlib
destination_directory_name = '/run/media/deck/YF8SD/Sync/Notebooks/Obsidian/Japanese/Yu-Gi-Oh/Cards/'
destination_path = Path(destination_directory_name)
-# Generate Hiragana and Katakana characters
-hiragana = tuple(chr(i) for i in range(12353, 12436)) # \u3041 - \u3094
-katakana = tuple(chr(i) for i in range(12450, 12532)) # \u30A2 - \u30F4
-punctuation = tuple(chr(i) for i in range(65281, 65382))
-
-# Combine both into one tuple
-all_kana = hiragana + katakana + punctuation + (' ', 'ー', '・')
-
-KANJI_RE = re.compile(r"[\u4E00-\u9FFF]")
-
-def katakana_to_hiragana(text: str) -> str:
- return "".join(
- chr(ord(ch) - 0x60) if 0x30A1 <= ord(ch) <= 0x30F6 else ch
- for ch in text
- )
-
-# def get_node_reading(node) -> str:
-# features = node.feature.split(",")
-# print()
-# if len(features) >= 8 and features[7] != "*":
-# return katakana_to_hiragana(features[7])
-# return node.surface
-
-def has_kanji(text: str) -> bool:
- return bool(KANJI_RE.search(text))
-
-def anki_fields_term(term : str) -> dict:
- params = {
- "text": term,
- "type": "term",
- "markers": ["audio", "cloze-body-kana", "conjugation", "expression", "furigana", "furigana-plain", "glossary", "glossary-brief", "glossary-no-dictionary", "glossary-first", "glossary-first-brief", "glossary-first-no-dictionary", "part-of-speech", "phonetic-transcriptions", "pitch-accents", "pitch-accent-graphs", "pitch-accent-graphs-jj", "pitch-accent-positions", "pitch-accent-categories", "reading", "tags", "clipboard-image", "clipboard-text", "cloze-body", "cloze-prefix", "cloze-suffix", "dictionary", "dictionary-alias", "document-title", "frequencies", "frequency-harmonic-rank", "frequency-harmonic-occurrence", "frequency-average-rank", "frequency-average-occurrence", "screenshot", "search-query", "popup-selection-text", "sentence", "sentence-furigana", "sentence-furigana-plain", "url"],
- "maxEntries": 1,
- "includeMedia": False,
- }
- response = requests.post(request_url + "/ankiFields", json = params, timeout = request_timeout)
- return json.loads(response.text)
-
-def term_entries(term :str) -> dict:
- #print("Requesting termEntries:")
- params = {
- "term": term,
- "maxEntries": 1,
- "includeMedia": False,
- }
- response = requests.post(request_url + "/termEntries", json = params, timeout = request_timeout)
- return json.loads(response.text)
-
-def get_glossary(word :str) -> list:
- glossary = list()
- dict_items = term_entries(word)
-
- entry = next(iter(dict_items.get("dictionaryEntries",[])),None)
- if entry:
- definition = next(iter(entry.get("definitions",[])),None)
- if definition:
- def_entry = next(iter(definition.get("entries", [])),None)
- if def_entry:
- glossary.extend( list(extract_text_by_type(def_entry, "glossary")) )
- return glossary[:2]
-
#print(annotate_phrase("私は学校へ行きます"))
## Make sure directories exist
@@ -81,6 +15,8 @@ if not destination_path.exists():
destination_path.mkdir(parents=True, exist_ok=True)
if not destination_path.joinpath('_attachments').exists():
destination_path.joinpath('_attachments').mkdir(parents=True, exist_ok=True)
+if not destination_path.joinpath('vocab').exists():
+ destination_path.joinpath('vocab').mkdir(parents=True, exist_ok=True)
with open("dump-withFuri.json", "r", encoding="utf-16") as f:
dump = json.load(f)
@@ -97,33 +33,64 @@ for cd in dump:
card_note.write("---\n")
## Name at the top
card_note.write(f"![[{cd}.jpg]]")
- card_note.write("\n##### Name\n")
+ card_note.write("\n#### Name\n")
card_note.write("")
card_note.write(dump[cd]['name_J'])
card_note.write("
")
card_note.write(dump[cd]['name_E'])
card_note.write("")
card_note.write(dump[cd]['desc_J'])
card_note.write("
")
card_note.write(dump[cd]['desc_E'])
card_note.write("