61 lines
2.1 KiB
Python
61 lines
2.1 KiB
Python
import io
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import pandas as pd
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import re
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import requests
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import zipfile
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url = "https://www.unicode.org/Public/15.1.0/ucd/Unihan.zip"
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print("📦 正在下载 Unihan 数据包...")
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r = requests.get(url)
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r.raise_for_status()
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with zipfile.ZipFile(io.BytesIO(r.content)) as z:
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txt = z.read("Unihan_Variants.txt").decode("utf-8") + \
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"\n" + z.read("Unihan_Readings.txt").decode("utf-8")
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print("✅ 数据加载成功")
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# --- 匹配所需字段 ---
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re_simpl = re.compile(r"U\+([0-9A-F]+)\tkSimplifiedVariant\t(U\+[0-9A-F]+)")
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re_zvar = re.compile(r"U\+([0-9A-F]+)\tkZVariant\t(U\+[0-9A-F]+)")
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re_jp_on = re.compile(r"U\+([0-9A-F]+)\tkJapaneseOn\t(.+)")
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re_jp_kun = re.compile(r"U\+([0-9A-F]+)\tkJapaneseKun\t(.+)")
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simpl_map, zvar_map, jp_on, jp_kun = {}, {}, {}, {}
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for m in re_simpl.finditer(txt):
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trad_hex, simp_hex = m.groups()
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trad, simp = chr(int(trad_hex, 16)), chr(int(simp_hex, 16))
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simpl_map[trad] = simp
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for m in re_zvar.finditer(txt):
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base_hex, var_hex = m.groups()
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base, var = chr(int(base_hex, 16)), chr(int(var_hex, 16))
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zvar_map[base] = var
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for m in re_jp_on.finditer(txt):
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code_hex, reading = m.groups()
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char = chr(int(code_hex, 16))
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jp_on[char] = reading.replace(" ", "、")
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for m in re_jp_kun.finditer(txt):
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code_hex, reading = m.groups()
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char = chr(int(code_hex, 16))
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jp_kun[char] = reading.replace(" ", "、")
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rows = []
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for trad, simp in simpl_map.items():
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# 关键：找繁体→日语新字体的异体关系
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if trad in zvar_map:
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jp_char = zvar_map[trad]
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if jp_char in jp_on or jp_char in jp_kun:
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kana_on = jp_on.get(jp_char, "")
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kana_kun = jp_kun.get(jp_char, "")
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kana = kana_on + ("、" + kana_kun if kana_on and kana_kun else kana_kun)
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rows.append([simp, trad, jp_char, kana, "是", "由繁体→简体+异体→日语新字体推导"])
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df = pd.DataFrame(rows, columns=["简体汉字", "繁体汉字", "日语汉字", "假名读音", "是否异体", "备注"])
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df.to_excel("中日汉字映射表_六列综合版.xlsx", index=False)
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print(f"✅ 已生成文件，共 {len(df)} 条记录。")
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