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import pandas as pd |
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import os |
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import datasets |
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XLS_FOLDER = "basic_korean_dict" |
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OUTPUT_FOLDER = "data" |
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SORT_KEY = ["어휘", "표제어"] |
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NUM_PROC = 32 |
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hf_access_token = "" |
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hf_ID = "" |
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ds_name = "basic_korean_dict" |
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def flatten_examples(example: dict) -> dict: |
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text_line = "" |
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for key in example: |
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if key in ["의미 번호", "동형어 번호"]: |
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continue |
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if (single_column := example[key]) == None: |
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continue |
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if key == "원어·어종": |
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single_column = single_column.removeprefix("안 밝힘 ") |
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text_line += key + ": " + single_column.strip() + ", " |
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return {"text": text_line.removesuffix(", ")} |
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if os.path.exists(XLS_FOLDER): |
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XLS_FOLDER = os.path.abspath(XLS_FOLDER) |
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xls_list = os.listdir(XLS_FOLDER) |
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else: |
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raise ValueError("input folder does not exist") |
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combined_df = pd.DataFrame() |
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length_check = 0 |
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for xls in sorted(xls_list): |
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xls_path = os.path.join(XLS_FOLDER, xls) |
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if os.path.exists(xls_path): |
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df = pd.read_excel(xls_path, header=0, index_col=None) |
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length_check += len(df) |
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combined_df = pd.concat([combined_df, df], ignore_index=True) |
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assert len(combined_df) == length_check |
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ds = datasets.Dataset.from_pandas(combined_df) |
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for key in SORT_KEY: |
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if key in ds.column_names: |
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sorted_ds = ds.sort(key) |
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processed_ds = sorted_ds.map(flatten_examples, num_proc=NUM_PROC).select_columns("text") |
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processed_ds.push_to_hub(repo_id=ds_name, token=hf_access_token) |
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