# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from typing import List, Dict, Union, Optional, Type from rich.console import Console from rich.theme import Theme from rich.markdown import Markdown from rich.table import Table from rich.highlighter import RegexHighlighter def _get_highlighter(word: str) -> Type[RegexHighlighter]: """construct Regex Highlighter class based on the word Args: word (str): the query word Returns: Type[RegexHighlighter]: the sub-class of RegexHighlighter """ class KeywordHighlighter(RegexHighlighter): base_style = "paddlenlp." highlights = [f"(?P{word})"] return KeywordHighlighter() def print_example_code(): # 1. define the console console = Console() markdown = """ ## you can download the above model with the following command: ### ***paddlenlp download --cache-dir ./paddle_pretrained_models *** ### ***the is copied from above table*** """ console.print(Markdown(markdown)) def tabulate( tables: List[Union[List[str], Dict[str, str]]], headers: Optional[List[str]] = None, highlight_word: Optional[str] = None, ): """print tabulate data into console Args: tables (List[Union[List[str], Dict[str, str]]]): the table instance data headers (Optional[List[str]], optional): the header configuration. Defaults to None. highlight_word (Optional[str], optional): the highlight word. Defaults to None. """ # 1. define the console theme = Theme({"paddlenlp.keyword": "bold magenta"}) console = Console(highlighter=_get_highlighter(highlight_word), theme=theme) table_instance = Table( title="PaddleNLP 模型检索结果", show_header=headers is not None, header_style="bold magenta", highlight=True ) # 2. add column headers = headers or [] for header in headers: if isinstance(header, str): table_instance.add_column(header) else: table_instance.add_column(**header) # 3. add row data for row_data in tables: table_instance.add_row(*row_data) console.print(table_instance, justify="center")