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| from __future__ import annotations | |
| import numpy as np | |
| import pandas as pd | |
| import requests | |
| from huggingface_hub.hf_api import SpaceInfo | |
| class PaperList: | |
| def __init__(self): | |
| self.organization_name = 'ICML2022' | |
| self.table = pd.read_csv('papers.csv') | |
| self._preprcess_table() | |
| self.table_header = ''' | |
| <tr> | |
| <td width="50%">Paper</td> | |
| <td width="26%">Authors</td> | |
| <td width="4%">pdf</td> | |
| <td width="4%">arXiv</td> | |
| <td width="4%">GitHub</td> | |
| <td width="4%">HF Spaces</td> | |
| <td width="4%">HF Models</td> | |
| <td width="4%">HF Datasets</td> | |
| </tr>''' | |
| def load_space_info(author: str) -> list[SpaceInfo]: | |
| path = 'https://huggingface.co/api/spaces' | |
| r = requests.get(path, params={'author': author}) | |
| d = r.json() | |
| return [SpaceInfo(**x) for x in d] | |
| def add_spaces_to_table(self, organization_name: str, | |
| df: pd.DataFrame) -> pd.DataFrame: | |
| spaces = self.load_space_info(organization_name) | |
| name2space = { | |
| s.id.split('/')[1].lower(): f'https://huggingface.co/spaces/{s.id}' | |
| for s in spaces | |
| } | |
| df['hf_space'] = df.loc[:, ['hf_space', 'github']].apply( | |
| lambda x: x[0] if isinstance(x[0], str) else name2space.get( | |
| x[1].split('/')[-1].lower() | |
| if isinstance(x[1], str) else '', np.nan), | |
| axis=1) | |
| return df | |
| def _preprcess_table(self) -> None: | |
| self.table = self.add_spaces_to_table(self.organization_name, | |
| self.table) | |
| self.table['title_lowercase'] = self.table.title.str.lower() | |
| rows = [] | |
| for row in self.table.itertuples(): | |
| paper = f'<a href="{row.url}" target="_blank">{row.title}</a>' | |
| pdf = f'<a href="{row.pdf}" target="_blank">pdf</a>' | |
| arxiv = f'<a href="{row.arxiv}" target="_blank">arXiv</a>' if isinstance( | |
| row.arxiv, str) else '' | |
| github = f'<a href="{row.github}" target="_blank">GitHub</a>' if isinstance( | |
| row.github, str) else '' | |
| hf_space = f'<a href="{row.hf_space}" target="_blank">Space</a>' if isinstance( | |
| row.hf_space, str) else '' | |
| hf_model = f'<a href="{row.hf_model}" target="_blank">Model</a>' if isinstance( | |
| row.hf_model, str) else '' | |
| hf_dataset = f'<a href="{row.hf_dataset}" target="_blank">Dataset</a>' if isinstance( | |
| row.hf_dataset, str) else '' | |
| row = f''' | |
| <tr> | |
| <td>{paper}</td> | |
| <td>{row.authors}</td> | |
| <td>{pdf}</td> | |
| <td>{arxiv}</td> | |
| <td>{github}</td> | |
| <td>{hf_space}</td> | |
| <td>{hf_model}</td> | |
| <td>{hf_dataset}</td> | |
| </tr>''' | |
| rows.append(row) | |
| self.table['html_table_content'] = rows | |
| def render(self, search_query: str, case_sensitive: bool, | |
| filter_names: list[str]) -> tuple[int, str]: | |
| df = self.add_spaces_to_table(self.organization_name, self.table) | |
| if search_query: | |
| if case_sensitive: | |
| df = df[df.title.str.contains(search_query)] | |
| else: | |
| df = df[df.title_lowercase.str.contains(search_query.lower())] | |
| has_arxiv = 'arXiv' in filter_names | |
| has_github = 'GitHub' in filter_names | |
| has_hf_space = 'HF Space' in filter_names | |
| has_hf_model = 'HF Model' in filter_names | |
| has_hf_dataset = 'HF Dataset' in filter_names | |
| df = self.filter_table(df, has_arxiv, has_github, has_hf_space, | |
| has_hf_model, has_hf_dataset) | |
| return len(df), self.to_html(df, self.table_header) | |
| def filter_table(df: pd.DataFrame, has_arxiv: bool, has_github: bool, | |
| has_hf_space: bool, has_hf_model: bool, | |
| has_hf_dataset: bool) -> pd.DataFrame: | |
| if has_arxiv: | |
| df = df[~df.arxiv.isna()] | |
| if has_github: | |
| df = df[~df.github.isna()] | |
| if has_hf_space: | |
| df = df[~df.hf_space.isna()] | |
| if has_hf_model: | |
| df = df[~df.hf_model.isna()] | |
| if has_hf_dataset: | |
| df = df[~df.hf_dataset.isna()] | |
| return df | |
| def to_html(df: pd.DataFrame, table_header: str) -> str: | |
| table_data = ''.join(df.html_table_content) | |
| html = f''' | |
| <table> | |
| {table_header} | |
| {table_data} | |
| </table>''' | |
| return html | |