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from __future__ import annotations
import pandas as pd
class PaperList:
def __init__(self):
self.table = pd.read_csv("papers.csv")
self._preprcess_table()
self.table_header = """
<tr>
<td width="50%">Paper</td>
<td width="22%">Authors</td>
<td width="4%">pdf</td>
<td width="4%">category</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 _preprcess_table(self) -> None:
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>' if isinstance(row.url, str) else row.title
pdf = f'<a href="{row.pdf}" target="_blank">pdf</a>' if isinstance(row.pdf, str) else ""
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>{row.category}</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], paper_categories: list[str]
) -> tuple[int, str]:
df = 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, paper_categories)
return len(df), self.to_html(df, self.table_header)
@staticmethod
def filter_table(
df: pd.DataFrame,
has_arxiv: bool,
has_github: bool,
has_hf_space: bool,
has_hf_model: bool,
has_hf_dataset: bool,
paper_categories: list[str],
) -> 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()]
df = df[df.category.isin(set(paper_categories))]
return df
@staticmethod
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
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