|
|
|
|
|
""" |
|
|
Generate enhanced HTML website from README.md table |
|
|
""" |
|
|
import pandas as pd |
|
|
import re |
|
|
import os |
|
|
|
|
|
def to_link_if_markdown(cell_text: str) -> str: |
|
|
"""Convert markdown links [text](url) to HTML <a> tags""" |
|
|
if not isinstance(cell_text, str): |
|
|
return str(cell_text) |
|
|
cell_text = re.sub(r'\[(.*?)\]\((.*?)\)', r'<a href="\2">\1</a>', cell_text) |
|
|
return cell_text.strip() |
|
|
|
|
|
def extract_table_from_readme(readme_path: str) -> pd.DataFrame: |
|
|
"""Extract the main projects table from README.md""" |
|
|
with open(readme_path, "r", encoding='utf-8') as f: |
|
|
text = f.readlines() |
|
|
|
|
|
table = [] |
|
|
in_projects_section = False |
|
|
|
|
|
for line in text: |
|
|
|
|
|
if line.strip() == "### Projects": |
|
|
in_projects_section = True |
|
|
continue |
|
|
|
|
|
|
|
|
if in_projects_section and line.startswith("### ") and "Projects" not in line: |
|
|
break |
|
|
|
|
|
|
|
|
if in_projects_section and len(re.findall(r"\|", line)) == 8: |
|
|
row = [cell.strip() for cell in line.split("|")[1:-1]] |
|
|
table.append(row) |
|
|
|
|
|
if len(table) < 2: |
|
|
raise ValueError("Could not find valid table in README.md") |
|
|
|
|
|
|
|
|
header = table[0] |
|
|
data = table[2:] if len(table) > 2 else [] |
|
|
|
|
|
df = pd.DataFrame(data, columns=header) |
|
|
|
|
|
df = df.applymap(to_link_if_markdown) |
|
|
|
|
|
return df |
|
|
|
|
|
def get_enhanced_html_template() -> str: |
|
|
"""Return the enhanced HTML template""" |
|
|
return '''<!DOCTYPE html> |
|
|
<html> |
|
|
<head> |
|
|
<meta charset="UTF-8"> |
|
|
<meta name="viewport" content="width=device-width, initial-scale=1.0"> |
|
|
<title>Awesome Computational Primatology</title> |
|
|
|
|
|
<!-- External Libraries --> |
|
|
<script src="https://code.jquery.com/jquery-3.7.1.min.js"></script> |
|
|
<link rel="stylesheet" href="https://cdn.datatables.net/2.0.2/css/dataTables.dataTables.css" /> |
|
|
<link rel="stylesheet" href="https://cdn.datatables.net/buttons/3.0.0/css/buttons.dataTables.css" /> |
|
|
<link rel="stylesheet" href="https://cdn.datatables.net/searchpanes/2.3.0/css/searchPanes.dataTables.css" /> |
|
|
<link rel="stylesheet" href="https://cdn.datatables.net/select/2.0.0/css/select.dataTables.css" /> |
|
|
|
|
|
<script src="https://cdn.datatables.net/2.0.2/js/dataTables.js"></script> |
|
|
<script src="https://cdn.datatables.net/buttons/3.0.0/js/dataTables.buttons.js"></script> |
|
|
<script src="https://cdn.datatables.net/buttons/3.0.0/js/buttons.html5.min.js"></script> |
|
|
<script src="https://cdn.datatables.net/searchpanes/2.3.0/js/dataTables.searchPanes.js"></script> |
|
|
<script src="https://cdn.datatables.net/select/2.0.0/js/dataTables.select.js"></script> |
|
|
|
|
|
<!-- Icons --> |
|
|
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css"> |
|
|
|
|
|
<style> |
|
|
:root { |
|
|
--primary-color: #2c3e50; |
|
|
--secondary-color: #3498db; |
|
|
--accent-color: #e74c3c; |
|
|
--success-color: #27ae60; |
|
|
--warning-color: #f39c12; |
|
|
--background-color: #f8f9fa; |
|
|
--card-background: #ffffff; |
|
|
--text-color: #2c3e50; |
|
|
--border-color: #dee2e6; |
|
|
--shadow: 0 2px 4px rgba(0,0,0,0.1); |
|
|
} |
|
|
|
|
|
* { |
|
|
box-sizing: border-box; |
|
|
} |
|
|
|
|
|
body { |
|
|
font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; |
|
|
background-color: var(--background-color); |
|
|
margin: 0; |
|
|
padding: 20px; |
|
|
color: var(--text-color); |
|
|
line-height: 1.6; |
|
|
} |
|
|
|
|
|
.container { |
|
|
max-width: 1400px; |
|
|
margin: 0 auto; |
|
|
background: var(--card-background); |
|
|
padding: 30px; |
|
|
border-radius: 12px; |
|
|
box-shadow: var(--shadow); |
|
|
} |
|
|
|
|
|
.header { |
|
|
text-align: center; |
|
|
margin-bottom: 40px; |
|
|
padding-bottom: 20px; |
|
|
border-bottom: 2px solid var(--border-color); |
|
|
} |
|
|
|
|
|
h1 { |
|
|
color: var(--primary-color); |
|
|
font-size: 2.5rem; |
|
|
margin-bottom: 10px; |
|
|
font-weight: 700; |
|
|
} |
|
|
|
|
|
.subtitle { |
|
|
color: #666; |
|
|
font-size: 1.1rem; |
|
|
margin-bottom: 20px; |
|
|
} |
|
|
|
|
|
.stats { |
|
|
display: flex; |
|
|
justify-content: center; |
|
|
gap: 30px; |
|
|
margin-bottom: 20px; |
|
|
flex-wrap: wrap; |
|
|
} |
|
|
|
|
|
.stat-item { |
|
|
text-align: center; |
|
|
padding: 15px; |
|
|
background: linear-gradient(135deg, var(--secondary-color), #5dade2); |
|
|
color: white; |
|
|
border-radius: 8px; |
|
|
min-width: 120px; |
|
|
box-shadow: var(--shadow); |
|
|
} |
|
|
|
|
|
.stat-number { |
|
|
font-size: 1.8rem; |
|
|
font-weight: bold; |
|
|
display: block; |
|
|
} |
|
|
|
|
|
.stat-label { |
|
|
font-size: 0.9rem; |
|
|
opacity: 0.9; |
|
|
} |
|
|
|
|
|
.legend { |
|
|
background: #f8f9fa; |
|
|
padding: 20px; |
|
|
border-radius: 8px; |
|
|
margin-bottom: 30px; |
|
|
border-left: 4px solid var(--secondary-color); |
|
|
} |
|
|
|
|
|
.legend h3 { |
|
|
margin-top: 0; |
|
|
color: var(--primary-color); |
|
|
} |
|
|
|
|
|
.legend-grid { |
|
|
display: grid; |
|
|
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr)); |
|
|
gap: 10px; |
|
|
margin-top: 15px; |
|
|
} |
|
|
|
|
|
.legend-item { |
|
|
display: flex; |
|
|
align-items: center; |
|
|
gap: 8px; |
|
|
} |
|
|
|
|
|
.legend-badge { |
|
|
background: var(--secondary-color); |
|
|
color: white; |
|
|
padding: 2px 8px; |
|
|
border-radius: 4px; |
|
|
font-size: 0.8rem; |
|
|
font-weight: bold; |
|
|
min-width: 35px; |
|
|
text-align: center; |
|
|
} |
|
|
|
|
|
.table-container { |
|
|
background: white; |
|
|
border-radius: 8px; |
|
|
overflow: hidden; |
|
|
box-shadow: var(--shadow); |
|
|
} |
|
|
|
|
|
table.dataTable { |
|
|
border-collapse: separate; |
|
|
border-spacing: 0; |
|
|
width: 100% !important; |
|
|
margin: 0 !important; |
|
|
} |
|
|
|
|
|
table.dataTable thead th { |
|
|
background: linear-gradient(135deg, var(--primary-color), #34495e); |
|
|
color: white; |
|
|
padding: 15px 10px; |
|
|
font-weight: 600; |
|
|
text-align: left; |
|
|
border: none; |
|
|
position: sticky; |
|
|
top: 0; |
|
|
z-index: 10; |
|
|
} |
|
|
|
|
|
table.dataTable tbody td { |
|
|
padding: 12px 10px; |
|
|
border-bottom: 1px solid #eee; |
|
|
vertical-align: middle; |
|
|
} |
|
|
|
|
|
table.dataTable tbody tr:hover { |
|
|
background-color: #f8f9fa; |
|
|
} |
|
|
|
|
|
.status-badge { |
|
|
padding: 4px 8px; |
|
|
border-radius: 20px; |
|
|
font-size: 0.8rem; |
|
|
font-weight: 600; |
|
|
text-decoration: none !important; |
|
|
display: inline-block; |
|
|
} |
|
|
|
|
|
.status-yes { |
|
|
background: #d4edda; |
|
|
color: #155724; |
|
|
border: 1px solid #c3e6cb; |
|
|
} |
|
|
|
|
|
.status-no { |
|
|
background: #f8d7da; |
|
|
color: #721c24; |
|
|
border: 1px solid #f5c6cb; |
|
|
} |
|
|
|
|
|
.status-partial { |
|
|
background: #fff3cd; |
|
|
color: #856404; |
|
|
border: 1px solid #ffeeba; |
|
|
} |
|
|
|
|
|
.status-request { |
|
|
background: #d1ecf1; |
|
|
color: #0c5460; |
|
|
border: 1px solid #bee5eb; |
|
|
} |
|
|
|
|
|
.topic-tag { |
|
|
background: var(--secondary-color); |
|
|
color: white; |
|
|
padding: 2px 6px; |
|
|
border-radius: 3px; |
|
|
font-size: 0.75rem; |
|
|
margin-right: 4px; |
|
|
display: inline-block; |
|
|
margin-bottom: 2px; |
|
|
} |
|
|
|
|
|
.year-cell { |
|
|
font-weight: 600; |
|
|
color: var(--primary-color); |
|
|
background: linear-gradient(135deg, #ecf0f1, #bdc3c7); |
|
|
text-align: center; |
|
|
} |
|
|
|
|
|
.species-macaque { background-color: #e8f5e8; } |
|
|
.species-chimp { background-color: #fff3e0; } |
|
|
.species-gorilla { background-color: #f3e5f5; } |
|
|
.species-marmoset { background-color: #e1f5fe; } |
|
|
.species-cross { background-color: #f9f9f9; } |
|
|
|
|
|
.dt-button { |
|
|
background: var(--secondary-color) !important; |
|
|
color: white !important; |
|
|
border: none !important; |
|
|
padding: 8px 15px !important; |
|
|
border-radius: 6px !important; |
|
|
margin-right: 8px !important; |
|
|
font-size: 0.9rem !important; |
|
|
transition: all 0.3s ease !important; |
|
|
} |
|
|
|
|
|
.dt-button:hover { |
|
|
background: #2980b9 !important; |
|
|
transform: translateY(-1px); |
|
|
box-shadow: 0 4px 8px rgba(0,0,0,0.2) !important; |
|
|
} |
|
|
|
|
|
/* Footer */ |
|
|
.footer { |
|
|
margin-top: 40px; |
|
|
padding: 30px 20px; |
|
|
background: linear-gradient(135deg, #f8f9fa, #e9ecef); |
|
|
border-radius: 8px; |
|
|
text-align: center; |
|
|
border-top: 3px solid var(--secondary-color); |
|
|
} |
|
|
|
|
|
.footer p { |
|
|
margin: 8px 0; |
|
|
color: #666; |
|
|
} |
|
|
|
|
|
.footer a { |
|
|
color: var(--secondary-color); |
|
|
text-decoration: none; |
|
|
font-weight: 500; |
|
|
transition: color 0.3s ease; |
|
|
} |
|
|
|
|
|
.footer a:hover { |
|
|
color: var(--primary-color); |
|
|
text-decoration: underline; |
|
|
} |
|
|
|
|
|
.footer-note { |
|
|
font-size: 0.9rem; |
|
|
color: #888; |
|
|
} |
|
|
|
|
|
#last-updated { |
|
|
font-weight: 600; |
|
|
color: var(--secondary-color); |
|
|
} |
|
|
|
|
|
@media (max-width: 768px) { |
|
|
.container { padding: 15px; } |
|
|
h1 { font-size: 2rem; } |
|
|
.stats { gap: 15px; } |
|
|
.stat-item { min-width: 100px; padding: 10px; } |
|
|
table.dataTable thead th, |
|
|
table.dataTable tbody td { padding: 8px 6px; font-size: 0.9rem; } |
|
|
.legend-grid { grid-template-columns: 1fr; } |
|
|
.footer { margin-top: 20px; padding: 20px 15px; } |
|
|
} |
|
|
</style> |
|
|
</head> |
|
|
<body> |
|
|
<div class="container"> |
|
|
<div class="header"> |
|
|
<h1>🐒 Awesome Computational Primatology</h1> |
|
|
<p class="subtitle">A curated list of machine learning research for non-human primatology</p> |
|
|
|
|
|
<div class="stats"> |
|
|
<div class="stat-item"> |
|
|
<span class="stat-number" id="total-papers">{total_papers}</span> |
|
|
<span class="stat-label">Papers</span> |
|
|
</div> |
|
|
<div class="stat-item"> |
|
|
<span class="stat-number" id="years-span">{years_span}</span> |
|
|
<span class="stat-label">Years</span> |
|
|
</div> |
|
|
<div class="stat-item"> |
|
|
<span class="stat-number" id="with-code">{with_code}</span> |
|
|
<span class="stat-label">With Code</span> |
|
|
</div> |
|
|
<div class="stat-item"> |
|
|
<span class="stat-number" id="with-data">{with_data}</span> |
|
|
<span class="stat-label">With Data</span> |
|
|
</div> |
|
|
</div> |
|
|
</div> |
|
|
|
|
|
<div class="legend"> |
|
|
<h3>🏷️ Topic Legend</h3> |
|
|
<div class="legend-grid"> |
|
|
<div class="legend-item"> |
|
|
<span class="legend-badge">PD</span> |
|
|
<span>Primate Detection</span> |
|
|
</div> |
|
|
<div class="legend-item"> |
|
|
<span class="legend-badge">BPE</span> |
|
|
<span>Body Pose Estimation</span> |
|
|
</div> |
|
|
<div class="legend-item"> |
|
|
<span class="legend-badge">FD</span> |
|
|
<span>Face Detection</span> |
|
|
</div> |
|
|
<div class="legend-item"> |
|
|
<span class="legend-badge">FLE</span> |
|
|
<span>Facial Landmark Estimation</span> |
|
|
</div> |
|
|
<div class="legend-item"> |
|
|
<span class="legend-badge">FR</span> |
|
|
<span>Face Recognition</span> |
|
|
</div> |
|
|
<div class="legend-item"> |
|
|
<span class="legend-badge">FAC</span> |
|
|
<span>Facial Action Coding</span> |
|
|
</div> |
|
|
<div class="legend-item"> |
|
|
<span class="legend-badge">BR</span> |
|
|
<span>Behavior Recognition</span> |
|
|
</div> |
|
|
<div class="legend-item"> |
|
|
<span class="legend-badge">AM</span> |
|
|
<span>Avatar/Mesh</span> |
|
|
</div> |
|
|
<div class="legend-item"> |
|
|
<span class="legend-badge">SI</span> |
|
|
<span>Species Identification</span> |
|
|
</div> |
|
|
<div class="legend-item"> |
|
|
<span class="legend-badge">RL</span> |
|
|
<span>Reinforcement Learning</span> |
|
|
</div> |
|
|
</div> |
|
|
</div> |
|
|
|
|
|
<div class="table-container"> |
|
|
{table_html} |
|
|
</div> |
|
|
|
|
|
<div class="footer"> |
|
|
<p> |
|
|
<strong>Maintained by:</strong> |
|
|
<a href="http://kordinglab.com" target="_blank">🧠 Kording Lab</a> • |
|
|
<a href="mailto:[email protected]">📧 Felipe Parodi</a> • |
|
|
<a href="https://github.com/KordingLab/awesome-computational-primatology" target="_blank">⭐ Star on GitHub</a> |
|
|
</p> |
|
|
<p class="footer-note"> |
|
|
Found a paper we missed? <a href="https://github.com/KordingLab/awesome-computational-primatology/blob/main/CONTRIBUTING.md">Contribute here!</a> |
|
|
• Last updated: <span id="last-updated"></span> |
|
|
</p> |
|
|
</div> |
|
|
</div> |
|
|
|
|
|
<script> |
|
|
$(document).ready(function() { |
|
|
var table = $('#table').DataTable({ |
|
|
paging: true, |
|
|
pageLength: 25, |
|
|
lengthMenu: [10, 25, 50, 100, -1], |
|
|
searching: true, |
|
|
ordering: true, |
|
|
info: true, |
|
|
responsive: true, |
|
|
|
|
|
dom: 'Bfrtip', |
|
|
buttons: [ |
|
|
{ |
|
|
extend: 'searchPanes', |
|
|
config: { |
|
|
cascadePanes: true, |
|
|
viewTotal: true, |
|
|
columns: [0, 2, 3, 4, 5] |
|
|
} |
|
|
}, |
|
|
'copy', 'csv', 'excel', |
|
|
{ |
|
|
text: 'Clear Filters', |
|
|
action: function(e, dt, node, config) { |
|
|
dt.searchPanes.clearSelections(); |
|
|
} |
|
|
} |
|
|
], |
|
|
|
|
|
searchPanes: { |
|
|
cascadePanes: true, |
|
|
viewTotal: true, |
|
|
columns: [0, 2, 3, 4, 5], |
|
|
initCollapsed: true |
|
|
}, |
|
|
|
|
|
columnDefs: [ |
|
|
{ |
|
|
targets: 0, |
|
|
type: 'num', |
|
|
className: 'year-cell', |
|
|
width: '80px' |
|
|
}, |
|
|
{ |
|
|
targets: 2, |
|
|
width: '150px', |
|
|
render: function(data, type, row) { |
|
|
if (type === 'display') { |
|
|
const topics = data.split(', '); |
|
|
return topics.map(topic => |
|
|
'<span class="topic-tag">' + topic.trim() + '</span>' |
|
|
).join(' '); |
|
|
} |
|
|
return data; |
|
|
} |
|
|
}, |
|
|
{ |
|
|
targets: 3, |
|
|
width: '120px', |
|
|
render: function(data, type, row) { |
|
|
if (type === 'display') { |
|
|
let className = 'species-cross'; |
|
|
const lowerData = data.toLowerCase(); |
|
|
if (lowerData.includes('macaque')) className = 'species-macaque'; |
|
|
else if (lowerData.includes('chimp')) className = 'species-chimp'; |
|
|
else if (lowerData.includes('gorilla')) className = 'species-gorilla'; |
|
|
else if (lowerData.includes('marmoset')) className = 'species-marmoset'; |
|
|
|
|
|
return '<span class="' + className + '" style="padding: 4px 8px; border-radius: 4px; display: inline-block;">' + data + '</span>'; |
|
|
} |
|
|
return data; |
|
|
} |
|
|
}, |
|
|
{ |
|
|
targets: [4, 5], |
|
|
width: '100px', |
|
|
render: function(data, type, row) { |
|
|
if (type === 'display') { |
|
|
let className = 'status-no'; |
|
|
let icon = '<i class="fas fa-times"></i> '; |
|
|
|
|
|
if (data.includes('Yes')) { |
|
|
className = 'status-yes'; |
|
|
icon = '<i class="fas fa-check"></i> '; |
|
|
} else if (data.includes('Code only') || data.includes('Some')) { |
|
|
className = 'status-partial'; |
|
|
icon = '<i class="fas fa-code"></i> '; |
|
|
} else if (data.includes('Upon request')) { |
|
|
className = 'status-request'; |
|
|
icon = '<i class="fas fa-envelope"></i> '; |
|
|
} |
|
|
|
|
|
return '<span class="status-badge ' + className + '">' + icon + data + '</span>'; |
|
|
} |
|
|
return data; |
|
|
} |
|
|
} |
|
|
], |
|
|
|
|
|
order: [[0, 'desc']], |
|
|
|
|
|
language: { |
|
|
search: '<i class="fas fa-search"></i>', |
|
|
searchPlaceholder: 'Search papers...', |
|
|
lengthMenu: 'Show _MENU_ papers per page', |
|
|
info: 'Showing _START_ to _END_ of _TOTAL_ papers', |
|
|
processing: '<i class="fas fa-spinner fa-spin"></i> Loading...' |
|
|
} |
|
|
}); |
|
|
|
|
|
// Set last updated date |
|
|
const lastUpdated = new Date().toLocaleDateString('en-US', { |
|
|
year: 'numeric', |
|
|
month: 'long', |
|
|
day: 'numeric' |
|
|
}); |
|
|
document.getElementById('last-updated').textContent = lastUpdated; |
|
|
}); |
|
|
</script> |
|
|
</body> |
|
|
</html>''' |
|
|
|
|
|
def calculate_stats(df: pd.DataFrame) -> dict: |
|
|
"""Calculate statistics from the dataframe""" |
|
|
total_papers = len(df) |
|
|
|
|
|
|
|
|
years = set() |
|
|
for year in df.iloc[:, 0]: |
|
|
if str(year).isdigit(): |
|
|
years.add(int(year)) |
|
|
years_span = len(years) |
|
|
|
|
|
|
|
|
with_code = 0 |
|
|
model_col = df.iloc[:, 4] if len(df.columns) > 4 else pd.Series() |
|
|
for value in model_col: |
|
|
if isinstance(value, str) and ('Yes' in value or 'Code only' in value): |
|
|
with_code += 1 |
|
|
|
|
|
|
|
|
with_data = 0 |
|
|
data_col = df.iloc[:, 5] if len(df.columns) > 5 else pd.Series() |
|
|
for value in data_col: |
|
|
if isinstance(value, str) and 'Yes' in value: |
|
|
with_data += 1 |
|
|
|
|
|
return { |
|
|
'total_papers': total_papers, |
|
|
'years_span': years_span, |
|
|
'with_code': with_code, |
|
|
'with_data': with_data |
|
|
} |
|
|
|
|
|
def main(): |
|
|
"""Main function to generate the website""" |
|
|
|
|
|
if os.path.exists("/home/runner/work"): |
|
|
|
|
|
base_path = "/home/runner/work/awesome-computational-primatology/awesome-computational-primatology" |
|
|
else: |
|
|
|
|
|
script_dir = os.path.dirname(os.path.abspath(__file__)) |
|
|
base_path = os.path.dirname(os.path.dirname(script_dir)) |
|
|
|
|
|
readme_path = os.path.join(base_path, "README.md") |
|
|
output_path = os.path.join(base_path, "index.html") |
|
|
|
|
|
print(f"Script location: {os.path.abspath(__file__)}") |
|
|
print(f"Base path: {base_path}") |
|
|
print(f"README path: {readme_path}") |
|
|
print(f"Output path: {output_path}") |
|
|
|
|
|
try: |
|
|
|
|
|
df = extract_table_from_readme(readme_path) |
|
|
print(f"Extracted table with {len(df)} rows and {len(df.columns)} columns") |
|
|
|
|
|
|
|
|
stats = calculate_stats(df) |
|
|
print(f"Statistics: {stats}") |
|
|
|
|
|
|
|
|
table_html = df.to_html( |
|
|
table_id="table", |
|
|
escape=False, |
|
|
index=False, |
|
|
classes="display" |
|
|
) |
|
|
|
|
|
|
|
|
template = get_enhanced_html_template() |
|
|
html_content = template.replace('{table_html}', table_html) |
|
|
html_content = html_content.replace('{total_papers}', str(stats['total_papers'])) |
|
|
html_content = html_content.replace('{years_span}', str(stats['years_span'])) |
|
|
html_content = html_content.replace('{with_code}', str(stats['with_code'])) |
|
|
html_content = html_content.replace('{with_data}', str(stats['with_data'])) |
|
|
|
|
|
|
|
|
with open(output_path, "w", encoding='utf-8') as f: |
|
|
f.write(html_content) |
|
|
|
|
|
print(f"✅ Generated enhanced website: {output_path}") |
|
|
|
|
|
except Exception as e: |
|
|
print(f"❌ Error generating website: {e}") |
|
|
raise |
|
|
|
|
|
if __name__ == "__main__": |
|
|
main() |
